WorldWideScience

Sample records for machining parameter study

  1. Pre-segmented 2-Step IMRT with subsequent direct machine parameter optimisation – a planning study

    Directory of Open Access Journals (Sweden)

    Flentje Michael

    2008-11-01

    Full Text Available Abstract Background Modern intensity modulated radiotherapy (IMRT mostly uses iterative optimisation methods. The integration of machine parameters into the optimisation process of step and shoot leaf positions has been shown to be successful. For IMRT segmentation algorithms based on the analysis of the geometrical structure of the planning target volumes (PTV and the organs at risk (OAR, the potential of such procedures has not yet been fully explored. In this work, 2-Step IMRT was combined with subsequent direct machine parameter optimisation (DMPO-Raysearch Laboratories, Sweden to investigate this potential. Methods In a planning study DMPO on a commercial planning system was compared with manual primary 2-Step IMRT segment generation followed by DMPO optimisation. 15 clinical cases and the ESTRO Quasimodo phantom were employed. Both the same number of optimisation steps and the same set of objective values were used. The plans were compared with a clinical DMPO reference plan and a traditional IMRT plan based on fluence optimisation and consequent segmentation. The composite objective value (the weighted sum of quadratic deviations of the objective values and the related points in the dose volume histogram was used as a measure for the plan quality. Additionally, a more extended set of parameters was used for the breast cases to compare the plans. Results The plans with segments pre-defined with 2-Step IMRT were slightly superior to DMPO alone in the majority of cases. The composite objective value tended to be even lower for a smaller number of segments. The total number of monitor units was slightly higher than for the DMPO-plans. Traditional IMRT fluence optimisation with subsequent segmentation could not compete. Conclusion 2-Step IMRT segmentation is suitable as starting point for further DMPO optimisation and, in general, results in less complex plans which are equal or superior to plans generated by DMPO alone.

  2. A Study of effect of Process Parameters of Abrasive jet machining

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    Jagtar Singh

    2011-01-01

    Full Text Available As Abrasive jet machining (AJM is similar to sand blasting and effectively removes hard and brittle materials. AJM has been applied to rough working such as deburring and rough finishing. With the increase of needs for machining of ceramics, semiconductors, electronic devices and L.C.D., AJM has become a useful technique for micromachining. This paper deals with various experiments which were conducted to assess the influence of abrasive jet machining (AJM process parameters on material removal rate and diameter of holes of glass plates using aluminum oxide type of abrasive particles. The experimental results of the present work are used to discuss thevalidity of proposed model as well as the other models. With the increase in nozzle tip distance (NTD, the top surface diameter and bottom surface diameter of hole increases as it is in general observation of abrasive jet machining process. As the pressure increases, the material removal rate (MRR is also increased.

  3. STUDY ON NEW METHOD OF IDENTIFYING GEOMETRIC ERROR PARAMETERS FOR NC MACHINE TOOLS

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    The methods of identifying geometric error parameters for NC machine tools are introduced. According to analyzing and comparing the different methods, a new method-displacement method with 9 lines is developed based on the theories of the movement errors of multibody system (MBS). A lot of experiments are also made to obtain 21 terms geometric error parameters by using the error identification software based on the new method.

  4. Experimental study on working parameters of earth pressure balance shield machine tunneling in soft ground

    Institute of Scientific and Technical Information of China (English)

    Hehua ZHU; Shaoming LIAO; Qianwei XU; Qizhen ZHENG

    2008-01-01

    Deep sedimentary deposits of soft clays are widely distributed in coastal areas as well as many interior major cities in China. In order to study the stratum adapt-ability of earth pressure balance (EPB) shield machine tunneling in such types of soft ground, model tests of tunneling excavation, using the running tunnel of the Shanghai Metro Line M8 as a background, are carried out with different over burden ratios, opening rates of cutter head, driving speeds and rotation speeds of screw conveyor. Based on the test results, the interrelationships between chamber pressure and mucking efficiency, muck-ing rate and driving speed, thrust force and torque are obtained. The influences of tunnel depth, opening rate of cutter head and driving speed on thrust force and tor-que are revealed. Such findings can not only facilitate establishing relationships between shield working para-meters and soil properties, but also serve as a guide for the design and construction of shield tunnel in soft ground.

  5. Online Dynamic Parameter Estimation of Synchronous Machines

    Science.gov (United States)

    West, Michael R.

    Traditionally, synchronous machine parameters are determined through an offline characterization procedure. The IEEE 115 standard suggests a variety of mechanical and electrical tests to capture the fundamental characteristics and behaviors of a given machine. These characteristics and behaviors can be used to develop and understand machine models that accurately reflect the machine's performance. To perform such tests, the machine is required to be removed from service. Characterizing a machine offline can result in economic losses due to down time, labor expenses, etc. Such losses may be mitigated by implementing online characterization procedures. Historically, different approaches have been taken to develop methods of calculating a machine's electrical characteristics, without removing the machine from service. Using a machine's input and response data combined with a numerical algorithm, a machine's characteristics can be determined. This thesis explores such characterization methods and strives to compare the IEEE 115 standard for offline characterization with the least squares approximation iterative approach implemented on a 20 h.p. synchronous machine. This least squares estimation method of online parameter estimation shows encouraging results for steady-state parameters, in comparison with steady-state parameters obtained through the IEEE 115 standard.

  6. Determination of Induction Machine Parameters by Simulation

    OpenAIRE

    Dr. E.A. Anazia; Engr. Samson Ugochukwu; Dr. J. C. Onuegbu; Engr. Onyedikachi S.N

    2016-01-01

    A 38.1 Watt fractional horse power induction laboratory test motor model was created using MotorSolve 5.2; an electrical machine design application. Initial machine parameters such as voltage, speed, and main dimensions were selected and fed into the application and simulations ran. The simulated results were presented and analyzed. Unlike other induction machine parameter identification process, this method is simple, flexible and accurate since it does not involve rigorous mathe...

  7. Prediction of Electrochemical Machining Process Parameters using Artificial Neural Networks

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    Hoda Hosny Abuzied

    2012-01-01

    Full Text Available Electrochemical machining (ECM is a non-traditional machining process used mainly to cut hard or difficult to cut metals, where the application of a more traditional process is not convenient. It offers several special advantages including higher machining rate, better precision and control, and a wider range of materials that can be machined. A suitable selection of machining parameters for the ECM process relies heavily on the operator’s technologies and experience because of their numerous and diverse range. Machining parameters provided by the machine tool builder cannot meet the operator’s requirements. So, artificial neural networks were introduced as an efficient approach to predict the values of resulting surface roughness and material removal rate. Many researchers usedartificial neural networks (ANN in improvement of ECM process and also in other nontraditional machining processes as well be seen in later sections. The present study is, initiated to predict values of some of resulting process parameters such as metal removal rate(MRR, and surface roughness (Ra using artificial neural networks based on variation of certain predominant parameters of an electrochemical broaching process such as applied voltage, feed rate and electrolyte flow rate. ANN was found to be an efficient approach as it reduced time & effort required to predict material removal rate & surface roughness if they were found experimentally using trial & error method. To validate the proposed approach the predicted values of surface roughness and material removal rate were compared with a previously obtained ones from the experimental work.

  8. ANALYSIS OF PARAMETERS AFFECTING THE QUALITY OF A CUTTING MACHINE

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    Iveta Onderová

    2014-02-01

    Full Text Available The quality of cutting machines is affected by several factors that can be directly or indirectly influenced by manufacturers, technicians and users of machine tools. The most critical qualitative evaluation parameters of machine tools include accuracy and stability. Investigations of accuracy and repeatable positioning accuracy were essential for the research presented in this paper. The aim was to develop and experimentally verify the design of a methodology for cutting centers aimed at achieving the desired working precision. Before working on the topic described here, it was necessary to make several scientific analyses, which are summarized in this paper. We can build on the initial working hypothesis that by improving the technological parameters (e.g. by increasing the working speed of the machine, or by improving the precision of the positioning the quality of the cutting machine will also be improved. For the purposes of our study, several investigated parameters were set affecting positioning accuracy, such as rigidity, positioning speed, etc. First, the stiffness of the portal structure of the cutting machine was analyzed. FEM analysis was used to investigate several alternative structures of the cutting machine, and also an innovative solution for beam mounting. The second step was to integrate two types of drives into the design of the cutting machine. The first drive is a classic rack and pinion drive for cutting machines. To increase (improve the working speed of the machine, linear motors were designed as an alternative drive. The portal of the cutting machine was designed for a working speed of 260mmin−1 and acceleration of 25 m. s−2. The third step was based on the results of the analysis. In collaboration with Microstep, an experimental cutting machine in a portal version was produced using linear synchronous motors driving the portal on both sides, and with direct linear metering of its position. In the fourth step, an

  9. Study on characteristic parameters influencing laser-induced damage threshold of KH(2)PO(4) crystal surface machined by single point diamond turning.

    Science.gov (United States)

    Chen, Mingjun; Li, Mingquan; Cheng, Jian; Jiang, Wei; Wang, Jian; Xu, Qiao

    2011-12-01

    It has fundamental meaning to find the elements influencing the laser-induced damage threshold (LIDT) of KH(2)PO(4) (KDP) crystal and to provide suitable characterization parameters for these factors in order to improve the LIDT of KDP. Using single-point diamond turning (SPDT) to process the KDP crystal, the machined surface quality has important effects on its LIDT. However, there are still not suitable characteristic parameters of surface quality of KDP to correspond with the LIDT nowadays. In this paper, guided by the Fourier model theory, we study deeply the relationship between the relevant characteristic parameters of surface topography of KDP crystal and the experimental LIDT. Research results indicate that the waviness rather than the roughness is the leading topography element on the KDP surface machined by the SPDT method when the LIDT is considered and the amplitude of micro-waviness has greater influence on the light intensity inside the KDP crystal within the scope of dangerous frequencies between (180 μm)(-1) and (90 μm)(-1); with suitable testing equipment, the characteristic parameters of waviness amplitude, such as the arithmetical mean deviation of three-dimensional profile S(a) or root mean square deviation of three-dimensional contour S(q), are able to be considered as suitable parameters to reflect the optical quality of the machined surface in order to judge approximately the LIDT of the KDP surface and guide the machining course.

  10. ASCERTAINMENT OF THE EQUIVALENT CIRCUIT PARAMETERS OF THE ASYNCHRONOUS MACHINE

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    V. S. Safaryan

    2015-01-01

    Full Text Available The article considers experimental and analytical determination of the asynchronous machine equivalent-circuit parameters with application of the reference data. Transient processes investigation of the asynchronous machines necessitates the equivalent circuit parameters (resistance impedance, inductances and coefficient of the stator-rotor contours mutual inductance that help form the transitory-process mathematical simulation model. The reference books do not provide those parameters; they instead give the rated ones (active power, voltage, slide, coefficient of performance and capacity coefficient as well as the ratio of starting and nominal currents and torques. The noted studies on the asynchronous machine equivalent-circuits parametrization fail to solve the problems ad finem or solve them with admissions. The paper presents experimental and analytical determinations of the asynchronous machine equivalent-circuit parameters: the experimental one based on the results of two measurements and the analytical one where the problem boils down to solving a system of nonlineal algebraic equations. The authors investigate the equivalent asynchronous machine input-resistance properties and adduce the dependence curvatures of the input-resistances on the slide. They present a symbolic model for analytical parameterization of the asynchronous machine equivalent-circuit that represents a system of nonlineal equations and requires one of the rotor-parameters arbitrary assignment. The article demonstrates that for the asynchronous machine equivalent-circuit experimental parameterization the measures are to be conducted of the stator-circuit voltage, current and active power with two different slides and arbitrary assignment of one of the rotor parameters. The paper substantiates the fact that additional measurement does not discard the rotor-parameter choice arbitrariness. The authors establish that in motoring mode there is a critical slide by which the

  11. An experimental study on the effect of parameters on the depth of crater machined by electrostatic field–induced electrolyte jet micro electrical discharge machining

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    Yaou Zhang

    2016-04-01

    Full Text Available Electrostatic field–induced electrolyte jet micro electrical discharge machining depends on heat generated by the periodic pulsed discharge between the workpiece and the electrolyte fine jet from the tip of Taylor cone, induced by the intense electric field, to erode the material from the workpiece. To further investigate the characteristics of this discharge process, with the NaCl solution as the electrostatic field–induced electrolyte jet electrolyte and the silicon wafer as the workpiece, the governing factors of machining polarity, nozzle-to-workpiece distance, voltage applied between positive and negative polarities, and the effect of concentration of the electrolyte on the depth of crater after a single electrostatic field–induced electrolyte jet discharge have been studied. The experimental results show that the average depth of crater increases with the increase in the voltage applied between the nozzle and the workpiece, and increases with the increase in the concentration of the electrolyte, but decreases with the increase in the distance between the nozzle and the workpiece. The results have also demonstrated that the polarity has no clear influence on the average depth of crater after a single discharge.

  12. Machinability study of Carbon Fiber Reinforced Polymer in the longitudinal and transverse direction and optimization of process parameters using PSO–GSA

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    K. Shunmugesh

    2016-09-01

    Full Text Available Carbon Fiber Reinforced Polymer (CFRP composites are widely used in aerospace industry in lieu of its high strength to weight ratio. This study is an attempt to evaluate the machinability of Bi-Directional Carbon Fiber–Epoxy composite and optimize the process parameters of cutting speed, feed rate and drill tool material. Machining trials were carried using drill bits made of high speed steel, TiN and TiAlN at different cutting speeds and feed rates. Output parameters of thrust force and torque were monitored using Kistler multicomponent dynamometer 9257B and vibrations occurring during machining normal to the work surface were measured by a vibration sensor (Dytran 3055B. Linear regression analysis was carried out by using Response Surface Methodology (RSM, to correlate the input and output parameters in drilling of the composite in the longitudinal and transverse directions. The optimization of process parameters were attempted using Genetic Algorithm (GA and Particle Swarm Optimization–Gravitational Search Algorithm (PSO–GSA techniques.

  13. A Review on Experimental Investigation of Machining Parameters during CNC Machining of OHNS

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    Surabhi Lata

    2016-02-01

    Full Text Available This review paper aims towards the optimization of CNC turning operation when used over an OHNS material. The lathe machine was chosen because of its widespread availability and its ability to perform various tasks without much change in its structure. Also using lathe machines is very cheap and hence it is beneficial from economic point of view as well. The turning operation was specifically chosen because of the various advantages that it offers. It can be used for machining a large variety of materials and it is cheaper than milling. OHNS (Oil Hardened Non Shrinking tool was chosen due to its hardness. These materials are used only for dies so it was chosen so that its industrial usage could be exploited. To comprehend the usage, all the input and output parameters that could affect the machining process, namely input parameters like feed, cutting conditions, speed, etc. and output parameters like surface roughness, surface finish, material removal rate were analyzed using the researches that had already been done on CNC turning. After careful study of a variety of research papers on this topic, it was decided that several input as well as the output parameters would be considered which included feed, depth of cut and cutting speed were taken as the input parameters whereas Material Removal Rate (MRR and surface finish were taken as the output parameters. From the results of the research papers, it was concluded that feed, depth of cut and cutting speed could be chosen as input parameters whereas MRR and surface finish would be the output parameters.

  14. Machinability studies on INCONEL 718

    Science.gov (United States)

    Xavior, M. Anthony; Patil, Mahesh; Maiti, Abheek; Raj, Mrinal; Lohia, Nitesh

    2016-09-01

    The main objective of proposed work is to determine the influence of controllable parameters on machining characteristics of Inconel-718 and to achieve the optimum parameters for sustainable and efficient turning. Understanding the consequences of advanced tool materials together with higher cutting speeds on the formation of residual stresses and therefore the underlying mechanisms of small structural alteration within the subterranean layer thereby becomes terribly crucial for predicting product quality and more optimizing the machining conditions. Controllable cutting parameters such as cutting velocity, feed rate and depth of cut were selected at different level for experimentations in accordance with the Taguchi L9 array method using Minimum Quantity Lubrication (MQL) cutting condition and three different tools namely PVD TiAlN carbide, Cubic boron nitride and ceramic. Extensive study is done on the resulting surface roughness, surface subsurface hardness, tool wear and chip morphology. The results obtained from each of the tool were thoroughly analyzed and finally the optimized parameters are obtained for efficient machining of Inconel 718.

  15. Multi-Parameter Analysis of Surface Finish in Electro-Discharge Machining of Tool Steels

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    Cornelia Victoria Anghel

    2006-10-01

    Full Text Available The paper presents a multi- parameter analysis of surface finish imparted to tool-steel plates by electro-discharge machining (EDM is presented. The interrelationship between surface texture parameters and process parameters is emphasized. An increased number of parameters is studied including amplitude, spacing, hybrid and fractal parameters,, as well. The correlation of these parameters with the machining conditions is investigated. Observed characteristics become more pronounced, when intensifying machining conditions. Close correlation exists between certain surface finish parameters and EDM input variables and single and multiple statistical regression models are developed.

  16. Identification of Mechanical parameters for Resistance Welding Machines

    DEFF Research Database (Denmark)

    Wu, Pei; Zhang, Wenqi; Bay, Niels

    2003-01-01

    Mechanical dynamic responses of resistance welding machine have a significant influence on weld quality and electrode service life, it must be considered when the real welding production is carried out or the welding process is simulated. The mathematical models for characterizing the mechanical...... to the complexities and differences of machine constructions. In this paper, a method of identifying the machine mechanical parameters based on the measured data is presented no matter how the machine construction and what types of machine are. The computations are implemented in MATLAB....

  17. Identification of Mechanical parameters for Resistance Welding Machines

    DEFF Research Database (Denmark)

    Wu, Pei; Zhang, Wenqi; Bay, Niels

    2003-01-01

    Mechanical dynamic responses of resistance welding machine have a significant influence on weld quality and electrode service life, it must be considered when the real welding production is carried out or the welding process is simulated. The mathematical models for characterizing the mechanical...... to the complexities and differences of machine constructions. In this paper, a method of identifying the machine mechanical parameters based on the measured data is presented no matter how the machine construction and what types of machine are. The computations are implemented in MATLAB....

  18. Application of case-based reasoning for machining parameters selection

    Science.gov (United States)

    Grabowik, C.; Kalinowski, K.; Krenczyk, D.; Paprocka, I.; Kempa, W.

    2016-08-01

    Process planning, as one of the most important stage of the technological production preparation, consists in selection of manufacturing operations taking into account the minimal manufacturing cost. The minimal manufacturing cost could be achieved by selection of the best sequence of manufacturing operations, machine tools, manufacturing tools, and accompanying machining parameters selection. On the other hand, it is almost impossible, especially in industrial conditions, to design an optimal process plan, first of all due to restrictions imposed by the installed in the factory machine park. Taking into consideration above, machining parameter selection seems to be one of the potential areas of optimization. In manual process planning process engineers select machining parameters using selection rules and data stored in manuals and tool catalogues. It makes this process time and labour consuming and non-error free. On the other hand, in workshop practice, machine operators select parameters having their skills and habits in mind. It could be a reason for suboptimal process planning. Considering this, new methods of machining parameters selection free of human factor influence are still sought. In our approach, we propose to apply case-based reasoning for machining parameter selection. In the paper, a detailed description of our approach is presented.

  19. Experimental Investigation of Machining Parameters in Drilling Operation Using Conventional and CNC Machines on Titanium Alloy

    Directory of Open Access Journals (Sweden)

    B.Suresh kumar

    2014-05-01

    Full Text Available Titanium alloy is one of the newer materials in manufacturing industries due to its high strength to weight ratio and corrosion resistance properties. Making a hole on this component is very difficult task due to its poor machinability. Hence, the machining parameter investigation on titanium alloy material is very important for predicting the drilling performance characteristics. In addition, the modern manufacturing industries are used the conventional drilling machine and CNC drilling machines for making a hole. In the sense, the main aim of this work is to investigate the machining parameters on vibration, thrust force, torque, machining time, burr dimension, tool wear and surface roughness occurrences when drilling titanium alloy with conventional and CNC machines. The effects of spindle speed and feed rate on these responses were reported.

  20. Parameter optimization model in electrical discharge machining process

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    Electrical discharge machining (EDM) process, at present is still an experience process, wherein selected parameters are often far from the optimum, and at the same time selecting optimization parameters is costly and time consuming. In this paper,artificial neural network (ANN) and genetic algorithm (GA) are used together to establish the parameter optimization model. An ANN model which adapts Levenberg-Marquardt algorithm has been set up to represent the relationship between material removal rate (MRR) and input parameters, and GA is used to optimize parameters, so that optimization results are obtained. The model is shown to be effective, and MRR is improved using optimized machining parameters.

  1. Nano-scale machining of polycrystalline coppers - effects of grain size and machining parameters.

    Science.gov (United States)

    Shi, Jing; Wang, Yachao; Yang, Xiaoping

    2013-11-22

    In this study, a comprehensive investigation on nano-scale machining of polycrystalline copper structures is carried out by molecular dynamics (MD) simulation. Simulation cases are constructed to study the impacts of grain size, as well as various machining parameters. Six polycrystalline copper structures are produced, which have the corresponding equivalent grain sizes of 5.32, 6.70, 8.44, 13.40, 14.75, and 16.88 nm, respectively. Three levels of depth of cut, machining speed, and tool rake angle are also considered. The results show that greater cutting forces are required in nano-scale polycrystalline machining with the increase of depth of cut, machining speed, and the use of the negative tool rake angles. The distributions of equivalent stress are consistent with the cutting force trends. Moreover, it is discovered that in the grain size range of 5.32 to 14.75 nm, the cutting forces and equivalent stress increase with the increase of grain size for the nano-structured copper, while the trends reserve after the grain size becomes even higher. This discovery confirms the existence of both the regular Hall-Petch relation and the inverse Hall-Petch relation in polycrystalline machining, and the existence of a threshold grain size allows one of the two relations to become dominant. The dislocation-grain boundary interaction shows that the resistance of the grain boundary to dislocation movement is the fundamental mechanism of the Hall-Petch relation, while grain boundary diffusion and movement is the reason of the inverse Hall-Petch relation.

  2. Machine Self-Teaching Methods for Parameter Optimization.

    Science.gov (United States)

    1986-12-01

    A199 285 MACHINE SELF- TEACHING METHODS FOR PARAMETER / OPTIMIZATION(U) NAVAL OCEAN SYSTEMS CENTER SAN DIEGO CA R A DILLARD DEC 86 NOSC/TR-1S39...Technical Document 1039 C) ,December 1986 Machine Self- Teaching Methods for Parameter Optimization Robin A. Dillard DTICS ELECTE MAY i01 𔄁 STAra Approved...ELEMEWt NO PROECi’ No TASK NO ARC Locally FundedI I1 I TE (ewd* Seawmy Cft*Wi., Machine Self- Teaching Methods for Parameter Optimization it PERSONAL

  3. Experimental Investigation of process parameters influence on machining Inconel 800 in the Electrical Spark Eroding Machine

    Science.gov (United States)

    Karunakaran, K.; Chandrasekaran, M.

    2016-11-01

    The Electrical Spark Eroding Machining is an entrenched sophisticated machining process for producing complex geometry with close tolerances in hard materials like super alloy which are extremely difficult-to-machine by using conventional machining processes. It is sometimes offered as a better alternative or sometimes as an only alternative for generating accurate 3D complex shapes of macro, micro and nano-features in such difficult-to-machine materials among other advanced machining processes. The accomplishment of such challenging task by use of Electrical Spark Eroding Machining or Electrical Discharge Machining (EDM) is depending upon selection of apt process parameters. This paper is about analyzing the influencing of parameter in electrical eroding machining for Inconel 800 with electrolytic copper as a tool. The experimental runs were performed with various input conditions to process Inconel 800 nickel based super alloy for analyzing the response of material removal rate, surface roughness and tool wear rate. These are the measures of performance of individual experimental value of parameters such as pulse on time, Pulse off time, peak current. Taguchi full factorial Design by using Minitab release 14 software was employed to meet the manufacture requirements of preparing process parameter selection card for Inconel 800 jobs. The individual parameter's contribution towards surface roughness was observed from 13.68% to 64.66%.

  4. Inrush Current Simulation of Power Transformer using Machine Parameters Estimated by Design Procedure of Winding Structure and Genetic Algorithm

    Science.gov (United States)

    Tokunaga, Yoshitaka

    This paper presents estimation techniques of machine parameters for power transformer using design procedure of transformer and genetic algorithm with real coding. Especially, it is very difficult to obtain machine parameters for transformers in customers' facilities. Using estimation techniques, machine parameters could be calculated from the only nameplate data of these transformers. Subsequently, EMTP-ATP simulation of the inrush current was carried out using machine parameters estimated by techniques developed in this study and simulation results were reproduced measured waveforms.

  5. Parameter Identifiability in Statistical Machine Learning: A Review.

    Science.gov (United States)

    Ran, Zhi-Yong; Hu, Bao-Gang

    2017-05-01

    This review examines the relevance of parameter identifiability for statistical models used in machine learning. In addition to defining main concepts, we address several issues of identifiability closely related to machine learning, showing the advantages and disadvantages of state-of-the-art research and demonstrating recent progress. First, we review criteria for determining the parameter structure of models from the literature. This has three related issues: parameter identifiability, parameter redundancy, and reparameterization. Second, we review the deep influence of identifiability on various aspects of machine learning from theoretical and application viewpoints. In addition to illustrating the utility and influence of identifiability, we emphasize the interplay among identifiability theory, machine learning, mathematical statistics, information theory, optimization theory, information geometry, Riemann geometry, symbolic computation, Bayesian inference, algebraic geometry, and others. Finally, we present a new perspective together with the associated challenges.

  6. TRANSLATOR OF FINITE STATE MACHINE MODEL PARAMETERS FROM MATLAB ENVIRONMENT INTO HUMAN-MACHINE INTERFACE APPLICATION

    OpenAIRE

    2012-01-01

    Technology and means for automatic translation of FSM model parameters from Matlab application to human-machine interface application is proposed. The example of technology application to the electric apparatus model is described.

  7. Parameter identification and slip estimation of induction machine

    Science.gov (United States)

    Orman, Maciej; Orkisz, Michal; Pinto, Cajetan T.

    2011-05-01

    This paper presents a newly developed algorithm for induction machine rotor speed estimation and parameter detection. The proposed algorithm is based on spectrum analysis of the stator current. The main idea is to find the best fit of motor parameters and rotor slip with the group of characteristic frequencies which are always present in the current spectrum. Rotor speed and parameters such as pole pairs or number of rotor slots are the results of the presented algorithm. Numerical calculations show that the method yields very accurate results and can be an important part of machine monitoring systems.

  8. Linear Parameter Varying Control of Doubly Fed Induction Machines

    NARCIS (Netherlands)

    Tien, H. Nguyen; Scherer, Carsten W.; Scherpen, Jacquelien M.A.; Müller, Volkmar

    2016-01-01

    This paper is concerned with the design of a self-scheduled current controller for doubly fed induction machines. The design is based on the framework of linear parameter-varying systems where the mechanical angular speed is considered to be a measurable time-varying parameter. The objective is to o

  9. Application of RBF Neural Network in OptimizingMachining Parameters

    Institute of Scientific and Technical Information of China (English)

    朱喜林; 吴博达; 武星星

    2004-01-01

    In machining processes, errors of rough in dimension, shape and location lead to changes in processing quantity, and the material of a workpiece may not be uniform. For these reasons, cutting force changes in machining, making the machining system deformable. Consequently errors in workpieces may occur. This is called the error reflection phenomenon. Generally, such errors can be reduced through repeated processing while using appropriate processing quantity in each processing based on operator's experience.According to the theory of error reflection, the error reflection coefficient indicates the extent to which errors of rough influence errors of workpieces. It is related to several factors such as machining condition, hardness of the workpiece, etc. This non-linear relation cannot be worked out using any formula. RBF neural network can approximate a non-linear function within any precision and be trained fast. In this paper, non-linear mapping ability of a fuzzy-neural network is utilized to approximate the non-linear relation. After training of the network with swatch collection obtained in experiments, an appropriate output can be obtained when an input is given. In this way, one can get the required number of processing and the processing quantity each time from the machining condition. Angular rigidity of a machining system,hardness of workpiece, etc., can be input in a form of fuzzy values. Feasibility in solving error reflection and optimizing machining parameters with a RBF neural network is verified by a simulation test with MATLAB.

  10. Strategic Optimization and Investigation Effect Of Process Parameters On Performance Of Wire Electric Discharge Machine (WEDM

    Directory of Open Access Journals (Sweden)

    ATUL KUMAR

    2012-06-01

    Full Text Available Wire electrical discharge machining (WEDM is widely used in machining of conductive materials when precision is of primary significance. Wire-cut electric discharge machining of Skd 61alloy has been considered in the present work. Experimentation has been completed by using Taguchi’s L18 (21x37 orthogonal array under different conditions of parameters. Optimal combinations of parameters were obtained by this technique. The study shows that with the minimum number of experiments the complete problem can be solvedwhen compared to full factorial design. Experimental results make obvious that the machining model is proper and the Taguchi’s method satisfies the practical conditions. The results obtained are analyzed for the selection of an optimal combination of WEDM parameters for proper machining of Skd 61 alloy to achieve better surface finish. Different analysis was made on the data obtained from the experiments.

  11. A GEOBIA framework to estimate forest parameters from lidar transects, Quickbird imagery and machine learning: A case study in Quebec, Canada

    Science.gov (United States)

    Chen, Gang; Hay, Geoffrey J.; St-Onge, Benoît

    2012-04-01

    The GEOgraphic Object-Based Image Analysis (GEOBIA) paradigm continues to prove its efficacy in remote sensing image analysis by providing tools which emulate human perception and combine analyst's experience with meaningful image-objects. However, challenges remain in the evolution of this new paradigm as sophisticated methods attempt to deliver on the goal of automated geo-intelligence (i.e., geospatial content within context) from geospatial sources. In order to generate geo-intelligence from a forest scene, this article introduces a GEOBIA framework to estimate canopy height, above-ground biomass (AGB) and volume by combining lidar (light detection and ranging) transects, Quickbird imagery and machine learning algorithms. This framework is comprised three main components: (i) image-object extraction, (ii) lidar transect selection, and (iii) forest parameter generalization. The rational for integrating these methods is to provide a semi-automatic GEOBIA approach from which detailed forest information is obtained at the individual tree crown or small tree cluster level (i.e., mean object size of 0.04 ha); while also dramatically reducing airborne lidar data acquisition costs. Analysis is performed over a 16,330 ha forested study site in Quebec, Canada. Forest parameter estimation results derived from our GEOBIA framework demonstrate a strong relationship with those using the full lidar cover; where the highest estimates for canopy height ( R = 0.85; RMSE = 3.37 m), AGB ( R = 0.85; RMSE = 39.48 Mg/ha) and volume ( R = 0.85; RMSE = 52.59 m 3/ha) were achieved using a lidar transect sample representing only 7.6% of the total study area.

  12. Influence of Induction Machine and Mechanism Parameters on Starting Transient Processes in Case of Constant Load Conditions

    Directory of Open Access Journals (Sweden)

    Dimitar Spirov

    2005-10-01

    Full Text Available Two-phase induction machine dynamic model in a coordinate system which rotates at synchronous speed and one-mass dynamic model of mechanism driven in relative units describing transient processes when starting an induction machine in case of constant load conditions are developed.The influence of equivalent circuit parameters of induction machine and mechanism parameters on impact currents and torques and starting time of common used induction machines is studied by means of design of experiment method.

  13. Effect of machining parameters on surface finish of Inconel 718 in end milling

    Directory of Open Access Journals (Sweden)

    Sarkar Bapi

    2017-01-01

    Full Text Available Surface finish is an important criteria in machining process and selection of proper machining parameters is important to obtain good surface finish. In the present work effects of the machining parameters in end milling of Inconel 718 were investigated. Central composite design was used to design the total number of experiments. A Mathematical model for surface roughness has been developed using response surface methodology. In this study, the influence of cutting parameters such as cutting speed, feed rate and depth of cut on surface roughness was analyzed. The study includes individual effect of cutting parameters on surface roughness as well as their interaction. The analysis of variance (ANOVA was employed to find the validity of the developed model. The results show that depth of cut mostly affected the surface roughness. It is also observed that surface roughness values are comparable in both dry and wet machining conditions.

  14. Selection of parameters for advanced machining processes using firefly algorithm

    Directory of Open Access Journals (Sweden)

    Rajkamal Shukla

    2017-02-01

    Full Text Available Advanced machining processes (AMPs are widely utilized in industries for machining complex geometries and intricate profiles. In this paper, two significant processes such as electric discharge machining (EDM and abrasive water jet machining (AWJM are considered to get the optimum values of responses for the given range of process parameters. The firefly algorithm (FA is attempted to the considered processes to obtain optimized parameters and the results obtained are compared with the results given by previous researchers. The variation of process parameters with respect to the responses are plotted to confirm the optimum results obtained using FA. In EDM process, the performance parameter “MRR” is increased from 159.70 gm/min to 181.6723 gm/min, while “Ra” and “REWR” are decreased from 6.21 μm to 3.6767 μm and 6.21% to 6.324 × 10−5% respectively. In AWJM process, the value of the “kerf” and “Ra” are decreased from 0.858 mm to 0.3704 mm and 5.41 mm to 4.443 mm respectively. In both the processes, the obtained results show a significant improvement in the responses.

  15. Study on spectral parameters and the support vector machine in surface enhanced Raman spectroscopy of serum for the detection of colon cancer

    Science.gov (United States)

    Li, Xiaozhou; Yang, Tianyue; Li, Siqi; Yao, Jun; Song, Youtao; Wang, Deli; Ding, Jianhua

    2015-11-01

    Surface enhanced Raman spectroscopy (SERS) has been recognized as an effective tool for the analysis of tissue samples and biofluids. In this work, a total of 27 spectral parameters were chosen and compared using SERS. Four parameters with the highest prediction ability were selected for further support vector machine (SVM) analysis. As a comparison, principal component analysis (PCA) was used on the same dataset for feature extraction. SVM was used with the above two data reduction methods separately to differentiate colon cancer and the control groups. Serum taken from 52 colon cancer patients and 60 healthy volunteers were collected and tested by SERS. The accuracy for Parameter-SVM was 95.0%, the sensitivity was 96.2%, and the specificity was 95.5%, which was much higher than the results using only one parameter, while for PCA-SVM, the results are 93.3%, 92.3%, and 92.9%, respectively. These results demonstrate that the SERS analysis method can be used to identify serum differences between colon cancer patients and normal people.

  16. Effect of Implantation Machine Parameters on N+ ion Implantation for Upland Cotton (Gossypium hirsutum L.) Pollen

    Institute of Scientific and Technical Information of China (English)

    YUE Jieyu; YU Lixiang; WU Yuejin; TANG Canming

    2008-01-01

    Effect of parameters of ion implantation machine,including ion energy,total dose,dose rate,impulse energy and implantation interval on the pollen grains of upland cotton implanted with nitrogen ion beam were studied.The best parameters were screened out.The results also showed that the vacuum condition before the nitrogen ion implantation does not affect the pollen viability.

  17. A study of electrodischarge machining–pulse electrochemical machining combined machining for holes with high surface quality on superalloy

    Directory of Open Access Journals (Sweden)

    Ning Ma

    2015-11-01

    Full Text Available Noncircular holes on the surface of turbine rotor blades are usually machined by electrodischarge machining. A recast layer containing numerous micropores and microcracks is easily generated during the electrodischarge machining process due to the rapid heating and cooling effects, which restrict the wide applications of noncircular holes in aerospace and aircraft industries. Owing to the outstanding advantages of pulse electrochemical machining, electrodischarge machining–pulse electrochemical machining combined technique is provided to improve the overall quality of electrodischarge machining-drilled holes. The influence of pulse electrochemical machining processing parameters on the surface roughness and the influence of the electrodischarge machining–pulse electrochemical machining method on the surface quality and accuracy of holes have been studied experimentally. The results indicate that the pulse electrochemical machining processing time for complete removal of the recast layer decreases with the increase in the pulse electrochemical machining current. The low pulse electrochemical machining current results in uneven dissolution of the recast layer, while the higher pulse electrochemical machining current induces relatively homogeneous dissolution. The surface roughness is reduced from 4.277 to 0.299 µm, and the hole taper induced by top-down electrodischarge machining process was reduced from 1.04° to 0.17° after pulse electrochemical machining. On account of the advantages of electrodischarge machining and the pulse electrochemical machining, the electrodischarge machining–pulse electrochemical machining combined technique could be applied for machining noncircular holes with high shape accuracy and surface quality.

  18. A Two-stage Tuning Method of Servo Parameters for Feed Drives in Machine Tools

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Based on the evaluation of dynamic performance for feed drives in machine tools, this paper presents a two-stage tuning method of servo parameters. In the first stage, the evaluation of dynamic performance, parameter tuning and optimization on a mechatronic integrated system simulation platform of feed drives are performed. As a result, a servo parameter combination is acquired. In the second stage, the servo parameter combination from the first stage is set and tuned further in a real machine tool whose dynamic performance is measured and evaluated using the cross grid encoder developed by Heidenhain GmbH. A case study shows that this method simplifies the test process effectively and results in a good dynamic performance in a real machine tool.

  19. Determining Machining Parameters of Corn Byproduct Filled Plastics

    Science.gov (United States)

    In a collaborative project between the USDA and Northern Illinois University, the use of corn ethanol processing byproducts (i.e., DDGS) as bio-filler materials in the compression molding of phenolic plastics has been studied. This paper reports on the results of a machinability study in the milling...

  20. Determination of Machining Parameters of Corn Byproduct Filled Plastics

    Science.gov (United States)

    In a collaborative project between the USDA and Northern Illinois University, the use of ethanol corn processing by-products as bio-filler materials in the compression molding of phenolic plastics has been studied. This paper reports on the results of a machinability study in the milling of various ...

  1. Influence of electrical resistivity and machining parameters on electrical discharge machining performance of engineering ceramics.

    Science.gov (United States)

    Ji, Renjie; Liu, Yonghong; Diao, Ruiqiang; Xu, Chenchen; Li, Xiaopeng; Cai, Baoping; Zhang, Yanzhen

    2014-01-01

    Engineering ceramics have been widely used in modern industry for their excellent physical and mechanical properties, and they are difficult to machine owing to their high hardness and brittleness. Electrical discharge machining (EDM) is the appropriate process for machining engineering ceramics provided they are electrically conducting. However, the electrical resistivity of the popular engineering ceramics is higher, and there has been no research on the relationship between the EDM parameters and the electrical resistivity of the engineering ceramics. This paper investigates the effects of the electrical resistivity and EDM parameters such as tool polarity, pulse interval, and electrode material, on the ZnO/Al2O3 ceramic's EDM performance, in terms of the material removal rate (MRR), electrode wear ratio (EWR), and surface roughness (SR). The results show that the electrical resistivity and the EDM parameters have the great influence on the EDM performance. The ZnO/Al2O3 ceramic with the electrical resistivity up to 3410 Ω·cm can be effectively machined by EDM with the copper electrode, the negative tool polarity, and the shorter pulse interval. Under most machining conditions, the MRR increases, and the SR decreases with the decrease of electrical resistivity. Moreover, the tool polarity, and pulse interval affect the EWR, respectively, and the electrical resistivity and electrode material have a combined effect on the EWR. Furthermore, the EDM performance of ZnO/Al2O3 ceramic with the electrical resistivity higher than 687 Ω·cm is obviously different from that with the electrical resistivity lower than 687 Ω·cm, when the electrode material changes. The microstructure character analysis of the machined ZnO/Al2O3 ceramic surface shows that the ZnO/Al2O3 ceramic is removed by melting, evaporation and thermal spalling, and the material from the working fluid and the graphite electrode can transfer to the workpiece surface during electrical discharge

  2. Influence of electrical resistivity and machining parameters on electrical discharge machining performance of engineering ceramics.

    Directory of Open Access Journals (Sweden)

    Renjie Ji

    Full Text Available Engineering ceramics have been widely used in modern industry for their excellent physical and mechanical properties, and they are difficult to machine owing to their high hardness and brittleness. Electrical discharge machining (EDM is the appropriate process for machining engineering ceramics provided they are electrically conducting. However, the electrical resistivity of the popular engineering ceramics is higher, and there has been no research on the relationship between the EDM parameters and the electrical resistivity of the engineering ceramics. This paper investigates the effects of the electrical resistivity and EDM parameters such as tool polarity, pulse interval, and electrode material, on the ZnO/Al2O3 ceramic's EDM performance, in terms of the material removal rate (MRR, electrode wear ratio (EWR, and surface roughness (SR. The results show that the electrical resistivity and the EDM parameters have the great influence on the EDM performance. The ZnO/Al2O3 ceramic with the electrical resistivity up to 3410 Ω·cm can be effectively machined by EDM with the copper electrode, the negative tool polarity, and the shorter pulse interval. Under most machining conditions, the MRR increases, and the SR decreases with the decrease of electrical resistivity. Moreover, the tool polarity, and pulse interval affect the EWR, respectively, and the electrical resistivity and electrode material have a combined effect on the EWR. Furthermore, the EDM performance of ZnO/Al2O3 ceramic with the electrical resistivity higher than 687 Ω·cm is obviously different from that with the electrical resistivity lower than 687 Ω·cm, when the electrode material changes. The microstructure character analysis of the machined ZnO/Al2O3 ceramic surface shows that the ZnO/Al2O3 ceramic is removed by melting, evaporation and thermal spalling, and the material from the working fluid and the graphite electrode can transfer to the workpiece surface during electrical

  3. Machine Learning of the Reactor Core Loading Pattern Critical Parameters

    Directory of Open Access Journals (Sweden)

    Krešimir Trontl

    2008-01-01

    Full Text Available The usual approach to loading pattern optimization involves high degree of engineering judgment, a set of heuristic rules, an optimization algorithm, and a computer code used for evaluating proposed loading patterns. The speed of the optimization process is highly dependent on the computer code used for the evaluation. In this paper, we investigate the applicability of a machine learning model which could be used for fast loading pattern evaluation. We employ a recently introduced machine learning technique, support vector regression (SVR, which is a data driven, kernel based, nonlinear modeling paradigm, in which model parameters are automatically determined by solving a quadratic optimization problem. The main objective of the work reported in this paper was to evaluate the possibility of applying SVR method for reactor core loading pattern modeling. We illustrate the performance of the solution and discuss its applicability, that is, complexity, speed, and accuracy.

  4. Justification for parameters of a dynamic stabilizer of the experimental stand mobile unit in studying of active rotational working tools of tiller machines

    Directory of Open Access Journals (Sweden)

    Vladimir F. Kupryashkin

    2017-03-01

    Full Text Available Introduction: The article deals with design options and technological modes of the dynamic stabilizer of the experimental stand mobile unit for studying tillage machine active rotating work tools. Based on theoretical and experimental studies, the possibility the movable module instability was discovered. This negatively affects on implementing the experiment program trough the especific method. The need in engineering solutions for the defect correction is shown. In addition, the authors consider the structural features and characteristics of the used devices for providing the stabilization of the movable module in the study of active rotating work tools of tillage machines. An electromagnetic brake dynamic stabilizer in the structure of the existing rolling module was proposed as an engineering device. Materials and Methods: A theoretical study of rolling module stability, based on synthesis of basic regulations and laws of mechanics related to active rotating work tools was conducted. As a result of the theoretical research, a design scheme of movable module loading was created. This scheme includes the design features and structural power factors. Results: A database representing the settings of power specification in the motion stability determining the mobile unit was created. Further use of the database values allow supporting the most optimal location of the electromagnetic brake with its design options. Discussion and Conclusions: The research of the electromagnetic brake in a mobile unit promoted stabilizing the unit movement, increased the frequency of its use and provided data that are more precise during experiments.

  5. Optimization of the Machining parameter of LM6 Alminium alloy in CNC Turning using Taguchi method

    Science.gov (United States)

    Arunkumar, S.; Muthuraman, V.; Baskaralal, V. P. M.

    2017-03-01

    Due to widespread use of highly automated machine tools in the industry, manufacturing requires reliable models and methods for the prediction of output performance of machining process. In machining of parts, surface quality is one of the most specified customer requirements. In order for manufactures to maximize their gains from utilizing CNC turning, accurate predictive models for surface roughness must be constructed. The prediction of optimum machining conditions for good surface finish plays an important role in process planning. This work deals with the study and development of a surface roughness prediction model for machining LM6 aluminum alloy. Two important tools used in parameter design are Taguchi orthogonal arrays and signal to noise ratio (S/N). Speed, feed, depth of cut and coolant are taken as process parameter at three levels. Taguchi’s parameters design is employed here to perform the experiments based on the various level of the chosen parameter. The statistical analysis results in optimum parameter combination of speed, feed, depth of cut and coolant as the best for obtaining good roughness for the cylindrical components. The result obtained through Taguchi is confirmed with real time experimental work.

  6. Optimal Parameter Selection for Support Vector Machine Based on Artificial Bee Colony Algorithm: A Case Study of Grid-Connected PV System Power Prediction

    Directory of Open Access Journals (Sweden)

    Xiang-ming Gao

    2017-01-01

    Full Text Available Predicting the output power of photovoltaic system with nonstationarity and randomness, an output power prediction model for grid-connected PV systems is proposed based on empirical mode decomposition (EMD and support vector machine (SVM optimized with an artificial bee colony (ABC algorithm. First, according to the weather forecast data sets on the prediction date, the time series data of output power on a similar day with 15-minute intervals are built. Second, the time series data of the output power are decomposed into a series of components, including some intrinsic mode components IMFn and a trend component Res, at different scales using EMD. The corresponding SVM prediction model is established for each IMF component and trend component, and the SVM model parameters are optimized with the artificial bee colony algorithm. Finally, the prediction results of each model are reconstructed, and the predicted values of the output power of the grid-connected PV system can be obtained. The prediction model is tested with actual data, and the results show that the power prediction model based on the EMD and ABC-SVM has a faster calculation speed and higher prediction accuracy than do the single SVM prediction model and the EMD-SVM prediction model without optimization.

  7. Studies for obtaining a small holle, rapid edm drilling machine

    Directory of Open Access Journals (Sweden)

    Mihai Şimon

    2011-12-01

    Full Text Available This paper studies the obtaining of an experimental rapid drilling machine, through EDM process for small holes. The best parameters such as peak current, pulse frequency, duty factor and electrode rotation speed were studied for best machining characteristics. An electrolytic copper rod 0.8 mm diameter was selected as a tool electrode. The experiments generate output responses such as maximum material removal rate (MRR and the dependence with peak current, duty factor and Electrode rotation, parameters. Finally, parameters were optimized for maximum MRR with desired surface roughness value and used for sizing the component for a better small rapid drilling machine.

  8. Optimizing the Machining Parameters for Minimum Surface Roughness in Turning of GFRP Composites Using Design of Experiments

    Institute of Scientific and Technical Information of China (English)

    K. Palanikumar; L.Karunamoorthy; R.Karthikeyan

    2004-01-01

    In recent years, glass fiber reinforced plastics (GFRP) are being extensively used in variety of engineering applications in many different fields such as aerospace, oil, gas and process industries. However, the users of FRP are facing difficulties to machine it, because of fiber delamination, fiber pull out, short tool life, matrix debonding, burning and formation of powder like chips. The present investigation focuses on the optimization of machining parameters for surface roughness of glass fiber reinforced plastics (GFRP) using design of experiments (DoE). The machining parameters considered were speed, feed, depth of cut and workpiece (fiber orientation). An attempt was made to analyse the influence of factors and their interactions during machining. The results of the present study gives the optimal combination of machining parameters and this will help to improve the machining requirements of GFRP composites.

  9. Helical Milling of CFRP/Ti-6Al-4V Stacks with Varying Machining Parameters

    Institute of Scientific and Technical Information of China (English)

    He Gaiyun; Li Hao; Jiang Yuedong; Qin Xuda; Zhang Xinpei; Guan Yi

    2015-01-01

    The hole-making process in stack materials consisting of carbon fiber reinforced plastics(CFRP) and Ti-6Al-4V remains a critical challenge. In this paper, an experimental study on the helical milling of CFRP/Ti-6Al-4V stacks was conducted by using two different machining strategies. Helical milling strategyⅠmachines both materials with identical machining parameters, while machining strategyⅡuses two sets of machining parameters to machine each material. Helical milling performance was evaluated by the following indicators: tool life, cutting forces, hole quality(including diameter deviation, roundness, roughness, and hole edge quality). The results demonstrate that heli-cal milling strategyⅡoutperformed strategyⅠ, leading to longer tool life(up to 48 holes), smaller cutting forces and better hole quality with higher geometric accuracy and smoother surface finish(Ra≤0.58μm for Ti-6Al-4V and Ra≤0.81μm for CFRP), eliminating the need for reaming or de-burring.

  10. APPLICATION DIMENSIONAL AND SIMILARITY THEORY IN DETERMINING THE PARAMETERS AND OPERATING MODES OF SOIL CULTIVATING MACHINES

    Directory of Open Access Journals (Sweden)

    Shhirov V. N.

    2015-06-01

    Full Text Available The article presents a study of parameters and modes of operation of machines for soil cultivation. In determining the parameters and modes of operation of machinery for tillage we have applied the theory of similarity and dimensions of physical quantities. We have obtained the regularities of disclosing the relationship of the parameters from the medium to the energy characteristics of the process. As the initial data we used test protocols of machines for soil cultivation (Central - Black Earth, Kubanskaya, Sibirskaya, of North - Caucasion MIS, RosNIITiM : KPI - 3.8, AРC - 3.9, AKV - 4, AKM - 6 - V, AMP - 4 APC - 4 A, AРC - 10 APR - 4.4, APU - 6.5 APSH - 6 , CNC - 6.0, CSТ - 3.8, APC - 4. We defined the formula оf dimension parameters and modes of operation of machines for soil cultivation and properties of soil (traction resistance, depth, width, speed, hardness of the soil, acceleration. Based on dimension theory we have received similarity criteria. Based on the correlation analysis and the least squares method we determined the nature of addiction and the coefficients for it. We have also received a graph for determining the operating modes and parameters of machines for soil cultivation

  11. Multi criteria decision making of machining parameters for Die Sinking EDM Process

    Directory of Open Access Journals (Sweden)

    G. K. Bose

    2015-04-01

    Full Text Available Electrical Discharge Machining (EDM is one of the most basic non-conventional machining processes for production of complex geometries and process of hard materials, which are difficult to machine by conventional process. It is capable of machining geometrically complex or hard material components, that are precise and difficult-to-machine such as heat-treated tool steels, composites, super alloys, ceramics, carbides, heat resistant steels etc. The present study is focusing on the die sinking electric discharge machining (EDM of AISI H 13, W.-Nr. 1.2344 Grade: Ovar Supreme for finding out the effect of machining parameters such as discharge current (GI, pulse on time (POT, pulse off time (POF and spark gap (SG on performance response like Material removal rate (MRR, Surface Roughness (Ra & Overcut (OC using Square-shaped Cu tool with Lateral flushing. A well-designed experimental scheme is used to reduce the total number of experiments. Parts of the experiment are conducted with the L9 orthogonal array based on the Taguchi methodology and significant process parameters are identified using Analysis of Variance (ANOVA. It is found that MRR is affected by gap current & Ra is affected by pulse on time. Moreover, the signal-to-noise ratios associated with the observed values in the experiments are determined by which factor is most affected by the responses of MRR, Ra and OC. These experimental data are further investigated using Grey Relational Analysis to optimize multiple performances in which different levels combination of the factors are ranked based on grey relational grade. The analysis reveals that substantial improvement in machining performance takes place following this technique.

  12. INFLUENCE OF TRACK-LAYER MACHINE RUNNING GEAR PARAMETERS ON ITS ROADHOLD CAPACITY AND EFFICIENCY

    OpenAIRE

    V. V. Guskov; V. V. Pavlova; V. V. Tomashevich

    2014-01-01

    The paper reveals an influence of track-layer machine parameters on its road-hold capacity and efficiency. Ration values of running gear length to track width characterizing propulsive coefficient and machine efficiency have been determined in the paper.

  13. Influence of introducing machine milking on biothermal parameters of lactating camels (Camelus dromedarius

    Directory of Open Access Journals (Sweden)

    Moez Ayadi

    2012-10-01

    Full Text Available The current study wanted to investigate the physiological suitability of using the machine milking in lactating camels by assessing several biothermal (thermophysiological and infra-red thermographical parameters. These parameters were assessed on 3 consecutive days, immediately before, immediately after, as well as 1 h after machine milking. The sample was composed of 12 multiparous dromedary camels at mid-lactation. The hypothesis of the current study was that introducing machine milking would produce noticeable effects on the physiological status of lactating camels. On the contrary, the obtained results revealed that machine milking had no effect (P>0.05 on average rectal (37.88±0.23°C and vaginal temperatures (37.94±0.14°C, as well as respiratory (16.12±0.23 breath/min and heart rates (56.78±1.89 beat/min. A significant decrease (P<0.001 in udder (-1.0°C and teat (-1.6°C surface temperatures, instead, was detected 1 h immediately after milking. Accordingly, this study provides a clear evidence that introducing machine milking has no effect on the homeothermic status of lactating camels.

  14. The Use of Response Surface Methodology to Optimize Parameter Adjustments in CNC Machine Tools

    Directory of Open Access Journals (Sweden)

    Shao-Hsien Chen

    2014-01-01

    Full Text Available This paper mainly covers a research intended to improve the circular accuracy of CNC machine tools and the adjustment and analysis of the main controller parameters applied to improve accuracy. In this study, controller analysis software was used to detect the adjustment status of the servo parameters of the feed axis. According to the FANUC parameter manual, the parameter address, frequency, response measurements, and the one-fourth corner acceleration and deceleration measurements of the machine tools were adjusted. The experimental design (DOE was adopted in this study for taking circular measurements and engaging in the planning and selection of important parameter data. The Minitab R15 software was adopted to predict the experimental data analysis, while the seminormal probability map, Plato, and analysis of variance (ANOVA were adopted to determine the impacts of the significant parameter factors and the interactions among them. Additionally, based on the response surface map and contour plot, the optimal values were obtained. In addition, comparison and verification were conducted through the Taguchi method, regression analysis to improved machining accuracy and efficiency. The unadjusted error was 7.8 μm; through the regression analysis method, the error was 5.8 μm and through the Taguchi analysis method, the error was 6.4 μm.

  15. Study On Machining Processing Technology Risk Control

    Institute of Scientific and Technical Information of China (English)

    Li Xiqing

    2015-01-01

    In the industrial production process,only to ful y guarantee the machining production safety, it can been ensured that the smooth completion of machining process.Under this back ground,in the machining production process,the machinery processing safety would been ful y concerned,several factors, which may lead to the problem of mechanical processing and production process,were analyzed,and the relevant control strategies were researched.In view of this situation,this paper wil specifical y combined with the machining process characteristics to study the machining process manufacturability risk control.

  16. A Method for Identifying the Mechanical Parameters in Resistance Spot Welding Machines

    DEFF Research Database (Denmark)

    Wu, Pei; Zhang, Wenqi; Bay, Niels

    2003-01-01

    Mechanical dynamic responses of resistance welding machine have a significant influence on weld quality and electrode service life, it must be considered when the real welding production is carried out or the welding process is stimulated. The mathematical models for characterizing the mechanical...... and differences of machine constructions. In this paper, a method of identifying the machine mechanical parameters based on measured data is presented, which is independent on the construction and the type of machines. The computations are implemented in MATLAB....

  17. Power System Parameters Forecasting Using Hilbert-Huang Transform and Machine Learning

    OpenAIRE

    Kurbatsky, Victor G.; Spiryaev, Vadim A.; Tomin, Nikita V.; Leahy, Paul G.; Sidorov, Denis N.; Zhukov, Alexei V.

    2014-01-01

    A novel hybrid data-driven approach is developed for forecasting power system parameters with the goal of increasing the efficiency of short-term forecasting studies for non-stationary time-series. The proposed approach is based on mode decomposition and a feature analysis of initial retrospective data using the Hilbert-Huang transform and machine learning algorithms. The random forests and gradient boosting trees learning techniques were examined. The decision tree techniques were used to ra...

  18. Optimization of Process Parameters And Dielectric Fluids on Machining En 31 By Using Topsis

    Directory of Open Access Journals (Sweden)

    A.Hemantha Kumar

    2016-09-01

    Full Text Available The electric discharge machining is the one of the most desirable machining process for the materials which are having high hardness and good thermal conductivity. The EDM process surpassed through the technological barriers by overcoming limitations like processing speed, material conductivity, dimensional accuracy, and surface finish and so on. However, environmental impact due to release of toxic emissions aerosols during the process, poor operational safety due to fire hazard, electromagnetic radiation and non-bio degradable waste are the major problems concerned with conventional dielectric fluids (i.e. kerosene, hydro carbon, etc.,. To reduce the problems with conventional die electric fluids waste palm oil blended with kerosene is used. The process is mostly used in situations where intricate, complex shapes need to be machined in very hard materials. The objective of this work is to study the influence of four design factors current (I, voltage (V, pulse on(P on, and pulse off(P off which are the most relevant parameters to be controlled by the EDM process over machining characteristics such as material removal rate (MRR characteristics of surface integrity such as average surface roughness (Ra. Multi Objective optimization of process parameters is done by using TOPSIS.

  19. Effect of Machining Parameters on Surface Integrity in Machining Nimonic C-263 Super Alloy Using Whisker-Reinforced Ceramic Insert

    Science.gov (United States)

    Ezilarasan, C.; Senthil kumar, V. S.; Velayudham, A.

    2013-06-01

    Whisker-reinforced ceramic inserts were used to conduct turning trials on nimonic C-263 super alloy to study the effect of different combinations of cutting parameters on surface integrity (roughness, microhardness, and residual stress) by employing energy dispersive spectroscopy, scanning electron microscopy, x-ray diffraction, and Vicker's microhardness test. Abrasion, adhesion and diffusion were found to be the main tool wear mechanisms in turning nimonic C-263 alloy. Based on characterization of surface roughness, a combination of 190 m/min cutting speed and 0.102 mm/rev feed rate was found to be the critical condition for turning nimonic C-263 alloy. Microhardness varied between 550 and 690 HV at the feed rates of 0.102-0.143 mm/rev for a cutting speed of 250 m/min after 9 min of turning. A tensile residual stress of 725-850 MPa on the machined surface was recorded at the preceding combination of cutting parameters. Cutting speed and cutting time had a dominant effect on the magnitude of the residual stress. No evidence of thermal relaxation and reduction in the degree of work hardening was noted during machining at high cutting speed.

  20. [Backscattering Characteristics of Machining Surfaces and Retrieval of Surface Multi-Parameters].

    Science.gov (United States)

    Tao, Hui-rong; Zhang, Fu-min; Qu, Xing-hua

    2015-07-01

    accuracy is high. It can reduce the impact of surface texture, the incident azimuth and incidence angle to the ranging scope. The experiments proved that the inversion of the surface parameters greatly broadened the ranging scope in no cooperation target laser ranging. Taking the Vertical milling sample with roughness Ra=6.3 microm for example, the measuring range can be increased by about 22 m when the incidence angle is increased in the incidence plane which is vertical to the surface texture. The study results of this paper have a certain reference value to the research of the backscattering of machined surface and its application in other areas.

  1. Effects of machining parameters on tool life and its optimization in turning mild steel with brazed carbide cutting tool

    Science.gov (United States)

    Dasgupta, S.; Mukherjee, S.

    2016-09-01

    One of the most significant factors in metal cutting is tool life. In this research work, the effects of machining parameters on tool under wet machining environment were studied. Tool life characteristics of brazed carbide cutting tool machined against mild steel and optimization of machining parameters based on Taguchi design of experiments were examined. The experiments were conducted using three factors, spindle speed, feed rate and depth of cut each having three levels. Nine experiments were performed on a high speed semi-automatic precision central lathe. ANOVA was used to determine the level of importance of the machining parameters on tool life. The optimum machining parameter combination was obtained by the analysis of S/N ratio. A mathematical model based on multiple regression analysis was developed to predict the tool life. Taguchi's orthogonal array analysis revealed the optimal combination of parameters at lower levels of spindle speed, feed rate and depth of cut which are 550 rpm, 0.2 mm/rev and 0.5mm respectively. The Main Effects plot reiterated the same. The variation of tool life with different process parameters has been plotted. Feed rate has the most significant effect on tool life followed by spindle speed and depth of cut.

  2. Electrical discharge machining studies on reactive sintered FeAl

    Indian Academy of Sciences (India)

    A K Khanra; S Patra; M M Godkhindi

    2006-06-01

    Electrical discharge machining (EDM) studies on reactive sintered FeAl were carried out with different process parameters. The metal removal rate and tool removal rate were found to increase with the applied pulse on-time. The surface roughness of machined surface also changed with the applied pulse on-time. XRD analysis of machined surface of sintered FeAl showed the formation of Fe3C phase during the EDM process. The debris analysis was used to identify the material removal mechanism occurring during the EDM of sintered FeAl.

  3. A Parameter Communication Optimization Strategy for Distributed Machine Learning in Sensors

    Directory of Open Access Journals (Sweden)

    Jilin Zhang

    2017-09-01

    Full Text Available In order to utilize the distributed characteristic of sensors, distributed machine learning has become the mainstream approach, but the different computing capability of sensors and network delays greatly influence the accuracy and the convergence rate of the machine learning model. Our paper describes a reasonable parameter communication optimization strategy to balance the training overhead and the communication overhead. We extend the fault tolerance of iterative-convergent machine learning algorithms and propose the Dynamic Finite Fault Tolerance (DFFT. Based on the DFFT, we implement a parameter communication optimization strategy for distributed machine learning, named Dynamic Synchronous Parallel Strategy (DSP, which uses the performance monitoring model to dynamically adjust the parameter synchronization strategy between worker nodes and the Parameter Server (PS. This strategy makes full use of the computing power of each sensor, ensures the accuracy of the machine learning model, and avoids the situation that the model training is disturbed by any tasks unrelated to the sensors.

  4. A Parameter Communication Optimization Strategy for Distributed Machine Learning in Sensors.

    Science.gov (United States)

    Zhang, Jilin; Tu, Hangdi; Ren, Yongjian; Wan, Jian; Zhou, Li; Li, Mingwei; Wang, Jue; Yu, Lifeng; Zhao, Chang; Zhang, Lei

    2017-09-21

    In order to utilize the distributed characteristic of sensors, distributed machine learning has become the mainstream approach, but the different computing capability of sensors and network delays greatly influence the accuracy and the convergence rate of the machine learning model. Our paper describes a reasonable parameter communication optimization strategy to balance the training overhead and the communication overhead. We extend the fault tolerance of iterative-convergent machine learning algorithms and propose the Dynamic Finite Fault Tolerance (DFFT). Based on the DFFT, we implement a parameter communication optimization strategy for distributed machine learning, named Dynamic Synchronous Parallel Strategy (DSP), which uses the performance monitoring model to dynamically adjust the parameter synchronization strategy between worker nodes and the Parameter Server (PS). This strategy makes full use of the computing power of each sensor, ensures the accuracy of the machine learning model, and avoids the situation that the model training is disturbed by any tasks unrelated to the sensors.

  5. 3-PRS serial-parallel machine tool error calibration and parameter identification

    Institute of Scientific and Technical Information of China (English)

    ZHAO Jun-wei; DAI Jun; HUANG Jun-jie

    2009-01-01

    3-PRS serial-parallel machine tool consists of a 3-degree-of-freedom (DOF) implementation platform and a 2-DOF X-Y platform. The error modeling and parameter identification methods were deduced based on 3-PRS serial-parallel machine tool. 3-PRS serial-parallel machine tool was researched, and the mechanism of error analysis, modeling, identification of error parameters and measurement equipment for the use of agency error of measurement were conducted. In order to achieve the geometric parameters calibration and error compensation of the serial-parallel machine tool, the nominal structural parameters of the controller was adjusted by identifying the structure of the machine tool. With the establishment of a vector space size chain, we can do the error analysis, error modeling, error measurement and error compensation can be done.

  6. Effect of Implantation Machine Parameters on N+ ion Implantation for Upland Cotton(Gossypium hirsutum L.) Pollen

    Science.gov (United States)

    Yue, Jieyu; Yu, Lixiang; Wu, Yuejin; Tang, Canming

    2008-10-01

    Effect of parameters of ion implantation machine, including ion energy, total dose, dose rate, impulse energy and implantation interval on the pollen grains of upland cotton implanted with nitrogen ion beam were studied. The best parameters were screened out. The results also showed that the vacuum condition before the nitrogen ion implantation does not affect the pollen viability.

  7. On the Physics of Machining Titanium Alloys: Interactions between Cutting Parameters, Microstructure and Tool Wear

    Directory of Open Access Journals (Sweden)

    Mohammed Nouari

    2014-07-01

    Full Text Available The current work deals with the analysis of mechanisms involved during the machining process of titanium alloys. Two different materials were chosen for the study: Ti-6Al-4V and Ti-55531. The objective was to understand the effect of all cutting parameters on the tool wear behavior and stability of the cutting process. The investigations were focused on the mechanisms of the chip formation process and their interaction with tool wear. At the microstructure scale, the analysis confirms the intense deformation of the machined surface and shows a texture modification. As the cutting speed increases, cutting forces and temperature show different progressions depending on the considered microstructure (Ti-6Al-4V or Ti-55531 alloy. Results show for both materials that the wear process is facilitated by the high cutting temperature and the generation of high stresses. The analysis at the chip-tool interface of friction and contact nature (sliding or sticking contact shows that machining Ti55531 often exhibits an abrasion wear process on the tool surface, while the adhesion and diffusion modes followed by the coating delamination process are the main wear modes when machining the usual Ti-6Al-4V alloy.

  8. An Experimental Study on Electro Chemical Machining of Microelectrode

    Institute of Scientific and Technical Information of China (English)

    ZHANG Liao-yuan; LIU Yao

    2006-01-01

    Puts forward a new method in machining microelectrode by electro chemical machining (ECM) and plastic deformed theory. Theprocedure of this method is to machine the microelectrode according to the basic rule of ECM theory at first. Then, with the change of ECM machining parameters, one of the microelectrode ends is exerted by a load. As a result, the elastic and plastic deformation is produced at the machining section and the microelectrode diameter is reduced.It has been proved that the proposed method can determine the optimum machining parameters to machine the microelectrode of Cu.

  9. GNSS TECHNOLOGY DETERMINATION OF FLYING MACHINE GUIDANCE PARAMETERS

    Directory of Open Access Journals (Sweden)

    Valeriy Konin

    2013-10-01

    Full Text Available Normal 0 false false false MicrosoftInternetExplorer4 An algorithm of calculating the guidance parameters for GNSS aircraft landing technology was considered. The simulation and evaluation of calculation parameters error were performed as well

  10. Inrush Current Simulation of Two Windings Power Transformer using Machine Parameters Estimated by Design Procedure of Winding Structure

    Science.gov (United States)

    Tokunaga, Yoshitaka; Kubota, Kunihiro

    This paper presents estimation techniques of machine parameters for two windings power transformer using design procedure of winding structure. Especially, it is very difficult to obtain machine parameters for transformers in customers' facilities. Using estimation techniques, machine parameters could be calculated from the only nameplate data of these transformers. Subsequently, EMTP-ATP simulation of the inrush current was carried out using machine parameters estimated by design procedure of winding structure and simulation results were reproduced measured waveforms.

  11. Machining parameter optimization of C/SiC composites using high power picosecond laser

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Ruoheng; Li, Weinan [State Key Laboratory of Transient Optics and Photonics, Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi’an, Shaanxi 10068 (China); Liu, Yongsheng, E-mail: yongshengliu@nwpu.edu.cn [Science and Technology on Thermostructure Composite Materials Laboratory, Northwestern Polytechnical University, Xi’an, Shaannxi 710072 (China); Wang, Chunhui; Wang, Jing [Science and Technology on Thermostructure Composite Materials Laboratory, Northwestern Polytechnical University, Xi’an, Shaannxi 710072 (China); Yang, Xiaojun [State Key Laboratory of Transient Optics and Photonics, Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi’an, Shaanxi 10068 (China); Cheng, Laifei, E-mail: liuys99067@163.com [Science and Technology on Thermostructure Composite Materials Laboratory, Northwestern Polytechnical University, Xi’an, Shaannxi 710072 (China)

    2015-03-01

    Highlights: • We found that the helical line width and the helical line spacing, machining time and the scanning speed on the surface morphology of machined holes had remarkable effects on the qualities of micro-holes such as shape and depth. • The debris consisted of C, Si and O was observed on the machined surface. The Si−C bonds of the SiC matrix transformed into Si−O bonds after machined. - Abstract: Picosecond laser is an important machining technology for high hardness materials. In this paper, high power picosecond laser was utilized to drill micro-holes in C/SiC composites, and the effects of different processing parameters including the helical line width and spacing, machining time and scanning speed were discussed. To characterize the qualities of machined holes, scanning electron microscope (SEM) was used to analyze the surface morphology, energy dispersive spectroscopy (EDS) and X-ray photoelectric spectroscopy (XPS) were employed to describe the element composition change between the untreated and laser-treated area. The experimental results indicated that all parameters mentioned above had remarkable effects on the qualities of micro-holes such as shape and depth. Additionally, the debris consisted of C, Si and O was observed on the machined surface. The Si−C bonds of the SiC matrix transformed into Si−O bonds after machined. Furthermore, the physical process responsible for the mechanism of debris formation was discussed as well.

  12. Local flow characteristics in a MHD induction machine duct at large parameters of electromagnetic interaction

    Energy Technology Data Exchange (ETDEWEB)

    Valdmane, R.A.; Krishberg, R.R.; Lielpeter, Ya.Ya.; Mikryukov, Ch.K.; Ulmanis, L.Ya.

    1977-07-01

    A study is made of the velocity distribution along the duct width of an induction MHD machine with a traveling magnetic field under pump, generator and damping conditions. The computed velocity profiles were compared to those obtained on a sodium circuit under pump and damping conditions. The parameter values for electromagnetic interaction E in the experiments and in the computations changed from 2 to 4.5. Agreement was obtained between the measured velocity distribution and the compared ones at values E > 1. 6 references, 7 figures.

  13. Predictive Models for Different Roughness Parameters During Machining Process of Peek Composites Using Response Surface Methodology

    Directory of Open Access Journals (Sweden)

    Mata-Cabrera Francisco

    2013-10-01

    Full Text Available Polyetheretherketone (PEEK composite belongs to a group of high performance thermoplastic polymers and is widely used in structural components. To improve the mechanical and tribological properties, short fibers are added as reinforcement to the material. Due to its functional properties and potential applications, it’s impor- tant to investigate the machinability of non-reinforced PEEK (PEEK, PEEK rein- forced with 30% of carbon fibers (PEEK CF30, and reinforced PEEK with 30% glass fibers (PEEK GF30 to determine the optimal conditions for the manufacture of the parts. The present study establishes the relationship between the cutting con- ditions (cutting speed and feed rate and the roughness (Ra , Rt , Rq , Rp , by develop- ing second order mathematical models. The experiments were planned as per full factorial design of experiments and an analysis of variance has been performed to check the adequacy of the models. These state the adequacy of the derived models to obtain predictions for roughness parameters within ranges of parameters that have been investigated during the experiments. The experimental results show that the most influence of the cutting parameters is the feed rate, furthermore, proved that glass fiber reinforcements produce a worse machinability.

  14. Influence of machining parameters on cutting tool life while machining aluminum alloy fly ash composite

    Science.gov (United States)

    Rao, C. R. Prakash; chandra, Poorna; Kiran, R.; Asha, P. B.

    2016-09-01

    Metal matrix composites containing fly ash as reinforcement are primarily preferred because these materials possess lower density and higher strength to weight ratio. The metal matrix composites possess hetrogeneous microstructure which is due to the presence of hard ceramic particles. While turning composites, the catastrophic failure of cutting tools is attributed to the presence of hard particles. Selection of optimal cutting conditions for a given machining process and grade of cutting tools are of utmost importance to enhance the tool life during turning operation. Thus the research work was aimed at the experimental investigation of the cutting tool life while machining aluminum alloy composite containing 0-15% fly-ash. The experiments carried out following ISO3685 standards. The carbide inserts of grade K10 and style CGGN120304 were the turning tools. The cutting speed selected was between 200m/min to 500m/min in step of 100m/min, feed of 0.08 & 0.16 mm/revolution and constant depth of cut of 1.0 mm. The experimental results revealed that the performance of K10 grade carbide insert found better while machining composite containing 5% filler, at all cutting speeds and 0.08mm/revolution feed. The failures of carbide tools are mainly due to notch wear followed by built up edge and edge chipping.

  15. Optimization of Process Parameters in Wire Electrical Discharge Machining of MMC: A Review

    Directory of Open Access Journals (Sweden)

    J.M.Pujara

    2015-07-01

    Full Text Available Wire electrical discharge machining (WEDM is a specialized thermal machining process capable of accurately machining parts with varying hardness or complex shapes, which have sharp edges that are very difficult to be machined by the main stream machining processes. This practical technology of the WEDM process is based on the conventional EDM sparking phenomenon utilizing the widely accepted non-contact technique of material removal. Since the introduction of the process, WEDM has evolved from a simple means of making tools and dies to the best alternative of producing micro-scale parts with the highest degree of dimensional accuracy and surface finish quality. Metal matrix composites are advanced materials having high specific strength, good wear resistance, and high thermal expansion coefficient. To achieve this task, machining parameters such as pulse on time, pulse off time, peak current, servo voltage, wire feed, wire tension etc. of this process should be selected such that optimal value of their performance measures like Material Removal Rate (MRR, Surface Roughness (SR, Gap current, Dimensional deviation, etc. can be obtained or improved. In past decades, intensive research work had been carried out by different researchers for improvement and optimization of WEDM performance measures using various optimization techniques like Taguchi, Response Surface Methodology (RSM, Artificial Neural Network (ANN, Genetic Algorithm (GA, etc. This paper also highlights the feasibility of the different control strategies of obtaining the optimal machining conditions. This literature review helps to identify the suitable process parameters and their ranges in machining of metal matrix composites.

  16. Using multi-objective optimization to design parameters in electro-discharge machining by wire

    Directory of Open Access Journals (Sweden)

    Carlos Alberto OCHOA

    2015-03-01

    Full Text Available The following paper describes the main objective to follow the methodology used and proposed to obtain the optimal values of WEDM process operation on the machine Robofil 310 by robust parameter design (RPD of Dr. G. Taguichi [TAGUCHI, G. 1993], through controllable factors which result in more inferences regarding the problem to noise signal (S / N, which for this study is the variability of the hardness of samples from 6061, also studied the behaviour of the output parameters as the material removal rate (MRR and surface roughness (Ra, subsequently took the RPD orthogonal array and characterized the individuals in the population, each optimal value is a gene and each possible solution is a chromosome, used multi-objective optimization using Non-dominated Sorting Genetic Algorithm to cross and mutate this population to generate better results MRR and Ra.

  17. Effect of cutting parameters on sustainable machining performance of coated carbide tool in dry turning process of stainless steel 316

    Science.gov (United States)

    Bagaber, Salem A.; Yusoff, Ahmed Razlan

    2017-04-01

    The manufacturing industry aims to produce many products of high quality with relatively less cost and time. Different cutting parameters affect the machining performance of surface roughness, cutting force, and material removal rate. Nevertheless, a few studies reported on the effects of sustainable factors such as power consumed, cycle time during machining, and tool life on the dry turning of AISI 316. The present study aims to evaluate the machining performance of coated carbide in the machining of hard steel AISI 316 under the dry turning process. The influence of cutting parameters of cutting speed, feed rate, and depth of cut with their five (5) levels is established by a central composite design. Highly significant parameters were determined by analysis of variance (ANOVA), and the main effects of power consumed and time during machining, surface roughness, and tool wear were observed. Results showed that the cutting speed was proportional to power consumption and tool wear. Meanwhile, insignificant to surface roughness, feed rate most significantly affected surface roughness and power consumption followed by depth of cut.

  18. Algorithm for Modeling Wire Cut Electrical Discharge Machine Parameters using Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    G.Sankara Narayanan

    2014-03-01

    Full Text Available Unconventional machining process finds lot of application in aerospace and precision industries. It is preferred over other conventional methods because of the advent of composite and high strength to weight ratio materials, complex parts and also because of its high accuracy and precision. Usually in unconventional machine tools, trial and error method is used to fix the values of process parameters which increase the production time and material wastage. A mathematical model functionally relating process parameters and operating parameters of a wire cut electric discharge machine (WEDM is developed incorporating Artificial neural network (ANN and the work piece material is SKD11 tool steel. This is accomplished by training a feed forward neural network with back propagation learning Levenberg-Marquardt algorithm. The required data used for training and testing the ANN are obtained by conducting trial runs in wire cut electric discharge machine in a small scale industry from South India. The programs for training and testing the neural network are developed, using matlab 7.0.1 package. In this work, we have considered the parameters such as thickness, time and wear as the input values and from that the values of the process parameters are related and a algorithm is arrived. Hence, the proposed algorithm reduces the time taken by trial runs to set the input process parameters of WEDM and thus reduces the production time along with reduction in material wastage. Thus the cost of machining processes is reduced and thereby increases the overall productivity.

  19. Multiple mental tasks classification based on nonlinear parameter of mean period using support vector machines

    Institute of Scientific and Technical Information of China (English)

    Liu Hailong; Wang Jue; Zheng Chongxun

    2007-01-01

    Mental task classification is one of the most important problems in Brain-computer interface. This paper studies the classification of five-class mental tasks. The nonlinear parameter of mean period obtained from frequency domain information was used as features for classification implemented by using the method of SVM (support vector machines). The averaged classification accuracy of 85.6% over 7 subjects was achieved for 2-second EEG segments. And the results for EEG segments of 0.5s and 5.0s compared favorably to those of Garrett's. The results indicate that the parameter of mean period represents mental tasks well for classification. Furthermore, the method of mean period is less computationally demanding, which indicates its potential use for online BCI systems.

  20. Relationship of goat milk flow emission variables with milking routine, milking parameters, milking machine characteristics and goat physiology.

    Science.gov (United States)

    Romero, G; Panzalis, R; Ruegg, P

    2017-04-10

    The aim of this paper was to study the relationship between milk flow emission variables recorded during milking of dairy goats with variables related to milking routine, goat physiology, milking parameters and milking machine characteristics, to determine the variables affecting milking performance and help the goat industry pinpoint farm and milking practices that improve milking performance. In total, 19 farms were visited once during the evening milking. Milking parameters (vacuum level (VL), pulsation ratio and pulsation rate, vacuum drop), milk emission flow variables (milking time, milk yield, maximum milk flow (MMF), average milk flow (AVMF), time until 500 g/min milk flow is established (TS500)), doe characteristics of 8 to 10 goats/farm (breed, days in milk and parity), milking practices (overmilking, overstripping, pre-lag time) and milking machine characteristics (line height, presence of claw) were recorded on every farm. The relationships between recorded variables and farm were analysed by a one-way ANOVA analysis. The relationships of milk yield, MMF, milking time and TS500 with goat physiology, milking routine, milking parameters and milking machine design were analysed using a linear mixed model, considering the farm as the random effect. Farm was significant (Pvariables. Milk emission flow variables were similar to those recommended in scientific studies. Milking parameters were adequate in most of the farms, being similar to those recommended in scientific studies. Few milking parameters and milking machine characteristics affected the tested variables: average vacuum level only showed tendency on MMF, and milk pipeline height on TS500. Milk yield (MY) was mainly affected by parity, as the interaction of days in milk with parity was also significant. Milking time was mainly affected by milk yield and breed. Also significant were parity, the interaction of days in milk with parity and overstripping, whereas overmilking showed a slight tendency

  1. Parallel Machine Scheduling Models with Fuzzy Parameters and Precedence Constraints: A Credibility Approach

    Institute of Scientific and Technical Information of China (English)

    HOU Fu-jun; WU Qi-zong

    2007-01-01

    A method for modeling the parallel machine scheduling problems with fuzzy parameters and precedence constraints based on credibility measure is provided.For the given n jobs to be processed on m machines, it is assumed that the processing times and the due dates are nonnegative fuzzy numbers and all the weights are positive, crisp numbers.Based on credibility measure, three parallel machine scheduling problems and a goal-programming model are formulated.Feasible schedules are evaluated not only by their objective values but also by the credibility degree of satisfaction with their precedence constraints.The genetic algorithm is utilized to find the best solutions in a short period of time.An illustrative numerical example is also given.Simulation results show that the proposed models are effective, which can deal with the parallel machine scheduling problems with fuzzy parameters and precedence constraints based on credibility measure.

  2. Beam interlock system and safe machine parameters system 2010 and beyond

    CERN Document Server

    Todd, B

    2010-01-01

    The Beam Interlock System (BIS) and Safe Machine Parameters (SMP) system are central to the protection of the Large Hadron Collider (LHC) machine. The BIS has been critical for the safe operation of LHC from the first day of operation. It has been installed and commissioned, only minor enhancements are required in order to accommodate all future LHC machine protection requirements. At reduced intensity, the SMP system is less critical for LHC operation. As such, the current system satisfies the 2010 operational requirements. Further developments are required, both at the SMP Controller level, and at the system level, in order to accommodate the requirements of the LHC beyond 2010.

  3. Experimental investigation of machining parameter under MQL milling of SS304

    Science.gov (United States)

    Gatade, Vivek T.; Patil, Vikas T.; Kuppan, P.; Balan, A. S. S.; Oyyaravelu, R.

    2016-09-01

    Minimum quantity lubrication (MQL) or near dry machining has been recognized by many researchers and industrialist in order to move one step ahead towards the green manufacturing. MQL assisted machining reduces the harmful environmental impact caused by flood coolant and machining cost. In this paper an attempt has been made to study the impact of oxygen as a carrier gas in MQL during end milling of austenitic stainless steel grade SS304. Also, the machining performance under conventional MQL with air and dry machining have been studied. The evaluation was done on tool wear, surface roughness and cutting forces under two distinct cutting speeds i.e. 75 m/min and 100 m/min. Investigation brings to light that presence of oxygen is susceptible in the case of machining of SS304, it provides extra protective oxide layer near the tool chip interface. Consequently, increased tool life, reduced surface roughness and cutting forces when compared to conventional MQL assisted milling.

  4. Experimental Study on Abrasive Water Jet Machining of PZT Ceramic

    Science.gov (United States)

    Dhanawade, Ajit; Upadhyai, Ravi; Rouniyar, Arunkumar; Kumar, Shailendra

    2017-07-01

    This paper presents research work involved in abrasive water jet machining of PZT ceramic material. Process parameters namely stand-off distance, water pressure and traverse rate are considered in the present study. Response surface methodology approach is used to design the experiments. Relative significance of process parameters and their influence on kerf properties are identified on the basis of analysis of variance. It is found that water pressure and traverse rate are most significant parameters followed by stand-off distance. On the basis of experimental analysis, regression models are developed to predict kerf taper and depth of cut. The models are developed with respect to significant parameters, interaction and quadratic terms. It is found that model predictions are in congruence with experimental results. Multi-response optimization of process parameters is also performed using desirability approach in order to minimize kerf taper and maximize depth of cut. Kerf wall features of machined surfaces are observed using scanning electron microscope. The findings of present study are useful to improve kerf properties in abrasive water jet machining of PZT ceramic materials.

  5. Investigating Effect of Machining Parameters of CNC Milling on Surface Finish by Taguchi Method

    Directory of Open Access Journals (Sweden)

    Amit Joshi

    2012-08-01

    Full Text Available CNC End milling is a unique adaption of the conventional milling process which uses an end mill tool for the machining process. CNC Vertical End Milling Machining is a widely accepted material removal process used to manufacture components with complicated shapes and profiles. During the End milling process, the material is removed by the end mill cutter. The effects of various parameters of end milling process like spindle speed, depth of cut, feed rate have been investigated to reveal their Impact on surface finish using Taguchi Methodology. Experimental plan is performed by a Standard Orthogonal Array. The results of analysis of variance (ANOVA indicate that the feed Rate is most influencing factor for modeling surface finish. The graph of S-N Ratio indicates the optimal setting of the machining parameter which gives the optimum value of surface finish. The optimal set of process parameters has also been predicted to maximize the surface finish.

  6. Investigating Effect of Machining Parameters of CNC Milling on Surface Finish by Taguchi Method

    Directory of Open Access Journals (Sweden)

    Amit Joshi

    2013-08-01

    Full Text Available CNC End milling is a unique adaption of the conventional milling process which uses an end mill tool for the machining process. CNC Vertical End Milling Machining is a widely accepted material removal process used to manufacture components with complicated shapes and profiles. During the End milling process, the material is removed by the end mill cutter. The effects of various parameters of end milling process like spindle speed, depth of cut, feed rate have been investigated to reveal their Impact on surface finish using Taguchi Methodology. Experimental plan is performed by a Standard Orthogonal Array. The results of analysis of variance (ANOVA indicate that the feed Rate is most influencing factor for modelling surface finish. The graph of S-N Ratio indicates the optimal setting of the machining parameter which gives the optimum value of surface finish. The optimal set of process parameters has also been predicted to maximize the surface finish.

  7. Dynamic study of synchronous machine electric drive

    Directory of Open Access Journals (Sweden)

    Dimitar Spirov

    2005-10-01

    Full Text Available The dynamic behaviour of the fan blower synchoronous machine drive have been studied in the paper. The equations for the voltages of the synchoronous machine windings are presented in a coordinate system which rotates at the angular speed of the rotor. The mechanical equipment is presented by means of a single-mass dynamic model. The derived system of differential equations is transformed and solved using suitable software product. The results obtained for rotation frequency and electromagnetic torque motor in the courses of different values of rated supply voltage and of different initial resistant moment of the mechanism have been graphically presented. Conclusions from the results obtained have been done.

  8. Influence of parameters of machine cutting on drills durability in a line of frame casting

    Directory of Open Access Journals (Sweden)

    J. Jaworski

    2009-01-01

    Full Text Available The text shows the influence of parameters of machine cutting on wear and tear of drills which are made of low-alloyed high-speed steal SW2M5 while holes drilling in spheroid cast iron samples GGG50. The results showed that only wear and tear of the VBwo tops ismonotonically rising in a time and can be assumed as criterion of wear and tear. The value of VBwo that starts the wear and tear depends on the parameters of machine cutting and features of material processing.

  9. Inflatable Wing Design Parameter Optimization Using Orthogonal Testing and Support Vector Machines

    Institute of Scientific and Technical Information of China (English)

    WANG Zhifei; WANG Hua

    2012-01-01

    The robust parameter design method is a traditional approach to robust experimental design that seeks to obtain the optimal combination of factors/levels.To overcome some of the defects of the inflatable wing parameter design method,this paper proposes an optimization design scheme based on orthogonal testing and support vector machines (SVMs).Orthogonal testing design is used to estimate the appropriate initial value and variation domain of each variable to decrease the number of iterations and improve the identification accuracy and efficiency.Orthogonal tests consisting of three factors and three levels are designed to analyze the parameters of pressure,uniform applied load and the number of chambers that affect the bending response of inflatable wings.An SVM intelligent model is established and limited orthogonal test swatches are studied.Thus,the precise relationships between each parameter and product quality features,as well the signal-to-noise ratio (SNR),can be obtained.This can guide general technological design optimization.

  10. A Fault Alarm and Diagnosis Method Based on Sensitive Parameters and Support Vector Machine

    Science.gov (United States)

    Zhang, Jinjie; Yao, Ziyun; Lv, Zhiquan; Zhu, Qunxiong; Xu, Fengtian; Jiang, Zhinong

    2015-08-01

    Study on the extraction of fault feature and the diagnostic technique of reciprocating compressor is one of the hot research topics in the field of reciprocating machinery fault diagnosis at present. A large number of feature extraction and classification methods have been widely applied in the related research, but the practical fault alarm and the accuracy of diagnosis have not been effectively improved. Developing feature extraction and classification methods to meet the requirements of typical fault alarm and automatic diagnosis in practical engineering is urgent task. The typical mechanical faults of reciprocating compressor are presented in the paper, and the existing data of online monitoring system is used to extract fault feature parameters within 15 types in total; the inner sensitive connection between faults and the feature parameters has been made clear by using the distance evaluation technique, also sensitive characteristic parameters of different faults have been obtained. On this basis, a method based on fault feature parameters and support vector machine (SVM) is developed, which will be applied to practical fault diagnosis. A better ability of early fault warning has been proved by the experiment and the practical fault cases. Automatic classification by using the SVM to the data of fault alarm has obtained better diagnostic accuracy.

  11. Learning Machine Learning: A Case Study

    Science.gov (United States)

    Lavesson, N.

    2010-01-01

    This correspondence reports on a case study conducted in the Master's-level Machine Learning (ML) course at Blekinge Institute of Technology, Sweden. The students participated in a self-assessment test and a diagnostic test of prerequisite subjects, and their results on these tests are correlated with their achievement of the course's learning…

  12. Learning Machine Learning: A Case Study

    Science.gov (United States)

    Lavesson, N.

    2010-01-01

    This correspondence reports on a case study conducted in the Master's-level Machine Learning (ML) course at Blekinge Institute of Technology, Sweden. The students participated in a self-assessment test and a diagnostic test of prerequisite subjects, and their results on these tests are correlated with their achievement of the course's learning…

  13. INFLUENCE OF WHEEL STRUCTURAL PARAMETERS ON MACHINING ACCURACY OF ULTRA-PRECISION PLANE HONING

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    A new idea for designing wheel patterns is presented so as to solve the problems about machining accuracy ofworkpiece and wear of honing wheel in ultra-precision plane honing. The influence factors on motion principle and pat-tern structures are analyzed and optimization machining parameters are obtained. By calculating effective cutting lengthon the surface of workpiece cut by wheel's abrasive and the orbit of one point on the surface of workpiece contactingwith wheel, the wear coefficient of different kinds of wheels and accuracy coefficient of workpiece machined by corre-sponding wheels are obtained. Furthermore, the simulation results show that the optimal pattern structure of wheel turnsout to have lower wheel wear and higher machining accuracy.

  14. Parameter selection of support vector machine for function approximation based on chaos optimization

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    The support vector machine (SVM) is a novel machine learning method,which has the ability to approximate nonlinear functions with arbitrary accuracy.Setting parameters well is very crucial for SVM learning results and generalization ability,and now there is no systematic,general method for parameter selection.In this article,the SVM parameter selection for function approximation is regarded as a compound optimization problem and a mutative scale chaos optimization algorithm is employed to search for optimal parameter values.The chaos optimization algorithm is an effective way for global optimal and the mutative scale chaos algorithm could improve the search efficiency and accuracy.Several simulation examples show the sensitivity of the SVM parameters and demonstrate the superiority of this proposed method for nonlinear function approximation.

  15. Studies of Machine Learning Photometric Classification of Supernovae

    Science.gov (United States)

    Macaluso, Joseph Nicholas; Cunningham, John; Kuhlmann, Stephen; Gupta, Ravi; Kovacs, Eve

    2017-01-01

    We studied the use of machine learning for the photometuric classification of Type Ia (SNIa) and core collapse (SNcc) supernovae. We used a combination of simulated data for the Dark Energy survey (DES) and real data from SDSS and chose our metrics to be the sample purity and the efficiency of identifying SNIa supernovae. Our focus was to quantify the effects of varying the training and parameters for random-forest decision-tree algorithms.

  16. Study of on-machine error identification and compensation methods for micro machine tools

    Science.gov (United States)

    Wang, Shih-Ming; Yu, Han-Jen; Lee, Chun-Yi; Chiu, Hung-Sheng

    2016-08-01

    Micro machining plays an important role in the manufacturing of miniature products which are made of various materials with complex 3D shapes and tight machining tolerance. To further improve the accuracy of a micro machining process without increasing the manufacturing cost of a micro machine tool, an effective machining error measurement method and a software-based compensation method are essential. To avoid introducing additional errors caused by the re-installment of the workpiece, the measurement and compensation method should be on-machine conducted. In addition, because the contour of a miniature workpiece machined with a micro machining process is very tiny, the measurement method should be non-contact. By integrating the image re-constructive method, camera pixel correction, coordinate transformation, the error identification algorithm, and trajectory auto-correction method, a vision-based error measurement and compensation method that can on-machine inspect the micro machining errors and automatically generate an error-corrected numerical control (NC) program for error compensation was developed in this study. With the use of the Canny edge detection algorithm and camera pixel calibration, the edges of the contour of a machined workpiece were identified and used to re-construct the actual contour of the work piece. The actual contour was then mapped to the theoretical contour to identify the actual cutting points and compute the machining errors. With the use of a moving matching window and calculation of the similarity between the actual and theoretical contour, the errors between the actual cutting points and theoretical cutting points were calculated and used to correct the NC program. With the use of the error-corrected NC program, the accuracy of a micro machining process can be effectively improved. To prove the feasibility and effectiveness of the proposed methods, micro-milling experiments on a micro machine tool were conducted, and the results

  17. Machining parameter optimization of C/SiC composites using high power picosecond laser

    Science.gov (United States)

    Zhang, Ruoheng; Li, Weinan; Liu, Yongsheng; Wang, Chunhui; Wang, Jing; Yang, Xiaojun; Cheng, Laifei

    2015-03-01

    Picosecond laser is an important machining technology for high hardness materials. In this paper, high power picosecond laser was utilized to drill micro-holes in C/SiC composites, and the effects of different processing parameters including the helical line width and spacing, machining time and scanning speed were discussed. To characterize the qualities of machined holes, scanning electron microscope (SEM) was used to analyze the surface morphology, energy dispersive spectroscopy (EDS) and X-ray photoelectric spectroscopy (XPS) were employed to describe the element composition change between the untreated and laser-treated area. The experimental results indicated that all parameters mentioned above had remarkable effects on the qualities of micro-holes such as shape and depth. Additionally, the debris consisted of C, Si and O was observed on the machined surface. The Sisbnd C bonds of the SiC matrix transformed into Sisbnd O bonds after machined. Furthermore, the physical process responsible for the mechanism of debris formation was discussed as well.

  18. Parameter Identification of Ship Maneuvering Models Using Recursive Least Square Method Based on Support Vector Machines

    Directory of Open Access Journals (Sweden)

    Man Zhu

    2017-03-01

    Full Text Available Determination of ship maneuvering models is a tough task of ship maneuverability prediction. Among several prime approaches of estimating ship maneuvering models, system identification combined with the full-scale or free- running model test is preferred. In this contribution, real-time system identification programs using recursive identification method, such as the recursive least square method (RLS, are exerted for on-line identification of ship maneuvering models. However, this method seriously depends on the objects of study and initial values of identified parameters. To overcome this, an intelligent technology, i.e., support vector machines (SVM, is firstly used to estimate initial values of the identified parameters with finite samples. As real measured motion data of the Mariner class ship always involve noise from sensors and external disturbances, the zigzag simulation test data include a substantial quantity of Gaussian white noise. Wavelet method and empirical mode decomposition (EMD are used to filter the data corrupted by noise, respectively. The choice of the sample number for SVM to decide initial values of identified parameters is extensively discussed and analyzed. With de-noised motion data as input-output training samples, parameters of ship maneuvering models are estimated using RLS and SVM-RLS, respectively. The comparison between identification results and true values of parameters demonstrates that both the identified ship maneuvering models from RLS and SVM-RLS have reasonable agreements with simulated motions of the ship, and the increment of the sample for SVM positively affects the identification results. Furthermore, SVM-RLS using data de-noised by EMD shows the highest accuracy and best convergence.

  19. Fault diagnosis based on support vector machines with parameter optimisation by artificial immunisation algorithm

    Science.gov (United States)

    Yuan, Shengfa; Chu, Fulei

    2007-04-01

    Support vector machines (SVM) is a new general machine-learning tool based on the structural risk minimisation principle that exhibits good generalisation when fault samples are few, it is especially fit for classification, forecasting and estimation in small-sample cases such as fault diagnosis, but some parameters in SVM are selected by man's experience, this has hampered its efficiency in practical application. Artificial immunisation algorithm (AIA) is used to optimise the parameters in SVM in this paper. The AIA is a new optimisation method based on the biologic immune principle of human being and other living beings. It can effectively avoid the premature convergence and guarantees the variety of solution. With the parameters optimised by AIA, the total capability of the SVM classifier is improved. The fault diagnosis of turbo pump rotor shows that the SVM optimised by AIA can give higher recognition accuracy than the normal SVM.

  20. Synthesis of parameters of a machine set, according to amplitudes of vibration, in the case of coaxial misalignment of shafts

    Science.gov (United States)

    Rondomanskas, M. S.; Ragulskis, K. M.; Ionushas, R. A.; Bansevichyus, R. Y.

    1973-01-01

    Dynamic synthesis of the coupling parameters permits the building of coaxially aligned connected machines with very small disturbing forces. Considered is the case of two machines connected by a flexible coupling; one machine is installed on shock absorbers with four degrees of freedom. A movement leveling synthesis considers the coaxial nonalignment parameters for the shaft arrangement and determines the optimum coupling rigidity at which the vibration amplitude is at a minimum.

  1. Artificial immune system based on adaptive clonal selection for feature selection and parameters optimisation of support vector machines

    Science.gov (United States)

    Sadat Hashemipour, Maryam; Soleimani, Seyed Ali

    2016-01-01

    Artificial immune system (AIS) algorithm based on clonal selection method can be defined as a soft computing method inspired by theoretical immune system in order to solve science and engineering problems. Support vector machine (SVM) is a popular pattern classification method with many diverse applications. Kernel parameter setting in the SVM training procedure along with the feature selection significantly impacts on the classification accuracy rate. In this study, AIS based on Adaptive Clonal Selection (AISACS) algorithm has been used to optimise the SVM parameters and feature subset selection without degrading the SVM classification accuracy. Several public datasets of University of California Irvine machine learning (UCI) repository are employed to calculate the classification accuracy rate in order to evaluate the AISACS approach then it was compared with grid search algorithm and Genetic Algorithm (GA) approach. The experimental results show that the feature reduction rate and running time of the AISACS approach are better than the GA approach.

  2. Analyzing the Effect of Machining Parameters Setting to the Surface Roughness during End Milling of CFRP-Aluminium Composite Laminates

    Directory of Open Access Journals (Sweden)

    M. Nurhaniza

    2016-01-01

    Full Text Available The quality of the machining is measured from surface finished and it is considered as the most important aspect in composite machining. An appropriate and optimum machining parameters setting is crucial during machining operation in order to enhance the surface quality. The objective of this research is to analyze the effect of machining parameters on the surface quality of CFRP-Aluminium in CNC end milling operation with PCD tool. The milling parameters evaluated are spindle speed, feed rate, and depth of cut. The L9 Taguchi orthogonal arrays, signal-to-noise (S/N ratio, and analysis of variance (ANOVA are employed to analyze the effect of these cutting parameters. The analysis of the results indicates that the optimal cutting parameters combination for good surface finish is high cutting speed, low feed rate, and low depth of cut.

  3. COMPARATIVE STUDY ON THE TECHNICAL PERFORMANCES OF TWO THICKNESSING MACHINES

    Directory of Open Access Journals (Sweden)

    Sergiu RĂCĂŞAN

    2015-06-01

    Full Text Available ract: The paper presents a series of experimental researches on two operating parameters – the energy consumption and the generated noise level – for two thicknessing machines of different generations: MRG8 (production year: 1972 and Felder D963 (production year: 2013. The aim was to highlight some of the developments registered over four decades by this type of woodworking machines. The results show that, in similar operating conditions, the new machine consume less energy and produce lower noise level.

  4. Baseline LHC machine parameters and configuration of the 2015 proton run

    CERN Document Server

    Bruce, R; Fartoukh, S; Giovannozzi, M; Lamont, M; Metral, E; Pieloni, T; Redaelli, S; Wenninger, J

    2015-01-01

    This paper shows the baseline LHC machine parameters for the 2015 start-up. Many systems have been upgraded during LS1 and in 2015 the LHC will operate at a higher energy than before and with a tighter filling scheme. Therefore, the 2015 commissioning phase risks to be less smooth than in 2012. The proposed starting configuration puts the focus on feasibility rather than peak performance and includes margins for operational uncertainties. Instead, once beam experience and a better machine knowledge has been obtained, a push in $\\beta^*$ and performance can be envisaged. In this paper, the focus is on collimation settings and reach in $\\beta^*$---other parameters are covered in greater depth by other papers in these proceedings.

  5. Improvement of Quality of a Modern Commercial Silk Mill through effective Process and Machine Control Parameters

    Directory of Open Access Journals (Sweden)

    Dr. Swapan Kumar Ghosh

    2016-08-01

    Full Text Available This paper deals with international and national scenario of commercial production and market share of silk fabrics with particular reference to process along with machine control parameters followed by adoption of good practices in the preparatory stages during production of the silk fabric in a commercial Silk Mill. An observatory report has been presented here for starting from yarn to the fabric stage, which indicates the major technical reasons for deterioration in the quality of the silk products affecting the cost factor and environment to some extent. This paper delineates an effective monitoring and controlling process variables along with machine parameters at every step of production of silk fabric from its filament yarn stage, particularly during the modern high speed silk twisting process, enhancing the quality of the finished product on one hand and minimizing wastage along with the cost of production and adverse environmental impact on the other

  6. Influence of design parameters on cogging torque in permanent magnet machines \\ud

    OpenAIRE

    Zhu, Z.Q.; Howe, D.

    2000-01-01

    The influence of various design parameters on the cogging torque developed by permanent magnet machines is investigated. It is shown that the slot and pole number combination has a significant effect on the cogging torque, and influences the optimal value of both skew angle and magnet arc, as well as determining the optimal number of auxiliary teeth/slots. A simple factor, which is proportional to the slot number and the pole number and inversely proportional to their smallest common multiple...

  7. Optimization of the WEDM Parameters on Machining Incoloy800 Super alloy with Multiple Quality Characteristics

    Directory of Open Access Journals (Sweden)

    Muthu Kumar V

    2010-06-01

    Full Text Available The present work demonstrates optimization of Wire Electrical Discharge Machining process parameters of Incoloy800 super alloy with multiple performance characteristics such as Material Removal Rate (MRR, surface roughness and Kerf based on the Grey–Taguchi Method. The process parameters considered in this research work are Gap Voltage, Pulse On-time, Pulse Off-time and Wire Feed. Taguchi’s L9 Orthogonal Array was used to conduct experiments. Optimal levels of process parameters were identified using Grey Relational Analysis and the relatively significant parameters were determined by Analysis of Variance. The variation of output responses with process parameters were mathematically modelled by using non-linear regression analysismethod and the models were checked for their adequacy. Result of confirmation experiments shows that the established mathematical models can predict the output responses with reasonable accuracy.

  8. Parametric modeling and optimization of laser scanning parameters during laser assisted machining of Inconel 718

    Science.gov (United States)

    Venkatesan, K.; Ramanujam, R.; Kuppan, P.

    2016-04-01

    This paper presents a parametric effect, microstructure, micro-hardness and optimization of laser scanning parameters (LSP) on heating experiments during laser assisted machining of Inconel 718 alloy. The laser source used for experiments is a continuous wave Nd:YAG laser with maximum power of 2 kW. The experimental parameters in the present study are cutting speed in the range of 50-100 m/min, feed rate of 0.05-0.1 mm/rev, laser power of 1.25-1.75 kW and approach angle of 60-90°of laser beam axis to tool. The plan of experiments are based on central composite rotatable design L31 (43) orthogonal array. The surface temperature is measured via on-line measurement using infrared pyrometer. Parametric significance on surface temperature is analysed using response surface methodology (RSM), analysis of variance (ANOVA) and 3D surface graphs. The structural change of the material surface is observed using optical microscope and quantitative measurement of heat affected depth that are analysed by Vicker's hardness test. The results indicate that the laser power and approach angle are the most significant parameters to affect the surface temperature. The optimum ranges of laser power and approach angle was identified as 1.25-1.5 kW and 60-65° using overlaid contour plot. The developed second order regression model is found to be in good agreement with experimental values with R2 values of 0.96 and 0.94 respectively for surface temperature and heat affected depth.

  9. Machine Learning-Based Parameter Tuned Genetic Algorithm for Energy Minimizing Vehicle Routing Problem

    Directory of Open Access Journals (Sweden)

    P. L. N. U. Cooray

    2017-01-01

    Full Text Available During the last decade, tremendous focus has been given to sustainable logistics practices to overcome environmental concerns of business practices. Since transportation is a prominent area of logistics, a new area of literature known as Green Transportation and Green Vehicle Routing has emerged. Vehicle Routing Problem (VRP has been a very active area of the literature with contribution from many researchers over the last three decades. With the computational constraints of solving VRP which is NP-hard, metaheuristics have been applied successfully to solve VRPs in the recent past. This is a threefold study. First, it critically reviews the current literature on EMVRP and the use of metaheuristics as a solution approach. Second, the study implements a genetic algorithm (GA to solve the EMVRP formulation using the benchmark instances listed on the repository of CVRPLib. Finally, the GA developed in Phase 2 was enhanced through machine learning techniques to tune its parameters. The study reveals that, by identifying the underlying characteristics of data, a particular GA can be tuned significantly to outperform any generic GA with competitive computational times. The scrutiny identifies several knowledge gaps where new methodologies can be developed to solve the EMVRPs and develops propositions for future research.

  10. OPTIMIZATION OF MACHINING PARAMETERS IN TURNING PROCESS USING GENETIC ALGORITHM AND PARTICLE SWARM OPTIMIZATION WITH EXPERIMENTAL VERIFICATION

    Directory of Open Access Journals (Sweden)

    K.RAMESH KUMAR

    2011-02-01

    Full Text Available Optimization of cutting parameters is one of the most important elements in any process planning of metal parts. Economy of machining operation plays a key role in competitiveness in the market. All CNCmachines produce finished components from cylindrical bar. Finished profiles consist of straight turning, facing, taper and circular machining. Finished profile from a cylindrical bar is done in two stages, rough machining and finish machining. Numbers of passes are required for rough machining and single pass is required for the finished pass. The machining parameters in multipass turning are depth of cut, cutting speed and feed. The machining performance is measured by the minimum production time. In this paper the optimal machining parameters for continuous profile machining are determinedwith respect to the minimum production time, subject to a set of practical constraints, cutting force, power and dimensional accuracy and surface finish. Due to complexity of this machining optimizationproblem, a genetic algorithm (GA and Particle Swarm Optimization (PSO are applied to resolve the problem and the results obtained from GA and PSO are compared.

  11. Optimization of process parameters on EN24 Tool steel using Taguchi technique in Electro-Discharge Machining (EDM)

    Science.gov (United States)

    Jeykrishnan, J.; Vijaya Ramnath, B.; Akilesh, S.; Pradeep Kumar, R. P.

    2016-09-01

    In the field of manufacturing sectors, electric discharge machining (EDM) is widely used because of its unique machining characteristics and high meticulousness which can't be done by other traditional machines. The purpose of this paper is to analyse the optimum machining parameter, to curtail the machining time with respect to high material removal rate (MRR) and low tool wear rate (TWR) by varying the parameters like current, pulse on time (Ton) and pulse off time (Toff). By conducting several dry runs using Taguchi technique of L9 orthogonal array (OA), optimized parameters were found using analysis of variance (ANOVA) and the error percentage can be validated and parameter contribution for MRR and TWR were found.

  12. OPTIMIZATION OF MACHINING PARAMETERS USING TAGUCHI APPROACH DURING HARD TURNING OF ALLOY STEEL WITH UNCOATED CARBIDE UNDER DRY CUTTING ENVIRONMENT

    Directory of Open Access Journals (Sweden)

    A. Das

    2015-12-01

    Full Text Available In today’s world of manufacturing by machining process two things are very important, one is productivity and the other one is quality. Quality of a product generally depends upon the surface finish and dimensional deviations. The productivity can be seen as a key economic indicator of innovation in terms of higher material removal rate with a less time and cost in machining industries. Taguchi method is a popular statistical technique for optimization of input parameters to get the best output results. Dry machining is a popular methodology for machining hard material and it has been accepted by many researchers to a great extent because of its low cost and safety. Many scientists have taken various input parameters and studied their effects on different output responses. In the present paper an attempt has been made to study the effect of input parameters such as cutting speed, feed rate and depth of cut on Surface roughness, Tool wear, Power consumption and Chip reduction co-efficient under dry condition using uncoated carbide insert. Signal to noise ratio has been used to select the optimal condition for various output responses. ANOVA table has been drawn for each output responses and finally mathematical model of multiple regression analysis has been prepared and authenticity of the statistical model have been checked by normal probability plot. It has been found from the experimental result that the power consumption and flank wear both were minimum at the cutting speed of 250 rpm and 400 rpm respectively. Chip reduction coefficient has been found minimum at a depth of cut of 0.3 mm and surface roughness was minimum at 0.1 mm/rev. feed rate.

  13. Investigation of the Effects of Machining Parameters on Material Removal Rate in Abrasive Waterjet Turning

    Directory of Open Access Journals (Sweden)

    Iman Zohourkari

    2014-05-01

    Full Text Available The effects of the main operational machining parameters on the material removal rate (MRR in abrasive waterjet turning (AWJT are presented in this paper using a statistical approach. The five most common machining parameters such as water pressure, abrasive mass flow rate, cutting head traverse speed, workpiece rotational speed, and depth of cut have been put into a five-level central composite rotatable experimental design (CCRD. The main effects of parameters and the interaction among them were analyzed by means of the analysis of variance (ANOVA and the response surfaces for MRR were obtained fitting a second-order polynomial function. It has been found that depth of cut and cutting head traverse speed are the most influential parameters, whereas the rotational speed is insignificant. In addition, the investigations show that interactions between traverse speed and pressure, abrasive mass flow rate and depth of cut, and pressure and depth of cut are significant on MRR. This result advances the AWJT state of the art. A complete model discussion has been reported drawing interesting considerations on the AWJT process characterising phenomena, where parameters interactions play a fundamental role.

  14. Optimization of espresso machine parameters through the analysis of coffee odorants by HS-SPME-GC/MS.

    Science.gov (United States)

    Caprioli, Giovanni; Cortese, Manuela; Cristalli, Gloria; Maggi, Filippo; Odello, Luigi; Ricciutelli, Massimo; Sagratini, Gianni; Sirocchi, Veronica; Tomassoni, Giacomo; Vittori, Sauro

    2012-12-01

    The aroma profile and the final quality of espresso coffee (EC) are influenced by such technical conditions as the EC machine extraction temperature and the pressure used. The effect of these two parameters on EC quality were studied in combination by headspace solid phase micro extraction-gas chromatography-mass spectrometry (SPME-GC-MS) and sensory profile. Moreover, 10 key odorants at the best EC machine settings were examined to compare the two coffee cultivars (Arabica and Robusta) and two EC machines [Aurelia Competizione (A) and Leva Arduino (B)]. The data obtained provides important information about espresso making technique, suggesting that the usual espresso machine temperature and pressure settings (i.e. 92°C and 9bar) are very close to those needed to obtain the best quality espresso. This confirms the traditional wisdom of coffee making, which judges 25ml, the typical volume of a certified Italian EC, to be ideal for very strong aroma intensity. Copyright © 2012 Elsevier Ltd. All rights reserved.

  15. Hybrid Swarm Algorithms for Parameter Identification of an Actuator Model in an Electrical Machine

    Directory of Open Access Journals (Sweden)

    Ying Wu

    2011-01-01

    Full Text Available Efficient identification and control algorithms are needed, when active vibration suppression techniques are developed for industrial machines. In the paper a new actuator for reducing rotor vibrations in electrical machines is investigated. Model-based control is needed in designing the algorithm for voltage input, and therefore proper models for the actuator must be available. In addition to the traditional prediction error method a new knowledge-based Artificial Fish-Swarm optimization algorithm (AFA with crossover, CAFAC, is proposed to identify the parameters in the new model. Then, in order to obtain a fast convergence of the algorithm in the case of a 30 kW two-pole squirrel cage induction motor, we combine the CAFAC and Particle Swarm Optimization (PSO to identify parameters of the machine to construct a linear time-invariant(LTI state-space model. Besides that, the prediction error method (PEM is also employed to identify the induction motor to produce a black box model with correspondence to input-output measurements.

  16. Study of Virtual Machine and its application

    Directory of Open Access Journals (Sweden)

    Rohaan Chandra

    2013-07-01

    Full Text Available A virtual machine is software that’s capable of executing programs as if it were a physical machine—it’s a computer within a computer. A virtual machine (VM is a software implemented abstraction of the underlying hardware, which is presented to the application layer of the system. Virtual machines may be based on specifications of a hypothetical computer or emulate the computer architecture and functions of a real world computer.

  17. EXPERIMENTAL STUDY OF THE DYNAMICS OF CENTRIFUGAL CASTING MACHINES FOR PRODUCTION OF MILL ROLLS

    Directory of Open Access Journals (Sweden)

    P. G. Anofriev

    2017-06-01

    Full Text Available Purpose. The main purpose of experimental studies is to establish the adequacy of the developed mathematical models of machine fluctuations and the actual parameters of machine vibration. Almost all casting machines for the production of mill rolls have a unique design and performances. The additional aim of this work is to compare the vibration level of the casting machine with the requirements of the current vibration standards for new technological machines. Frequency analysis of the oscillations allows establishing defects in workmanship, errors of rotating parts installation and their influence on the dynamics of the machine. Methodology. Measurement of vibration parameters was performed on the moving parts of roller bearings of the machine. To measure the amplitudes of accelerations in three mutually perpendicular directions piezoelectric sensors with magnetic mount were used. Electrical signals from the sensors were recorded on magnetic tape. Further analysis of the oscillations was carried out and visualized using specialized frequency analyzer. The frequency analyzer implements the algorithm of fast Fourier transformation and/or integration of sensor input signal. After the first integration the data for plotting the vibration velocity spectrogram were obtained and as a result of the second integration there are the data of vibration displacements spectrogram of the machine supports. Findings. The results of experimental studies of centrifugal casting machine vibrations for the production of two-layer rolls were presented. There were obtained and analyzed the spectrograms of accelerations, velocities and displacements of moving parts of the upper and lower roller supports. The work of the machine is associated with the calculated values passing of critical frequencies and the short-term development of resonance oscillations of the rotor and roller bearings. Originality. For the first time the author obtained the frequency spectra of

  18. Study on Simulation of Machining Errors Caused by Cutting Force

    Institute of Scientific and Technical Information of China (English)

    SHAO Xiaodong; ZHANG Liu; LIN Zhaoxu

    2006-01-01

    Machining errors caused by cutting force are studied in this paper, and an algorithm to simulate errors is putted forward. In the method, continuous machining process is separated into many machining moments. The deformation of work-piece and cutter at every moment is calculated by finite element method. The machined work-piece is gained by Boolean operation between deformed work-piece and cutter. By analyzing data of final work-piece, machining errors are predicted. The method is proved true by experiment.

  19. Effect of different parameters on machining of SiC/SiC composites via pico-second laser

    Energy Technology Data Exchange (ETDEWEB)

    Li, Weinan; Zhang, Ruoheng [State Key Laboratory of Transient Optics and Photonics, Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi’an, Shaanxi 10068 (China); Liu, Yongsheng, E-mail: yongshengliu@nwpu.edu.cn [Science and technology on Thermostructure Composite Materials Laboratory, Northwestern Polytechnical University, Xi’an, Shaanxi 710072 (China); Wang, Chunhui; Wang, Jing [Science and technology on Thermostructure Composite Materials Laboratory, Northwestern Polytechnical University, Xi’an, Shaanxi 710072 (China); Yang, Xiaojun [State Key Laboratory of Transient Optics and Photonics, Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi’an, Shaanxi 10068 (China); Cheng, Laifei [Science and technology on Thermostructure Composite Materials Laboratory, Northwestern Polytechnical University, Xi’an, Shaanxi 710072 (China)

    2016-02-28

    Graphical abstract: - Highlights: • The highlights of the manuscript include the following two aspects. • First, we found that the different machining modes (helical line scanning and single ring line scanning) and processing power of machining have remarkable effect on the surface morphology of the machined area, such as the shape, depth and the formation of different surface structures. • Secondly, we investigated that the debris consisted of C, Si and O was observed on the machined surface. • Some of the Si–C bonds of the SiC matrix and fibers would be transformed into Si–O bonds after machined, depending on the processing power. - Abstract: Pico-second laser plays an important role in modern machining technology, especially in machining high hardness materials. In this article, pico-second laser was utilized for irradiation on SiC/SiC composites, and effects of different processing parameters including the machining modes and laser power were discussed in detail. The results indicated that the machining modes and laser power had great effect on machining of SiC/SiC composites. Different types of surface morphology and structure were observed under helical line scanning and single ring line scanning, and the analysis of their formulation was discussed in detail. It was believed that the machining modes would be responsible to the different shapes of machining results at the same parameters. The processing power shall also influence the surface morphology and quality of machining results. In micro-hole drilling process, large amount of debris and fragments were observed within the micro-holes, and XPS analysis showed that there existed Si–O bonds and Si–C bonds, indicating that the oxidation during processing was incomplete. Other surface morphology, such as pores and pits were discussed as well.

  20. Electron cloud studies for heavy-ion and proton machines

    CERN Document Server

    Petrov, F; Weiland, Th

    2013-01-01

    Electron cloud effects are a known problem in various accelerator facilities around the world. Electron clouds cause instabilities and emittance growth in positron and proton beams as well as in heavy ion beams. Most of the hadron machines experience the build-up of EC due to the multipacting. In LHC and in positron machines production of electrons due to the synchrotron radiation becomes as important as the build-up due to the secondary emission. The main source of seed electrons in heavy ion machines is the residual gas ionization. FAIR facility in Darmstadt will operate with heavy-ion and proton beams. However, the beam parameters are such that the multipacting will start to play a role only for the unconditioned wall with the secondary emission yieldmore than 1.8. In this paperwe study the electron cloud build-up and its effect on the beam stability for FAIR heavy-ion coasting beams. These beams will be used during slow extraction. Electron scattering on the beam ions and its effect on the final neutraliz...

  1. Parameters identification of the compound cage rotor induction machine based on linearized Kalman filtering

    Institute of Scientific and Technical Information of China (English)

    王铁成; 李伟力; 孙建伟

    2003-01-01

    A mathematical model has been built up for compound cage rotor induction machine with the rotor re-sistance and leakage inductance in the model identified through Kalman filtering method. Using the identifiedparameters, simulation studies are performed, and simulation results are compared with testing results.

  2. Using Phun to Study "Perpetual Motion" Machines

    Science.gov (United States)

    Kores, Jaroslav

    2012-01-01

    The concept of "perpetual motion" has a long history. The Indian astronomer and mathematician Bhaskara II (12th century) was the first person to describe a perpetual motion (PM) machine. An example of a 13th-century PM machine is shown in Fig. 1. Although the law of conservation of energy clearly implies the impossibility of PM construction, over…

  3. Recovery studies for plutonium machining oil coolant

    Energy Technology Data Exchange (ETDEWEB)

    Navratil, J. D.; Baldwin, C. E.

    1977-04-27

    Lathe coolant oil, contaminated with plutonium and having a carbon tetrachloride diluent, is generated in plutonium machining areas at Rocky Flats. A research program was initiated to determine the nature of plutonium in this mixture of oil and carbon tetrachloride. Appropriate methods then could be developed to remove the plutonium and to recycle the oil and carbon tetrachloride. Studies showed that the mixtures of spent oil and carbon tetrachloride contained particulate plutonium and plutonium species that are soluble in water or in oil and carbon tetrachloride. The particulate plutonium was removed by filtration; the nonfilterable plutonium was removed by adsorption on various materials. Laboratory-scale tests indicated the lathe-coolant oil mixture could be separated by distilling the carbon tetrachloride to yield recyclable products.

  4. Using Phun to Study ``Perpetual Motion'' Machines

    Science.gov (United States)

    Koreš, Jaroslav

    2012-05-01

    The concept of "perpetual motion" has a long history. The Indian astronomer and mathematician Bhaskara II (12th century) was the first person to describe a perpetual motion (PM) machine. An example of a 13th- century PM machine is shown in Fig. 1. Although the law of conservation of energy clearly implies the impossibility of PM construction, over the centuries numerous proposals for PM have been made, involving ever more elements of modern science in their construction. It is possible to test a variety of PM machines in the classroom using a program called Phun2 or its commercial version Algodoo.3 The programs are designed to simulate physical processes and we can easily simulate mechanical machines using them. They provide an intuitive graphical environment controlled with a mouse; a programming language is not needed. This paper describes simulations of four different (supposed) PM machines.4

  5. Optimization and Analysis of Laser Beam Machining Parameters for Al7075-TiB2 In-situ Composite

    Science.gov (United States)

    Manjoth, S.; Keshavamurthy, R.; Pradeep Kumar, G. S.

    2016-09-01

    The paper focuses on laser beam machining (LBM) of In-situ synthesized Al7075-TiB2 metal matrix composite. Optimization and influence of laser machining process parameters on surface roughness, volumetric material removal rate (VMRR) and dimensional accuracy of composites were studied. Al7075-TiB2 metal matrix composite was synthesized by in-situ reaction technique using stir casting process. Taguchi's L9 orthogonal array was used to design experimental trials. Standoff distance (SOD) (0.3 - 0.5mm), Cutting Speed (1000 - 1200 m/hr) and Gas pressure (0.5 - 0.7 bar) were considered as variable input parameters at three different levels, while power and nozzle diameter were maintained constant with air as assisting gas. Optimized process parameters for surface roughness, volumetric material removal rate (VMRR) and dimensional accuracy were calculated by generating the main effects plot for signal noise ratio (S/N ratio) for surface roughness, VMRR and dimensional error using Minitab software (version 16). The Significant of standoff distance (SOD), cutting speed and gas pressure on surface roughness, volumetric material removal rate (VMRR) and dimensional error were calculated using analysis of variance (ANOVA) method. Results indicate that, for surface roughness, cutting speed (56.38%) is most significant parameter followed by standoff distance (41.03%) and gas pressure (2.6%). For volumetric material removal (VMRR), gas pressure (42.32%) is most significant parameter followed by cutting speed (33.60%) and standoff distance (24.06%). For dimensional error, Standoff distance (53.34%) is most significant parameter followed by cutting speed (34.12%) and gas pressure (12.53%). Further, verification experiments were carried out to confirm performance of optimized process parameters.

  6. Taguchi optimization of machining parameters in drilling of AISI D2 steel using cryo-treated carbide drills

    Indian Academy of Sciences (India)

    GULSAH AKINCIOGLU; FARUK MENDI; ADEM CICEK; SITKI AKINCIOGLU

    2017-02-01

    This study focused on using the Taguchi technique to optimize the process parameters in drilling of AISI D2 steel with carbide drills to minimize the surface roughness (Ra) and thrust forces (Ff). The drilling experiments were conducted on a CNC vertical machining centre according to the L18 experimental design. Uncoated drills were classified into three groups: untreated (U), cryo-treated (CT) and cryo-treated and tempered (CTT). The experimental results showed that the CTT drills exhibited the best performance in terms of Ra and Ff due to the improved wear resistance of carbide drills after the cryogenic treatment and tempering. As a result of analysis of variance (ANOVA), it was found that the most influential parameter on both Ra and Ff was the feed rate, with percentage contributions of 66.97% and 80.07%, respectively. The results showed that the Taguchitechnique is a powerful method to optimize the process parameters in drilling of tool steel.

  7. A Method for Identifying the Mechanical Parameters in Resistance Spot Welding Machines

    DEFF Research Database (Denmark)

    Wu, Pei; Zhang, Wenqi; Bay, Niels

    2003-01-01

    Mechanical dynamic responses of resistance welding machine have a significant influence on weld quality and electrode service life, it must be considered when the real welding production is carried out or the welding process is stimulated. The mathematical models for characterizing the mechanical...... dynamic responses are normally a few coupled differential equations which can be easily created according to the theories of kinematics and dynamics, however the problem is that the parameters contained in the equations are unavailable and hard to be determined directly due to the complexities...

  8. Optimization of the machining parameters for EDM wire cutting of Tungsten Carbide

    Directory of Open Access Journals (Sweden)

    Kumar Gaurav

    2016-01-01

    Full Text Available Electrical discharge machining is a thermal erosion process which is based on thermoelectric energy between the work piece and electrode. Its capability of machining in hard and difficult to cut materials has made it most popular. Tungsten carbide is widely used in industry due to its unique properties combination of hardness and wear resistance. But the machining of the tungsten carbide is very difficult. In our research we tried to find optimized procedure to cut the Tungsten carbide by variation of different parameters so that process can be carried out in maximum Material Removal Rate (MRR with better surface finish. During the experimentation, Brass wire is used for cutting.. The experiment is designed with the help of Taguchi method and further analysis done with the help of ANOVA. In this experiment we find that the minimum mean of surface roughness is 2.214 achieved at Tension- 0.6 N, Feed- 10m/min, Flushing Pressure- 3kg/cm2, Current- 80A.

  9. A Review on Optimization of Process Parameters for Improving Performance in Electrical Discharge Machining

    Directory of Open Access Journals (Sweden)

    Viral B. Prajapati

    2014-02-01

    Full Text Available The correct selection of manufacturing conditions is one of the most important aspects to take into consideration in the majority of manufacturing processes and, particularly, in processes related to Electrical Discharge Machining (EDM. It is a capable of machining geometrically complex or hard material components, that are precise and difficult-to-machine such as heat treated tool steels, composites, super alloys, ceramics, carbides, heat resistant steels etc. being widely used in die and mold making industries, aerospace, aeronautics and nuclear industries. From the point of view of industrial applications, SS 410 is a very important material and that’s why for the purpose of experimentation SS 410 with copper electrode and EDM oil as dielectric has been used In the present work. I will take input parameter discharge current, pulse on time and pulse off time. Design of Experiment (DOE with full factorial design has been explored to produce 27 specimens on SS 410 by edm operation. MRR will be calculated from MRR equation and software available for it and then compare it. Collected data related to surface roughness have been utilized for optimization.

  10. Optimization of Machining Parameters for Minimization of Roundness Error in Deep Hole Drilling using Minimum Quantity Lubricant

    Directory of Open Access Journals (Sweden)

    Kamaruzaman Anis Farhan

    2016-01-01

    Full Text Available This paper presents an experimental investigation of deep hole drilling using CNC milling machine. This experiment investigates the effect of machining parameters which are spindle speed, feed rate and depth of hole using minimum quantity lubricant on the roundness error. The experiment was designed using two level full factorial with four center point. Finally, the machining parameters were optimized in obtaining the minimum value of roundness error. The minimum value of roundness error for deep hole drilling is 0.0266 at the spindle speed is 800 rpm, feed rate is 60 mm/min, depth of hole is 70 mm and minimum quantity lubricant is 30ml/hr.

  11. Automated process parameters tuning for an injection moulding machine with soft computing§

    Institute of Scientific and Technical Information of China (English)

    Peng ZHAO; Jian-zhong FU; Hua-min ZHOU; Shu-biao CUI

    2011-01-01

    In injection moulding production, the tuning of the process parameters is a challenging job, which relies heavily on the experience of skilled operators. In this paper, taking into consideration operator assessment during moulding trials, a novel intelligent model for automated tuning of process parameters is proposed. This consists of case based reasoning (CBR), empirical model (EM), and fuzzy logic (FL) methods. CBR and EM are used to imitate recall and intuitive thoughts of skilled operators,respectively, while FL is adopted to simulate the skilled operator optimization thoughts. First, CBR is used to set up the initial process parameters. If CBR fails, EM is employed to calculate the initial parameters. Next, a moulding trial is performed using the initial parameters. Then FL is adopted to optimize these parameters and correct defects repeatedly until the moulded part is found to be satisfactory. Based on the above methodologies, intelligent software was developed and embedded in the controller of an injection moulding machine. Experimental results show that the intelligent software can be effectively used in practical production, and it greatly reduces the dependence on the experience of the operators.

  12. The use of a realistic VMAT delivery emulator to optimize dynamic machine parameters for improved treatment efficiency

    Energy Technology Data Exchange (ETDEWEB)

    Boylan, C J; Rowbottom, C G; Mackay, R I, E-mail: Christopher.Boylan@physics.cr.man.ac.uk [North Western Medical Physics, Christie NHS Foundation Trust, Wilmslow Road, Manchester M20 4BX (United Kingdom)

    2011-07-07

    The delivery of volumetric modulated arc therapy (VMAT) requires the simultaneous movement of the linear accelerator gantry, multi-leaf collimators and jaws while the dose rate is varied. In this study, a VMAT delivery emulator was developed to accurately predict the characteristics of a given treatment plan, incorporating realistic parameters for gantry inertia and the variation in leaf speed with respect to gravity. The emulator was used to assess the impact of dynamic machine parameters on the delivery efficiency, using a set of prostate and head and neck VMAT plans. Initially, assuming a VMAT system with fixed dose rate bins, the allowable leaf and jaw speeds were increased and a significant improvement in treatment time and average dose rate was observed. The software was then adapted to simulate a VMAT system with continuously varying dose rate, and the increase in delivery efficiency was quantified, along with the impact of an increased leaf and jaw speed. Finally, a set of optimal dynamic machine parameters was derived assuming an idealized scenario in which the treatment is delivered in a single arc at constant maximum gantry speed.

  13. Diamond Tool Specific Wear Rate Assessment in Granite Machining by Means of Knoop Micro-Hardness and Process Parameters

    Science.gov (United States)

    Goktan, R. M.; Gunes Yılmaz, N.

    2017-09-01

    The present study was undertaken to investigate the potential usability of Knoop micro-hardness, both as a single parameter and in combination with operational parameters, for sawblade specific wear rate (SWR) assessment in the machining of ornamental granites. The sawing tests were performed on different commercially available granite varieties by using a fully instrumented side-cutting machine. During the sawing tests, two fundamental productivity parameters, namely the workpiece feed rate and cutting depth, were varied at different levels. The good correspondence observed between the measured Knoop hardness and SWR values for different operational conditions indicates that it has the potential to be used as a rock material property that can be employed in preliminary wear estimations of diamond sawblades. Also, a multiple regression model directed to SWR prediction was developed which takes into account the Knoop hardness, cutting depth and workpiece feed rate. The relative contribution of each independent variable in the prediction of SWR was determined by using test statistics. The prediction accuracy of the established model was checked against new observations. The strong prediction performance of the model suggests that its framework may be applied to other granites and operational conditions for quantifying or differentiating the relative wear performance of diamond sawblades.

  14. Advances in three-dimensional field analysis and evaluation of performance parameters of electrical machines

    Science.gov (United States)

    Sivasubramaniam, Kiruba

    This thesis makes advances in three dimensional finite element analysis of electrical machines and the quantification of their parameters and performance. The principal objectives of the thesis are: (1)the development of a stable and accurate method of nonlinear three-dimensional field computation and application to electrical machinery and devices; and (2)improvement in the accuracy of determination of performance parameters, particularly forces and torque computed from finite elements. Contributions are made in two general areas: a more efficient formulation for three dimensional finite element analysis which saves time and improves accuracy, and new post-processing techniques to calculate flux density values from a given finite element solution. A novel three-dimensional magnetostatic solution based on a modified scalar potential method is implemented. This method has significant advantages over the traditional total scalar, reduced scalar or vector potential methods. The new method is applied to a 3D geometry of an iron core inductor and a permanent magnet motor. The results obtained are compared with those obtained from traditional methods, in terms of accuracy and speed of computation. A technique which has been observed to improve force computation in two dimensional analysis using a local solution of Laplace's equation in the airgap of machines is investigated and a similar method is implemented in the three dimensional analysis of electromagnetic devices. A new integral formulation to improve force calculation from a smoother flux-density profile is also explored and implemented. Comparisons are made and conclusions drawn as to how much improvement is obtained and at what cost. This thesis also demonstrates the use of finite element analysis to analyze torque ripples due to rotor eccentricity in permanent magnet BLDC motors. A new method for analyzing torque harmonics based on data obtained from a time stepping finite element analysis of the machine is

  15. Design of Parameter Independent, High Performance Sensorless Controllers for Permanent Magnet Synchronous Machines

    DEFF Research Database (Denmark)

    Xie, Ge

    parameters such as resistance and inductance are involved in many existing sensorless control algorithms. Therefore, varying machine parameters due to different operation conditions may affect the accuracy of the position estimation and the drive performance consequently. For power converter manufactures...... of the typical sensorless algorithm – the INFORM method is implemented and tested. It is demonstrated that the voltage error may seriously affect the performance of the position estimator. To overcome this difficulty, a new implementation scheme of the INFORM method with easy inverter voltage error compensation......) PWM periods. In the injection period, the voltage output from the inverter is forced to be zero. The rotor position and the speed are then estimated simply from the current changes during this zero voltage injection period. This method provides a good performance for the rotor position estimation...

  16. Fundamental Parameters of Main-Sequence Stars in an Instant with Machine Learning

    CERN Document Server

    Bellinger, Earl P; Hekker, Saskia; Basu, Sarbani; Ball, Warrick; Guggenberger, Elisabeth

    2016-01-01

    Owing to the remarkable photometric precision of space observatories like Kepler, stellar and planetary systems beyond our own are now being characterized en masse for the first time. These characterizations are pivotal for endeavors such as searching for Earth-like planets and solar twins, understanding the mechanisms that govern stellar evolution, and tracing the dynamics of our Galaxy. The volume of data that is becoming available, however, brings with it the need to process this information accurately and rapidly. While existing methods can constrain fundamental stellar parameters such as ages, masses, and radii from these observations, they require substantial computational efforts to do so. We develop a method based on machine learning for rapidly estimating fundamental parameters of main-sequence solar-like stars from classical and asteroseismic observations. We first demonstrate this method on a hare-and-hound exercise and then apply it to the Sun, 16 Cyg A & B, and 34 planet-hosting candidates th...

  17. Parameters optimization in a fission-fusion system with a mirror machine based neutron source

    Science.gov (United States)

    Yurov, D. V.; Anikeev, A. V.; Bagryansky, P. A.; Brednikhin, S. A.; Frolov, S. A.; Lezhnin, S. I.; Prikhodko, V. V.

    2012-06-01

    Long-lived fission products utilization is a problem of high importance for the modern nuclear reactor technology. BINP jointly with NSI RAS develops a conceptual design of a hybrid sub-critical minor actinides burner with a neutron source based on the gas dynamic mirror machine (GDT) to resolve the stated task. A number of modelling tools was created to calculate the main parameters of the device. First of the codes, GENESYS, is a zero-dimensional code, designed for plasma dynamics numerical investigation in a GDT-based neutron source. The code contains a Monte-Carlo module for the determination of linear neutron emission intensity along the machine axis. Fuel blanket characteristics calculation was implemented by means of a static Monte-Carlo code NMC. Subcritical core, which has been previously analyzed by OECD-NEA, was used as a template for the fuel blanket of the modelled device. This article represents the codes used and recent results of the described system parameters optimization. Particularly, optimum emission zone length of the source and core multiplicity dependence on buffer zone thickness were defined.

  18. Optimization of Process Parameters on MRR and Overcut in Electrochemical Micro Machining on Metal Matrix Composites Using Grey Relational Analysis

    Directory of Open Access Journals (Sweden)

    S.Dharmalingam

    2014-05-01

    Full Text Available This paper investigates the influence of the process parameters like machining voltage, electrolyte concentration, frequency on the over cut and Material Removal Rate (MRR through taguchi methodology and grey relational analysis. This paper discusses a methodology for the optimization of the machining parameters on drilling of Al - 6% Gr Metal Matrix composites using Electrochemical Micro Machining (EMM. Based on the analysis, optimum levels of parameters were determined and the same to validate through the confirmation test. Experimental results are in close agreement with the developed model. The confirmation results reveal that, there is considerable improvement in Material Removal Rate, Overcut, Grey relational grade are improved by 08.33 %, 41.17 % and 81.77 % respectively. It is observed that the machining performance can be effectively improved with respect to initial parametric setting.

  19. Communication Studies of DMP and SMP Machines

    Science.gov (United States)

    Sohn, Andrew; Biswas, Rupak; Chancellor, Marisa K. (Technical Monitor)

    1997-01-01

    Understanding the interplay between machines and problems is key to obtaining high performance on parallel machines. This paper investigates the interplay between programming paradigms and communication capabilities of parallel machines. In particular, we explicate the communication capabilities of the IBM SP-2 distributed-memory multiprocessor and the SGI PowerCHALLENGEarray symmetric multiprocessor. Two benchmark problems of bitonic sorting and Fast Fourier Transform are selected for experiments. Communication-efficient algorithms are developed to exploit the overlapping capabilities of the machines. Programs are written in Message-Passing Interface for portability and identical codes are used for both machines. Various data sizes and message sizes are used to test the machines' communication capabilities. Experimental results indicate that the communication performance of the multiprocessors are consistent with the size of messages. The SP-2 is sensitive to message size but yields a much higher communication overlapping because of the communication co-processor. The PowerCHALLENGEarray is not highly sensitive to message size and yields a low communication overlapping. Bitonic sorting yields lower performance compared to FFT due to a smaller computation-to-communication ratio.

  20. Effect of different parameters on machining of SiC/SiC composites via pico-second laser

    Science.gov (United States)

    Li, Weinan; Zhang, Ruoheng; Liu, Yongsheng; Wang, Chunhui; Wang, Jing; Yang, Xiaojun; Cheng, Laifei

    2016-02-01

    Pico-second laser plays an important role in modern machining technology, especially in machining high hardness materials. In this article, pico-second laser was utilized for irradiation on SiC/SiC composites, and effects of different processing parameters including the machining modes and laser power were discussed in detail. The results indicated that the machining modes and laser power had great effect on machining of SiC/SiC composites. Different types of surface morphology and structure were observed under helical line scanning and single ring line scanning, and the analysis of their formulation was discussed in detail. It was believed that the machining modes would be responsible to the different shapes of machining results at the same parameters. The processing power shall also influence the surface morphology and quality of machining results. In micro-hole drilling process, large amount of debris and fragments were observed within the micro-holes, and XPS analysis showed that there existed Si-O bonds and Si-C bonds, indicating that the oxidation during processing was incomplete. Other surface morphology, such as pores and pits were discussed as well.

  1. Studies on parametric optimization for abrasive water jet machining of Al7075-TiB2 in-situ composite

    Science.gov (United States)

    Kavya, J. T.; Keshavamurthy, R.; Pradeep Kumar, G. S.

    2016-09-01

    The study focuses on optimization and determination of significant process parameter for Abrasive Water Jet Machining of Al7075-TiB2metal matrix composite. Al-TiB2 metal matrix composite is synthesized by stir casting using in-situ technique. Optimization of machining parameters is done using Taguchi's L25orthogonal array for the experimental trials, with cutting speed, stand-off distance and Abrasive Flow rate as input parameters at five different levels. Analysis Of Variance (ANOVA) method is used for identifying the effect of machining parameters on volumetric material removal rate, surface roughness and dimensional accuracy. Then the results are validated by conducting verification experiments.

  2. Mathematical modeling and analysis of WEDM machining parameters of nickel-based super alloy using response surface methodology

    Indian Academy of Sciences (India)

    M P GARG; ANISH KUMAR; C K SAHU

    2017-06-01

    Inconel 625 is one of the most versatile nickel-based super alloy used in the aerospace, automobile, chemical processing, oil refining, marine, waste treatment, pulp and paper, and power industries. Wire electrical discharge machining (WEDM) is the process considered in the present text for machining of Inconel 625 as it can provide an effective solution for machining ultra-hard, high-strength and temperature-resistant materials and alloys, overcoming the constraints of the conventional processes. The present work is mainly focused on the analysis and optimization of the WEDM process parameters of Inconel 625. The four machining parameters, that is, pulse on time, pulse off time, spark gap voltage and wire feed have been varied to investigate their effects onthree output responses, such as cutting speed, gap current, and surface roughness. Response surface methodology was used to develop the experimental models. The parametric analysis-based results revealed that pulse on time and pulse off time were significant, spark gap voltage is the least significant, and wire feed as a single factor is insignificant. Multi-objective optimization technique was employed using desirability approach to obtain theoptimal parameters setting. Furthermore, surface topography in terms of machining parameters revealed that pulse on time and pulse off time significantly deteriorate the surface of the machined samples, which produce thedeeper, wider overlapping craters and globules of debris.

  3. Investigation of Effect of Operating Parameters of A CNC Cylindrical Grinding Machine on Geometric Dimensioning and Tolerancing

    Directory of Open Access Journals (Sweden)

    Jayalakshmi

    2014-03-01

    Full Text Available Machining processes are met with dimensional and geometrical variations in a product during machining operation. The amount of variation needs to be more strictly defined for accurately machined parts. Geometric dimensioning and tolerancing (GD&T definition provides the precision required for allowing manufacturing of most economical parts. Crankshaft flange is required to be machined with higher degree of precision. If geometrical accuracies are not met the crankshaft-flywheel assembly will cause wear, unbalance and vibration, leading to poor functionality. The face of crankshaft flange is evaluated for geometric tolerances- flatness and runout. A two level three factor factorial model is designed and analyzed on Minitab 16 software to identify the most affecting machining parameter among speed, feed and depth of cut on face flatness and face runout.

  4. Beam Dynamics Studies in Recirculating Machines

    CERN Document Server

    Pellegrini, Dario; Latina, A

    The LHeC and the CLIC Drive Beam share not only the high-current beams that make them prone to show instabilities, but also unconventional lattice topologies and operational schemes in which the time sequence of the bunches varies along the machine. In order to asses the feasibility of these projects, realistic simulations taking into account the most worrisome effects and their interplays, are crucial. These include linear and non-linear optics with time dependent elements, incoherent and coherent synchrotron radiation, short and long-range wakefields, beam-beam effect and ion cloud. In order to investigate multi-bunch effects in recirculating machines, a new version of the tracking code PLACET has been developed from scratch. PLACET2, already integrates most of the effects mentioned before and can easily receive additional physics. Its innovative design allows to describe complex lattices and track one or more bunches accordingly to the machine operation, reproducing the bunch train splitting and recombinat...

  5. 深孔钻镗床控制系统改造与切削参数监测研究%Study on Control System Transformation and Cutting Parameter Monitoring for Deep Hole Boring Machine

    Institute of Scientific and Technical Information of China (English)

    杨福合; 胡振华; 庞明超

    2015-01-01

    Combining with actual situation of production and processing, the original machine tool control system defects were an⁃alyzed. According to the needs of users, a high automatic control and detection scheme was presented. The system was mainly composed by PLC, touch screen, inverter, servo drives, and the stepless speed regulation of spindle and tool feed speed, feed depth arbitrary control could be realized, so flexibility of the machining process could be ensured to the maximum extent. At the same time, cutting pa⁃rameter monitoring function could be used to improve machining precision and efficiency, to ensure the machining quality, reduce waste product rate.%结合生产加工的实际情况,分析了原深孔加工机床控制系统存在的缺陷,并根据用户的需求提出了一种高自动化的控制与检测方案。系统主要由PLC、触摸屏、变频器、伺服驱动组成,可实现主轴的无级调速和刀具进给速度、进给深度的任意控制,最大程度上保证了加工工艺的灵活性。同时,切削参数监控功能在提高加工精度与效率的同时,保证了加工质量,降低了废品率。

  6. Study on the nano machining process with a vibrating AFM tip on the polymer surface

    Energy Technology Data Exchange (ETDEWEB)

    Liu Weitao [State Key Laboratory of Robotics and Systems, Robotics Institute, Harbin Institute of Technology, Harbin 150080 (China); Center for Precision Engineering, Harbin Institute of Technology, Harbin, Heilongjiang 150001 (China); Yan Yongda, E-mail: yanyongda@yahoo.com.cn [State Key Laboratory of Robotics and Systems, Robotics Institute, Harbin Institute of Technology, Harbin 150080 (China); Center for Precision Engineering, Harbin Institute of Technology, Harbin, Heilongjiang 150001 (China); Hu Zhenjiang; Zhao Xuesen; Yan Jiucun; Dong Shen [Center for Precision Engineering, Harbin Institute of Technology, Harbin, Heilongjiang 150001 (China)

    2012-01-15

    The polymer has been proved to be nano machined by a vibrating tip in tapping mode of Atomic Force Microscope (AFM). The force between the tip and the surface is an important factor which determines success of the machining process. Controlling this force with high accuracy is the foundation of nanomachining in AFM tapping mode. To achieve a deeper understanding on this process, the tip is modeled as a driving oscillator with damping. Factors affecting the nano machining process are studied. The Hertz elastic contact theory is used to calculate the maximum contact pressure applied by the tip which is employed as a criterion to judge the deformation state of the sample. The simulation results show that: The driven amplitude can be used as a main parameter of controlling the machined depth. Sharper tips and harder cantilevers should be used for successful nanomachining with the vibrating tip. Under the same conditions, a larger tip radius will not only result in the machining error, but also lead to failure of the nanomachining process. The higher driving frequency will lead to a larger tapping force. However it cannot be used as a parameter to control the machined depth because of its narrow variation range. But it is a main error source for the nanomachining process in AFM tapping mode. Moreover, a larger Young's modulus polymer sample will induce a smaller machined depth, a larger maximum contact pressure and a bigger tapping force.

  7. Detection of Periodic Leg Movements by Machine Learning Methods Using Polysomnographic Parameters Other Than Leg Electromyography

    Directory of Open Access Journals (Sweden)

    İlhan Umut

    2016-01-01

    Full Text Available The number of channels used for polysomnographic recording frequently causes difficulties for patients because of the many cables connected. Also, it increases the risk of having troubles during recording process and increases the storage volume. In this study, it is intended to detect periodic leg movement (PLM in sleep with the use of the channels except leg electromyography (EMG by analysing polysomnography (PSG data with digital signal processing (DSP and machine learning methods. PSG records of 153 patients of different ages and genders with PLM disorder diagnosis were examined retrospectively. A novel software was developed for the analysis of PSG records. The software utilizes the machine learning algorithms, statistical methods, and DSP methods. In order to classify PLM, popular machine learning methods (multilayer perceptron, K-nearest neighbour, and random forests and logistic regression were used. Comparison of classified results showed that while K-nearest neighbour classification algorithm had higher average classification rate (91.87% and lower average classification error value (RMSE = 0.2850, multilayer perceptron algorithm had the lowest average classification rate (83.29% and the highest average classification error value (RMSE = 0.3705. Results showed that PLM can be classified with high accuracy (91.87% without leg EMG record being present.

  8. TECHNOLOGICAL PROVISION OF ACCURACY AND QUALITY PARAMETERS OF INTRICATE PROFILE PARTS AT HIGH-SPEED MULTI-COORDINATE MACHINING

    Directory of Open Access Journals (Sweden)

    V. K. Sheleg

    2009-01-01

    Full Text Available The paper considers requirements to CAM-systems for provision of high-speed multi-coordinate milling, principles of generation and recommendations on trajectory programming for high-speed machining, influence of vibration and balancing of the technological system on parameters of  the machining accuracy, characteristics of a cutting tool, types of tool coatings that is rather actual for improvement of accuracy and quality of intricate profile parts.

  9. Fundamental Parameters of Main-Sequence Stars in an Instant with Machine Learning

    Science.gov (United States)

    Bellinger, Earl P.; Angelou, George C.; Hekker, Saskia; Basu, Sarbani; Ball, Warrick H.; Guggenberger, Elisabeth

    2016-10-01

    Owing to the remarkable photometric precision of space observatories like Kepler, stellar and planetary systems beyond our own are now being characterized en masse for the first time. These characterizations are pivotal for endeavors such as searching for Earth-like planets and solar twins, understanding the mechanisms that govern stellar evolution, and tracing the dynamics of our Galaxy. The volume of data that is becoming available, however, brings with it the need to process this information accurately and rapidly. While existing methods can constrain fundamental stellar parameters such as ages, masses, and radii from these observations, they require substantial computational effort to do so. We develop a method based on machine learning for rapidly estimating fundamental parameters of main-sequence solar-like stars from classical and asteroseismic observations. We first demonstrate this method on a hare-and-hound exercise and then apply it to the Sun, 16 Cyg A and B, and 34 planet-hosting candidates that have been observed by the Kepler spacecraft. We find that our estimates and their associated uncertainties are comparable to the results of other methods, but with the additional benefit of being able to explore many more stellar parameters while using much less computation time. We furthermore use this method to present evidence for an empirical diffusion-mass relation. Our method is open source and freely available for the community to use.6

  10. Parameters selection in gene selection using Gaussian kernel support vector machines by genetic algorithm

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    In microarray-based cancer classification, gene selection is an important issue owing to the large number of variables and small number of samples as well as its non-linearity. It is difficult to get satisfying results by using conventional linear statistical methods. Recursive feature elimination based on support vector machine (SVM RFE) is an effective algorithm for gene selection and cancer classification, which are integrated into a consistent framework. In this paper, we propose a new method to select parameters of the aforementioned algorithm implemented with Gaussian kernel SVMs as better alternatives to the common practice of selecting the apparently best parameters by using a genetic algorithm to search for a couple of optimal parameter. Fast implementation issues for this method are also discussed for pragmatic reasons. The proposed method was tested on two representative hereditary breast cancer and acute leukaemia datasets. The experimental results indicate that the proposed method performs well in selecting genes and achieves high classification accuracies with these genes.

  11. Microcanonical Annealing and Threshold Accepting for Parameter Determination and Feature Selection of Support Vector Machines

    Directory of Open Access Journals (Sweden)

    Seyyid Ahmed Medjahed

    2016-12-01

    Full Text Available Support vector machine (SVM is a popular classification technique with many diverse applications. Parameter determination and feature selection significantly influences the classification accuracy rate and the SVM model quality. This paper proposes two novel approaches based on: Microcanonical Annealing (MA-SVM and Threshold Accepting (TA-SVM to determine the optimal value parameter and the relevant features subset, without reducing SVM classification accuracy. In order to evaluate the performance of MA-SVM and TA-SVM, several public datasets are employed to compute the classification accuracy rate. The proposed approaches were tested in the context of medical diagnosis. Also, we tested the approaches on DNA microarray datasets used for cancer diagnosis. The results obtained by the MA-SVM and TA-SVM algorithms are shown to be superior and have given a good performance in the DNA microarray data sets which are characterized by the large number of features. Therefore, the MA-SVM and TA-SVM approaches are well suited for parameter determination and feature selection in SVM.

  12. A Machine Learning Method to Infer Fundamental Stellar Parameters from Photometric Light Curves

    CERN Document Server

    Miller, A A; Richards, J W; Lee, Y S; Starr, D L; Butler, N R; Tokarz, S; Smith, N; Eisner, J A

    2014-01-01

    A fundamental challenge for wide-field imaging surveys is obtaining follow-up spectroscopic observations: there are > $10^9$ photometrically cataloged sources, yet modern spectroscopic surveys are limited to ~few x $10^6$ targets. As we approach the Large Synoptic Survey Telescope (LSST) era, new algorithmic solutions are required to cope with the data deluge. Here we report the development of a machine-learning framework capable of inferring fundamental stellar parameters (Teff, log g, and [Fe/H]) using photometric-brightness variations and color alone. A training set is constructed from a systematic spectroscopic survey of variables with Hectospec/MMT. In sum, the training set includes ~9000 spectra, for which stellar parameters are measured using the SEGUE Stellar Parameters Pipeline (SSPP). We employed the random forest algorithm to perform a non-parametric regression that predicts Teff, log g, and [Fe/H] from photometric time-domain observations. Our final, optimized model produces a cross-validated root...

  13. A Confident Information First Principle for Parameter Reduction and Model Selection of Boltzmann Machines.

    Science.gov (United States)

    Zhao, Xiaozhao; Hou, Yuexian; Song, Dawei; Li, Wenjie

    2017-03-16

    Typical dimensionality reduction (DR) methods are data-oriented, focusing on directly reducing the number of random variables (or features) while retaining the maximal variations in the high-dimensional data. Targeting unsupervised situations, this paper aims to address the problem from a novel perspective and considers model-oriented DR in parameter spaces of binary multivariate distributions. Specifically, we propose a general parameter reduction criterion, called confident-information-first (CIF) principle, to maximally preserve confident parameters and rule out less confident ones. Formally, the confidence of each parameter can be assessed by its contribution to the expected Fisher information distance within a geometric manifold over the neighborhood of the underlying real distribution. Then, we demonstrate two implementations of CIF in different scenarios. First, when there are no observed samples, we revisit the Boltzmann machines (BMs) from a model selection perspective and theoretically show that both the fully visible BM and the BM with hidden units can be derived from the general binary multivariate distribution using the CIF principle. This finding would help us uncover and formalize the essential parts of the target density that BM aims to capture and the nonessential parts that BM should discard. Second, when there exist observed samples, we apply CIF to the model selection for BM, which is in turn made adaptive to the observed samples. The sample-specific CIF is a heuristic method to decide the priority order of parameters, which can improve the search efficiency without degrading the quality of model selection results as shown in a series of density estimation experiments.

  14. Applying machine learning to identify autistic adults using imitation: An exploratory study.

    Science.gov (United States)

    Li, Baihua; Sharma, Arjun; Meng, James; Purushwalkam, Senthil; Gowen, Emma

    2017-01-01

    Autism spectrum condition (ASC) is primarily diagnosed by behavioural symptoms including social, sensory and motor aspects. Although stereotyped, repetitive motor movements are considered during diagnosis, quantitative measures that identify kinematic characteristics in the movement patterns of autistic individuals are poorly studied, preventing advances in understanding the aetiology of motor impairment, or whether a wider range of motor characteristics could be used for diagnosis. The aim of this study was to investigate whether data-driven machine learning based methods could be used to address some fundamental problems with regard to identifying discriminative test conditions and kinematic parameters to classify between ASC and neurotypical controls. Data was based on a previous task where 16 ASC participants and 14 age, IQ matched controls observed then imitated a series of hand movements. 40 kinematic parameters extracted from eight imitation conditions were analysed using machine learning based methods. Two optimal imitation conditions and nine most significant kinematic parameters were identified and compared with some standard attribute evaluators. To our knowledge, this is the first attempt to apply machine learning to kinematic movement parameters measured during imitation of hand movements to investigate the identification of ASC. Although based on a small sample, the work demonstrates the feasibility of applying machine learning methods to analyse high-dimensional data and suggest the potential of machine learning for identifying kinematic biomarkers that could contribute to the diagnostic classification of autism.

  15. Prediction and Optimization Approaches for Modeling and Selection of Optimum Machining Parameters in CNC down Milling Operation

    Directory of Open Access Journals (Sweden)

    Asaad A. Abdullah

    2014-04-01

    Full Text Available In this study, we suggested intelligent approach to predict and optimize the cutting parameters when down milling of 45# steel material with cutting tool PTHK- (Ø10*20C*10D*75L -4F-1.0R under dry condition. The experiments were performed statistically according to four factors with three levels in Taguchi experimental design method. Adaptive Neuro-fuzzy inference system is utilized to establish the relationship between the inputs and output parameter exploiting the Taguchi orthogonal array L27. The Particle Swarm Optimized-Adaptive Neuro-Fuzzy Inference System (PSOANFIS is suggested to select the best cutting parameters providing the lower surface through from the experimental data using ANFIS models to predict objective functions. The PSOANFIS optimization approach that improves the surface quality from 0.212 to 0.202, as well as the cutting time is also reduced from 7.5 to 4.78 sec according to machining parameters before and after optimization process. From these results, it can be readily achieved that the advanced study is trusted and suitable for solving other problems encountered in metal cutting operations and the same surface roughness.

  16. A feasibility study of automatic lung nodule detection in chest digital tomosynthesis with machine learning based on support vector machine

    Science.gov (United States)

    Lee, Donghoon; Kim, Ye-seul; Choi, Sunghoon; Lee, Haenghwa; Jo, Byungdu; Choi, Seungyeon; Shin, Jungwook; Kim, Hee-Joung

    2017-03-01

    The chest digital tomosynthesis(CDT) is recently developed medical device that has several advantage for diagnosing lung disease. For example, CDT provides depth information with relatively low radiation dose compared to computed tomography (CT). However, a major problem with CDT is the image artifacts associated with data incompleteness resulting from limited angle data acquisition in CDT geometry. For this reason, the sensitivity of lung disease was not clear compared to CT. In this study, to improve sensitivity of lung disease detection in CDT, we developed computer aided diagnosis (CAD) systems based on machine learning. For design CAD systems, we used 100 cases of lung nodules cropped images and 100 cases of normal lesion cropped images acquired by lung man phantoms and proto type CDT. We used machine learning techniques based on support vector machine and Gabor filter. The Gabor filter was used for extracting characteristics of lung nodules and we compared performance of feature extraction of Gabor filter with various scale and orientation parameters. We used 3, 4, 5 scales and 4, 6, 8 orientations. After extracting features, support vector machine (SVM) was used for classifying feature of lesions. The linear, polynomial and Gaussian kernels of SVM were compared to decide the best SVM conditions for CDT reconstruction images. The results of CAD system with machine learning showed the capability of automatically lung lesion detection. Furthermore detection performance was the best when Gabor filter with 5 scale and 8 orientation and SVM with Gaussian kernel were used. In conclusion, our suggested CAD system showed improving sensitivity of lung lesion detection in CDT and decide Gabor filter and SVM conditions to achieve higher detection performance of our developed CAD system for CDT.

  17. Studying depression using imaging and machine learning methods.

    Science.gov (United States)

    Patel, Meenal J; Khalaf, Alexander; Aizenstein, Howard J

    2016-01-01

    Depression is a complex clinical entity that can pose challenges for clinicians regarding both accurate diagnosis and effective timely treatment. These challenges have prompted the development of multiple machine learning methods to help improve the management of this disease. These methods utilize anatomical and physiological data acquired from neuroimaging to create models that can identify depressed patients vs. non-depressed patients and predict treatment outcomes. This article (1) presents a background on depression, imaging, and machine learning methodologies; (2) reviews methodologies of past studies that have used imaging and machine learning to study depression; and (3) suggests directions for future depression-related studies.

  18. Estimation errors of the parameters of the induction machine. Comparison of models in sinusoidal regime; Erreurs d'estimation des parametres de la machine asynchrone. Comparaison de modeles en regime sinusoidal

    Energy Technology Data Exchange (ETDEWEB)

    Laroche, E. [Centre National de la Recherche Scientifique (CNRS UMR), Lab. des Sciences de l' Image, de l' Informatique et de la Teledetection, 67 - Illkirch (France); Durieu, C.; Louis, J.P. [Centre National de la Recherche Scientifique (CNRS UPRESA 8029), Lab. d' Electricite, Signaux et Robotique, 94 - Cachan (France)

    2002-07-01

    Many parametric models of induction machines in sinusoidal mode, some of which account for saturation and iron losses, are available. These models must not only be identifiable, they must also provide for an accurate estimation of physical parameters. In this paper, parameter estimation errors due to measurement noise and model errors are analyzed. The most perturbed cases, such as those neglecting saturation or iron losses, are given special consideration herein. This study allows drawing conclusions as to the practical identifiability of the various models. Results are then used to design optimal experiments in which parameter estimation errors have been minimized. (authors)

  19. The Effect of Operational Cutting Parameters on Nitinol-60 in Wire Electrodischarge Machining

    Directory of Open Access Journals (Sweden)

    Ali Akbar LotfiNeyestanak

    2013-01-01

    Full Text Available Shape memory alloys are a kind of active materials, which have significant characteristics in comparison with other alloys. Since these materials are applicable in different fields such as aerospace, automobile industry, medicine, and dentistry, the effects of wire electrodischarge machining on the properties of these alloys have been studied. In this paper, changes in the shape recovery ability and microhardness of the machined surface of Nitonol-60 shape memory alloy have been studied considering recasting and formation of resolidificated layer on the shape memory alloy surface. XRD and EDXA analyses of the surface layer of the sample besides a microscopic study of the shape memory alloy layer by SEM and a study of the changes in mechanical properties of the surface layer were done by performing microhardness and tension tests on the work piece surface. Considering the surface layer, reversible strain has been studied according to the shape recovery percentage of Nitinol-60 shape memory alloy. Results show that the surface layer formed on the surface of the samples has caused changes in both physical and mechanical properties of the cut surface because of the penetration of the separated materials in comparison with deeper layers of the piece.

  20. A MACHINE-LEARNING METHOD TO INFER FUNDAMENTAL STELLAR PARAMETERS FROM PHOTOMETRIC LIGHT CURVES

    Energy Technology Data Exchange (ETDEWEB)

    Miller, A. A. [Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, MS 169-506, Pasadena, CA 91109 (United States); Bloom, J. S.; Richards, J. W.; Starr, D. L. [Department of Astronomy, University of California, Berkeley, CA 94720-3411 (United States); Lee, Y. S. [Department of Astronomy and Space Science, Chungnam National University, Daejeon 305-764 (Korea, Republic of); Butler, N. R. [School of Earth and Space Exploration, Arizona State University, Tempe, AZ 85281 (United States); Tokarz, S. [Smithsonian Astrophysical Observatory, Cambridge, MA 02138 (United States); Smith, N.; Eisner, J. A., E-mail: amiller@astro.caltech.edu [Steward Observatory, University of Arizona, Tucson, AZ 85721 (United States)

    2015-01-10

    A fundamental challenge for wide-field imaging surveys is obtaining follow-up spectroscopic observations: there are >10{sup 9} photometrically cataloged sources, yet modern spectroscopic surveys are limited to ∼few× 10{sup 6} targets. As we approach the Large Synoptic Survey Telescope era, new algorithmic solutions are required to cope with the data deluge. Here we report the development of a machine-learning framework capable of inferring fundamental stellar parameters (T {sub eff}, log g, and [Fe/H]) using photometric-brightness variations and color alone. A training set is constructed from a systematic spectroscopic survey of variables with Hectospec/Multi-Mirror Telescope. In sum, the training set includes ∼9000 spectra, for which stellar parameters are measured using the SEGUE Stellar Parameters Pipeline (SSPP). We employed the random forest algorithm to perform a non-parametric regression that predicts T {sub eff}, log g, and [Fe/H] from photometric time-domain observations. Our final optimized model produces a cross-validated rms error (RMSE) of 165 K, 0.39 dex, and 0.33 dex for T {sub eff}, log g, and [Fe/H], respectively. Examining the subset of sources for which the SSPP measurements are most reliable, the RMSE reduces to 125 K, 0.37 dex, and 0.27 dex, respectively, comparable to what is achievable via low-resolution spectroscopy. For variable stars this represents a ≈12%-20% improvement in RMSE relative to models trained with single-epoch photometric colors. As an application of our method, we estimate stellar parameters for ∼54,000 known variables. We argue that this method may convert photometric time-domain surveys into pseudo-spectrographic engines, enabling the construction of extremely detailed maps of the Milky Way, its structure, and history.

  1. Investigation of the influential parameters of machining of AISI 304 stainless steel

    Indian Academy of Sciences (India)

    R A Mahdavinejad; S Saeedy

    2011-12-01

    Austenitic stainless steels are hard materials to machine, due to their high strength, high ductility and low thermal conductivity. The last characteristic results in heat concentration at the tool cutting edge. This paper aims to optimize turning parameters of AISI 304 stainless steel. Turning tests have been performed in three different feed rates (0.2, 0.3, 0.4 mm/rev) at the cutting speeds of 100, 125, 150, 175 and 200 m/min with and without cutting fluid. A design of experiments (DOE) and an analysis of variance (ANOVA) have been made to determine the effects of each parameter on the tool wear and the surface roughness. It is being inferred that cutting speed has the main influence on the flank wear and as it increases to 175 m/min, the flank wear decreases. The feed rate has the most important influence on the surface roughness and as it decreases, the surface roughness also decreases. Also, the application of cutting fluid results in longer tool life and better surface finish.

  2. Back Analysis of Geomechanical Parameters Using Hybrid Algorithm Based on Difference Evolution and Extreme Learning Machine

    Directory of Open Access Journals (Sweden)

    Zhan-ping Song

    2015-01-01

    Full Text Available Since the geological bodies where tunnels are located have uncertain and complex characteristics, the inverse problem plays an important role in geotechnical engineering. In order to improve the accuracy and speed of surrounding rock identification, the back analysis objective function with usage of the displacement and stress monitoring data has been constructed, with a hybrid algorithm proposed. An extreme learning machine (ELM is employed with optimal architecture trained by the difference evolution (DE arithmetic. First, the three-dimensional numerical simulation is used in the creation of training and testing samples for ELM model construction. Second, the nonlinear relationship between rock parameters and displacement is constructed by numerical simulation. Finally, the geophysics parameters are obtained by DE optimization arithmetic taking into consideration the monitoring data including both displacement and pressure. This method had been applied in the Fusong highway tunnel in Fusong City of China’s Jilin Province, with a good effect obtained. It takes full advantage of DE and ELM and has both calculation speed and precision in the back analysis.

  3. Experimental Investigation of Effect of Process Parameters on Mrr and Surface Roughness In Turning Operation on Conventional Lathe Machine For Aluminum 6082 Grade Material Using Taguchi Method

    Directory of Open Access Journals (Sweden)

    Mihir T. Patel

    2014-01-01

    Full Text Available In this study, the effect of the machining parameters like spindle speed, feed, depth of cut and nose radius on material removal rate and surface roughness are investigated, also optimum process parameters are studied. An L8 orthogonal array (mixed level design, analysis of variance (ANOVA and the signal –to-noise (S/N ratio are used in this study. Mixed levels of machining parameters are used and experiments are done on conventional lathe machine. Aluminum Alloy - Al 6082 grade material is used in high stress applications, Trusses, Bridges, Cranes, Transport applications, Ore skips, Beer barrels, Milk churns etc. The most significant parameters for material removal rate are speed, depth of cut and least significant factor for MRR is nose radius For surface roughness speed, nose radius are the most significant parameters and least significant factor for surface roughness is depth of cut. The mathematical model obtained as a result of regression analysis can be reliable to predict MRR and surface roughness Ra.

  4. DETERMINATION OF MAIN OUTPUT PARAMETERS FOR HYDROFICATED CONSTRUCTION AND ROAD-BUILDING MACHINES AT OPERATIONAL STAGE OF THEIR LIFE CYCLE

    Directory of Open Access Journals (Sweden)

    A. N. Maximenko

    2014-01-01

    Full Text Available Usage efficiency of mechanical engineering products is determined by level of their operating capability. Expenses connected with provision of operating capability for the whole operational period exceed initial cost of the products by 6-10-fold. Moreover , while being used the expenses have a tendency to increase with reduction of output parameters that ensure product application efficiency for its intended purpose. It is necessary to take into account these changes at manufacturing stages of mechanical engineering products. Maximum efficiency can be obtained at the operational stage of the product life cycle only as a result of complex and interrelated measures during designing, manufacturing and usage of the specific product for its intended purpose with due account of its output parameter dynamics. While using the product an analysis of its output parameter dynamics will make it possible to determine maximum value of the operating capability, operational expenses and best practices for obtaining maximum profit per operating time unit.Taking hydroficated excavators of the 5th grade as an example the paper presents dynamics of main output parameters at the operational stage of their life cycle; reveals the main factor influencing on intensity of hydroficated machine operating capability reduction; substantiates an expediency of taking into account output parameter dynamics while evaluating efficiency of its usage; proposes a methodology for determination of or a pay-off time period for recoupment of expenses pertaining to machine procurement and optimum time period for operational stage, its life cycle that corresponds to obtaining maximum profit.Nowadays constant values of main output parameters (operating capability, self cost of machine-hour corresponding to the beginning of operation are to be taken into account while determining expediency of machine creation. Practically they significantly change in the process of machine operation this

  5. Evaluation of Machining Parameters Influencing Thrust Force in Drilling of Al– SiC–Gr Metal Matrix Composites using RSM

    Directory of Open Access Journals (Sweden)

    A. Munia raj

    2014-10-01

    Full Text Available This paper focused on evaluation of machining parameters influencing thrust force during drilling of Al–SiC–Gr metal matrix composites using multifaceted carbide drills. There are three machining parameters i.e. Spindle speed, Feed rate, Drill diameter. Experiments are conducted on a vertical machining centre using Taguchi design of experiments. Taguchi orthogonal array is designed with three levels of drilling parameters with the help of software Minitab 15. A model is developed to correlate the drilling parameters with thrust force using Response surface Methodology (RSM.The results indicate that the developed model is suitable for prediction of thrust forces in drilling of Al/SiC/Gr composites. The influences of different machining parameters on thrust force of Al/SiC/Gr composites have been analyzed through contour graphs and 3D plots. The investigation has revealed that the type of spindle speed affects the thrust force significantly followed by the feed rate and drill diameter.

  6. A Comparative Study of Control Strategies for Performance Optimisation of Brushless Doubly- Fed Reluctance Machines

    Directory of Open Access Journals (Sweden)

    Milutin G. Jovanović

    2006-12-01

    Full Text Available The brushless doubly-fed machine (BDFM allows the use of a partially rated inverter and represents an attractive cost-effective candidate for variable speed applications with limited speed ranges. In its induction machine form (BDFIM, the BDFM has significant rotor losses and poor efficiency due to the cage rotor design which makes the machine dynamic models heavily parameter dependent and the resulting controller configuration complicated and difficult to implement. A reluctance version of the BDFM, the brushless doubly-fed reluctance machine (BDFRM, ideally has no rotor losses, and therefore offers the prospect for higher efficiency and simpler control compared to the BDFIM. A detailed study of this interesting and emerging machine is very important to gain a thorough understanding of its unusual operation, control aspects and compromises between optimal performance and the size of the inverter and the machine. This paper will attempt to address these issues specifically concentrating on developing conditions for various control properties of the machine such as maximum power factor, maximum torque per inverter ampere and minimum copper losses, as well as analysing the associated trade-offs.

  7. A Study on the Reliability of a Large Vibration Machine

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    This study aims at the reliability of a large vibration machine ZM2800, including the measurement and analysis of its dynamic load, the stress and reliability analysis of key fragile components as well as the system reliability analysis and calculation of the ma chine. The result of the study provides valuable reference for the evaluation and improve-ment of the structure and performance of the machine.

  8. Case study of virtual reality in CNC machine tool exhibition

    Directory of Open Access Journals (Sweden)

    Kao Yung-Chou

    2017-01-01

    Full Text Available Exhibition and demonstration are generally used in the promotion and sale-assistance of manufactured products. However, the transportation cost of the real goods from the vender factory to the exposition venue is generally expensive for huge and heavy commodity. With the advancement of computing, graphics, mobile apps, and mobile hardware the 3D visibility technology is getting more and more popular to be adopted in visual-assisted communication such as amusement games. Virtual reality (VR technology has therefore being paid great attention in emulating expensive small and/or huge and heavy equipment. Virtual reality can be characterized as 3D extension with Immersion, Interaction and Imagination. This paper was then be focused on the study of virtual reality in the assistance of CNC machine tool demonstration and exhibition. A commercial CNC machine tool was used in this study to illustrate the effectiveness and usability of using virtual reality for an exhibition. The adopted CNC machine tool is a large and heavy mill-turn machine with the width up to eleven meters and weighted about 35 tons. A head-mounted display (HMD was attached to the developed VR CNC machine tool for the immersion viewing. A user can see around the 3D scene of the large mill-turn machine and the operation of the virtual CNC machine can be actuated by bare hand. Coolant was added to demonstrate more realistic operation while collision detection function was also added to remind the operator. The developed VR demonstration system has been presented in the 2017 Taipei International Machine Tool Show (TIMTOS 2017. This case study has shown that young engineers and/or students are very impressed by the VR-based demonstration while elder persons could not adapt themselves easily to the VR-based scene because of eyesight issues. However, virtual reality has successfully being adopted and integrated with the CNC machine tool in an international show. Another machine tool on

  9. Sensitivity Analysis of the Transmission Chain of a Horizontal Machining Tool Axis to Design and Control Parameters

    Directory of Open Access Journals (Sweden)

    Stefano Mauro

    2014-03-01

    Full Text Available This paper reports how a numerical controlled machine axis was studied through a lumped parameter model. Firstly, a linear model was derived in order to apply a modal analysis, which estimated the first mechanical frequency of the system as well as its damping coefficients. Subsequently, a nonlinear system was developed by adding friction through experimentation. Results were validated through the comparison with a commercial servoaxis equipped with a Siemens controller. The model was then used to evaluate the effect of the stiffness of the structural parts of the axis on its first natural frequency. It was further used to analyse precision, energy consumption, and axis promptness. Finally a cost function was generated in order to find an optimal value for the main proportional gain of the position loop.

  10. Femtosecond laser ablation properties of transparent materials: impact of the laser process parameters on the machining throughput

    Science.gov (United States)

    Matylitsky, V. V.; Hendricks, F.; Aus der Au, J.

    2013-03-01

    High average power, high repetition rate femtosecond lasers with μJ pulse energies are increasingly used for bio-medical and material processing applications. With the introduction of femtosecond laser systems such as the SpiritTM platform developed by High Q Lasers and Spectra-Physics, micro-processing of solid targets with femtosecond laser pulses have obtained new perspectives for industrial applications [1]. The unique advantage of material processing with subpicosecond lasers is efficient, fast and localized energy deposition, which leads to high ablation efficiency and accuracy in nearly all kinds of solid materials. The study on the impact of the laser processing parameters on the removal rate for transparent substrate using femtosecond laser pulses will be presented. In particular, examples of micro-processing of poly-L-lactic acid (PLLA) - bio-degradable polyester and XensationTM glass (Schott) machined with SpiritTM ultrafast laser will be shown.

  11. A study of parameter identification

    Science.gov (United States)

    Herget, C. J.; Patterson, R. E., III

    1978-01-01

    A set of definitions for deterministic parameter identification ability were proposed. Deterministic parameter identificability properties are presented based on four system characteristics: direct parameter recoverability, properties of the system transfer function, properties of output distinguishability, and uniqueness properties of a quadratic cost functional. Stochastic parameter identifiability was defined in terms of the existence of an estimation sequence for the unknown parameters which is consistent in probability. Stochastic parameter identifiability properties are presented based on the following characteristics: convergence properties of the maximum likelihood estimate, properties of the joint probability density functions of the observations, and properties of the information matrix.

  12. Taguchi design optimization of machining parameters on the CNC end milling process of halloysite nanotube with aluminium reinforced epoxy matrix (HNT/Al/Ep hybrid composite

    Directory of Open Access Journals (Sweden)

    J.S. Pang

    2014-08-01

    Full Text Available This paper introduces the application of Taguchi optimization methodology in optimizing the cutting parameters of end-milling process for machining the halloysite nanotubes (HNTs with aluminium reinforced epoxy hybrid composite material under dry condition. The machining parameters which are chosen to be evaluated in this study are the depth of cut (d, cutting speed (S and feed rate (f. While, the response factors to be measured are the surface roughness of the machined composite surface and the cutting force. An orthogonal array of the Taguchi method was set-up and used to analyse the effect of the milling parameters on the surface roughness and cutting force. The result from this study shows that the application of the Taguchi method can determine the best combination of machining parameters that can provide the optimal machining response conditions which are the lowest surface roughness and lowest cutting force value. For the best surface finish, A1–B3–C3 (d = 0.4 mm, S = 1500 rpm, f = 60 mmpm is found to be the optimized combination of levels for all the three control factors from the analysis. Meanwhile, the optimized combination of levels for all the three control factors from the analysis which provides the lowest cutting force was found to be A2–B2–C2 (d = 0.6 mm, S = 1000 rpm, f = 40 mmpm.

  13. Comparison of effects of machine performance parameters and energy indices of soybean production in conservation and conventional tillage systems

    Directory of Open Access Journals (Sweden)

    A Sharifi

    2016-09-01

    Full Text Available Introduction Nowadays, agricultural systems are seeking economic, ecological and bioenvironmental goals for production of agricultural crops with protection and sustainability of the environment. Therefore, there is need to extend sustainable agricultural systems such as conservation agriculture. One of the principles of conservation agriculture is conservation tillage. Conservation tillage is a kind of tillage that retains crop residues on the soil surface or mixes it with soil using related machines. It could also affect on machine performance parameters. Energy consumption for producing one kilogram crop could be studied for conservation tillage. Several researchers have conducted studies on this issue for production of different crops including wheat, sunflower and forage crops. This study conducted to assess machine performance parameters and energy indices of conservation tillage systems for soybean cultivation in Golestan province. Materials and Methods This study was conducted to investigate the effects of conservation tillage systems on machine performance and energy indices in soybean production at the Gorgan research station of Golestan Agricultural and Natural Resource Research Center in 2012. The precipitation was 450 mm. Soil texture was silty clay loam. Treatments were four tillage methods, including no-till using row crop direct planter, no-till using grain direct drill, conventional tillage usin a disk harrow with working depth of 10-15 cm and minimum tillage using chisel packer with a working depth of 20 cm. Machine performance parameters and energy indices studied in a farm covered by wheat residues in a randomized complete block design (RCBD with four treatments and four replications. Machine performance parameters consisted of field efficiency, field capacity, total field capacity and planting uniformity index were measured. Energy indices such as energy ratio, energy productivity, energy intensity and net energy gain were

  14. Effect of cutting parameters on machinability characteristics in milling of magnesium alloy with carbide tool

    Directory of Open Access Journals (Sweden)

    Kaining Shi

    2016-01-01

    Full Text Available Magnesium alloy has attracted more attentions due to its excellent mechanical properties. However, in process of dry cutting operation, many problems restrict its further development. In this article, the effect of cutting parameters on machinabilities of magnesium alloy is explored under dry milling condition. This research is an attempt to investigate the impact of cutting speed at multiple feed rates on cutting force and surface roughness, while a statistical analysis is adopted to determine the influential intensities accurately. The results showed that cutting force is affected by the positively constant intensity from feed rate and the increasingly negative intensity from cutting speed. In contrast, surface roughness is determined by the gradually increasing negative tendency from feed rate and the positive effect with constant intensity from cutting speed. Within the range of the experiments, feed rate is the leading contribution for cutting force while the cutting speed is the dominant factor for surface roughness according to the absolute intensity values. Meanwhile, the trends of influencing intensities between cutting force and surface roughness are opposite. Besides, it is also found that in milling magnesium alloy, chip morphology is highly sensitive to cutting speed while the chip quality mainly depends on feed rate.

  15. The effects of machine parameters on residual stress determined using micro-Raman spectroscopy

    Energy Technology Data Exchange (ETDEWEB)

    Sparks, R.G.; Enloe, W.S.; Paesler, M.A.

    1988-12-01

    The effects of machine parameters on residual stresses in single point diamond turned silicon and germanium have been investigated using micro-Raman spectroscopy. Residual stresses were sampled across ductile feed cuts in < 100 > silicon and germanium which were single point diamond turned using a variety of feed rates, rake angles and clearance angles. High spatial resolution micro-Raman spectra (1{mu}m spot) were obtained in regions of ductile cutting where no visible surface damage was present. The use of both 514-5nm and 488.0nm excitation wavelengths, by virtue of their differing characteristic penetration depths in the materials, allowed determinations of stress profiles as a function of depth into the sample. Previous discussions have demonstrated that such Raman spectra will exhibit asymmetrically broadened peaks which are characteristic of the superposition of a continuum of Raman scatterers from the various depths probed. Depth profiles of residual stress were obtained using computer deconvolution of the resulting asymmetrically broadened raman spectra.

  16. The Hybrid Dynamic Prototype Construction and Parameter Optimization with Genetic Algorithm for Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Chun-Liang Lu

    2015-10-01

    Full Text Available The optimized hybrid artificial intelligence model is a potential tool to deal with construction engineering and management problems. Support vector machine (SVM has achieved excellent performance in a wide variety of applications. Nevertheless, how to effectively reduce the training complexity for SVM is still a serious challenge. In this paper, a novel order-independent approach for instance selection, called the dynamic condensed nearest neighbor (DCNN rule, is proposed to adaptively construct prototypes in the training dataset and to reduce the redundant or noisy instances in a classification process for the SVM. Furthermore, a hybrid model based on the genetic algorithm (GA is proposed to simultaneously optimize the prototype construction and the SVM kernel parameters setting to enhance the classification accuracy. Several UCI benchmark datasets are considered to compare the proposed hybrid GA-DCNN-SVM approach with the previously published GA-based method. The experimental results illustrate that the proposed hybrid model outperforms the existing method and effectively improves the classification performance for the SVM.

  17. Alternating current multi-circuit electric machines a new approach to the steady-state parameter determination

    CERN Document Server

    Asanbayev, Valentin

    2015-01-01

    This book details an approach for realization of the field decomposition concept. The book presents the  methods as well as techniques and procedures for establishing electric machine circuit-loops and determining their parameters. The methods developed have been realized using the models of machines with laminated and solid rotor having classical structure. The use of such models are well recognized and simplifies practical implementation of the obtained results. This book also: ·         Includes methods for a construction of electric machine equivalent circuits that allows the replacement of the field models of the machine with simple circuit models ·         Demonstrates the practical implementation of the proposed techniques and procedures ·         Presents parameters of the circuit-loops in the form most convenient for practical implementation ·         Uses methods based on machine models widely used in practice

  18. The upgraded Large Plasma Device, a machine for studying frontier basic plasma physics.

    Science.gov (United States)

    Gekelman, W; Pribyl, P; Lucky, Z; Drandell, M; Leneman, D; Maggs, J; Vincena, S; Van Compernolle, B; Tripathi, S K P; Morales, G; Carter, T A; Wang, Y; DeHaas, T

    2016-02-01

    In 1991 a manuscript describing an instrument for studying magnetized plasmas was published in this journal. The Large Plasma Device (LAPD) was upgraded in 2001 and has become a national user facility for the study of basic plasma physics. The upgrade as well as diagnostics introduced since then has significantly changed the capabilities of the device. All references to the machine still quote the original RSI paper, which at this time is not appropriate. In this work, the properties of the updated LAPD are presented. The strategy of the machine construction, the available diagnostics, the parameters available for experiments, as well as illustrations of several experiments are presented here.

  19. Multi-attribute optimization of machining process parameters in powder mixed electro-discharge machining using TOPSIS and grey relational analysis

    Directory of Open Access Journals (Sweden)

    S. Tripathy

    2016-03-01

    Full Text Available Powder Mixed Electro-Discharge Machining (PMEDM is a hybrid machining process where a conductive powder is mixed to the dielectric fluid to facilitate effective machining of advanced material. In the present work application of Taguchi method in combination with Technique for order of preference by similarity to ideal solution (TOPSIS and Grey Relational Analysis (GRA have been adopted to evaluate the effectiveness of optimizing multiple performance characteristics for PMEDM of H-11 die steel using copper electrode. The effect of process variables such as powder concentration (Cp, peak current (Ip, pulse on time (Ton, duty cycle (DC and gap voltage (Vg on response parameters such as Material Removal Rate (MRR, Tool Wear Rate (TWR, Electrode Wear Ratio (EWR and Surface Roughness (SR have been investigated using chromium powder mixed to the dielectric fluid. Analysis of variance (ANOVA and F-test were performed to determine the significant parameters at a 95% confidence interval. Predicted results have been verified by confirmatory tests which show an improvement of 0.161689 and 0.2593 in the preference values using TOPSIS and GRA respectively. The recommended settings of process parameters is found to be Cp = 6 g/l, Ip = 6Amp, Ton = 100 µs, DC = 90% and Vg = 50 V from TOPSIS and Cp = 6 g/l, Ip = 3Amp, Ton = 150 µs, DC = 70% and Vg = 30 V from GRA. The microstructure analysis has been done for the optimal sample using Scanning Electron Microscope (SEM.

  20. Study on the all position automatic pipeline backing weld machine

    Institute of Scientific and Technical Information of China (English)

    Tang Deyu; Feng Biao; Li Chunrun; Niu Huli; Zhang Yongsheng; Zhang Jianhu

    2008-01-01

    As a result of the lower backing weld efficiency, the applying of automatic welding is seriously limited. So a kind of special automatic welder is designed and manufactured for backing weld. This paper introduces the character of the assembled pulse CO2 arc welding machine which has strong penetrability. It specifies the technology of controlling the parameters of all position automatic welding by computer and multi-axis controller. Moreover typical welding proce-dure parameters are provided. It is proved by examination that the economical and practical equipment and technology are suitable for the long-distance transmission pipeline, and it has a good foreground of spreading and applying.

  1. Optimization of AVR Parameters of a Multi-machine Power System ...

    African Journals Online (AJOL)

    user1

    which are the Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). The ... optimal) solution with these methods for a multi-machine system. ..... representation whereas the PSO optimized AVR and GA optimized AVR achieve good.

  2. Effects of cutting parameters and machining environments on surface roughness in hard turning using design of experiment

    Science.gov (United States)

    Mia, Mozammel; Bashir, Mahmood Al; Dhar, Nikhil Ranjan

    2016-07-01

    Hard turning is gradually replacing the time consuming conventional turning process, which is typically followed by grinding, by producing surface quality compatible to grinding. The hard turned surface roughness depends on the cutting parameters, machining environments and tool insert configurations. In this article the variation of the surface roughness of the produced surfaces with the changes in tool insert configuration, use of coolant and different cutting parameters (cutting speed, feed rate) has been investigated. This investigation was performed in machining AISI 1060 steel, hardened to 56 HRC by heat treatment, using coated carbide inserts under two different machining environments. The depth of cut, fluid pressure and material hardness were kept constant. The Design of Experiment (DOE) was performed to determine the number and combination sets of different cutting parameters. A full factorial analysis has been performed to examine the effect of main factors as well as interaction effect of factors on surface roughness. A statistical analysis of variance (ANOVA) was employed to determine the combined effect of cutting parameters, environment and tool configuration. The result of this analysis reveals that environment has the most significant impact on surface roughness followed by feed rate and tool configuration respectively.

  3. A low cost implementation of multi-parameter patient monitor using intersection kernel support vector machine classifier

    Science.gov (United States)

    Mohan, Dhanya; Kumar, C. Santhosh

    2016-03-01

    Predicting the physiological condition (normal/abnormal) of a patient is highly desirable to enhance the quality of health care. Multi-parameter patient monitors (MPMs) using heart rate, arterial blood pressure, respiration rate and oxygen saturation (S pO2) as input parameters were developed to monitor the condition of patients, with minimum human resource utilization. The Support vector machine (SVM), an advanced machine learning approach popularly used for classification and regression is used for the realization of MPMs. For making MPMs cost effective, we experiment on the hardware implementation of the MPM using support vector machine classifier. The training of the system is done using the matlab environment and the detection of the alarm/noalarm condition is implemented in hardware. We used different kernels for SVM classification and note that the best performance was obtained using intersection kernel SVM (IKSVM). The intersection kernel support vector machine classifier MPM has outperformed the best known MPM using radial basis function kernel by an absoute improvement of 2.74% in accuracy, 1.86% in sensitivity and 3.01% in specificity. The hardware model was developed based on the improved performance system using Verilog Hardware Description Language and was implemented on Altera cyclone-II development board.

  4. Machining Performance Study on Metal Matrix Composites-A Response Surface Methodology Approach

    Directory of Open Access Journals (Sweden)

    A. Srinivasan

    2012-01-01

    Full Text Available Problem statement: Metal Matrix Composites (MMC have become a leading material among composite materials and in particular, particle reinforced aluminum MMCs have received considerable attention due to their excellent engineering properties. These materials are known as the difficult-to-machine materials because of the hardness and abrasive nature of reinforcement element-like Alumina (Al2O3. Approach: In this study, an attempt has been made to model the machinability evaluation through the response surface methodology in machining of homogenized 10% micron Al2O3 LM25 Al MMC manufactured through stir casting method. Results: The combined effects of three machining parameters including cutting speed (s, feed rate (f and depth of cut (d on the basis of three performance characteristics of tool wear (VB, surface Roughness (Ra and cutting Force (Fz were investigated. The contour plots were generated to study the effect of process parameters as well as their interactions. Conclusion: The process parameters are optimized using desirability-based approach response surface methodology.

  5. Study of cutting forces in machining of magnesium composite by response surface methodology

    Directory of Open Access Journals (Sweden)

    M. Saravanakumar

    2015-01-01

    Full Text Available Metal Matrix composites (MMCs has many excellent engineering properties like good strength to weight ratio, stiffness and increased wear resistance etc., These properties are the main requirements in aerospace, automotive industries and hence the MMCs are extensively used in these industries. This paper presents the detailed experimental study on cutting forces and surface roughness aspects in turning of 5% Graphite reinforced AZ91D Magnesium alloy metal matrix composite (AZ91D Magnesium alloy matrix + 5 % Graphite reinforcement. The stir casting process under inert atmosphere is followed for synthesis of the composite. The turning process is followed using Tungsten carbide cutting tool, in a lathe. The effect of machining parameters viz., cutting speed, feed rate and depth of cut, on the cutting forces and surface roughness (Ra achieved during the machining are analysed and modelled through the response surface methodology (RSM. Study of effect of machining parameters and their interactions are carried out by using the surface, contour plots of RSM. The experimental result shows that the most significant machining parameter affecting surface roughness and cutting forces is cutting speed. The experimental results and predicted values are observed as in good agreement.

  6. PARAMETER DETERMINATION FOR ADDITIONAL OPERATING FORCE MECHANISM IN DEVICE FOR PNEUMO-CENTRIFUGAL MACHINING OF BALL-SHAPED WORKPIECES

    Directory of Open Access Journals (Sweden)

    A. A. Sukhotsky

    2014-01-01

    Full Text Available The paper describes development of the methodology for optimization of parameters for an additional operating force mechanism in a device for pneumo-centrifugal machining of glass balls. Specific feature in manufacturing glass balls for micro-optics in accordance with technological process for obtaining ball-shaped workpieces is grinding and polishing of spherical surface in a free state. In this case component billets of future balls are made in the form of cubes and the billets are given preliminary a form of ball with the help of rough grinding. An advanced method for obtaining ball-shaped work-pieces from brittle materials is a pneumocentrifugal machining. This method presupposes an application of two conic rings with abrasive working surfaces which are set coaxially with large diameters to each other and the billets are rolled along these rings. Rotation of the billets is conveyed by means of pressure medium.The present devices for pneumo-centrifugal machining are suitable for obtaining balls up to 6 mm. Machining of the work-pieces with full spherical surfaces and large diameter is non-productive due to impossibility to ensure a sufficient force on the billet in the working zone. For this reason the paper proposes a modified device where an additional force on the machined billet is created by upper working disc that is making a reciprocating motion along an axis of abrasive conic rings. The motion is realized with the help of a cylindrical camshaft mechanism in the form of a ring with a profile working end face and the purpose of present paper is to optimize parameters of the proposed device.The paper presents expressions for calculation of constitutive parameters of the additional operating force mechanism including parameters of loading element motion, main dimensions of the additional operating force mechanism and parameters of a profile element in the additional operating force mechanism.Investigation method is a mathematical

  7. RFX machine and power supply improvements for RFP advanced studies

    Energy Technology Data Exchange (ETDEWEB)

    Piovan, R. E-mail: piovan@igi.pd.cnr.it; Gnesotto, F.; Ortolani, S.; Baker, W.; Barana, O.; Bettini, P.; Cavazzana, R.; Chitarin, G.; Dal Bello, S.; De Lorenzi, A.; Fiorentin, P.; Gaio, E.; Grando, L.; Luchetta, A.; Manduchi, G.; Marchiori, G.; Marcuzzi, D.; Masiello, A.; Milani, F.; Peruzzo, S.; Pomaro, N.; Sonato, P.; Taliercio, C.; Toigo, V.; Zaccaria, P.; Zanotto, L.; Zollino, G

    2001-10-01

    Experimental results and theoretical studies call for Reversed Field Experiment (RFX) machine and power supply improvements to allow studies that go beyond those of a conventional Reversed Field Pinch (RFP) with passively stabilized turbulent MHD dynamo. The new paths opened by recent results in RFX and other RFP machines are introduced; then the goals and the design lines of the technical modifications of RFX, mainly addressed to improve the first wall, the plasma magnetic boundaries and to increase the operational flexibility of the toroidal field circuit power supply, are reported.

  8. Determination of optimal parameters in drilling composite materials to minimize the machining temperature using the Taguchi method

    OpenAIRE

    Lopes, Ana C.; Fernandes, Maria G.A.; Ribeiro, J. E.; Fonseca, E.M.M.

    2016-01-01

    Dental implant is used to replace the natural dental root. The process to fix the dental implant in the maxillary bone needs a previous drilling operation. This machining operation involves the increasing of temperature in the drilled region which can reach values higher than 47°C and for this temperature is possible to occur the osseous necrosis [I]. The main goal of this work is to implement an optimization method to define the optimal drilling parameters that cou...

  9. Support vector machine to predict diesel engine performance and emission parameters fueled with nano-particles additive to diesel fuel

    Science.gov (United States)

    Ghanbari, M.; Najafi, G.; Ghobadian, B.; Mamat, R.; Noor, M. M.; Moosavian, A.

    2015-12-01

    This paper studies the use of adaptive Support Vector Machine (SVM) to predict the performance parameters and exhaust emissions of a diesel engine operating on nanodiesel blended fuels. In order to predict the engine parameters, the whole experimental data were randomly divided into training and testing data. For SVM modelling, different values for radial basis function (RBF) kernel width and penalty parameters (C) were considered and the optimum values were then found. The results demonstrate that SVM is capable of predicting the diesel engine performance and emissions. In the experimental step, Carbon nano tubes (CNT) (40, 80 and 120 ppm) and nano silver particles (40, 80 and 120 ppm) with nanostructure were prepared and added as additive to the diesel fuel. Six cylinders, four-stroke diesel engine was fuelled with these new blended fuels and operated at different engine speeds. Experimental test results indicated the fact that adding nano particles to diesel fuel, increased diesel engine power and torque output. For nano-diesel it was found that the brake specific fuel consumption (bsfc) was decreased compared to the net diesel fuel. The results proved that with increase of nano particles concentrations (from 40 ppm to 120 ppm) in diesel fuel, CO2 emission increased. CO emission in diesel fuel with nano-particles was lower significantly compared to pure diesel fuel. UHC emission with silver nano-diesel blended fuel decreased while with fuels that contains CNT nano particles increased. The trend of NOx emission was inverse compared to the UHC emission. With adding nano particles to the blended fuels, NOx increased compared to the net diesel fuel. The tests revealed that silver & CNT nano particles can be used as additive in diesel fuel to improve complete combustion of the fuel and reduce the exhaust emissions significantly.

  10. One or 4 h of "in-house" reconditioning by machine perfusion after cold storage improve reperfusion parameters in porcine kidneys.

    Science.gov (United States)

    Gallinat, Anja; Efferz, Patrik; Paul, Andreas; Minor, Thomas

    2014-11-01

    In-house machine perfusion after cold storage (hypothermic reconditioning) has been proposed as convenient tool to improve kidney graft function. This study investigated the role of machine perfusion duration for early reperfusion parameters in porcine kidneys. Kidney function after cold preservation (4 °C, 18 h) and subsequent reconditioning by one or 4 h of pulsatile, nonoxygenated hypothermic machine perfusion (HMP) was studied in an isolated kidney perfusion model in pigs (n = 6, respectively) and compared with simply cold-stored grafts (CS). Compared with CS alone, one or 4 h of subsequent HMP similarly and significantly improved renal flow and kidney function (clearance and sodium reabsorption) upon warm reperfusion, along with reduced perfusate concentrations of endothelin-1 and increased vascular release of nitric oxide. Molecular effects of HMP comprised a significant (vs CS) mRNA increase in the endothelial transcription factor KLF2 and lower expression of endothelin that were observed already at the end of one-hour HMP after CS. Reconditioning of cold-stored kidneys is possible, even if clinical logistics only permit one hour of therapy, while limited extension of the overall storage time by in-house machine perfusion might also allow for postponing of transplantation from night to early day work. © 2014 Steunstichting ESOT.

  11. Oxygenated machine perfusion preservation of predamaged kidneys with HTK and Belzer machine perfusion solution: An experimental study in pigs

    NARCIS (Netherlands)

    Manekeller, S.; Leuvenink, Henri; Sitzia, M.; Minor, T.

    2005-01-01

    The objective of the present study was to evaluate the recently proposed aerobic machine preservation with the noncolloidal HTK solution by comparison with the colloidal Belzer machine perfusion solution (MPS) after procurement of marginal kidneys from non-heart-beating donors. Kidneys were harveste

  12. Oxygenated machine perfusion preservation of predamaged kidneys with HTK and Belzer machine perfusion solution : An experimental study in pigs

    NARCIS (Netherlands)

    Manekeller, S; Leuvenink, H; Sitzia, M; Minor, T

    2005-01-01

    The objective of the present study was to evaluate the recently proposed aerobic machine preservation with the noncolloidal HTK solution by comparison with the colloidal Belzer machine perfusion solution (MPS) after procurement of marginal kidneys from non-heart-beating donors. Kidneys were harveste

  13. Process parameters effect on material removal mechanism and cut quality of abrasive water jet machining

    Directory of Open Access Journals (Sweden)

    Janković P.

    2013-01-01

    Full Text Available The process of the abrasive water jet cutting of materials, supported by the theories of fluid mechanics, abrasive wear and damage mechanics, is a high-tech technologies that provides unique capabilities compared to conventional machining processes. This paper, along the theoretical derivations, provides original contributions in the form of mathematical models of the quantity of the cut surface damage, expressed by the values of cut surface roughness. The particular part of this paper deal with the results of the original experimental research. The research aim was connected with the demands of industry, i.e. the end user. Having in mind that the conventional machining processes are not only lagging behind in terms of quality of cut, or even some requests are not able to meet, but with the advent of composite materials were not able to machine them, because they occurred unacceptable damage (mechanical damage or delamination, fiber pull-out, burning, frayed edges.

  14. A novel approach on parameter identification for inverter driven induction machines

    NARCIS (Netherlands)

    Koning, R.F.F.; Chou, C.T.; Verhaegen, M.H.G.; Klaassens, J.B.; Uittenbogaart, J.R.

    2000-01-01

    AC machines are applied in actuator systems for many applications. The development of fast processors open up the possibilities to apply new techniques for identification and control of electrical drives in real-time, so as to improve and optimize their performances. The paper presents a systematic

  15. Optimal Design of the Transverse Flux Machine Using a Fitted Genetic Algorithm with Real Parameters

    DEFF Research Database (Denmark)

    Argeseanu, Alin; Ritchie, Ewen; Leban, Krisztina Monika

    2012-01-01

    This paper applies a fitted genetic algorithm (GA) to the optimal design of transverse flux machine (TFM). The main goal is to provide a tool for the optimal design of TFM that is an easy to use. The GA optimizes the analytic basic design of two TFM topologies: the C-core and the U-core. First...

  16. Experimental Study of Machinability in Mill-grinding of SiCp/Al Composites

    Institute of Scientific and Technical Information of China (English)

    LI Jianguang; DU Jinguang; YAO Yingxue; HAO Zhaopeng; LIU Xiao

    2014-01-01

    An attempt was made to investigate the machinability of SiCp/Al composites based on the experimental study using mill-grinding processing method. The experiments were carried out on a high-speed CNC machining center using integrated abrasive cutting tool. The effects of combined machining parameters, e g, cutting speed (vs), feed rate (vf), and depth of cut (ap), with the same change of material removal rate (MRR) on the mill-grinding force and surface roughness (Ra) were investigated. The formation mechanism of typical machined surface defects was analyzed by SEM. The experimental results reveal that with the same change of material removal rate, lower mill-grinding force values can be gained by increasing depth of cut and feed rate simultaneously at higher cutting speed. With the same change of MRR value, lower surface roughness values can be gained by increasing the feed rate at higher cutting speed, rather than just increasing the depth of cut, or increasing the feed rate and depth of cut simultaneously. The machined surface of SiCp/Al composites reveals typical defects which can influence surface integrity.

  17. Experimental study of surface roughness in Electric Discharge Machining (EDM based on Grey Relational Analysis

    Directory of Open Access Journals (Sweden)

    Mat Deris Ashanira

    2016-01-01

    Full Text Available Electric Discharge Machining (EDM is one of the modern machining which is capable in handling hard and difficult-to-machine material. The successful of EDM basically depends on its performances such as surface roughness (Ra, material removal rate (MRR, electrode wear rate (EWR and dimensional accuracy (DA. Ra is considered as the most important performance due to it role as a technological quality measurement for a product and also a factor that significantly affects the manufacturing process. This paper presents the experimental study of surface roughness in die sinking EDM using stainless steel SS316L with copper impregnated graphite electrode. The machining experimental is conducted based on the two levels full factorial design of design of experiment (DOE with five machining parameters which are peak current, servo voltage, servo speed, pulse on time and pulse off time. The results were analyzed using grey relational analysis (GRA and it was found that pulse on time and servo voltage give the most influence to the Ra value.

  18. [Influence of milking technique, milking hygiene and environmental hygiene parameters on the microbial contamination of milking machines].

    Science.gov (United States)

    Feldmann, M; Zimmermann, A; Hoedemaker, M

    2006-07-01

    It was the aim of this study to investigate the effect of various factors of the milking technique, milking hygiene and environment on microbial contamination of the milking machine. In 31 dairy herds, the degree of bacterial contamination was examined by taking swabs at four locations (teat cup liner, claw, short and long milk tube) before the milking procedure was started using a standardized protocol (DIN ISO 6887-1:1999). Furthermore, the total germ count was determined in the first milk entering the bulk tank as well as in the bulk tank milk following milking. For each farm, the quality of the milking process and the condition of the milking machine as well as of various environmental factors were recorded. A subjective evaluation of the status of the milking cluster or other parts of the milking machine ("good" or "moderate-poor") gave more information about bacterial contamination than the determination of age and type of material used. A temperature of the rinsing water of teat cleaning before milking or of postmilking teat disinfection did not affect the contamination of the milking machine and the bulk tank milk with environmental bacteria. Furthermore, type of bedding material affected bacterial contamination of milking clusters and bulk tank milk. In conclusion, our results suggest that the microbial contamination of the milking machine is not only influenced by the sanitation pro-

  19. Optimal machining parameters module development based on CAD/CAM system

    Science.gov (United States)

    Zhang, Jinichun; Gong, Xiansheng; Xie, Guanghui; Yin, Ling

    2011-05-01

    In view of the actual numerical control processing in cutting specifications' establishment question, take Windows as the service platform, used the grid algorithm and using VC6.0, MFC (the Microsoft foundation class) and tool research and so on C-HOOKS has developed with the MasterCAM seamless integration cutting specifications optimization module. Carries on the practical application which on the numerical control milling machine to the connecting rod mold electrode the cutting specifications optimize to indicate that through the optimization, obtained the small depth of cut and the roughing feed speed combination, the connecting rod electrode surface has pulls out the mold ascent, used the small depth of cut to enable the electrode surface to obtain the good smooth finish, its machining time saved 49%, the processing efficiency obtains the large scale promotion nearly, the product quality has the enhancement.

  20. Elongational Viscosity Rheological Parameter Study

    Science.gov (United States)

    1982-06-01

    can prepare a simple table of collapse ratios as a function of prts.-orc ±t,.s. ii Table. Collapse Ratios as a Function of Pressure Ratios (i = 1.4...that were used in this study were all water soluble polyrner systems. The two polymers used were carboxymethylcellulose (CMC) 40U t

  1. EXPERIMENTAL IMPACT ASSESSMENT OF PARAMETERS PERTAINING TO BLANK TWO-DIMENSIONAL CIRCULAR MOTION ON INTENSITY OF ITS CUTTING AND QUALITY OF MACHINED SURFACE

    National Research Council Canada - National Science Library

    M. G. Kiselev; A. V. Drozdov; S. G. Monich; D. A. Yamnaya

    2014-01-01

    The purpose of the paper is to make an experimental impact assessment of parameters pertaining to blank two-dimensional circular blank motion on intensity of its cutting and quality of the machined surfaces...

  2. Study of CNC Grinding Machining Method About Isometric Polygon Profile

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    The formed principle and CNC grinding machining method of isometric polygonal profile are studied deeply and systematically. Equation about section curve of isometric polygon profile is set up by means of geometric principle. With the use of differential geometry theory, the curve is proved to be with geometric feature of convex curve. It is referred to as Isometric Polygonal Curve (IPC), because that is a kind of convex curve on which the distance between any parallel tangent lines is equal. Isometric Poly...

  3. Fall detection using supervised machine learning algorithms: A comparative study

    KAUST Repository

    Zerrouki, Nabil

    2017-01-05

    Fall incidents are considered as the leading cause of disability and even mortality among older adults. To address this problem, fall detection and prevention fields receive a lot of intention over the past years and attracted many researcher efforts. We present in the current study an overall performance comparison between fall detection systems using the most popular machine learning approaches which are: Naïve Bayes, K nearest neighbor, neural network, and support vector machine. The analysis of the classification power associated to these most widely utilized algorithms is conducted on two fall detection databases namely FDD and URFD. Since the performance of the classification algorithm is inherently dependent on the features, we extracted and used the same features for all classifiers. The classification evaluation is conducted using different state of the art statistical measures such as the overall accuracy, the F-measure coefficient, and the area under ROC curve (AUC) value.

  4. A Comparison Study of Extreme Learning Machine and Least Squares Support Vector Machine for Structural Impact Localization

    OpenAIRE

    Qingsong Xu

    2014-01-01

    Extreme learning machine (ELM) is a learning algorithm for single-hidden layer feedforward neural network dedicated to an extremely fast learning. However, the performance of ELM in structural impact localization is unknown yet. In this paper, a comparison study of ELM with least squares support vector machine (LSSVM) is presented for the application on impact localization of a plate structure with surface-mounted piezoelectric sensors. Both basic and kernel-based ELM regression models have b...

  5. Multi-criteria decision making in the selection of machining parameters for Inconel 718

    Energy Technology Data Exchange (ETDEWEB)

    Thirumalai, R. [SNS College of Technology, Coimbatore (India); Senthilkumaar, J. S. [Bharathithasan Engineering College, Nattrampalli (India)

    2013-04-15

    Taguchi's methods and design of experiments are invariably used and adopted as quality improvement techniques in several manufacturing industries as tools for offline quality control. These methods optimize single-response processes. However, Taguchi's method is not appropriate for optimizing a multi-response problem. In other situations, multi-responses need to be optimized simultaneously. This paper presents multi-response optimization techniques. A set of non-dominated solutions are obtained using non-sorted genetic algorithm for multi-objective functions. Multi-criteria decision making (MCDM) is proposed in this work for selecting a single solution from nondominated solutions. This paper addresses a new method of MCDM concept based on technique for order preference by similarity to ideal solution (TOPSIS). TOPSIS determines the shortest distance to the positive-ideal solution and the greatest distance from the negative-ideal solution. This work involves the high-speed machining of Inconel 718 using carbide cutting tool with six objective functions that are considered as attributes against the process variables of cutting speed, feed, and depth of cut. The higher-ranked solution is selected as the best solution for the machining of Inconel 718 in its respective environment.

  6. Statistical regression modeling and machinability study of hardened AISI 52100 steel using cemented carbide insert

    Directory of Open Access Journals (Sweden)

    Amlana Panda

    2017-01-01

    Full Text Available The present study investigates performance and feasibility of application of low cost cemented carbide insert in dry machining of AISI 52100 steel hardened to (55 ± 1 HRC which is rarely researched as far as machining of bearing steel is concerned. Machinability studies i.e. flank wear, surface roughness and morphology analysis of chip has been investigated and statistical regression modeling has been developed. The test has been conducted based on Taguchi L16 OA taking machining parameters like cutting speed, feed and depth of cut. It is observed that uncoated cemented carbide insert performs well at some selected runs (Run 1, 5 and 9 which show its feasibility for hard turning applications. The developed serrated saw tooth chip of burnt blue colour adversely affects the surface quality. Adequacy of the developed statistical regression model has been checked using ANOVA analysis (depending on F value, P value and R2 value and normal probability plot at 95% confidence level. The results of optimal parametric combinations may be adopted while turning hardened AISI 52100 steel under dry environment with uncoated cemented carbide insert.

  7. The rise of machine consciousness: studying consciousness with computational models.

    Science.gov (United States)

    Reggia, James A

    2013-08-01

    Efforts to create computational models of consciousness have accelerated over the last two decades, creating a field that has become known as artificial consciousness. There have been two main motivations for this controversial work: to develop a better scientific understanding of the nature of human/animal consciousness and to produce machines that genuinely exhibit conscious awareness. This review begins by briefly explaining some of the concepts and terminology used by investigators working on machine consciousness, and summarizes key neurobiological correlates of human consciousness that are particularly relevant to past computational studies. Models of consciousness developed over the last twenty years are then surveyed. These models are largely found to fall into five categories based on the fundamental issue that their developers have selected as being most central to consciousness: a global workspace, information integration, an internal self-model, higher-level representations, or attention mechanisms. For each of these five categories, an overview of past work is given, a representative example is presented in some detail to illustrate the approach, and comments are provided on the contributions and limitations of the methodology. Three conclusions are offered about the state of the field based on this review: (1) computational modeling has become an effective and accepted methodology for the scientific study of consciousness, (2) existing computational models have successfully captured a number of neurobiological, cognitive, and behavioral correlates of conscious information processing as machine simulations, and (3) no existing approach to artificial consciousness has presented a compelling demonstration of phenomenal machine consciousness, or even clear evidence that artificial phenomenal consciousness will eventually be possible. The paper concludes by discussing the importance of continuing work in this area, considering the ethical issues it raises

  8. Optimization of machining and vibration parameters for residual stresses minimization in ultrasonic assisted turning of 4340 hardened steel.

    Science.gov (United States)

    Sharma, Varun; Pandey, Pulak M

    2016-08-01

    The residual stresses generated in the machined work piece have detrimental effect on fatigue life, corrosion resistance and tribological properties. However, the effect of cutting and vibration parameters on residual stresses in Ultrasonic Assisted Turning (UAT) has not been dealt with. The present paper highlights the effect of feed rate, depth of cut, cutting velocity and percentage intensity of ultrasonic power on residual stress generation. XRD analysis has been carried out to measure the residual stress while turning 4340 hardened steel using UAT. The experiments were performed based on response surface methodology to develop statistical model for residual stress. The outcome of ANOVA revealed that percentage intensity and feed rate significantly affect the residual stress generation. The significant interactions between process parameters have also been presented tin order to understand the thermo-mechanical mechanism responsible for residual stress generation.

  9. [Prediction model of net photosynthetic rate of ginseng under forest based on optimized parameters support vector machine].

    Science.gov (United States)

    Wu, Hai-wei; Yu, Hai-ye; Zhang, Lei

    2011-05-01

    Using K-fold cross validation method and two support vector machine functions, four kernel functions, grid-search, genetic algorithm and particle swarm optimization, the authors constructed the support vector machine model of the best penalty parameter c and the best correlation coefficient. Using information granulation technology, the authors constructed P particle and epsilon particle about those factors affecting net photosynthetic rate, and reduced these dimensions of the determinant. P particle includes the percent of visible spectrum ingredients. Epsilon particle includes leaf temperature, scattering radiation, air temperature, and so on. It is possible to obtain the best correlation coefficient among photosynthetic effective radiation, visible spectrum and individual net photosynthetic rate by this technology. The authors constructed the training set and the forecasting set including photosynthetic effective radiation, P particle and epsilon particle. The result shows that epsilon-SVR-RBF-genetic algorithm model, nu-SVR-linear-grid-search model and nu-SVR-RBF-genetic algorithm model obtain the correlation coefficient of up to 97% about the forecasting set including photosynthetic effective radiation and P particle. The penalty parameter c of nu-SVR-linear-grid-search model is the minimum, so the model's generalization ability is the best. The authors forecasted the forecasting set including photosynthetic effective radiation, P particle and epsilon particle by the model, and the correlation coefficient is up to 96%.

  10. Machining Duplex Stainless Steel: Comparative Study Regarding End Mill Coated Tools

    Directory of Open Access Journals (Sweden)

    Ronny M. Gouveia

    2016-10-01

    Full Text Available The difficulties in the machining of duplex stainless steel are well known. However, research on this matter is rather limited. Suppliers offer quite different cutting tools for the same raw material, with end mills of two, three or even four knives and a huge number of distinct coatings, some of them under commercial brands, making it difficult to assess the advantages they offer. Furthermore, there is a remarkable difference among the several types of duplex stainless steel available nowadays on the market. The present work intends to assess the machining performance of different tools, analyzing the behavior and wear mechanisms with two different cutting lengths, keeping constant the machining trajectory. Some other parameters were also kept constant, such as cutting speed, depth of cut and cutting width, as well as feed per tooth. The machining process was carried out under lubricated conditions, using an emulsion of 5% oil in water. Tools provided with a different number of teeth and surface coatings were tested, analyzing the wear behavior of each cutting length using scanning electron microscopy, trying to identify wear performance and how each coating contributes to increased tool life. The surfaces produced were also analyzed by means of profilometry measurements, correlating tool wear and part surface roughness. This comparative study allows determining the advantages of different tools relative to others, based on coatings and tool geometry.

  11. MATHEMATICAL MODEL FOR THE STUDY AND DESIGN OF A ROTARY-VANE GAS REFRIGERATION MACHINE

    Directory of Open Access Journals (Sweden)

    V. V. Trandafilov

    2016-08-01

    Full Text Available This paper presents a mathematical model of calculating the main parameters the operating cycle, rotary-vane gas refrigerating machine that affect installation, machine control and working processes occurring in it at the specified criteria. A procedure and a graphical method for the rotary-vane gas refrigerating machine (RVGRM are proposed. A parametric study of the main geometric variables and temperature variables on the thermal behavior of the system is analyzed. The model considers polytrope index for the compression and expansion in the chamber. Graphs of the pressure and temperature in the chamber of the angle of rotation of the output shaft are received. The possibility of inclusion in the cycle regenerative heat exchanger is appreciated. The change of the coefficient of performance machine after turning the cycle regenerative heat exchanger is analyzed. It is shown that the installation of a regenerator RVGRM cycle results in increased COP more than 30%. The simulation results show that the proposed model can be used to design and optimize gas refrigerator Stirling.

  12. 葡萄秧埋枝机运动参数的研究%Design on the Vine Wood Burying Machine Motion Parameters

    Institute of Scientific and Technical Information of China (English)

    王福燕; 邓春岩; 陈立东; 李国昉

    2014-01-01

    为了保证葡萄秧安全过冬,入冬前需把葡萄秧掩埋起来。通过分析酒葡萄规模化种植农艺模式,研究葡萄秧埋枝机的作业条件,计算了埋枝机的取土深度,提出了采用两个拨土轮做啮合式旋转的新方法,对土壤进行刮削式挖掘,保证防冻土的细碎、密实,对埋枝机拨土轮的运动参数进行了分析和设计。%In order to ensure the safety of the vine in winter , the vine should be buried before winter .Through analyzing the wine grape scale planting mode , studying the operating conditions of the vine wood burying machine , this paper gave the sampling depth of buried branch machine by calculating , and proposed a new type of the two earth drawing wheel meshing rotary,the soil scraping type mining to ensure the freezing soil fine ,dense.In this paper,the movement parameters of the wood burying machine scarification wheel is analyzed and designed .

  13. A Study on the Optimization Performance of Fireworks and Cuckoo Search Algorithms in Laser Machining Processes

    Science.gov (United States)

    Goswami, D.; Chakraborty, S.

    2014-11-01

    Laser machining is a promising non-contact process for effective machining of difficult-to-process advanced engineering materials. Increasing interest in the use of lasers for various machining operations can be attributed to its several unique advantages, like high productivity, non-contact processing, elimination of finishing operations, adaptability to automation, reduced processing cost, improved product quality, greater material utilization, minimum heat-affected zone and green manufacturing. To achieve the best desired machining performance and high quality characteristics of the machined components, it is extremely important to determine the optimal values of the laser machining process parameters. In this paper, fireworks algorithm and cuckoo search (CS) algorithm are applied for single as well as multi-response optimization of two laser machining processes. It is observed that although almost similar solutions are obtained for both these algorithms, CS algorithm outperforms fireworks algorithm with respect to average computation time, convergence rate and performance consistency.

  14. Monte Carlo study of MLC fields for cobalt therapy machine

    Directory of Open Access Journals (Sweden)

    Komanduri M Ayyangar

    2014-01-01

    Full Text Available An automated Multi-Leaf Collimator (MLC system has been developed as add-on for the cobalt-60 teletherapy machines available in India. The goal of the present computational study is to validate the MLC design using Monte Carlo (MC modeling. The study was based on the Kirloskar-supplied Phoenix model machines that closely match the Atomic Energy of Canada Limited (AECL theratron-80 machine. The MLC is a retrofit attachment to the collimator assembly, with 14 non-divergent leaf pairs of 40 mm thick, 7 mm wide, and 150 mm long tungsten alloy plates with rounded edges and 20 mm tongue and 2 mm groove in each leaf. In the present work, the source and collimator geometry has been investigated in detail to arrive at a model that best represents the measured dosimetric data. The authors have studied in detail the proto-I MLC built for cobalt-60. The MLC field sizes were MC simulated for 2 × 2 cm 2 to 14 × 14 cm 2 square fields as well as irregular fields, and the percent depth dose (PDD and profile data were compared with ROPS† treatment planning system (TPS. In addition, measured profiles using the IMATRIXX system‡ were also compared with the MC simulations. The proto-I MLC can define radiation fields up to 14 × 14 cm΂ within 3 mm accuracy. The maximum measured leakage through the leaf ends in closed condition was 3.4% and interleaf leakage observed was 7.3%. Good agreement between MC results, ROPS and IMATRIXX results has been observed. The investigation also supports the hypothesis that optical and radiation field coincidence exists for the square fields studied with the MLC. Plots of the percent depth dose (PDD data and profile data for clinically significant irregular fields have also been presented. The MC model was also investigated to speed up the calculations to allow calculations of clinically relevant conformal beams.

  15. A semi-supervised support vector machine approach for parameter setting in motor imagery-based brain computer interfaces

    Science.gov (United States)

    Long, Jinyi; Yu, Zhuliang

    2010-01-01

    Parameter setting plays an important role for improving the performance of a brain computer interface (BCI). Currently, parameters (e.g. channels and frequency band) are often manually selected. It is time-consuming and not easy to obtain an optimal combination of parameters for a BCI. In this paper, motor imagery-based BCIs are considered, in which channels and frequency band are key parameters. First, a semi-supervised support vector machine algorithm is proposed for automatically selecting a set of channels with given frequency band. Next, this algorithm is extended for joint channel-frequency selection. In this approach, both training data with labels and test data without labels are used for training a classifier. Hence it can be used in small training data case. Finally, our algorithms are applied to a BCI competition data set. Our data analysis results show that these algorithms are effective for selection of frequency band and channels when the training data set is small. PMID:21886673

  16. Development of an equipment based in microcomputer for the determination of synchronous machine parameters through the frequency response method; Desenvolvimento de um equipamento baseado em microcomputador para determinacao de parametros de maquinas sincronas atraves do metodo de resposta em frequencia

    Energy Technology Data Exchange (ETDEWEB)

    Costa Bortoni, Edson da; Jardini, Jose Antonio [Sao Paulo Univ., SP (Brazil). Escola Politecnica

    1995-12-31

    This work presents the development of a equipment to be used for the determination of synchronous machines parameters though the frequency response method. The methodology is presented. A case study based on literature data is presented 9 figs., 2 tabs., 7 refs.

  17. Machine Protection Studies for a Crab Cavity in the LHC

    CERN Document Server

    Yee-Rendon, B; Baer, T; Barranco, J; Calaga, R; Marsili, A; Tomas, R; Zimmermann, F

    2013-01-01

    Crab cavities (CCs) apply a transverse kick that rotates the bunches so as to have a head-on collision at the interaction point (IP). Such cavities were successfully used to improve the luminosity of KEKB. They are also a key ingredient of the HL-LHC project to increase the luminosity of the LHC. As CCs can rapidly change the particle trajectories, machine protection studies are required to assess the beam losses due to fast CC failures. In this paper, we discuss the effect of rapid voltage or phase changes in a CC for the HL-LHC layout using measured beam distributions from the present LHC.

  18. Machine self-teaching methods for parameter optimization. Final report, October 1984-August 1986

    Energy Technology Data Exchange (ETDEWEB)

    Dillard, R.A.

    1986-12-01

    The problem of determining near-optimum parameter-control logic is addressed for cases where a sensor or communication system is highly flexible and the logic cannot be determined analytically. A system that supports human-like learning of optimum parameters is outlined. The major subsystems are (1) a simulation system (described for a radar example), (2) a performance monitoring system, (3) the learning system, and (4) the initial knowledge used by all subsystems. The initial knowledge is expressed modularly as specifications (e.g., radar constraints, performance measures, and target characteristics), relationships (among parameters, intermediate measures, and component performance measures), and formulas. The intent of the learning system is to relieve the human from the very tedious trial-and-error process of examining performance, selecting and applying curve-fitting methods, and selecting the next trial set of parameters. A learning system to design a simple radar meeting specific performance constraints is described in detail, for experimental purposes, in generic object-based code.

  19. 电火花线切割机床加工工艺参数的研究%Research on Wire Electrical Discharge Machining Processing Technology Parameters

    Institute of Scientific and Technical Information of China (English)

    杨亚琴

    2012-01-01

    This paper describes the processing mechanism of wire electrical discharge machining, by using orthogonal test, makes optimization design of peak current, pulse width, and intrapulse ratio of wire electrical discharge machining with high cutting rate and low wire wear, reduce the experiment times, shorten the cycle and improve the efficiency and benefit, so as to optimize processing technology parameter, improve the product quality- It concluded the relation of electric parameters and the processing speed, and surface roughness, for providing the basis for further studying on the processing law of wire electrical discharge machining.%本文阐述了电火花线切割机床的加工机理,利用正交试验的方法,对高速走丝电火花线切割机床加工中的峰值电流、脉冲宽度、脉间比等工艺条件进行了试验的优化设计,减少了试验的次数,缩短了实验周期,提高了效率和效益;从而优化了电火花线切割机床加工工艺参数,提高了加工件的质量;得出了电参数与加工速度和表面粗糙度之间的联系,为进一步研究电火花线切割加工工艺规律提供了基础.

  20. Experimental Investigation of Machining Parameters For Surface Roughness In High Speed CNC Turning of EN-24 Alloy Steel Using Response Surface Methodology

    Directory of Open Access Journals (Sweden)

    Puneet Saini

    2014-05-01

    Full Text Available Alloy Steel EN-24 (Medium Carbon Steel used in manufacturing of Automotive & aircraft components, Axles & Axles components, Shafts, Heavy duty Gears, Spindles, Studs, Pins, collets, bolts, couplings, sprockets, pinions & pinion arbors. Turning is the most common process used in manufacturing sector to produce smooth finish on cylindrical surfaces. Surface roughness is the important performance characteristics to be considered in the turning process is affected by several factors such as cutting tool material, spindle speed, feed rate, depth of cut and material properties. In this research Response surface methodology (RSM was applied to determine the optimum machining parameters leading to minimum surface roughness in turning process. The main purpose of this research is to study the effect of carbide inserts on EN-24 Alloy Steel surface by using three parameters (spindle speed, feed rate and depth of cut. This research was conducted by using 100 HS Stallion CNC Lathe machine. Seventeen sets of experiments were performed. In this work empirical models were developed for surface roughness by considering spindle speed, feed rate and depth of cut as main controlling factors using response surface methodology. The optimum value of the surface roughness (Ra comes out to be 0.48 µm. It is also concluded that feed rate is the most significant factor affecting surface roughness followed by depth of cut. As Cutting speed is the less significant factor affecting surface roughness. Optimum results are finally verified with the help of confirmation experiments. Keywords:

  1. A testing method for the machine details state by means of the speckle image parameters analysis

    Science.gov (United States)

    Malov, A. N.; Pavlov, P. V.; Neupokoeva, A. V.

    2016-08-01

    Non destructive testing method, allowing to define a residual resource of power details of mechanical engineering designs under the analysis of registered speckle-image parameters, it is discussed. The "chessboard" algorithm based on calculation of correlation between the given speckle-image and the a chessboard image is considered. Experimental research results of an offered non destructive testing method are presented. It is established, that to increase in quantity of a power detail tests cycles there is an increase in roughness parameters that conducts to reduction of correlation factor between reference and to resultants the image at the given stage of test. Knowing of correlation factor change dynamics, it is possible to define a residual resource of power details while in exploitation.

  2. Predicting Complexation Thermodynamic Parameters of β-Cyclodextrin with Chiral Guests by Using Swarm Intelligence and Support Vector Machines

    Directory of Open Access Journals (Sweden)

    Luckhana Lawtrakul

    2009-05-01

    Full Text Available The Particle Swarm Optimization (PSO and Support Vector Machines (SVMs approaches are used for predicting the thermodynamic parameters for the 1:1 inclusion complexation of chiral guests with β-cyclodextrin. A PSO is adopted for descriptor selection in the quantitative structure-property relationships (QSPR of a dataset of 74 chiral guests due to its simplicity, speed, and consistency. The modified PSO is then combined with SVMs for its good approximating properties, to generate a QSPR model with the selected features. Linear, polynomial, and Gaussian radial basis functions are used as kernels in SVMs. All models have demonstrated an impressive performance with R2 higher than 0.8.

  3. Key Performance Parameter Driven Technology Goals for Electric Machines and Power Systems

    Science.gov (United States)

    Bowman, Cheryl; Jansen, Ralph; Brown, Gerald; Duffy, Kirsten; Trudell, Jeffrey

    2015-01-01

    Transitioning aviation to low carbon propulsion is one of the crucial strategic research thrust and is a driver in the search for alternative propulsion system for advanced aircraft configurations. This work requires multidisciplinary skills coming from multiple entities. The feasibility of scaling up various electric drive system technologies to meet the requirements of a large commercial transport is discussed in terms of key parameters. Functional requirements are identified that impact the power system design. A breakeven analysis is presented to find the minimum allowable electric drive specific power and efficiency that can preserve the range, initial weight, operating empty weight, and payload weight of the base aircraft.

  4. Study of the stiffness for predicting the accuracy of machine tools; Estudio de la rigidez para la prediccion de la precision de las maquinas-herramientas

    Energy Technology Data Exchange (ETDEWEB)

    Ortega, N.; Campa, F.J.; Fernandez Valdivielso, A.; Alonso, U.; Olvera, D.; Compean, F.I.

    2010-07-01

    Machining processes are frequently faced with the challenge of achieving more and more precision and surface qualities. These requirements are usually attained taking into account some process variables, including the cutting parameters and the use or not of refrigerant, leaving aside the mechanical aspects associated with the influence of machine tool itself. There are many sources of error linked with machine-workpiece interaction, but, in general, we can summarize them into two types of error: quasi-static and dynamic. This paper shows the influence of quasi-static error caused by low machine rigidity on the accuracy applied on two very different processes: turning and grinding. For the study of the static stiffness of these two machines, two different methods are proposed, both of them equally valid. The first one is based on separated parameters and the second one on finite elements. (Author).

  5. Study of acrylamide level in food from vending machines

    Directory of Open Access Journals (Sweden)

    Naceur Haouet

    2016-11-01

    Full Text Available Acrylamide is a by-product of the Maillard reaction and is potentially carcinogenic to humans. It is found in a number of foods with higher concentrations in carbohydrate-rich foods and moderate levels of protein-rich foods such as meat, fish and seafood. Acrylamide levels in food distributed in vending machines placed in public areas of the city of Perugia were analysed by high-performance liquid chromatography. Samples included five different categories, depending on the characteristics of the products: i potato chips; ii salted bakery products; iii biscuits and wafers; iv sweet bakery products; v sandwiches. A high variability in acrylamide level among different foods and within the same category was detected. Potato chips showed the highest amount of acrylamide (1781±637 μg/kg followed by salted bakery products (211±245 μg/kg, biscuits and wafers (184±254 μg/kg, sweet bakery products (100±72 μg/kg and sandwiches (42±10 μg/kg. In the potato chips and sandwiches categories, all of the samples revealed the presence of acrylamide, while different prevalence was registered in the other foods considered. The data of this study highlight the presence of acrylamide in different foods sold in vending machines and this data could be useful to understand the contribution of this type of consumption to human exposure to this compound.

  6. Five-Phase Modular External Rotor PM Machines with Different Rotor Poles: A Comparative Simulation Study

    Directory of Open Access Journals (Sweden)

    A. S. Abdel-Khalik

    2012-01-01

    Full Text Available The performance of fault-tolerant modular permanent magnet machines depends on the proper selection of the pole and slot numbers which result in negligible coupling between phases. The preferred slot and pole number combinations eliminate the effect of low-order harmonics in the stator magnetomotive force and thereby the vibration and stray loss are reduced. In this paper, three external rotor machines with identical machine dimensions are designed with different slots per phase per pole ratios. A simulation study is carried out using finite element analysis to compare the performance of the three machines in terms of machine torque density, ripple torque, core loss, and machine efficiency. A mathematical model based on the conventional-phase-model approach is also used for the comparative study. The simulation study is extended to depict machine performance under fault conditions.

  7. MODEL STUDY OF THE DOUBLE FED MACHINE WITH CURRENT CONTROL

    Directory of Open Access Journals (Sweden)

    A. S. Lyapin

    2016-07-01

    Full Text Available The paper deals with modeling results of the double fed induction machine with current control in the rotor circuit. We show the most promising applications of electric drives on the basis of the double fed induction machine and their advantages. We present and consider functional scheme of the electric drive on the basis of the double fed induction machine with current control. Equations are obtained for creation of such machine mathematical model. Expressions for vector projections of rotor current are given. According to the obtained results, the change of the vector projections of rotor current ensures operation of the double fed induction machine with the specified values of active and reactive stator power throughout the variation range of sliding motion. We consider static characteristics of double fed machine with current control. Energy processes proceeding in the machine are analyzed. We confirm the operationpossibility of double fed induction machine with current controlin the rotor circuit with given values of active and reactive stator power. The presented results can be used for creation of mathematical models and static characteristics of double fed machines with current control of various capacities.

  8. Monte Carlo study of MLC fields for cobalt therapy machine

    Science.gov (United States)

    Ayyangar, Komanduri M.; Rani, Roopa A.; Kumar, Anil; Reddy, A. R.

    2014-01-01

    An automated Multi-Leaf Collimator (MLC) system has been developed as add-on for the cobalt-60 teletherapy machines available in India. The goal of the present computational study is to validate the MLC design using Monte Carlo (MC) modeling. The study was based on the Kirloskar-supplied Phoenix model machines that closely match the Atomic Energy of Canada Limited (AECL) theratron-80 machine. The MLC is a retrofit attachment to the collimator assembly, with 14 non-divergent leaf pairs of 40 mm thick, 7 mm wide, and 150 mm long tungsten alloy plates with rounded edges and 20 mm tongue and 2 mm groove in each leaf. In the present work, the source and collimator geometry has been investigated in detail to arrive at a model that best represents the measured dosimetric data. The authors have studied in detail the proto-I MLC built for cobalt-60. The MLC field sizes were MC simulated for 2 × 2 cm2 to 14 × 14 cm2 square fields as well as irregular fields, and the percent depth dose (PDD) and profile data were compared with ROPS† treatment planning system (TPS). In addition, measured profiles using the IMATRIXX system‡ were also compared with the MC simulations. The proto-I MLC can define radiation fields up to 14 × 14 cm2 within 3 mm accuracy. The maximum measured leakage through the leaf ends in closed condition was 3.4% and interleaf leakage observed was 7.3%. Good agreement between MC results, ROPS and IMATRIXX results has been observed. The investigation also supports the hypothesis that optical and radiation field coincidence exists for the square fields studied with the MLC. Plots of the percent depth dose (PDD) data and profile data for clinically significant irregular fields have also been presented. The MC model was also investigated to speed up the calculations to allow calculations of clinically relevant conformal beams. †Radiation Oncology Planning System (ROPS) is supplied by Tirumala Jyothi Computer Systems described at https

  9. Study on the effect of thermal property of metals in ultrasonic-assisted laser machining

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Hu Seung; Kim, Gun Woo; Park, Jong Eun [Dept. of Mechanical Engineering, Korea Advanced Institute of Science and Technology, Daejeon (Korea, Republic of); Cho, Sung Hak; Yang, Min Yang; Park, Jong Kweon [Korea Institute of Machinery and Materials, Deajeon (Korea, Republic of)

    2015-08-15

    The laser machining process has been proposed as an advanced process for the selective fabrication of electrodes without a mask. In this study, we adapt laser machining to metals that have different thermal properties. Based on the results, the metals exhibit a different surface morphology, heat-affected zone (HAZ), and a recast layer around the machined surface according to their thermal conductivity, boiling point, and thermal diffusivity. Then, we apply ultrasonic-assisted laser machining to remove the recast layer. The ultrasonic-assisted laser machining exhibits a better surface quality in metals with higher diffusivity than those having lower diffusivity.

  10. Studies on the Material Removal Rate of Al-SiC Composites Machined by Powder- Mixed EDM Technique

    Directory of Open Access Journals (Sweden)

    G P Anuraag

    2016-04-01

    Full Text Available The metal-matrix composites are preferred due to their high hardness, light weight, flexibility, high strength, simplicity and ease of applicability which make them potentially valuable in every industrious area like motor vehicles industries, mechanical tools manufacturing industries, structural applications and aerospace industries. Electro-discharge machining is a non-conventional machining process which uses short electrical discharges to machine any material of any hardness and strength levels provided that they are electrically conductive. In this paper, an attempt was made to find the machinability of aluminium metal matrix composite using powder mixed electric discharge machining (PMEDM. The aluminium matrix was reinforced with different percentages of silicon carbide (3%, 9% & 15% to form the composites using stir casting process. The Characteristic Material removal rate (MRR was studied while varying the process parameters of discharge time (TON, peak current (I and concentration of SiC in work material (C according to the face cantered central composite design for a constant voltage of 40 volts. The Electric Discharge Machining of the composites was carried out using a copper electrode of Ø6mm and kerosene mixed with aluminium powder was used as dielectric fluid.

  11. The Experimental Investigation of The Effect of Machining Parameters on Burr Formation in Drilling of AISI D2 and AISI D3 Cold Work Steels

    Directory of Open Access Journals (Sweden)

    Yavuz Kaplan

    2011-06-01

    Full Text Available In this study, the effect of changing processing parameters on the burr formation ats the exit end of hole during the drilling process in milling machines of CNC (Computer Numerical Control was examined. . In experimental studies, cold work tool steels (AISI D2, 20 HRC and AISI D3, 28 HRC were drilling by HSS cutting tools with four different lengths in two different diameters (Ø 8 mm and Ø 10 mm. Three different cutting speeds (5 m/min, 10 m/min, 15 m/min and three different feed rates values (0.04 mm/rev, 0.05 mm/rev, 0.06 mm/rev were used in experiments. According to outcomes of the experiment, it was detected that burr height decreases depending on feed rates increase and burr height increases depending on the number of holes, cutting speed and material hardness.

  12. Machine Translation

    Institute of Scientific and Technical Information of China (English)

    张严心

    2015-01-01

    As a kind of ancillary translation tool, Machine Translation has been paid increasing attention to and received different kinds of study by a great deal of researchers and scholars for a long time. To know the definition of Machine Translation and to analyse its benefits and problems are significant for translators in order to make good use of Machine Translation, and helpful to develop and consummate Machine Translation Systems in the future.

  13. Study of an NC system of machining crown gears

    Science.gov (United States)

    Xu, Xiaogang; Wang, Huaqing; Yan, Jian; Gao, Shenyou

    2005-12-01

    Crown gear couplings are usually used in metallurgy and steel rolling equipments, which is manufactured by duplicating processing in common. The method makes the manipulator work hard, and the efficiency is low. The machining precision is limited to the shape of the mold and it is difficult to control the movement of machines table. This work stated an NC system to use hobbing machine. It consists of an industrial control computer, grating sensor, servo- motor and its driver source, servo driver card and other I/O equipments of inputting and outputting. The grating sensor was installed in the axial direction to trace the instantaneous position of gob rest. The radial movement of the machine table was controlled by a servomotor. When the computer captures the axial signal, this system controls the machine table by moving ahead or backwards according to the calculated value of interpolation theory. Thus, two dimensions (axial and radial) associated movement was realized while the crown gear was processed. The feature of the system is that a grating sensor used in the axial direction replaces the servomotor. By making a little change in the mechanism of the machine, NC can be implement and its redesign cost is very low. The design software has an interpolation function for a circular arc and line. The system has been used on a Y1380 gear hobbing machine, and the correlative software of machining crown gear has been designed as well. Satisfactory results have been obtained, showing facility and reliability in practical operation.

  14. Study of the Service Reliability of Machines Based on Safety

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    From the point of safety being the basic requirement of machine operation, equivalent failure number, which is employed to replace the actual statistical failure number, is introduced. Calculating theory of service reliability indexes of machines based on safety is developed. The method proposed in this paper can reflect the damage degree of failure.

  15. Machine Protection Studie for a Crab Cavity in the LHC

    CERN Document Server

    Yee-Rendon, B; Baer, T; Barranco, J; Calaga, R; Marsili, A; Tomas, R; Zimmermann, F

    2013-01-01

    Crab cavities (CCs) apply a transverse kick that rotates the bunches so as to have a head-on collision at the interaction point (IP). Such cavities were successfully used to improve the luminosity of KEKB. They are also a key ingredient of the HL-LHC project to increase the luminosity of the LHC. As CCs can rapidly change the particle trajectories, machine protection studies are required to assess the beam losses due to fast CC failures. In this paper, we discuss the effect of rapid voltage or phase changes in a CC for the HL-LHC layout using measured beam distributions from the present LHC. Presented at IPAC'13 Shanghai, 12-17 May 2013

  16. THE STUDY OF SELF-BALANCED POTATO SORTING MACHINE WITH LINEAR INDUCTION DRIVE

    Directory of Open Access Journals (Sweden)

    Linenko A. V.

    2016-04-01

    Full Text Available In the article we have considered the self-balanced potato sorting machine differing from existing designs of self-balanced potato sorting machines with an oscillatory electric drive. That drive uses a linear induction motor. As the counterbalancing device, the method of the duplicating mechanism is applied. The duplicating mechanism is a specular reflection of the main working body, and also participates in technological process. Its application in the drive of machine allows not only to increase efficiency of cleaning, drying and sorting of potatoes, but also to increase reliability of sorting installation that corresponds to the newest tendencies of development of technology. We have brought the mathematical model of the offered electric drive of potato sorting machine, which is implemented in the environment of object and visual modeling of Matlab |Simulink|. The mathematical model allows investigating influence of parameters of the linear induction electric drive on parameters of oscillatory process of working body in dynamics. The developed technique of research and the created experimental potato sorting machine with the linear induction drive have confirmed theoretical researches. The main kinematic sizes of machine and technical parameters of individual nodes are determined. It is shown, that the efficiency of inertial transportation can be increased for 20% in comparison with the classical drive from the motor of rotation. Results of research will allow to realize energetically and technologically effective potato sorting machines with the linear induction drive

  17. A Machine Learning Approach to Estimate Riverbank Geotechnical Parameters from Sediment Particle Size Data

    Science.gov (United States)

    Iwashita, Fabio; Brooks, Andrew; Spencer, John; Borombovits, Daniel; Curwen, Graeme; Olley, Jon

    2015-04-01

    Assessing bank stability using geotechnical models traditionally involves the laborious collection of data on the bank and floodplain stratigraphy, as well as in-situ geotechnical data for each sedimentary unit within a river bank. The application of geotechnical bank stability models are limited to those sites where extensive field data has been collected, where their ability to provide predictions of bank erosion at the reach scale are limited without a very extensive and expensive field data collection program. Some challenges in the construction and application of riverbank erosion and hydraulic numerical models are their one-dimensionality, steady-state requirements, lack of calibration data, and nonuniqueness. Also, numerical models commonly can be too rigid with respect to detecting unexpected features like the onset of trends, non-linear relations, or patterns restricted to sub-samples of a data set. These shortcomings create the need for an alternate modelling approach capable of using available data. The application of the Self-Organizing Maps (SOM) approach is well-suited to the analysis of noisy, sparse, nonlinear, multidimensional, and scale-dependent data. It is a type of unsupervised artificial neural network with hybrid competitive-cooperative learning. In this work we present a method that uses a database of geotechnical data collected at over 100 sites throughout Queensland State, Australia, to develop a modelling approach that enables geotechnical parameters (soil effective cohesion, friction angle, soil erodibility and critical stress) to be derived from sediment particle size data (PSD). The model framework and predicted values were evaluated using two methods, splitting the dataset into training and validation set, and through a Bootstrap approach. The basis of Bootstrap cross-validation is a leave-one-out strategy. This requires leaving one data value out of the training set while creating a new SOM to estimate that missing value based on the

  18. Influence of Cutting Parameters and Tool Wear on the Surface Integrity of Cobalt-Based Stellite 6 Alloy When Machined Under a Dry Cutting Environment

    Science.gov (United States)

    Yingfei, Ge; de Escalona, Patricia Muñoz; Galloway, Alexander

    2016-11-01

    The efficiency of a machining process can be measured by evaluating the quality of the machined surface and the tool wear rate. The research reported herein is mainly focused on the effect of cutting parameters and tool wear on the machined surface defects, surface roughness, deformation layer and residual stresses when dry milling Stellite 6, deposited by overlay on a carbon steel surface. The results showed that under the selected cutting conditions, abrasion, diffusion, peeling, chipping and breakage were the main tool wear mechanisms presented. Also the feed rate was the primary factor affecting the tool wear with an influence of 83%. With regard to the influence of cutting parameters on the surface roughness, the primary factors were feed rate and cutting speed with 57 and 38%, respectively. In addition, in general, as tool wear increased, the surface roughness increased and the deformation layer was found to be influenced more by the cutting parameters rather than the tool wear. Compressive residual stresses were observed in the un-machined surface, and when machining longer than 5 min, residual stress changed 100% from compression to tension. Finally, results showed that micro-crack initiation was the main mechanism for chip formation.

  19. Comparison of direct machine parameter optimization versus fluence optimization with sequential sequencing in IMRT of hypopharyngeal carcinoma

    Directory of Open Access Journals (Sweden)

    Bogner Ludwig

    2007-09-01

    Full Text Available Abstract Background To evaluate the effects of direct machine parameter optimization in the treatment planning of intensity-modulated radiation therapy (IMRT for hypopharyngeal cancer as compared to subsequent leaf sequencing in Oncentra Masterplan v1.5. Methods For 10 hypopharyngeal cancer patients IMRT plans were generated in Oncentra Masterplan v1.5 (Nucletron BV, Veenendal, the Netherlands for a Siemens Primus linear accelerator. For optimization the dose volume objectives (DVO for the planning target volume (PTV were set to 53 Gy minimum dose and 59 Gy maximum dose, in order to reach a dose of 56 Gy to the average of the PTV. For the parotids a median dose of 22 Gy was allowed and for the spinal cord a maximum dose of 35 Gy. The maximum DVO to the external contour of the patient was set to 59 Gy. The treatment plans were optimized with the direct machine parameter optimization ("Direct Step & Shoot", DSS, Raysearch Laboratories, Sweden newly implemented in Masterplan v1.5 and the fluence modulation technique ("Intensity Modulation", IM which was available in previous versions of Masterplan already. The two techniques were compared with regard to compliance to the DVO, plan quality, and number of monitor units (MU required per fraction dose. Results The plans optimized with the DSS technique met the DVO for the PTV significantly better than the plans optimized with IM (p = 0.007 for the min DVO and p 0.05. Plan quality, target coverage and dose homogeneity inside the PTV were superior for the plans optimized with DSS for similar dose to the spinal cord and lower dose to the normal tissue. The mean dose to the parotids was lower for the plans optimized with IM. Treatment plan efficiency was higher for the DSS plans with (901 ± 160 MU compared to (1151 ± 157 MU for IM (p-value Renormalization of the IM plans to the mean of the dose to 95% of the PTV (D95 of the DSS plans, resulted in similar target coverage and dose to the parotids for both

  20. Machinability Studies on Turning Al 6061alloy with 10% Reinforcement of B4C on MMC

    Directory of Open Access Journals (Sweden)

    Srivathsan A.

    2016-01-01

    Full Text Available Aluminum Boron Carbide Metal Matrix Composites (Al-MMC have revolutionized aeronautical and automobile industries, in the recent times due to their exceptional mechanical and physical properties. However it is seen that the machinability of these composites is greatly reduced by the hardness of constituent reinforcement particles. Moreover these constituent reinforcement particles serve as disadvantage by increasing tool wear accompanying undesirable depression in life of tool. This paper presents the experimental investigations on turning of Al6061 matrix metal reinforced with 10 % by weight of boron carbide (B4Cp particles - which was fabricated using Stir casting method. Fabricated samples are turned on medium duty lathe of 2kW spindle power with Polycrystalline Diamond (PCD inserts of 1500 grade at various cutting conditions by varying parameters. Hence, parameters such as power consumed by main spindle, machined surface roughness and tool wear are studied and recorded. Furthermore, study results are supported using concurring images obtained from Scanning Electron Microscopy (SEM. It is observed that surface finish and power consumed for 1500 grade insert are comparatively better at higher cutting speeds. Additionally it is observed that tool wear is strongly dependent on abrasive hard reinforcement particles.

  1. EXPERIMENTAL EVALUATION OF WEDM MACHINED SURFACE WAVINESS

    Directory of Open Access Journals (Sweden)

    Katerina Mouralova

    2016-10-01

    Full Text Available Wire Electrical Discharge Machining (WEDM an unconventional machining technology which has become indispensable in many industries. The typical morphology of a surface machined using the electrical discharge technology is characterized with a large number of craters caused by electro-spark discharges produced during the machining process. The study deals with an evaluation of the machine parameter setting on the profile parameters of surface waviness on samples made of two metal materials Al 99.5 and Ti-6Al-4V. Attention was also paid to an evaluation of the surface morphology using 3D colour filtered and non-filtered images.

  2. The application of PID parameter self-tuning fuzzy controller in the constant-power speed control system of heading machine

    Science.gov (United States)

    Mao, Jun; Hou, Jian; Shen, Dong

    2013-03-01

    This article describes the control system of PID parameter self-tuning fuzzy controller. For cutting the coal of different hardness, adopt fuzzy techniques, automatically adjust the feed speed of operating mechanism, and maintain the control of operating mechanism of heading machine with constant power.

  3. Proton-Ion Medical Machine Study (PIMMS), 2

    CERN Document Server

    Bryant, P J; Benedikt, Michael; Crescenti, M; Holy, P; Maier, A T; Pullia, M; Reimoser, S; Rossi, S; Borri, G; Knaus, P; Gramatica, F; Pavlovic, M; Weisser, L

    2000-01-01

    The Proton-Ion Medical Machine Study (PIMMS) group was formed following an agreement between the Med-AUSTRON (Austria) and the TERA Foundation (Italy) to combine their efforts in the design of a cancer therapy synchrotron capable of accelerating either light ions or protons. CERN agreed to support and host this study in its PS Division. A close collaboration was also set up with GSI (Germany). The study group was later joined by Onkologie-2000 (Czech Republic). Effort was first focused on the theoretical understanding of slow extraction and the techniques required to produce a smooth beam spill for the conformal treatment of complex-shaped tumours with a sub-millimetre accuracy by active scanning with proton and carbon ion beams. Considerations for passive beam spreading were also included for protons. The study has been written in two parts. The more general and theoretical aspects are recorded in Part I and the specific technical design considerations are presented in the present volume, Part II. An accompa...

  4. Proton-Ion Medical Machine Study (PIMMS), 1

    CERN Document Server

    Badano, L; Bryant, P J; Crescenti, M; Holy, P; Maier, A T; Pullia, M; Rossi, S; Knaus, P

    2000-01-01

    The Proton-Ion Medical Machine Study (PIMMS) group was formed following an agreement between the Med-AUSTRON (Austria) and the TERA Foundation (Italy) to combine their efforts in the design of a cancer therapy synchrotron. CERN agreed to host this study in its PS Division and a close collaboration was set up with GSI (Germany). The study group was later joined by Onkologie-2000 (Czech Republic). Effort was first focused on the theoretical understanding of slow extraction and the techniques required to produce a smooth beam spill for the conformal treatment of complex-shaped tumours with a sub-millimetre accuracy by active scanning with proton and carbon ion beams. Considerations for passive scanning were also included. The more general and theoretical aspects of the study are recorded in Part I and the more specific technical design considerations are presented in a second volume Part II. The PIMMS team started their work in January 1996 in the PS Division and continued for a period of three years.

  5. comparative study of moore and mealy machine models adaptation ...

    African Journals Online (AJOL)

    user

    Information and Communications Technology has influenced the need for automated machines that can carry out important production ... enjoys a reputation for improving or eliminating uneven skin tone ..... Information Management Vol. 5, pp.

  6. Study on full automatic arc welding machine for spherical tank

    Institute of Scientific and Technical Information of China (English)

    蒋力培; 张甲英; 俞建荣

    2002-01-01

    A full automatic welding machine for spherical tanks' all position multi-layer welds has been developed. This machine is mainly composed of a two-dimension seam tracking system based on microcomputer's memory and a welding tractor as well as rail. The main features of the machine are: while welding the first layer of a seam, its microcomputer system can analyze and store the tracing information from a two-dimension sensor, and control the welding head device to realize two-dimension real time tracing; while welding the second layer up to the top layer of the seam, it can realize two-dimension tracing based on the memorial data, automatically determine the layer number and continually sway the welding head. The welding test shows that the machine has good tracing and welding behavior, and is suitable for spherical tank's all position multi-layer welds.

  7. Conceptual Study of Permanent Magnet Machine Ship Propulsion Systems

    Science.gov (United States)

    1977-12-01

    thyristors and can be either water or air cooled. The machine-cycloconverter, many-phase or parallel three-phase connection design offers a drive system with characteristics well matched to a ship propulsion system.

  8. Study the effect of cryogenic cooling on orthogonal machining Process

    Directory of Open Access Journals (Sweden)

    Arvind Kaushal

    2016-06-01

    Full Text Available In present scenario , all the manufacturing organization aims to maximize the productivity of organization in respect of all the aspect of manufacturing process, in case of machining process, it associated with various factors which affect the productivity directly in sense of tool life . Temperature, cutting forces, shear angle, work-piece surface finishing & accuracy, amount of power consumed in machining process and other thing also. All the factors might be optimized by applying effective and efficient amount of coolant throughout the process, to get desired efficiency of process. A coolant play a vital role in machining operation but which must have specific properties which have been reviewed in previous article of various student , research scholars , scientist and industrial candidates .in this research paper , we were focusing on the effect of cryogenic cooling on cutting temperature , cutting forces , chip behavior , shear angle , when alloy steel EN-8 and aluminum alloy 6061-T89 was machined by carbide cutting tool (coated & uncoated & applying liquid nitrogen as a coolant and observed that temperature was decreased during the machining process about 16% to 27% and cutting forces improved to 13%when the machining was performed , the same without cooling of EN-8 alloy, similarly on the other hand in case of aluminum alloy 6061-T89 , temperature was decreased to 25% to 37% and cutting force improved to 9% .

  9. 油茶果脱壳机的设计与工作参数优化%Design of shelling machine forcamellia oleifera fruit and operating parameter optimization

    Institute of Scientific and Technical Information of China (English)

    朱广飞; 任嘉嘉; 王振; 相海; 牟仁生; 李少华

    2016-01-01

    In China,Camellia oleifera fruit is deeply loved by consumers as specific woody oil resource. Because of the composition of fatty acid for camellia seed oil is highly similar to olive oil, it is also known as “Oriental olive oil”. However, the shelling operation ofCamellia oleiferafruit largely relies on natural drying, which is of low efficiency, high labor intensity, high processing cost, and great dependence on weather. In order to improve the performance of shelling machine forCamellia oleiferafruit, increase the shelling rate and reduce the seed breaking rate, choosing the shelling rate and seed breaking rate as the indices, 3 aspects were studied based on the existing shelling equipment and practical engineering experience in this paper. Firstly, the physical parameters ofCamellia oleiferafruit were studied. The parameters such as density, bulk density, grain size, water content and proportion of each component ofCamellia oleiferafruit from Changning City were measured, which provided the data for the design of shelling machine parts. Secondly, the mechanism and main structure of the shelling machine were studied. In the beginning, the merits and defects of commonly-used methods for shelling were summed based on their working principle and mechanism. According to practical engineering experience and the measured data above, the final squeeze-rub shelling method forCamellia oleiferafruit was determined. Then the structure of main parts was designed, which included the shelling device consisting of the roller, annular plate and the regulating mechanism, and the separation device consisting of stirring shaft and circular groove structure screen. Finally, the three-dimensional (3D) prototype model was established and the drawing design was completed. Thirdly, the operating parameters of shelling machine forCamellia oleifera fruit were studied. The shelling machine forCamellia oleiferafruit was manufactured based on the structure design, and then the operating

  10. Study on Performance of Integration Control by Man and Machine in Stage of Final Approaching for Spaceship Rendezvous and Docking

    Science.gov (United States)

    Zhou, Qianxiang; Liu, Zhongqi

    With the development of manned space technology, space rendezvous and docking (RVD) technology will play a more and more important role. The astronauts’ participation in a final close period of man-machine combination control is an important way of RVD technology. Spacecraft RVD control involves control problem of a total of 12 degrees of freedom (location) and attitude which it relative to the inertial space the orbit. Therefore, in order to reduce the astronauts’ operation load and reduce the security requirements to the ground station and achieve an optimal performance of the whole man-machine system, it is need to study how to design the number of control parameters of astronaut or aircraft automatic control system. In this study, with the laboratory conditions on the ground, a method was put forward to develop an experimental system in which the performance evaluation of spaceship RVD integration control by man and machine could be completed. After the RVD precision requirements were determined, 26 male volunteers aged 20-40 took part in the performance evaluation experiments. The RVD integration control success rates and total thruster ignition time were chosen as evaluation indices. Results show that if less than three RVD parameters control tasks were finished by subject and the rest of parameters control task completed by automation, the RVD success rate would be larger than eighty-eight percent and the fuel consumption would be optimized. In addition, there were two subjects who finished the whole six RVD parameters control tasks by enough train. In conclusion, if the astronauts' role should be integrated into the RVD control, it was suitable for them to finish the heading, pitch and roll control in order to assure the man-machine system high performance. If astronauts were needed to finish all parameter control, two points should be taken into consideration, one was enough fuel and another was enough long operation time.

  11. Impact of the HEALTHY Study on Vending Machine Offerings in Middle Schools

    Science.gov (United States)

    Hartstein, Jill; Cullen, Karen W.; Virus, Amy; El Ghormli, Laure; Volpe, Stella L.; Staten, Myrlene A.; Bridgman, Jessica C.; Stadler, Diane D.; Gillis, Bonnie; McCormick, Sarah B.; Mobley, Connie C.

    2011-01-01

    Purpose/Objectives: The purpose of this study is to report the impact of the three-year middle school-based HEALTHY study on intervention school vending machine offerings. There were two goals for the vending machines: serve only dessert/snack foods with 200 kilocalories or less per single serving package, and eliminate 100% fruit juice and…

  12. The Influence Study of Ultrasonic honing parameters to workpiece surface temperature

    Directory of Open Access Journals (Sweden)

    Zhang Xiaoqiang

    2016-01-01

    Full Text Available Ultrasonic vibration honing(UVH, a machine technology, has a lot of advantages. Lower grinding temperature is a significant character and is beneficial for both processing and workpiece surface. But the high temperature caused by big honing pressure becomes the main factor to produce workpiece heat damage in grinding zone. In various honing parameter combinations, the showing effect is different. Based on the thermodynamics classical theory, established the heat transfer equation for grinding zone, simplified the model and obtained the two-dimenssion temperature field expression for workpiece, then simulated the temperature changing trend in a variety of conditions. It is shown that themain temp is in a range of 700K to 1200K. In addition, the variation is huge for every parameter. The study provides a theoretical basis for deeply seeking reasonable machining parameter and obtaining better workpiece quality.

  13. Study on Measuring System of Casing Machine Based on PLC

    Directory of Open Access Journals (Sweden)

    Huiqiang Wang

    2014-05-01

    Full Text Available According to the technology requirements of measurement for animal casing, in this paper, we use PLC and touch screen as the control core, the electromechanical integration design ideas to research the methods and principles for casing measure, and analyze the mechanical structures and mechanical characteristics of casing machine. As the control core, the programmable logic controller (PLC ensures that the whole control system has high precision, high stability, high reliability during the operation time. Through PLC and touch screen well match with PLC which make the casing machine more convenient to operate the whole system. The configuration software form has a brief and intuitive interface on touch screen which makes it easy to use. The mechanical structure and control system of this casing machine are more stable, more reliable and with high anti-interference ability, and satisfies various requirements for animal casings, easy and convenient to operate.

  14. Study on Application of Grey Prediction Model in Superalloy MAR-247 Machining

    Directory of Open Access Journals (Sweden)

    Chen Shao-Hsien

    2015-01-01

    Full Text Available Superalloy MAR-247 is mainly applied in the space industry and die industry. With its characteristics of mechanical property, fatigue resistance, and high temperature corrosion resistance, therefore, it is mainly applied in machine parts of high temperature and corrosion resistance, such as turbine blades and rotor of the aeroengine and turbine assembly in the nuclear power plant. However, considering that its properties of high strength, low thermal conductivity, being difficult to soften, and work hardening may reduce the life of cutting-tool and weaken the surface accuracy, the study provided minimizing experiment occurring during milling process for superalloy material. As a statistical approach used to analyse experiment data, this study used GM(1,1 in the grey prediction model to conduct simulation and then predict and analyze its characteristics based on the experimental data, focusing on the tool life and surface accuracy. Moreover, with the superalloy machining parameters of the current effective application improved grey prediction model, it can decrease the errors, extend the tool life, and improve the prediction precision of surface accuracy.

  15. Tackling EEG signal classification with least squares support vector machines: a sensitivity analysis study.

    Science.gov (United States)

    Lima, Clodoaldo A M; Coelho, André L V; Eisencraft, Marcio

    2010-08-01

    The electroencephalogram (EEG) signal captures the electrical activity of the brain and is an important source of information for studying neurological disorders. The proper analysis of this biological signal plays an important role in the domain of brain-computer interface, which aims at the construction of communication channels between human brain and computers. In this paper, we investigate the application of least squares support vector machines (LS-SVM) to the task of epilepsy diagnosis through automatic EEG signal classification. More specifically, we present a sensitivity analysis study by means of which the performance levels exhibited by standard and least squares SVM classifiers are contrasted, taking into account the setting of the kernel function and of its parameter value. Results of experiments conducted over different types of features extracted from a benchmark EEG signal dataset evidence that the sensitivity profiles of the kernel machines are qualitatively similar, both showing notable performance in terms of accuracy and generalization. In addition, the performance accomplished by optimally configured LS-SVM models is also quantitatively contrasted with that obtained by related approaches for the same dataset. Copyright 2010 Elsevier Ltd. All rights reserved.

  16. Optimization of process parameters for electrical discharge machining%电火花加工工艺电参数的优化

    Institute of Scientific and Technical Information of China (English)

    郭晓霞

    2013-01-01

    以Cr12MoV为工件材料,研究电火花加工中脉冲宽度、脉冲间隔和放电电流等工艺参数对工艺指标材料去除率、电极损耗率和表面粗糙度的影响。为了优化工艺指标,将相关分析方法与Taguchi方法相结合,通过灰相关度系数值决定优化的工艺参数,最后利用方差分析,确定放电电流对工艺指标的最大影响。%Electrical discharge machining of Cr 12MoV is studied.Influence of pulse-on time,pulse-off time and discharge current are investigated for material removal rate and electrode wear ratio and surface roughness .In order to optimization process respon-ses,the grey relational analysis based Taguchi method is used .The grey relational grade is used to determine the optimal process parameters .Analysis of variance shows that discharge current is the most significant parameter for process reponses .

  17. Parameter Studies for the VISTA Spacecraft Concept

    Energy Technology Data Exchange (ETDEWEB)

    Orth, C D

    2000-11-21

    The baseline design for the VISTA spacecraft concept employs a diode-pumped solid-state laser (DPSSL) driver. This type of driver is now under development at LLNL and elsewhere as an extension of the mature solid-state (glass) laser technology developed for terrestrial applications of inertial confinement fusion (ICF). A DPSSL is repratable up to at least 30 Hz, and has an efficiency soon to be experimentally verified of at least 10%. By using a detailed systems code including the essential physics of a DPSSL, we have run parameter studies for the baseline roundtrip (RT) to Mars with a 100-ton payload. We describe the results of these studies as a function of the optimized (minimum) RT flight duration. We also demonstrate why DT fuel gives the best performance, although DD, D3He, or even antimatter can be used, and why DT-ignited DD is probably the fuel most preferred. We also describe the overall power flow, showing where the fusion energy is ultimately utilized, and estimate the variation in performance to the planets dictated by variations in target gain and other parameters.

  18. Quantified Relationship between Shaft Drilling Parameters and Drilling Machine Performances%钻井参数与钻机性能间的量化关系

    Institute of Scientific and Technical Information of China (English)

    曹钧; 芦伟

    2015-01-01

    A quantified relationship between shaft drilling parameters and drilling machine performan -ces always is a weak link in a research on the shaft drilling engineering. With a quantified analysis ,a introduction on a conception of a rock breaking specific power and a derivation calculation conducted , a quantified relationship between the shaft drilling parameters and drilling machine performances was provided.In the engineering practices ,the research on the quantified relationship could be applied to optimize the parameter design on the shaft drilling technique and to improve the actual application effi ‐ciency of the drilling machine.Based on the variation conditions of the shaft drilling technical parame ‐ters ,the level of the drilling machine performances played could be predicted ,the drilling machine acci‐dent occurred could be prevented and the construction target could be scientifically and rationally real ‐ized.%钻井参数与钻机性能间的量化关系问题,一直是钻井工程研究中的薄弱环节。通过量化分析,引入破岩比功概念,并对其进行推导计算,给出了钻井参数与钻机性能间的量化关系。在工程实践中,可通过研究该量化关系,优化钻井工艺参数设计,提高钻机实际使用效率;并可根据钻井工艺参数的变化情况,预测钻机性能发挥水平,防止钻机故障发生,实现科学合理的施工目标。

  19. Gaussian Process Regression as a machine learning tool for predicting organic carbon from soil spectra - a machine learning comparison study

    Science.gov (United States)

    Schmidt, Andreas; Lausch, Angela; Vogel, Hans-Jörg

    2016-04-01

    Diffuse reflectance spectroscopy as a soil analytical tool is spreading more and more. There is a wide range of possible applications ranging from the point scale (e.g. simple soil samples, drill cores, vertical profile scans) through the field scale to the regional and even global scale (UAV, airborne and space borne instruments, soil reflectance databases). The basic idea is that the soil's reflectance spectrum holds information about its properties (like organic matter content or mineral composition). The relation between soil properties and the observable spectrum is usually not exactly know and is typically derived from statistical methods. Nowadays these methods are classified in the term machine learning, which comprises a vast pool of algorithms and methods for learning the relationship between pairs if input - output data (training data set). Within this pool of methods a Gaussian Process Regression (GPR) is newly emerging method (originating from Bayesian statistics) which is increasingly applied to applications in different fields. For example, it was successfully used to predict vegetation parameters from hyperspectral remote sensing data. In this study we apply GPR to predict soil organic carbon from soil spectroscopy data (400 - 2500 nm). We compare it to more traditional and widely used methods such as Partitial Least Squares Regression (PLSR), Random Forest (RF) and Gradient Boosted Regression Trees (GBRT). All these methods have the common ability to calculate a measure for the variable importance (wavelengths importance). The main advantage of GPR is its ability to also predict the variance of the target parameter. This makes it easy to see whether a prediction is reliable or not. The ability to choose from various covariance functions makes GPR a flexible method. This allows for including different assumptions or a priori knowledge about the data. For this study we use samples from three different locations to test the prediction accuracies. One

  20. A study of electrodischarge machining–pulse electrochemical machining combined machining for holes with high surface quality on superalloy

    OpenAIRE

    Ning Ma; Xiaolong Yang; Mingqian Gao; Jinlong Song; Ganlin Liu; Wenji Xu

    2015-01-01

    Noncircular holes on the surface of turbine rotor blades are usually machined by electrodischarge machining. A recast layer containing numerous micropores and microcracks is easily generated during the electrodischarge machining process due to the rapid heating and cooling effects, which restrict the wide applications of noncircular holes in aerospace and aircraft industries. Owing to the outstanding advantages of pulse electrochemical machining, electrodischarge machining–pulse electrochemic...

  1. 基于改进静止频率响应试验的同步电机参数辨识%Parameter identification of the synchronous machine based on an improved standstill frequency response test

    Institute of Scientific and Technical Information of China (English)

    蔡然; 杨俊华; 杨梦丽; 潘观海

    2015-01-01

    In order to identify the parameters of the synchronous machine , the relationship of the d , q-axis flux link-age with stator current and excitation voltage was studied , and a model of the synchronous machine was built with cur-rent as state variables .By analyzing the standstill frequency response curves , the gain and phase of different parame-ters with various frequencies were obtained so as to replace the relevant parts in the characteristic transfer function e -quations which represented the d , q-axis electromagnetic parameters .The mathematic model and the state-space equa-tions of the synchronous machine were simplified .The data processing method was improved and the parameters of the machine were identified based on the status analysis results of the machine at the open field excitation winding and the open stator winding .The parameters had better consistency than the measured parameters with other test methods , and therefore the effectiveness of the proposed parameter identification method was verified .%针对同步电机参数辨识问题,以全电流为状态变量,研究同步电机d、q轴磁链与定子电流及励磁电压的关系,建立电机的数学模型。通过分析静止频率响应试验曲线,获得不同频率下各测试参数的增益和相位,替换d、q轴电磁参数特性传递函数方程中的相关部分,简化电机数学模型及其状态空间方程。基于励磁和定子回路开路时电机状态的分析结果,改进数据处理过程,辨识电机参数,对比采用其它方法测取的结果,有较好的一致性,所提参数辨识方法的有效性得以验证。

  2. Machine Learning Model of the Swift/BAT Trigger Algorithm for Long GRB Population Studies

    CERN Document Server

    Graff, Philip B; Baker, John G; Sakamoto, Takanori

    2015-01-01

    To draw inferences about gamma-ray burst (GRB) source populations based on Swift observations, it is essential to understand the detection efficiency of the Swift burst alert telescope (BAT). This study considers the problem of modeling the Swift/BAT triggering algorithm for long GRBs, a computationally expensive procedure, and models it using machine learning algorithms. A large sample of simulated GRBs from Lien 2014 is used to train various models: random forests, boosted decision trees (with AdaBoost), support vector machines, and artificial neural networks. The best models have accuracies of $\\gtrsim97\\%$ ($\\lesssim 3\\%$ error), which is a significant improvement on a cut in GRB flux which has an accuracy of $89.6\\%$ ($10.4\\%$ error). These models are then used to measure the detection efficiency of Swift as a function of redshift $z$, which is used to perform Bayesian parameter estimation on the GRB rate distribution. We find a local GRB rate density of $n_0 \\sim 0.48^{+0.41}_{-0.23} \\ {\\rm Gpc}^{-3} {\\...

  3. Application of two machine learning algorithms to genetic association studies in the presence of covariates

    Directory of Open Access Journals (Sweden)

    Foulkes Andrea S

    2008-11-01

    Full Text Available Abstract Background Population-based investigations aimed at uncovering genotype-trait associations often involve high-dimensional genetic polymorphism data as well as information on multiple environmental and clinical parameters. Machine learning (ML algorithms offer a straightforward analytic approach for selecting subsets of these inputs that are most predictive of a pre-defined trait. The performance of these algorithms, however, in the presence of covariates is not well characterized. Methods and Results In this manuscript, we investigate two approaches: Random Forests (RFs and Multivariate Adaptive Regression Splines (MARS. Through multiple simulation studies, the performance under several underlying models is evaluated. An application to a cohort of HIV-1 infected individuals receiving anti-retroviral therapies is also provided. Conclusion Consistent with more traditional regression modeling theory, our findings highlight the importance of considering the nature of underlying gene-covariate-trait relationships before applying ML algorithms, particularly when there is potential confounding or effect mediation.

  4. Application of two machine learning algorithms to genetic association studies in the presence of covariates.

    Science.gov (United States)

    Nonyane, Bareng A S; Foulkes, Andrea S

    2008-11-14

    Population-based investigations aimed at uncovering genotype-trait associations often involve high-dimensional genetic polymorphism data as well as information on multiple environmental and clinical parameters. Machine learning (ML) algorithms offer a straightforward analytic approach for selecting subsets of these inputs that are most predictive of a pre-defined trait. The performance of these algorithms, however, in the presence of covariates is not well characterized. In this manuscript, we investigate two approaches: Random Forests (RFs) and Multivariate Adaptive Regression Splines (MARS). Through multiple simulation studies, the performance under several underlying models is evaluated. An application to a cohort of HIV-1 infected individuals receiving anti-retroviral therapies is also provided. Consistent with more traditional regression modeling theory, our findings highlight the importance of considering the nature of underlying gene-covariate-trait relationships before applying ML algorithms, particularly when there is potential confounding or effect mediation.

  5. Mortality studies of machining fluid exposure in the automobile industry. IV: A case-control study of lung cancer.

    Science.gov (United States)

    Schroeder, J C; Tolbert, P E; Eisen, E A; Monson, R R; Hallock, M F; Smith, T J; Woskie, S R; Hammond, S K; Milton, D K

    1997-05-01

    Machining fluids are diverse products that contain numerous additives and contaminants, including polycyclic aromatic hydrocarbons. Studies treating machining fluids as an aggregate exposure have found both positive and negative associations with lung cancer. In this nested case-control study of automotive workers (667 cases and 3,041 matched controls), individual estimates of exposure quantity and duration for specific classes of machining fluids were derived. An inverse dose-response relationship was found between synthetic machining fluids and lung cancer mortality, with an odds ratio of 0.6 (95% CI = 0.4, 0.8) for the highest level of lifetime exposure. The relationship was strongest for recent exposures. There was little evidence of an association with soluble or straight oil machining fluids. Risks were inconsistently elevated in workers exposed to aluminum. Results from this study provide strong evidence that exposure to machining fluids is not associated with an increased risk of lung cancer mortality in automotive workers.

  6. Study on Applying Hybrid Machine Learning into Family Apparel Expenditure

    Institute of Scientific and Technical Information of China (English)

    SHEN Lei

    2008-01-01

    Hybrid Machine Learning (HMD is a kind of advanced algorithm in the field of intelligent information process.It combines the induced learning based-on decision-making tree with the blocking neural network.And it provides a useful intelligent knowledge-based data mining technique.Its core algorithm is ID3 and Field Theory based ART (FTART).The paper introduces the principals of hybrid machine learning firstly, and then applies it into analyzing family apparel expenditures and their influencing factors systematically.Finally, compared with those from the traditional statistic methods, the results from HML is more friendly and easily to be understood.Besides, the forecasting by HML is more correct than by the traditional ways.

  7. Study on Support Vector Machine Based on 1-Norm

    Institute of Scientific and Technical Information of China (English)

    PAN Mei-qin; HE Guo-ping; HAN Cong-ying; XUE Xin; SHI You-qun

    2006-01-01

    The model of optimization problem for Support Vector Machine(SVM) is provided, which based on the definitions of the dual norm and the distance between a point and its projection onto a given plane. The model of improved Support Vector Machine based on 1-norm (1 - SVM) is provided from the optimization problem, yet it is a discrete programming. With the smoothing technique and optimality knowledge, the discrete programming is changed into a continuous programming. Experimental results show that the algorithm is easy to implement and this method can select and suppress the problem features more efficiently.Illustrative examples show that the 1 - SVM deal with the linear or nonlinear classification well.

  8. Study of Machining Error Forecast in NC Lathe

    Institute of Scientific and Technical Information of China (English)

    LIU Jiwei; ZHANG Ying; YANG Zheqing

    2006-01-01

    This paper brings forward a kind of machining error forecast principle in NC lathe simulation system. It combines the method of math, dynamic, material and mechanism, etc, sums up the factors which can affect the machining error, coalescent knowledge of mechanism manufacture technique and interconvert characteristic, mapped the change of physics factor in cutting process into virtual manufacture system by mathematical model. On the platform of Windows 2000 and Visual C++, applying program is developed by use of C++. The lean warehouse of MATLAB is transferred in order to command MATLAB on the language platform of MATLAB, and then the curve of the results is drawn by the outcome of calculation, which is based on the mathematical model in order to manifest the simulation results in the pattern of data and curve.

  9. A comparative study of slope failure prediction using logistic regression, support vector machine and least square support vector machine models

    Science.gov (United States)

    Zhou, Lim Yi; Shan, Fam Pei; Shimizu, Kunio; Imoto, Tomoaki; Lateh, Habibah; Peng, Koay Swee

    2017-08-01

    A comparative study of logistic regression, support vector machine (SVM) and least square support vector machine (LSSVM) models has been done to predict the slope failure (landslide) along East-West Highway (Gerik-Jeli). The effects of two monsoon seasons (southwest and northeast) that occur in Malaysia are considered in this study. Two related factors of occurrence of slope failure are included in this study: rainfall and underground water. For each method, two predictive models are constructed, namely SOUTHWEST and NORTHEAST models. Based on the results obtained from logistic regression models, two factors (rainfall and underground water level) contribute to the occurrence of slope failure. The accuracies of the three statistical models for two monsoon seasons are verified by using Relative Operating Characteristics curves. The validation results showed that all models produced prediction of high accuracy. For the results of SVM and LSSVM, the models using RBF kernel showed better prediction compared to the models using linear kernel. The comparative results showed that, for SOUTHWEST models, three statistical models have relatively similar performance. For NORTHEAST models, logistic regression has the best predictive efficiency whereas the SVM model has the second best predictive efficiency.

  10. 容错式永磁游标电机关键参数分析及实验研究%Leading Design Parameter Analysis and Experimental Validation of a Fault Tolerant Permanent Magnet Vernier Machine

    Institute of Scientific and Technical Information of China (English)

    徐亮; 刘国海; 赵文祥; 吉敬华; 张步峰

    2016-01-01

    In order to enhance electromagnetic torque and optimization efficiency of the five-phase fault-tolerant permanent-magnet vernier (FT-PMV) machine, the leading design parameters of the five-phase FT-PMV machine on the electromagnetic torque were investigated. The power equation of the FT-PMV machine was derived for identifying the leading design parameters. By using the analytical method, feasible variation ranges of the leading design parameters were obtained, thus providing a basis for design optimization. In addition, the leading design parameters were optimized by a global optimization with genetic algorithm for maximal torque production. A prototype machine with 1.6kW was fabricated and tested. Finally, experimental studies on the prototype machine were carried out when it operated under both healthy and fault-tolerant conditions. Both the simulated and experimental results reveal that the FT-PMV machine definitely takes the merits of high torque and high reliability. Meanwhile, the effectiveness of the theoretical analysis presented in this paper is validated.%为了提升五相容错式永磁游标(five-phase fault-tolerant permanent-magnet vernier,FT-PMV)电机的输出转矩和设计优化的效率,该文对影响五相 FT-PMV 电机转矩性能的关键设计参数进行了研究。首先,推导了电机的功率方程,确定了影响电机转矩性能的关键设计参数,并通过解析法计算得到参数的合理取值范围,为电机转矩的优化提供基础。其次,以最大输出转矩为目标,利用遗传算法,对电机的关键设计参数进行了全局优化,设计并制造了一台1.6kW 实验样机。最后,对样机开展了正常运行和故障容错运行的实验研究。仿真和实验结果表明样机确实具有高可靠性、高转矩的优点,同时证明了理论分析的有效性。

  11. Detecting Safety Zone Drill Process Parameters for Uncoated HSS Twist Drill in Machining GFRP Composites by Integrating Wear Rate and Wear Transition Mapping

    Directory of Open Access Journals (Sweden)

    Sathish Rao Udupi

    2016-01-01

    Full Text Available The previous research investigations informed that the tool wear of any machining operation could be minimized by controlling the machining factors such as speed, feed, geometry, and type of cutting tool. Hence the present research paper aims at controlling the process parameters to minimize the drill tool wear, during the machining of Glass Fiber Reinforced Polymer (GFRP composites. Experiments were carried out to find the tool wear rate and a wear mechanism map of uncoated High Speed Steel (HSS drill of 10 mm diameter was developed for the drilling of GFRP composite laminates. The surface micrograph images on the drill land surface displayed dominant wear mechanisms induced on HSS drill during machining of GFRP and they were found to be adhesive wear, adhesive and abrasive wear, abrasive wear, and diffusion and fatigue wear. A “safety wear zone” was identified on the wear mechanism map, where the minimum tool wear of the HSS drill occurs. From the safety zone boundaries, it was inferred that the drill spindle speed should be set between 1200 and 1590 rpm and feed rate must be set within a range of 0.10–0.16 mm/rev for GFRP work and HSS tool combination to enhance the service life of 10 mm HSS drills and to minimize the tool wear.

  12. Study of the machining process of nano-electrical discharge machining based on combined atomistic-continuum modeling method

    Science.gov (United States)

    Zhang, Guojun; Guo, Jianwen; Ming, Wuyi; Huang, Yu; Shao, Xinyu; Zhang, Zhen

    2014-01-01

    Nano-electrical discharge machining (nano-EDM) is an attractive measure to manufacture parts with nanoscale precision, however, due to the incompleteness of its theories, the development of more advanced nano-EDM technology is impeded. In this paper, a computational simulation model combining the molecular dynamics simulation model and the two-temperature model for single discharge process in nano-EDM is constructed to study the machining mechanism of nano-EDM from the thermal point of view. The melting process is analyzed. Before the heated material gets melted, thermal compressive stress higher than 3 GPa is induced. After the material gets melted, the compressive stress gets relieved. The cooling and solidifying processes are also analyzed. It is found that during the cooling process of the melted material, tensile stress higher than 3 GPa arises, which leads to the disintegration of material. The formation of the white layer is attributed to the homogeneous solidification, and additionally, the resultant residual stress is analyzed.

  13. The impact of machine learning techniques in the study of bipolar disorder: A systematic review.

    Science.gov (United States)

    Librenza-Garcia, Diego; Kotzian, Bruno Jaskulski; Yang, Jessica; Mwangi, Benson; Cao, Bo; Pereira Lima, Luiza Nunes; Bermudez, Mariane Bagatin; Boeira, Manuela Vianna; Kapczinski, Flávio; Passos, Ives Cavalcante

    2017-07-18

    Machine learning techniques provide new methods to predict diagnosis and clinical outcomes at an individual level. We aim to review the existing literature on the use of machine learning techniques in the assessment of subjects with bipolar disorder. We systematically searched PubMed, Embase and Web of Science for articles published in any language up to January 2017. We found 757 abstracts and included 51 studies in our review. Most of the included studies used multiple levels of biological data to distinguish the diagnosis of bipolar disorder from other psychiatric disorders or healthy controls. We also found studies that assessed the prediction of clinical outcomes and studies using unsupervised machine learning to build more consistent clinical phenotypes of bipolar disorder. We concluded that given the clinical heterogeneity of samples of patients with BD, machine learning techniques may provide clinicians and researchers with important insights in fields such as diagnosis, personalized treatment and prognosis orientation. Copyright © 2017 Elsevier Ltd. All rights reserved.

  14. A Study on Automatic Scoring for Machine Translation Systems

    Institute of Scientific and Technical Information of China (English)

    Yao Jianmin(姚建民); Zhang Jing; Zhao Tiejun; Li Sheng

    2004-01-01

    String similarity measures of edit distance, cosine correlation and Dice coefficient are adopted to evaluate machine translation results. Experiment shows that the evaluation method distinguishes well between "good" and "bad" translations. Another experiment manifests a consistency between human and automatic scorings of 6 general-purpose MT systems. Equational analysis validates the experimental results. Although the data and graphs are very promising, correlation coefficient and significance tests at 0.01 level are made to ensure the reliability of the results. Linear regression is made to map the automatic scoring results to human scorings.

  15. Machinability of Green Powder Metallurgy Components: Part II. Sintered Properties of Components Machined in Green State

    Science.gov (United States)

    Robert-Perron, Etienne; Blais, Carl; Pelletier, Sylvain; Thomas, Yannig

    2007-06-01

    The green machining process is virtually a must if the powder metallurgy (PM) industries are to solve the lower machining performances associated with PM components. This process is known for lowering the rate of tool wear. Recent improvements in binder/lubricant technologies have led to high-green-strength systems that enable green machining. Combined with the optimized cutting parameters determined in Part I of the study, the green machining of PM components seems to be a viable process for fabricating high performance parts on large scale and complete other shaping processes. This second part of our study presents a comparison between the machining behaviors and the sintered properties of components machined prior to or after sintering. The results show that the radial crush strength measured on rings machined in their green state is equal to that of parts machined after sintering.

  16. Study on Surface Engineering of Normalized Steels Subjected To Machine

    Institute of Scientific and Technical Information of China (English)

    Hardening

    2004-01-01

    Engineering the surfaces of components to improve the life and performance of parts used in automotive and aerospace engineering is the active area of research. Suitable Thermal/Mechanical/Thermo mechanical surface engineering treatments will produce extensive rearrangement of atoms in metals and alloys and corresponding marked variations in Physical, Chemical and Mechanical properties. Among the more important of these treatments are heat treatment processes such as hardening by Quenching, Induction hardening and Case Carburizing which rely on phase transformations to produce desired changes in mechanical properties. Other processes where phase transformation occur are casting, welding and machining etc. [1] Phase transformation may be homogeneous or heterogeneous. Homogeneous involves rearrangements in the structure of the material taking place simultaneously in all parts of the solid, while the heterogeneous transformation involves structural changes which are more localized. Alternatively they could be called as Isothermal and Nonisothermal transformation. But irrespective of the classification, these transformations alter the structure of the material giving rise to changes in the mechanical and physical properties of the processed material. It is of interest to review some consequences of surface modification in isothermal (Normalizing) and nonisothermal transformations (Machining) of low carbon steels.

  17. Modeling the Relationship between Vibration Features and Condition Parameters Using Relevance Vector Machines for Health Monitoring of Rolling Element Bearings under Varying Operation Conditions

    Directory of Open Access Journals (Sweden)

    Lei Hu

    2015-01-01

    Full Text Available Rotational speed and load usually change when rotating machinery works. Both this kind of changing operational conditions and machine fault could make the mechanical vibration characteristics change. Therefore, effective health monitoring method for rotating machinery must be able to adjust during the change of operational conditions. This paper presents an adaptive threshold model for the health monitoring of bearings under changing operational conditions. Relevance vector machines (RVMs are used for regression of the relationships between the adaptive parameters of the threshold model and the statistical characteristics of vibration features. The adaptive threshold model is constructed based on these relationships. The health status of bearings can be indicated via detecting whether vibration features exceed the adaptive threshold. This method is validated on bearings running at changing speeds. The monitoring results show that this method is effective as long as the rotational speed is higher than a relative small value.

  18. Study on electroplating technology of diamond tools for machining hard and brittle materials

    Science.gov (United States)

    Cui, Ying; Chen, Jian Hua; Sun, Li Peng; Wang, Yue

    2016-10-01

    With the development of the high speed cutting, the ultra-precision machining and ultrasonic vibration technique in processing hard and brittle material , the requirement of cutting tools is becoming higher and higher. As electroplated diamond tools have distinct advantages, such as high adaptability, high durability, long service life and good dimensional stability, the cutting tools are effective and extensive used in grinding hard and brittle materials. In this paper, the coating structure of electroplating diamond tool is described. The electroplating process flow is presented, and the influence of pretreatment on the machining quality is analyzed. Through the experimental research and summary, the reasonable formula of the electrolyte, the electroplating technologic parameters and the suitable sanding method were determined. Meanwhile, the drilling experiment on glass-ceramic shows that the electroplating process can effectively improve the cutting performance of diamond tools. It has laid a good foundation for further improving the quality and efficiency of the machining of hard and brittle materials.

  19. Effectiveness of Hamstring Knee Rehabilitation Exercise Performed in Training Machine vs. Elastic Resistance Electromyography Evaluation Study

    DEFF Research Database (Denmark)

    Jakobsen, M. D.; Sundstrup, E.; Andersen, C. H.

    2014-01-01

    Objective The aim of this study was to evaluate muscle activity during hamstring rehabilitation exercises performed in training machine compared with elastic resistance. Design Six women and 13 men aged 28-67 yrs participated in a crossover study. Electromyographic (EMG) activity was recorded...... in the biceps femoris and the semitendinosus during the concentric and the eccentric phase of hamstring curls performed with TheraBand elastic tubing and Technogym training machines and normalized to maximal voluntary isometric contraction-EMG (normalized EMG). Knee joint angle was measured using electronic...... inclinometers. Results Training machines and elastic resistance showed similar high levels of muscle activity (biceps femoris and semitendinosus peak normalized EMG >80%). EMG during the concentric phase was higher than during the eccentric phase regardless of exercise and muscle. However, compared with machine...

  20. Machine performance assessment and enhancement for a hexapod machine

    Energy Technology Data Exchange (ETDEWEB)

    Mou, J.I. [Arizona State Univ., Tempe, AZ (United States); King, C. [Sandia National Labs., Livermore, CA (United States). Integrated Manufacturing Systems Center

    1998-03-19

    The focus of this study is to develop a sensor fused process modeling and control methodology to model, assess, and then enhance the performance of a hexapod machine for precision product realization. Deterministic modeling technique was used to derive models for machine performance assessment and enhancement. Sensor fusion methodology was adopted to identify the parameters of the derived models. Empirical models and computational algorithms were also derived and implemented to model, assess, and then enhance the machine performance. The developed sensor fusion algorithms can be implemented on a PC-based open architecture controller to receive information from various sensors, assess the status of the process, determine the proper action, and deliver the command to actuators for task execution. This will enhance a hexapod machine`s capability to produce workpieces within the imposed dimensional tolerances.

  1. Specimen Machining for the Study of the Effect of Swelling on CGR in PWR Environment.

    Energy Technology Data Exchange (ETDEWEB)

    Teysseyre, Sebastien Paul [Idaho National Lab. (INL), Idaho Falls, ID (United States)

    2015-06-01

    This report describes the preparation of ten specimens to be used for the study of the effect of swelling on the propagation of irradiation assisted stress corrosion cracking cracks. Four compact tension specimens, four microscopy plates and two tensile specimens were machined from a AISI 304 material that was irradiated up to 33 dpa. The specimens had been machined such as to represent the behavior of materials with 3.7%swelling and <2% swelling.

  2. Study on Machining Properties of Eucalyptus urophylla × E. Grandis: Ⅰ. Planing and Sanding Properties

    Institute of Scientific and Technical Information of China (English)

    HOU Xinyi; JIANG Xiaomei; GAO Jianmin; YIN Yafang

    2006-01-01

    The research method in this paper is based on the standard of American Society for Testing and Materials (ASTM), Planing and sanding are selected to study the machining properties of E. Urophylla × E. Grandis plantation wood. Moreover, the reasons for machining defects are analyzed. The results show E. Urophylla × E. Grandis planted in south China is a good species with a great potential for solid wood utilization.

  3. Atomic structure of machined semiconducting chips: An x-ray absorption spectroscopy study

    Energy Technology Data Exchange (ETDEWEB)

    Paesler, M.; Sayers, D.

    1988-12-01

    X-ray absorption spectroscopy (XAS) has been used to examine the atomic structure of chips of germanium that were produced by single point diamond machining. It is demonstrated that although the local (nearest neighbor) atomic structure is experimentally quite similar to that of single crystal specimens information from more distant atoms indicates the presence of considerable stress. An outline of the technique is given and the strength of XAS in studying the machining process is demonstrated.

  4. The Employment Effects of High-Technology: A Case Study of Machine Vision. Research Report No. 86-19.

    Science.gov (United States)

    Chen, Kan; Stafford, Frank P.

    A case study of machine vision was conducted to identify and analyze the employment effects of high technology in general. (Machine vision is the automatic acquisition and analysis of an image to obtain desired information for use in controlling an industrial activity, such as the visual sensor system that gives eyes to a robot.) Machine vision as…

  5. A Study of Electrochemical Machining of Ti-6Al-4V in NaNO3 solution

    Science.gov (United States)

    Li, Hansong; Gao, Chuanping; Wang, Guoqian; Qu, Ningsong; Zhu, Di

    2016-01-01

    The titanium alloy Ti-6Al-4V is used in many industries including aviation, automobile manufacturing, and medical equipment, because of its low density, extraordinary corrosion resistance and high specific strength. Electrochemical machining (ECM) is a non-traditional machining method that allows applications to all kinds of metallic materials in regardless of their mechanical properties. It is widely applied to the machining of Ti-6Al-4V components, which usually takes place in a multicomponent electrolyte solution. In this study, a 10% NaNO3 solution was used to make multiple holes in Ti-6Al-4V sheets by through-mask electrochemical machining (TMECM). The polarization curve and current efficiency curve of this alloy were measured to understand the electrical properties of Ti-6Al-4V in a 10% NaNO3 solution. The measurements show that in a 10% NaNO3 solution, when the current density was above 6.56 A·cm−2, the current efficiency exceeded 100%. According to polarization curve and current efficiency curve, an orthogonal TMECM experiment was conducted on Ti-6Al-4V. The experimental results suggest that with appropriate process parameters, high-quality holes can be obtained in a 10% NaNO3 solution. Using the optimized process parameters, an array of micro-holes with an aperture of 2.52 mm to 2.57 mm and maximum roundness of 9 μm were produced using TMECM. PMID:27734951

  6. A Study of Electrochemical Machining of Ti-6Al-4V in NaNO3 solution.

    Science.gov (United States)

    Li, Hansong; Gao, Chuanping; Wang, Guoqian; Qu, Ningsong; Zhu, Di

    2016-10-13

    The titanium alloy Ti-6Al-4V is used in many industries including aviation, automobile manufacturing, and medical equipment, because of its low density, extraordinary corrosion resistance and high specific strength. Electrochemical machining (ECM) is a non-traditional machining method that allows applications to all kinds of metallic materials in regardless of their mechanical properties. It is widely applied to the machining of Ti-6Al-4V components, which usually takes place in a multicomponent electrolyte solution. In this study, a 10% NaNO3 solution was used to make multiple holes in Ti-6Al-4V sheets by through-mask electrochemical machining (TMECM). The polarization curve and current efficiency curve of this alloy were measured to understand the electrical properties of Ti-6Al-4V in a 10% NaNO3 solution. The measurements show that in a 10% NaNO3 solution, when the current density was above 6.56 A·cm(-2), the current efficiency exceeded 100%. According to polarization curve and current efficiency curve, an orthogonal TMECM experiment was conducted on Ti-6Al-4V. The experimental results suggest that with appropriate process parameters, high-quality holes can be obtained in a 10% NaNO3 solution. Using the optimized process parameters, an array of micro-holes with an aperture of 2.52 mm to 2.57 mm and maximum roundness of 9 μm were produced using TMECM.

  7. Comparison of machine-learning algorithms to build a predictive model for detecting undiagnosed diabetes - ELSA-Brasil: accuracy study.

    Science.gov (United States)

    Olivera, André Rodrigues; Roesler, Valter; Iochpe, Cirano; Schmidt, Maria Inês; Vigo, Álvaro; Barreto, Sandhi Maria; Duncan, Bruce Bartholow

    2017-01-01

    Type 2 diabetes is a chronic disease associated with a wide range of serious health complications that have a major impact on overall health. The aims here were to develop and validate predictive models for detecting undiagnosed diabetes using data from the Longitudinal Study of Adult Health (ELSA-Brasil) and to compare the performance of different machine-learning algorithms in this task. Comparison of machine-learning algorithms to develop predictive models using data from ELSA-Brasil. After selecting a subset of 27 candidate variables from the literature, models were built and validated in four sequential steps: (i) parameter tuning with tenfold cross-validation, repeated three times; (ii) automatic variable selection using forward selection, a wrapper strategy with four different machine-learning algorithms and tenfold cross-validation (repeated three times), to evaluate each subset of variables; (iii) error estimation of model parameters with tenfold cross-validation, repeated ten times; and (iv) generalization testing on an independent dataset. The models were created with the following machine-learning algorithms: logistic regression, artificial neural network, naïve Bayes, K-nearest neighbor and random forest. The best models were created using artificial neural networks and logistic regression. -These achieved mean areas under the curve of, respectively, 75.24% and 74.98% in the error estimation step and 74.17% and 74.41% in the generalization testing step. Most of the predictive models produced similar results, and demonstrated the feasibility of identifying individuals with highest probability of having undiagnosed diabetes, through easily-obtained clinical data.

  8. A Study of Electrochemical Machining of Ti-6Al-4V in NaNO3 solution

    Science.gov (United States)

    Li, Hansong; Gao, Chuanping; Wang, Guoqian; Qu, Ningsong; Zhu, Di

    2016-10-01

    The titanium alloy Ti-6Al-4V is used in many industries including aviation, automobile manufacturing, and medical equipment, because of its low density, extraordinary corrosion resistance and high specific strength. Electrochemical machining (ECM) is a non-traditional machining method that allows applications to all kinds of metallic materials in regardless of their mechanical properties. It is widely applied to the machining of Ti-6Al-4V components, which usually takes place in a multicomponent electrolyte solution. In this study, a 10% NaNO3 solution was used to make multiple holes in Ti-6Al-4V sheets by through-mask electrochemical machining (TMECM). The polarization curve and current efficiency curve of this alloy were measured to understand the electrical properties of Ti-6Al-4V in a 10% NaNO3 solution. The measurements show that in a 10% NaNO3 solution, when the current density was above 6.56 A·cm-2, the current efficiency exceeded 100%. According to polarization curve and current efficiency curve, an orthogonal TMECM experiment was conducted on Ti-6Al-4V. The experimental results suggest that with appropriate process parameters, high-quality holes can be obtained in a 10% NaNO3 solution. Using the optimized process parameters, an array of micro-holes with an aperture of 2.52 mm to 2.57 mm and maximum roundness of 9 μm were produced using TMECM.

  9. Least Squares Support Vector Machine Based Real-Time Fault Diagnosis Model for Gas Path Parameters of Aero Engines

    Institute of Scientific and Technical Information of China (English)

    WANG Xu-hui; HUANG Sheng-guo; WANG Ye; LIU Yong-jian; SHU Ping

    2009-01-01

    Least squares support vector machine (LS-SVM) is applied in gas path fault diagnosis for aero engines.Firstly,the deviation data of engine cruise are analyzed.Then,model selection is conducted using pattern search method.Finally,by decoding aircraft communication addressing and reporting system (ACARS) report,a real-time cruise data set is acquired,and the diagnosis model is adopted to process data.In contrast to the radial basis function (RBF) neutral network,LS-SVM is more suitable for real-time diagnosis of gas turbine engine.

  10. Design and parameter optimization of portable tree transplanting machine%便携式苗木移植机设计及工作参数优化

    Institute of Scientific and Technical Information of China (English)

    张京平; 朱建锡; 孙腾

    2014-01-01

    Summary Seedling transplanting plays an important role in urban greening and forest plantation.However, this job is still relying on manual labor in China.There are many disadvantages such as heavy labor intensity,high cost and low survival rate of seedlings in this situation.Thus it is necessary to design a machine that can replace artificial seedling transplant. First,a simple,convenient and reliable portable tree transplanting machine was designed,which mainly included damping handle,gasoline engine,deceleration strip,eccentric vibration device,vibration shovel and so on.When this machine was used to transplant trees,the eccentric block was driven by the gasoline engine through the deceleration strip.Combining this with a vertical vibration and a torsion vibration in a horizontal direction and users depression,the tree transplanting machine can excavate seedling easily.Furthermore,the format of the vibration shovel was suitable to some different trees whose diameter ranged from 100 mm to 200 mm.Second,in order to increase the machines working performance,a response surface method was considered to optimize the working parameter of the portable tree transplanting machine. According to the Box-Behnken principles of experimental design,the operating parameters such as eccentric block roller speed,eccentric block mass and linear eccentricity were selected as independent variables,which would influence the time of machine digging down 200 mm.Meanwhile,the software of Design-Expert 7.0.0 was taken to analyze the experimental data,and the quadratic regression mathematical model was established which can expound the relationship between the three operating parameters and response value. The analysis of variance and significance test of the regression coefficients showed that the quadratic regression mathematical model was consistent with the actual situation and also could predict the test results accurately.Lastly,in line with the optimization of the quadratic

  11. Computer-aided Selection System for Cutting Tools and Parameters Based on Machining Features%面向加工特征的刀具和切削参数计算机辅助选择系统

    Institute of Scientific and Technical Information of China (English)

    郝传海; 刘战强; 任小平; 万熠

    2012-01-01

    Cutting tool manufacturers are facing increasing demands to supply a comprehensive advice service with relation to selection of appropriate tools and cutting parameters for a widely variety of part materials and machining features. The central element for process planning is to select the appropriate cutting tools and machining parameters, too. However, the main attention has been only paid on the part materials. It causes the mismatches between workpieces and tools. This study is to describe the development of a computer - aided selection system for cutting tools and cutting parameters based on machining features (FTCPS), which is designed to cover different component shapes including turning, milling, drilling as well as boring operation features. The kinematic link between machined surface feature with a simple icon based interface being used to input data records, and a relational database combined with data - driven method and rule - based decision logic is used to select cutting tool geometry and machining parameters for a range of machining operations. The system also utilizes mathematical model to calculate processing conditions (machining time in single path, cutting power, maximum harshness, etc. ). Process planning is completed in the end. By turning tools and turning parameters selection for example , the result shows the realization method of system. FTCPS will help the designers and manufacturing planners to select optimal set of cutting tools and cutting conditions.%切削刀具制造商面临围绕大量工件材料和加工特征为客户提供合理刀具和切削参数的现状,切削工艺规划的核心步骤也是刀具和切削参数的确定.确定刀具和切削参数一般多从零件材料角度出发,可能导致工件与刀具不匹配.文中提出面向加工特征的刀具和切削参数计算机辅助选择系统的开发.系统包括车削特征、铣削特征、钻削和镗削加工特征,系统利用特征

  12. Dynamics of cyclic machines

    CERN Document Server

    Vulfson, Iosif

    2015-01-01

    This book focuses on modern methods of oscillation analysis in machines, including cyclic action mechanisms (linkages, cams, steppers, etc.). It presents schematization techniques and mathematical descriptions of oscillating systems, taking into account the variability of the parameters and nonlinearities, engineering evaluations of dynamic errors, and oscillation suppression methods. The majority of the book is devoted to the development of new methods of dynamic analysis and synthesis for cyclic machines that form regular oscillatory systems with multiple duplicate modules.  There are also sections examining aspects of general engineering interest (nonlinear dissipative forces, systems with non-stationary constraints, impacts and pseudo-impacts in clearances, etc.)  The examples in the book are based on the widely used results of theoretical and experimental studies as well as engineering calculations carried out in relation to machines used in the textile, light, polygraphic and other industries. Particu...

  13. 应用于加工中心的钻削用量确定方法%Determination Method of Drilling Parameters Applied for Machining Centers

    Institute of Scientific and Technical Information of China (English)

    施志辉; 刘刚

    2009-01-01

    提出一种适用于加工中心的钻削用量确定方法,分析了钻削用量与刀具耐用度的关系,介绍了钻削用量(包括钻削深度、进给率和钻削速度)的选取方法,并给出了计算实例.%A kind of determination method of drilling pararameters which is suitable for machining centers was presented. The relationship between drilling parameters and cutter's endurance was analyzed, the choosing methods of drilling parameters, includ-ing depth of drilhng, feed rate and drilling speed, were introduced, and a calculating example was given.

  14. Optimization experiment of operating parameters on vibration sorting-clip device for vegetable grafting machine%蔬菜嫁接机嫁接夹振动排序装置工作参数优化试验

    Institute of Scientific and Technical Information of China (English)

    田素博; 杨继峰; 王瑞丽; 徐冬雷; 李天来

    2014-01-01

    Vegetable grafting machines are extensively studied by Japan, South Korea, China and North America, and various types of grafting machines were developed successfully. In China, Zhang Tiezhong, Gu Song, and other researchers carried out ample work on cut-pasting in vegetable grafting machines. However, due to the complexity of grafting technology and the poor applicability of the grafting machine, these machines are not widely used in China. Therefore, it is significant to develop an automatic grafting machine that can be suitable for agricultural production in northeast China. In order to realize automation of a vegetable grafting machine, and solve the difficulties of automatic sorting grafting clips because of their complex shape and structure, a vibration sorting-clip device for vegetable grafting machine was designed, and the working parameters of the device were optimized by using the experimental methods in this study. The circular cylindrical hopper is one of the most important structures in the vibration sorting-clip device. The spiral material passage’s inner wall of a circular cylindrical hopper is installed by four fixed guiding mechanisms which are used to sort and direct vegetable grafting clips while conveying them. The first and the second fixed guiding mechanism are both sheet-shaped structures, the third is rod-shaped and the fourth is hole-shaped. A screening dam bar is another key component of the vibration sorting-clip device that is installed on a lateral plate between the end of the spiral material passage and the discharge port. The installing angle and installing length of the screening dam bar can be adjusted and the two major factors will affect the performance of the vibration delivery device. In addition, the input vibration voltage is also another major factor that will affect the performance of the vibration sorting-clip device. The grafting clips for the typical muskmelon were selected as the research objects. Three variables were

  15. A Simulation Model for Machine Efficiency Improvement Using Reliability Centered Maintenance: Case Study of Semiconductor Factory

    Directory of Open Access Journals (Sweden)

    Srisawat Supsomboon

    2014-01-01

    Full Text Available The purpose of this study was to increase the quality of product by focusing on the machine efficiency improvement. The principle of the reliability centered maintenance (RCM was applied to increase the machine reliability. The objective was to create preventive maintenance plan under reliability centered maintenance method and to reduce defects. The study target was set to reduce the Lead PPM for a test machine by simulating the proposed preventive maintenance plan. The simulation optimization approach based on evolutionary algorithms was employed for the preventive maintenance technique selection process to select the PM interval that gave the best total cost and Lead PPM values. The research methodology includes procedures such as following the priority of critical components in test machine, analyzing the damage and risk level by using Failure Mode and Effects Analysis (FMEA, calculating the suitable replacement period through reliability estimation, and optimizing the preventive maintenance plan. From the result of the study it is shown that the Lead PPM of test machine can be reduced. The cost of preventive maintenance, cost of good product, and cost of lost product were decreased.

  16. Machining studies of die cast aluminum alloy-silicon carbide composites

    Science.gov (United States)

    Sornakumar, Thambu; Kathiresan, Marimuthu

    2010-10-01

    Metal matrix composites (MMCs) with high specific stiffness, high strength, improved wear resistance, and thermal properties are being increasingly used in advanced structural, aerospace, automotive, electronics, and wear applications. Aluminum alloy-silicon carbide composites were developed using a new combination of the vortex method and the pressure die-casting technique in the present work. Machining studies were conducted on the aluminum alloy-silicon carbide (SiC) composite work pieces using high speed steel (HSS) end-mill tools in a milling machine at different speeds and feeds. The quantitative studies on the machined work piece show that the surface finish is better for higher speeds and lower feeds. The surface roughness of the plain aluminum alloy is better than that of the aluminum alloy-silicon carbide composites. The studies on tool wear show that flank wear increases with speed and feed. The end-mill tool wear is higher on machining the aluminum alloy-silicon carbide composites than on machining the plain aluminum alloy.

  17. A Rapid Compression Expansion Machine (RCEM) for studying chemical kinetics: Experimental principle and first applications

    CERN Document Server

    Werler, Marc; Maas, Ulrich

    2016-01-01

    A novel extension of a rapid compression machine (RCM), namely a Rapid Compression Expansion Machine (RCEM), is described and its use for studying chemical kinetics is demonstrated. Like conventional RCMs, the RCEM quickly compresses a fuel/air mixture by pushing a piston into a cylinder; the resulting high temperatures and pressures initiate chemical reactions. In addition, the machine can rapidly expand the compressed gas in a controlled way by pulling the piston outwards again. This freezes chemical activity after a pre-defined reaction duration, and therefore allows a convenient probe sampling and ex-situ gas analysis of stable species. The RCEM therefore is a promising instrument for studying chemical kinetics, including also partially reacted fuel/air mixtures. The setup of the RCEM, its experimental characteristics and its use for studying chemical reactions are outlined in detail. To allow comparisons of RCEM results with predictions of chemical reaction mechanisms, a simple numerical model of the RCE...

  18. Effectiveness of hamstring knee rehabilitation exercise performed in training machine vs. elastic resistance: electromyography evaluation study.

    Science.gov (United States)

    Jakobsen, Markus Due; Sundstrup, Emil; Andersen, Christoffer H; Persson, Roger; Zebis, Mette K; Andersen, Lars L

    2014-04-01

    The aim of this study was to evaluate muscle activity during hamstring rehabilitation exercises performed in training machine compared with elastic resistance. Six women and 13 men aged 28-67 yrs participated in a crossover study. Electromyographic (EMG) activity was recorded in the biceps femoris and the semitendinosus during the concentric and the eccentric phase of hamstring curls performed with TheraBand elastic tubing and Technogym training machines and normalized to maximal voluntary isometric contraction-EMG (normalized EMG). Knee joint angle was measured using electronic inclinometers. Training machines and elastic resistance showed similar high levels of muscle activity (biceps femoris and semitendinosus peak normalized EMG >80%). EMG during the concentric phase was higher than during the eccentric phase regardless of exercise and muscle. However, compared with machine exercise, slightly lower (P knee joint angle for the semitendinosus and the biceps femoris during the concentric and the eccentric phase, respectively. Perceived loading (Borg CR10) was significantly higher (P exercise performed with elastic resistance induces similar peak hamstring muscle activity but slightly lower EMG values at more extended knee angles and with higher perceived loading as hamstring curls using training machines.

  19. Students' perspectives on promoting healthful food choices from campus vending machines: a qualitative interview study.

    Science.gov (United States)

    Ali, Habiba I; Jarrar, Amjad H; Abo-El-Enen, Mostafa; Al Shamsi, Mariam; Al Ashqar, Huda

    2015-05-28

    Increasing the healthfulness of campus food environments is an important step in promoting healthful food choices among college students. This study explored university students' suggestions on promoting healthful food choices from campus vending machines. It also examined factors influencing students' food choices from vending machines. Peer-led semi-structured individual interviews were conducted with 43 undergraduate students (33 females and 10 males) recruited from students enrolled in an introductory nutrition course in a large national university in the United Arab Emirates. Interviews were audiotaped, transcribed, and coded to generate themes using N-Vivo software. Accessibility, peer influence, and busy schedules were the main factors influencing students' food choices from campus vending machines. Participants expressed the need to improve the nutritional quality of the food items sold in the campus vending machines. Recommendations for students' nutrition educational activities included placing nutrition tips on or beside the vending machines and using active learning methods, such as competitions on nutrition knowledge. The results of this study have useful applications in improving the campus food environment and nutrition education opportunities at the university to assist students in making healthful food choices.

  20. A Case Study of Employing A Single Server Nonpreemptive Priority Queuing Model at ATM Machine

    OpenAIRE

    Abdullah Furquan; Abdullah Imran

    2015-01-01

    This paper discusses a case study of employing a single server nonpreemptivepriorityqueuing model [1]at ATM machine which originally operates on M/M/1 model. In this study we have taken two priority classes of people in following order:- .Priority class 1- woman .Priority class 2- man Sometimea long queue is formed at ATMmachine (single server)but the bank management don’t have enough money to invest on installing new ATM machine.In this situation we want to apply single ser...

  1. Analysis and testing research on dynamic properties of machine tools based on joints parameters%基于结合面参数的整机动态特性分析与试验研究

    Institute of Scientific and Technical Information of China (English)

    郭成龙; 袁军堂; 李奎; 翁德凯; 陈展翼

    2012-01-01

    Since the joint surface properties of the machine tools influences the performance of the machine tools greatly,modal analysis of vertical milling machine tool AVCP1200H was carried out utilizing ANSYS based on the finite element models of rigid connection and flexible connection of the joints.Then the analyzing tests for two finite element models were verified to be identical through modal test to the machine.In addition the reasons of test error occurred were analyzed and optimization for the model was sug-gested, which provided a reference for studying dynamics of the machine tools as well as digital design and manufacturing.The test results show that: the modal analysis for flexible connection of the joints was in good agreement with the hammering test results with 3 order more errors being within 20%,which dynamic characteristic parameters were proven to impact the performance of the machine significantly.%机床结合面特性对其整体性能具有很大影响,利用ANSYS软件分别对立式数控铣床AVCP1200H结合面刚性联接、柔性联接的有限元模型进行模态分析,然后通过整机模态试验验证两种有限元模型的分析吻合,并对试验误差产生的原因进行分析,提出了优化模型的建议,为该型机床动力学研究及数字化设计制造提供了参考.试验结果表明:结合面柔性联接的模态分析与锤击试验结果较为吻合,3阶以上的误差均在20%以内,证明结合面处的动态特性参数对机床性能有很大影响.

  2. Study on Braiding Parameters of a Biodegradable Nerve Regeneration Conduit with Regular Braided Structure

    Institute of Scientific and Technical Information of China (English)

    LIU Guo-hua; ZHANG Pei-hua; WANG Wen-zu; FENG Xun-wei; LIU Hong-feng

    2004-01-01

    A biodegradable nerve regeneration conduit has been developed by the regular braided technique on a spindle-braiding machine. The geometry property indexes of braided nerve conduit consist of pitch, density, wall thickness and porosity etc. In this article, the influences of the braiding parameters i.e. the linear density of yarn, gear ratio and spindle number of the braiding machine on these geometry property indexes of nerve conduit were discussed from which the optimal braiding parameters were obtained.

  3. Does machine perfusion decrease ischemia reperfusion injury?

    Science.gov (United States)

    Bon, D; Delpech, P-O; Chatauret, N; Hauet, T; Badet, L; Barrou, B

    2014-06-01

    In 1990's, use of machine perfusion for organ preservation has been abandoned because of improvement of preservation solutions, efficient without perfusion, easy to use and cheaper. Since the last 15 years, a renewed interest for machine perfusion emerged based on studies performed on preclinical model and seems to make consensus in case of expanded criteria donors or deceased after cardiac death donations. We present relevant studies highlighted the efficiency of preservation with hypothermic machine perfusion compared to static cold storage. Machines for organ preservation being in constant evolution, we also summarized recent developments included direct oxygenation of the perfusat. Machine perfusion technology also enables organ reconditioning during the last hours of preservation through a short period of perfusion on hypothermia, subnormothermia or normothermia. We present significant or low advantages for machine perfusion against ischemia reperfusion injuries regarding at least one primary parameter: risk of DFG, organ function or graft survival. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

  4. 基于遗传算法的茶叶理条机参数优化设计%Optimization Design of Tea Carding Machine Parameters Based on Genetic Algorithms

    Institute of Scientific and Technical Information of China (English)

    王小勇; 李兵; 曾晨; 李尚庆

    2016-01-01

    To reduce noise and vibration in working process, improve transmission performance of the machine and tea processing quality, genetic algorithms and Matlab toolbox were used to establish an optimal mathematical model of the planetary gear mechanism of the tea carding machine. The objective function and constraints were firstly set, the optimal parameters were calculated by matlab genetic algorithm toolbox and then verified by validation tests. The optimization results showed that the minimum transmission angle , working stroke , Polar angle were 71.1°, 122 mm and 3.6°, respectively. When tea carding machine was performed under optimal parameters, the noise decreased by 2 dB and the stripping tea rate increased by 2%. The study has significant importance for improving performance of tea carding machine and extending machine life.%为了降低茶叶理条机在工作过程中的噪音与振动,提高机器的传动性能与茶叶的加工质量,运用遗传算法和 Matlab 工具箱,建立理条机传动机构的参数优化数学模型,编制目标函数与约束条件,然后通过Matlab 遗传算法工具箱对参数进行优化计算并进行验证试验。优化后各参数为:理条机最小传动角为71.1°,工作行程为122 mm;极位夹角为3.6°,在优化参数下,噪音减低2 dB,茶叶成条率提高了2%。该研究为提高茶叶理条机的工作性能与延长机器的使用寿命具有重要意义。

  5. End mill tools integration in CNC machining for rapid manufacturing processes: simulation studies

    Directory of Open Access Journals (Sweden)

    Muhammed Nafis Osman Zahid

    2015-01-01

    Full Text Available Computer numerical controlled (CNC machining has been recognized as a manufacturing process that is capable of producing metal parts with high precision and reliable quality, whereas many additive manufacturing methods are less capable in these respects. The introduction of a new layer-removal methodology that utilizes an indexing device to clamp the workpiece can be used to extend CNC applications into the realm of rapid manufacturing (CNC-RM processes. This study aims to improve the implementation of CNC machining for RM by formulating a distinct approach to integrate end mill tools during finishing processes. A main objective is to enhance process efficiency by minimizing the staircasing effect of layer removal so as to improve the quality of machined parts. In order to achieve this, different types of end mill tools are introduced to cater for specific part surfaces during finishing operations. Virtual machining simulations are executed to verify the method and the implications. The findings indicate the advantages of the approach in terms of cutting time and excess volume left on the parts. It is shown that using different tools for finishing operations will improve the capabilities of CNC machining for rapid manufacturing applications.

  6. Holographic study on the jet quenching parameter in anisotropic systems

    CERN Document Server

    Wang, Luying

    2016-01-01

    We first calculate the jet quenching parameter of an anisotropic plasma with a U(1) chemical potential via the AdS/CFT duality. The effects of charge, anisotropy parameter and quark motion direction on the jet quenching parameter are investigated. We then discuss the situation of anisotropic black brane in the IR region. We study both the jet quenching parameters along the longitudinal direction and transverse plane.

  7. Holographic study of the jet quenching parameter in anisotropic systems

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Luying [Shanghai University, Department of Physics, Shanghai (China); Wu, Shang-Yu [National Chiao Tung University, Department of Electrophysics, Hsinchu (China)

    2016-11-15

    We first calculate the jet quenching parameter of an anisotropic plasma with a U(1) chemical potential via AdS/CFT duality. The effects of charge, anisotropy parameter, and quark motion direction on the jet quenching parameter are investigated. We then discuss the situation of an anisotropic black brane in the IR region. We study both the jet quenching parameters along the longitudinal direction and the transverse plane. (orig.)

  8. The Study of an Improved Relevant Vector Machine MUD Based on Perfect Sampling

    Institute of Scientific and Technical Information of China (English)

    YANGTao; XIEJianying

    2004-01-01

    In this paper, we investigate the recently introduced new learning technique-rrelevant vector machine (RVM) to construct a Multi-user detection (MUD) scheme through perfect sampling~ which forms a new a posteriori parameter distribution estimation scheme based on Markov chain Monte Carlo (MCMC) algorithm. First set a prior on the parameter to be estimated, then have the parameter as a state variable. As the parameter in MUD is concerned, the number of w is prefixed, then make use of the given prior and perfect sampling to acquire a posteriori estimation ofw. Once Bit error rate (BER) representing a kernel function output increases, a timely updating of mean and variance of prior distribution is implemented to acquire the ‘needed sample'. Thus the evaluation of w forms an adaptive close loop process, which generates predictive distribution rather than makes point prediction, meanwhile the sparseness is acquired through a Jeffreys prior. Compared with other Bayesian detection scheme, this algorithm is especially efficient in solving high dimension and global optimization problems. Digital result shows that the detection performance is better than that of conventional Support vector machine (SVM) as well as Minimum mean square error (MMSE) scheme especially under massive user environment.

  9. Transmission Parameter Design for Special 5000 KN Friction Welding Machine%5000 KN专用摩擦焊机传动参数设计

    Institute of Scientific and Technical Information of China (English)

    尹海鹏; 辛舟; 孔永永

    2016-01-01

    Transmission parameter is an important part of the transmission system. The transmission parameter determines the size of the headstock, the quality of the machine, the manufacturing cost and the lubrication conditions. lt is especial y important to fix a rational transmission parameter in a complete set of transmission system. High power and high torque are characteristic of the special 5000KN friction welding machine transmission system. Based on the principle of high power gear transmission being equivalent to the minimum moment of inertia, the transmission series are determined, and with the help of the entropy weight theory, the al ocation of transmission ratio is theoretical y optimized.%传动参数是传动系统的重要组成部分,传动参数直接关系到主轴箱尺寸的大小、整机质量、制造成本、润滑条件等,传动参数的合理确定在一套完整的传动系统中显得尤为重要。5000KN专用摩擦焊机传动系统具有功率大、扭矩大的特点。基于大功率齿轮传动等效转动惯量最小原则确定其传动级数,并借助于熵权理论,在理论上优化配置该摩擦焊机的传动比。

  10. Short-Term Wind Speed Forecasting Using the Data Processing Approach and the Support Vector Machine Model Optimized by the Improved Cuckoo Search Parameter Estimation Algorithm

    Directory of Open Access Journals (Sweden)

    Chen Wang

    2016-01-01

    Full Text Available Power systems could be at risk when the power-grid collapse accident occurs. As a clean and renewable resource, wind energy plays an increasingly vital role in reducing air pollution and wind power generation becomes an important way to produce electrical power. Therefore, accurate wind power and wind speed forecasting are in need. In this research, a novel short-term wind speed forecasting portfolio has been proposed using the following three procedures: (I data preprocessing: apart from the regular normalization preprocessing, the data are preprocessed through empirical model decomposition (EMD, which reduces the effect of noise on the wind speed data; (II artificially intelligent parameter optimization introduction: the unknown parameters in the support vector machine (SVM model are optimized by the cuckoo search (CS algorithm; (III parameter optimization approach modification: an improved parameter optimization approach, called the SDCS model, based on the CS algorithm and the steepest descent (SD method is proposed. The comparison results show that the simple and effective portfolio EMD-SDCS-SVM produces promising predictions and has better performance than the individual forecasting components, with very small root mean squared errors and mean absolute percentage errors.

  11. Study of the Induction Machine Unsymmetrical Condition Using In Total Fluxes Equations

    Directory of Open Access Journals (Sweden)

    SIMION, A.

    2010-02-01

    Full Text Available On the basis of the mathematical model, called in total fluxes in a previous paper, and which is proper for the analysis of transient operation of the two-phase induction machine, one obtains the symmetrical steady-state equations, which are valid for three-phase machines, as well. The obtained mathematical expressions are much more simple and easier to use than the consecrated ones, which are generally applied in scientific literature. Moreover, considerations are to be made upon the space-time rotational vectors, emphasizing their importance in understanding the physical phenomena that characterize induction machines. The use of these space vectors is further tested out for the study of unsymmetrical supply, which gives a much faster method in obtaining the electromagnetic torque expression. Finally, the results are compared with the ones that come out from the traditional methods, more exactly, the symmetric component method.

  12. The Dynamic Study of the Weft Insertion of Air Jet Weaving Machines

    Directory of Open Access Journals (Sweden)

    Gabriella Oroszlány

    2010-10-01

    Full Text Available The application of the air jet loom is widespread in the textile industry because ofits high productivity, convenient controllability, high filling insertion rate, low noise andlow vibration levels. Air stream in confusor guides can be classified into two types. A weftyarn ejected with high speed air flow is given the drag force caused by friction between theweft yarn and the air flow. In this article we show the study of the dynamics of the type Pair jet weaving machines and the definition of the skin friction coefficient for multifilamentweft. We have given a calculation procedure for the dynamic description of the insertionprocess of weaving machines marked P.

  13. Comparative aspects about the studying methods of cast irons machinability, based on the tool wear

    Science.gov (United States)

    Carausu, C.; Pruteanu, O.

    2016-08-01

    The paper presents some considerations of the authors, regarding the studying methods of the cast irons machinability, based on the tools wear on drilling operations. Are described the conditions in which the experimental researches were conducted, intended to offer an overview on drilling machinability of some cast irons categories. It is presented a comparison between long-term methods and short-term methods, for determining the optimal speed chipping of a grey cast iron with lamellar graphite, with average values of tensile strength. Are described: the research methodology, obtained results and conclusions drawn after the results analysis.

  14. Machine Learning Approaches for High-resolution Urban Land Cover Classification: A Comparative Study

    Energy Technology Data Exchange (ETDEWEB)

    Vatsavai, Raju [ORNL; Chandola, Varun [ORNL; Cheriyadat, Anil M [ORNL; Bright, Eddie A [ORNL; Bhaduri, Budhendra L [ORNL; Graesser, Jordan B [ORNL

    2011-01-01

    The proliferation of several machine learning approaches makes it difficult to identify a suitable classification technique for analyzing high-resolution remote sensing images. In this study, ten classification techniques were compared from five broad machine learning categories. Surprisingly, the performance of simple statistical classification schemes like maximum likelihood and Logistic regression over complex and recent techniques is very close. Given that these two classifiers require little input from the user, they should still be considered for most classification tasks. Multiple classifier systems is a good choice if the resources permit.

  15. A comparison study of two Tricept units for reconfigurable parallel kinematic machines

    Institute of Scientific and Technical Information of China (English)

    Shi Junshan; Tang Xiaoqiang; Lin Chunshen; Wang Liping

    2005-01-01

    This paper presents a comparison study of workspace and dexterity of two Tricept units for Reconfigurable Parallel Kinematic Machines (RPKMs). The modular leg of RPKMs is designed and the RPKMs can be built by changing the setting of modules. A compositive kinematic model is developed accordingly. The inverse kinematics and Jacobian of these two Tricept units are analyzed. Considering workspace volume and dexterity, the effects of geometric size of some modules on the two Tricept units are discussed. In the end, comparison results of these two Tricept units are given. The comparison of two kinds of Parallel Kinematic Machines (PKMs) can be of help in the design and configuration planning of the RPKMs.

  16. Investigation on influence parameters in measurements of the optomechanical hole plate using an optical coordinate measuring machine

    DEFF Research Database (Denmark)

    Morace, Renate Erica; Hansen, Hans Nørgaard; De Chiffre, Leonardo

    2003-01-01

    This paper describes the results of an experimental investigation on influence parameters in optical coordinate measurements of the optomechanical hole plate. Special attention was paid to the background of the object, which strongly influences the measurement result. Furthermore, it is seen that...

  17. Investigation on influence parameters in measurements of the optomechanical hole plate using an optical coordinate measuring machine

    DEFF Research Database (Denmark)

    Morace, Renate Erica; Hansen, Hans Nørgaard; De Chiffre, Leonardo;

    2003-01-01

    This paper describes the results of an experimental investigation on influence parameters in optical coordinate measurements of the optomechanical hole plate. Special attention was paid to the background of the object, which strongly influences the measurement result. Furthermore, it is seen...

  18. Researches regarding the reducing of burr size by optimising the cutting parameters on a CNC milling machine

    Directory of Open Access Journals (Sweden)

    Biriş Cristina

    2017-01-01

    Full Text Available This paper presents some experimental researches regarding burrs dimensions reduction that appear after the milling process together with an approach to reduce or eliminate the burrs resulted after this process. In order to reduce burrs dimensions, the milling process was executed with different cutting parameters and strategies then the results were evaluated.

  19. A comparative study of surface EMG classification by fuzzy relevance vector machine and fuzzy support vector machine.

    Science.gov (United States)

    Xie, Hong-Bo; Huang, Hu; Wu, Jianhua; Liu, Lei

    2015-02-01

    We present a multiclass fuzzy relevance vector machine (FRVM) learning mechanism and evaluate its performance to classify multiple hand motions using surface electromyographic (sEMG) signals. The relevance vector machine (RVM) is a sparse Bayesian kernel method which avoids some limitations of the support vector machine (SVM). However, RVM still suffers the difficulty of possible unclassifiable regions in multiclass problems. We propose two fuzzy membership function-based FRVM algorithms to solve such problems, based on experiments conducted on seven healthy subjects and two amputees with six hand motions. Two feature sets, namely, AR model coefficients and room mean square value (AR-RMS), and wavelet transform (WT) features, are extracted from the recorded sEMG signals. Fuzzy support vector machine (FSVM) analysis was also conducted for wide comparison in terms of accuracy, sparsity, training and testing time, as well as the effect of training sample sizes. FRVM yielded comparable classification accuracy with dramatically fewer support vectors in comparison with FSVM. Furthermore, the processing delay of FRVM was much less than that of FSVM, whilst training time of FSVM much faster than FRVM. The results indicate that FRVM classifier trained using sufficient samples can achieve comparable generalization capability as FSVM with significant sparsity in multi-channel sEMG classification, which is more suitable for sEMG-based real-time control applications.

  20. Study of Material Densification of In718 in the Higher Throughput Parameter Regime

    Science.gov (United States)

    Cordner, Samuel

    2016-01-01

    Selective Laser Melting (SLM) is a powder bed fusion additive manufacturing process used increasingly in the aerospace industry to reduce the cost, weight, and fabrication time for complex propulsion components. Previous optimization studies for SLM using the Concept Laser M1 and M2 machines at NASA Marshall Space Flight Center have centered on machine default parameters. The objective of this project is to characterize how heat treatment affects density and porosity from a microscopic point of view. This is performs using higher throughput parameters (a previously unexplored region of the manufacturing operating envelope for this application) on material consolidation. Density blocks were analyzed to explore the relationship between build parameters (laser power, scan speed, and hatch spacing) and material consolidation (assessed in terms of density and porosity). The study also considers the impact of post-processing, specifically hot isostatic pressing and heat treatment, as well as deposition pattern on material consolidation in the higher energy parameter regime. Metallurgical evaluation of specimens will also be presented. This work will contribute to creating a knowledge base (understanding material behavior in all ranges of the AM equipment operating envelope) that is critical to transitioning AM from the custom low rate production sphere it currently occupies to the world of mass high rate production, where parts are fabricated at a rapid rate with confidence that they will meet or exceed all stringent functional requirements for spaceflight hardware. These studies will also provide important data on the sensitivity of material consolidation to process parameters that will inform the design and development of future flight articles using SLM.

  1. Design of Demining Machines

    CERN Document Server

    Mikulic, Dinko

    2013-01-01

    In constant effort to eliminate mine danger, international mine action community has been developing safety, efficiency and cost-effectiveness of clearance methods. Demining machines have become necessary when conducting humanitarian demining where the mechanization of demining provides greater safety and productivity. Design of Demining Machines describes the development and testing of modern demining machines in humanitarian demining.   Relevant data for design of demining machines are included to explain the machinery implemented and some innovative and inspiring development solutions. Development technologies, companies and projects are discussed to provide a comprehensive estimate of the effects of various design factors and to proper selection of optimal parameters for designing the demining machines.   Covering the dynamic processes occurring in machine assemblies and their components to a broader understanding of demining machine as a whole, Design of Demining Machines is primarily tailored as a tex...

  2. Metal matrix composites synthesis, wear characteristics, machinability study of MMC brake drum

    CERN Document Server

    Natarajan, Nanjappan; Davim, J Paulo

    2015-01-01

    This book is dedicated to composite materials, presenting different synthesis processes, composite properties and their machining behaviour. The book describes also the problems on manufacturing of metal matrix composite components. Among others, it provides procedures for manufacturing of metal matrix composites and case studies.

  3. Individualized prediction of illness course at the first psychotic episode: a support vector machine MRI study.

    LENUS (Irish Health Repository)

    Mourao-Miranda, J

    2012-05-01

    To date, magnetic resonance imaging (MRI) has made little impact on the diagnosis and monitoring of psychoses in individual patients. In this study, we used a support vector machine (SVM) whole-brain classification approach to predict future illness course at the individual level from MRI data obtained at the first psychotic episode.

  4. Machine-induced Background Simulation Studies for LHC Run 1, Run 2 and HL-LHC

    CERN Document Server

    Kwee-Hinzmann, Regina; Bruce, Roderik; Cerutti, Francesco; Esposito, Luigi Salvatore; Gibson, Stephen; Lechner, Anton; Garcia Morales, Hector; Yin Vallgren, Christina

    2017-01-01

    The study of machine-induced background to the experiments is vital for several reasons. Too much background can be an issue for operation and the difficult part is to judge when exactly “too much” is attained. It is a complex topic as experiments are directly or indirectly affected by conditions all around the LHC ring e.g. collimation settings and vacuum quality. A detailed study of background can also help understanding the machine better to identify potential issues and complemented by dedicated machine tests. Finally such a study is relevant for the experiments to analyse the characteristics of machine background to make sure not to count it into a new physics signal. This report summarises simulation results of three background sources, local beam-gas, beam-halo from the betatron collimation in IR7 and for the first time beam-halo from momentum collimation in IR3. Two of the most dominant sources, local beam-gas and betatron halo, have been systematically studied for LHC Run 1 and Run 2 cases, and ...

  5. Polishing tool and the resulting TIF for three variable machine parameters as input for the removal simulation

    Science.gov (United States)

    Schneider, Robert; Haberl, Alexander; Rascher, Rolf

    2017-06-01

    The trend in the optic industry shows, that it is increasingly important to be able to manufacture complex lens geometries on a high level of precision. From a certain limit on the required shape accuracy of optical workpieces, the processing is changed from the two-dimensional to point-shaped processing. It is very important that the process is as stable as possible during the in point-shaped processing. To ensure stability, usually only one process parameter is varied during processing. It is common that this parameter is the feed rate, which corresponds to the dwell time. In the research project ArenA-FOi (Application-oriented analysis of resource-saving and energy-efficient design of industrial facilities for the optical industry), a touching procedure is used in the point-attack, and in this case a close look is made as to whether a change of several process parameters is meaningful during a processing. The ADAPT tool in size R20 from Satisloh AG is used, which is also available for purchase. The behavior of the tool is tested under constant conditions in the MCP 250 CNC by OptoTech GmbH. A series of experiments should enable the TIF (tool influence function) to be determined using three variable parameters. Furthermore, the maximum error frequency that can be processed is calculated as an example for one parameter set and serves as an outlook for further investigations. The test results serve as the basic for the later removal simulation, which must be able to deal with a variable TIF. This topic has already been successfully implemented in another research project of the Institute for Precision Manufacturing and High-Frequency Technology (IPH) and thus this algorithm can be used. The next step is the useful implementation of the collected knowledge. The TIF must be selected on the basis of the measured data. It is important to know the error frequencies to select the optimal TIF. Thus, it is possible to compare the simulated results with real measurement

  6. Optimization the machining parameters by using VIKOR and Entropy Weight method during EDM process of Al–18% SiCp Metal matrix composit

    Directory of Open Access Journals (Sweden)

    Rajesh Kumar Bhuyan

    2016-06-01

    Full Text Available The objective of this paper is to optimize the process parameters by combined approach of VIKOR and Entropy weight measurement method during Electrical discharge machining (EDM process of Al-18wt.%SiCp metal matrix composite (MMC. The central composite design (CCD method is considered to evaluate the effect of three process parameters; namely pulse on time (Ton, peak current (Ip and flushing pressure (Fp on the responses like material removal rate (MRR, tool wear rate (TWR, Radial over cut (ROC and surface roughness (Ra. The Entropy weight measurement method evaluates the individual weights of each response and, using VIKOR method, the multi-objective responses are optimized to get a single numerical index known as VIKOR Index. Then the Analysis of Variance (ANOVA technique is used to determine the significance of the process parameters on the VIKOR Index. Finally, the result of the VIKOR Indexed is validated by conformation test using the liner mathematical model equation develop by responses surface methodology to identify the effectiveness of the proposed method.

  7. Asynchronized synchronous machines

    CERN Document Server

    Botvinnik, M M

    1964-01-01

    Asynchronized Synchronous Machines focuses on the theoretical research on asynchronized synchronous (AS) machines, which are "hybrids” of synchronous and induction machines that can operate with slip. Topics covered in this book include the initial equations; vector diagram of an AS machine; regulation in cases of deviation from the law of full compensation; parameters of the excitation system; and schematic diagram of an excitation regulator. The possible applications of AS machines and its calculations in certain cases are also discussed. This publication is beneficial for students and indiv

  8. A Comparative Study of Distribution System Parameter Estimation Methods

    Energy Technology Data Exchange (ETDEWEB)

    Sun, Yannan; Williams, Tess L.; Gourisetti, Sri Nikhil Gup

    2016-07-17

    In this paper, we compare two parameter estimation methods for distribution systems: residual sensitivity analysis and state-vector augmentation with a Kalman filter. These two methods were originally proposed for transmission systems, and are still the most commonly used methods for parameter estimation. Distribution systems have much lower measurement redundancy than transmission systems. Therefore, estimating parameters is much more difficult. To increase the robustness of parameter estimation, the two methods are applied with combined measurement snapshots (measurement sets taken at different points in time), so that the redundancy for computing the parameter values is increased. The advantages and disadvantages of both methods are discussed. The results of this paper show that state-vector augmentation is a better approach for parameter estimation in distribution systems. Simulation studies are done on a modified version of IEEE 13-Node Test Feeder with varying levels of measurement noise and non-zero error in the other system model parameters.

  9. A Comparison Study of Machine Learning Based Algorithms for Fatigue Crack Growth Calculation.

    Science.gov (United States)

    Wang, Hongxun; Zhang, Weifang; Sun, Fuqiang; Zhang, Wei

    2017-05-18

    The relationships between the fatigue crack growth rate ( d a / d N ) and stress intensity factor range ( Δ K ) are not always linear even in the Paris region. The stress ratio effects on fatigue crack growth rate are diverse in different materials. However, most existing fatigue crack growth models cannot handle these nonlinearities appropriately. The machine learning method provides a flexible approach to the modeling of fatigue crack growth because of its excellent nonlinear approximation and multivariable learning ability. In this paper, a fatigue crack growth calculation method is proposed based on three different machine learning algorithms (MLAs): extreme learning machine (ELM), radial basis function network (RBFN) and genetic algorithms optimized back propagation network (GABP). The MLA based method is validated using testing data of different materials. The three MLAs are compared with each other as well as the classical two-parameter model ( K * approach). The results show that the predictions of MLAs are superior to those of K * approach in accuracy and effectiveness, and the ELM based algorithms show overall the best agreement with the experimental data out of the three MLAs, for its global optimization and extrapolation ability.

  10. Pavement Subgrade Performance Study in the Danish Road Testing Machine

    DEFF Research Database (Denmark)

    Ullidtz, Per; Ertman Larsen, Hans Jørgen

    1997-01-01

    Most existing pavement subgrade criteria are based on the AASHO Road Test, where only one material was tested and for only one climatic condition. To study the validity of these criteria and to refine the criteria a co-operative research program entitled the "International Pavement Subgrade Perfo...

  11. A Study of Synchronous Machine Model Implementations in Matlab/Simulink Simulations for New and Renewable Energy Systems

    DEFF Research Database (Denmark)

    Chen, Zhe; Blaabjerg, Frede; Iov, Florin

    2005-01-01

    A direct phase model of synchronous machines implemented in MA TLAB/SIMULINK is presented. The effects of the machine saturation have been included. Simulation studies are performed under various conditions. It has been demonstrated that the MATLAB/SIMULINK is an effective tool to study the complex...

  12. A Study of Synchronous Machine Model Implementations in Matlab/Simulink Simulations for New and Renewable Energy Systems

    DEFF Research Database (Denmark)

    Chen, Zhe; Blaabjerg, Frede; Iov, Florin

    2005-01-01

    A direct phase model of synchronous machines implemented in MA TLAB/SIMULINK is presented. The effects of the machine saturation have been included. Simulation studies are performed under various conditions. It has been demonstrated that the MATLAB/SIMULINK is an effective tool to study the complex...

  13. A study conducted on the impact of effluent waste from machining process on the environment by water analysis

    Energy Technology Data Exchange (ETDEWEB)

    Kovoor, Punnose P.; Idris, Mohd Razif [Kuala Lumpur Univ. (Malaysia). Inst. of Product Design and Manufacturing, IPROM; Hassan, Masjuki Haji [Univ. of Malaya, Kuala Lumpur (Malaysia). Dept. of Mechanical Engineering; Tengku Yahya, Tengku Fazli [Kuala Lumpur Univ., Melaka (Malaysia). Malaysian Inst. of Chemical and Bio Engineering Technology, MICET

    2012-11-01

    Ferrous block metals are used frequently in large quantities in various sectors of industry for making automotive, furniture, electrical and mechanical items, body parts for consumables, and so forth. During the manufacturing stage, the block metals are subjected to some form of material removal process either through turning, grinding, milling, or drilling operations to obtain the final product. Wastes are generated from the machining process in the form of effluent waste, solid waste, atmospheric emission, and energy emission. These wastes, if not recycled or treated properly before disposal, will have a detrimental impact on the environment through air, water, and soil pollution. The purpose of this paper is to determine the impact of the effluent waste from the machining process on the environment through water analysis. A twofold study is carried out to determine the impact of the effluent waste on the water stream. The preliminary study consists of a scenario analysis where five scenarios are drawn out using substances such as spent coolant, tramp oil, solvent, powdered chips, and sludge, which are commonly found in the effluent waste. The wastes are prepared according to the scenarios and are disposed through the Institute of Product Design and Manufacturing (IPROM) storm water drain. Samples of effluent waste are collected at specific locations according to the APHA method and are tested for parameters such as pH, ammoniacal nitrogen, dissolved oxygen, biochemical oxygen demand, chemical oxygen demand, and total suspended solids. A subsequent study is done by collecting 30 samples of the effluent waste from the machining operations from two small- and medium-scale enterprise locations and the IPROM workshop to test the quality of water. The results obtained from the tests showed high values of chemical oxygen demand, ammoniacal nitrogen, and total suspended solids when compared with the Standard B specification for inland water bodies as specified by the

  14. Dynamic Analysis of Foundation Supporting Rotary Machine

    Directory of Open Access Journals (Sweden)

    Utkarsh S. Patel

    2015-08-01

    Full Text Available With the advancement of technology in the field of industry, high speed machinery has been developed. As the speed of machinery has increased, vibrations also increased. Machines transmit vibrations to the structure supporting them. Hence, it is important to design and develop such structure which sustains the vibrations of machinery. Hence, in this study it has been aimed to execute the study on foundations supporting rotary type of machine like blower. In this paper, the most important parameters like frequency and amplitude are considered while execution of analysis of machine foundation supporting blower type machine. This paper shows, better interface between foundation designer and machine manufacturer for better performance of machine. The design aids/approaches for foundation design is also described in this paper and an attempt has been made to study the dynamic behaviour of a foundation structure for blower type machine subjected to forces due to operation of blower machine. Two different types of foundations for Rotary type Machine that is Blower have been studied in this paper

  15. Setup Time Reduction On Solder Paste Printing Machine – A Case Study

    Directory of Open Access Journals (Sweden)

    Rajesh Dhake

    2013-06-01

    Full Text Available Lean manufacturing envisages the reduction of the seven deadly wastes referred to as MUDA. Setup time forms a major component of the equipment downtime. It leads to lower machine utilization and restricts the output and product variety. This necessitates the requirement for quick setups. Single Minute Exchange of Die philosophy (a lean manufacturing tool here after referred as “SMED” is one of the important tool which aims at quick setups driving smaller lot sizes, lower production costs, improve productivity in terms of increased output, increased utilization of machine and labor hours, make additional capacity available (often at bottleneck resources, reduce scrap and rework, and increase flexibility[3]. This paper focuses on the application of Single Minute Exchange of Die[1] and Quick Changeover Philosophy[2] for reducing setup time on Solder Past Printing Machine (bottleneck machine in a electronic speedo-cluster manufacturing company. The four step SMED philosophy was adopted to effect reduction in setup time. The initial step was gathering information about the present setup times and its proportion to the total productive time. A detailed video based time study of setup activities was done to classify them into external and internal setup activities in terms of their need (i.e. preparation, replacement or adjustment, time taken and the way these could be reduced, simplified or eliminated. The improvements effected were of three categories viz., mechanical, procedural and organizational. The paper concludes by comparing the present and proposed (implemented methods of setup procedures.

  16. Impact of corpus domain for sentiment classification: An evaluation study using supervised machine learning techniques

    Science.gov (United States)

    Karsi, Redouane; Zaim, Mounia; El Alami, Jamila

    2017-07-01

    Thanks to the development of the internet, a large community now has the possibility to communicate and express its opinions and preferences through multiple media such as blogs, forums, social networks and e-commerce sites. Today, it becomes clearer that opinions published on the web are a very valuable source for decision-making, so a rapidly growing field of research called “sentiment analysis” is born to address the problem of automatically determining the polarity (Positive, negative, neutral,…) of textual opinions. People expressing themselves in a particular domain often use specific domain language expressions, thus, building a classifier, which performs well in different domains is a challenging problem. The purpose of this paper is to evaluate the impact of domain for sentiment classification when using machine learning techniques. In our study three popular machine learning techniques: Support Vector Machines (SVM), Naive Bayes and K nearest neighbors(KNN) were applied on datasets collected from different domains. Experimental results show that Support Vector Machines outperforms other classifiers in all domains, since it achieved at least 74.75% accuracy with a standard deviation of 4,08.

  17. Experimental study on bearing preload optimum of machine tool spindle

    Science.gov (United States)

    Xu, Tao; Xu, Guanghua; Zhang, Qin; Hua, Cheng; Zhang, Hu; Jiang, Kuosheng

    2012-05-01

    An experimental study is conducted to investigate the possibility and the effect of temperature rise and vibration level of bearing by adjusting axial preloads and radial loads in spindle bearing test rig. The shaft of the test rig is driven by a motorized high speed spindle at the range of 0~20000 rpm. The axial preloads and radial loads on bearings are controlled by using hydraulic pressure which can be adjusted automatically. Temperature rise and radial vibration of test bearings are measured by thermocouples and Polytec portable laser vibrometer PDV100. Experiment shows that the temperature rise of bearings is nonlinear varying with the increase of radial loads, but temperature rise almost increases linearly with the increase of axial preload and rotating speed. In this paper, an alternate axial preload is used for bearings. When the rotating speed passes through the critical speed of the shaft, axial preload of bearings will have a remarkable effect. The low preload could reduce bearing vibration and temperature rise for bearings as well. At the others speed, the high preload could improve the vibration performance of high speed spindle and the bearing temperature was lower than that of the constant pressure preload spindle.

  18. Man or machine? An experimental study of prehospital emergency amputation.

    Science.gov (United States)

    Leech, Caroline; Porter, Keith

    2016-09-01

    Prehospital emergency amputation is a rare procedure, which may be necessary to free a time-critical patient from entrapment. This study aimed to evaluate four techniques of cadaveric lower limb prehospital emergency amputation. A guillotine amputation of the distal femur was undertaken in fresh frozen self-donated cadavers. A prehospital doctor conducted a surgical amputation with Gigli saw or hacksaw for bone cuts and firefighters carried out the procedure using the reciprocating saw and Holmatro device. The primary outcome measures were time to full amputation and the number of attempts required. The secondary outcomes were observed quality of skin cut, soft tissue cut and CT assessment of the proximal bone. Observers also noted the potential risks to the rescuer or patient during the procedure. All techniques completed amputation within 91 s. The reciprocating saw was the quickest technique (22 s) but there was significant blood spattering and continuation of the cut to the surface under the leg. The Holmatro device took less than a minute. The quality of the proximal femur was acceptable with all methods, but 5 cm more proximal soft tissue damage was made by the Holmatro device. Emergency prehospital guillotine amputation of the distal femur can effectively be performed using scalpel and paramedic shears with bone cuts by the Gigli saw or fire service hacksaw. The reciprocating saw could be used to cut bone if no other equipment was available but carried some risks. The Holmatro cutting device is a viable option for a life-threatening entrapment where only firefighters can safely access the patient, but would not be a recommended primary technique for medical staff. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

  19. 新型果园除草机的参数分析与设计%Parameter Analysis and Design of New Orchard Weeding Machine

    Institute of Scientific and Technical Information of China (English)

    卢彦群; 孔江生; 卢玉坤; 张哲

    2017-01-01

    advantages are flexi-ble , good weeding effect , good adaptability to more gravel orchard etc .While because the working parts of high speed ro-tation will inevitably collide with rocks in the grass , the dynamic stress may be too great so that split the cutting tools . This paper theoretically analyzed the dynamic stress of cutting head after impact with the stones and designed the structure parameters .In the field test , the machine can weed about 2 Mu of weeds per hour , weeding effect is good , the machine has a relatively long life [ 1-2 ] .

  20. Machinability evaluation of machinable ceramics with fuzzy theory

    Institute of Scientific and Technical Information of China (English)

    YU Ai-bing; ZHONG Li-jun; TAN Ye-fa

    2005-01-01

    The property parameters and machining output parameters were selected for machinability evaluation of machinable ceramics. Based on fuzzy evaluation theory, two-stage fuzzy evaluation approach was applied to consider these parameters. Two-stage fuzzy comprehensive evaluation model was proposed to evaluate machinability of machinable ceramic materials. Ce-ZrO2/CePO4 composites were fabricated and machined for evaluation of machinable ceramics. Material removal rates and specific normal grinding forces were measured. The parameters concerned with machinability were selected as alternative set. Five grades were chosen for the machinability evaluation of machnable ceramics. Machinability grades of machinable ceramics were determined through fuzzy operation. Ductile marks are observed on Ce-ZrO2/CePO4 machined surface. Five prepared Ce-ZrO2/CePO4 composites are classified as three machinability grades according to the fuzzy comprehensive evaluation results. The machinability grades of Ce-ZrO2/CePO4 composites are concerned with CePO4 content.

  1. An Active Instance-based Machine Learning method for Stellar Population Studies

    CERN Document Server

    Solorio, T; Terlevich, R J; Terlevich, E; Solorio, Thamar; Fuentes, Olac; Terlevich, Roberto; Terlevich, Elena

    2005-01-01

    We have developed a method for fast and accurate stellar population parameters determination in order to apply it to high resolution galaxy spectra. The method is based on an optimization technique that combines active learning with an instance-based machine learning algorithm. We tested the method with the retrieval of the star-formation history and dust content in "synthetic" galaxies with a wide range of S/N ratios. The "synthetic" galaxies where constructed using two different grids of high resolution theoretical population synthesis models. The results of our controlled experiment shows that our method can estimate with good speed and accuracy the parameters of the stellar populations that make up the galaxy even for very low S/N input. For a spectrum with S/N=5 the typical average deviation between the input and fitted spectrum is less than 10**{-5}. Additional improvements are achieved using prior knowledge.

  2. A Study on Effect of Graphite Particles on Tensile, Hardness and Machinability of Aluminium 8011 Matrix Material

    Science.gov (United States)

    Latha Shankar, B.; Anil, K. C.; Karabasappagol, Prasann J.

    2016-09-01

    Industrial application point of view, metal matrix composites in general and Aluminium alloy matrix composites in particular are ideal candidates because of their favourable engineering properties. Being lightweight Aluminium matrix composites are widely used in aircraft, defence and automotive industries. In this work Aluminium 8011 metal matrix was reinforced with fine Graphite particles of 50 μm. developed by two-step Stir casting method. Graphite weight %was varied in the range 2, 4, 6 and 8%. Uniform dispersion of graphite particle is examined under optical microscope. Tensile test coupons were prepared as per standard to determine % of elongation and tensile strength for various % of graphite particle. Hardness of developed composite for various % of graphite particle and Machinability parameters were also studied for effect on surface finish. It was observed that with increase of weight percentage of Graphite particles up to 8% in Aluminium 8011 alloy matrix there was increase in tensile strength, decrease in % of elongation with increase in hardness. Machinability study revealed that, there was decrease in surface roughness with increase in Graphite content.

  3. Application of RBF Neural Network in Optimizing Machining Parameters%径向基函数网络在优化机械加工参数中的应用

    Institute of Scientific and Technical Information of China (English)

    朱喜林; 吴博达; 武星星

    2004-01-01

    In machining processes, errors of rough in dimension, shape and location lead to changes in processing quantity, and the material of a workpiece may not be uniform. For these reasons, cutting force changes in machining, making the machining system deformable. Consequently errors in workpieces may occur. This is called the error reflection phenomenon. Generally, such errors can be reduced through repeated processing while using appropriate processing quantity in each processing based on operator's experience.According to the theory of error reflection, the error reflection coefficient indicates the extent to which errors of rough influence errors of workpieces. It is related to several factors such as machining condition, hardness of the workpiece, etc. This non-linear relation cannot be worked out using any formula. RBF neural network can approximate a non-linear function within any precision and be trained fast. In this paper, non-linear mapping ability of a fuzzy-neural network is utilized to approximate the non-linear relation. After training of the network with swatch collection obtained in experiments, an appropriate output can be obtained when an input is given. In this way, one can get the required number of processing and the processing quantity each time from the machining condition. Angular rigidity of a machining system,hardness of workpiece, etc., can be input in a form of fuzzy values. Feasibility in solving error reflection and optimizing machining parameters with a RBF neural network is verified by a simulation test with MATLAB.

  4. Studying and Modeling the Effect of Graphite Powder Mixing Electrical Discharge Machining on the Main Process Characteristics

    Directory of Open Access Journals (Sweden)

    Ahmed N. Al-Khazraji

    2015-09-01

    Full Text Available This paper concerned with study the effect of a graphite micro powder mixed in the kerosene dielectric fluid during powder mixing electric discharge machining (PMEDM of high carbon high chromium AISI D2 steel. The type of electrode (copper and graphite, the pulse current and the pulse-on time and mixing powder in kerosene dielectric fluid are taken as the process main input parameters. The material removal rate MRR, the tool wear ratio TWR and the work piece surface roughness (SR are taken as output parameters to measure the process performance. The experiments are planned using response surface methodology (RSM design procedure. Empirical models are developed for MRR, TWR and SR, using the analysis of variance (ANOVA.The best results for the productivity of the process (MRR obtained when using the graphite electrodes, the pulse current (22 A, the pulse on duration (120 µs and using the graphite powder mixing in kerosene dielectric reaches (82.84mm³/min. The result gives an improvement in material removal rate of (274% with respect to the corresponding value obtained when copper electrodes with kerosene dielectric alone. The best results for the tool wear ratio (TWR of the process obtained when using the copper electrodes, the pulse current (8 A, the pulse on duration (120 µs and using the kerosene dielectric alone reaches (0.31 %. The use of graphite electrodes, the kerosene dielectric with 5g/l graphite powder mixing, the pulse current (8 A, the pulse on duration (40 µs give the best surface roughness of a value (2.77 µm.This result yields an improvement in SR by (141% with respect to the corresponding value obtained when using copper electrodes and the kerosene dielectric alone with the same other parameters and machining conditions.

  5. 新型捻线机多参数控制系统研究%Multi-Parameter Controlling System for Latest-Twisting-Machines

    Institute of Scientific and Technical Information of China (English)

    张智明; 徐巧; 梅顺齐

    2011-01-01

    为了保证纱线加捻过程中卷取成型良好和张力恒定,针对传统捻线机机械传动系统复杂特点,提出新型捻线机多电机控制系统,建立纱线运动数学模型.在PLC的控制协调下,该系统采用一个异步电动机实现锭子加捻运动、一个异步电动机实现卷取运动、两个伺服电动机实现导纱运动,这些运动控制由RS-485通讯实现.捻线机的主要参数如捻度、捻向、卷取角、锭速等参数通过触摸屏实时显示和监测.实践证明多电动机系统简化了机器机构,而且控制系统简单可靠、纱线卷取成型良好.%In order to get constant tension and good shaping rove during twisting,the paper put forward a controlling system of latest-twisting-machines based on multi-motor and set up the mathematical model of yam movement in accordance with the traditional twister machine features of complex mechanical driving system.The moving of twisting and winding was realized through adopting RS-485 communication technology and servo motors were driven to-and-fro guiding-yarn moving under the PLC's controlling.The main parameters,such as the twist,direction,twisting angle,velocity of the spindle can be real-time showed and supervised on the touching screen.The results show that not only does the multi-motor system simplify the twisting machine,but also this controlling system is dependable and the yam is well shaped.

  6. EXPERIMENTAL IMPACT ASSESSMENT OF PARAMETERS PERTAINING TO BLANK TWO-DIMENSIONAL CIRCULAR MOTION ON INTENSITY OF ITS CUTTING AND QUALITY OF MACHINED SURFACE

    Directory of Open Access Journals (Sweden)

    M. G. Kiselev

    2014-01-01

    Full Text Available The purpose of the paper is to make an experimental impact assessment of parameters pertaining to blank two-dimensional circular blank motion on intensity of its cutting and quality of the machined surfaces. Experimental data have been obtained that reveal efficiency in application of blank circular motion and improvement of its output cutting indices.A methodology has been developed for execution of comparative experimental investigations on cutting glass, nephrite and jasper specimens as under conventional conditions required for the operation so while transferring induced oscillations to boom suspension assembly that ensure specimen.The proposed methodology makes it possible to assess quantitatively intensity of specimen cutting and quality of its machined surface. The paper has shown that a positive impact of the specimen circular motion on quality improvement of its cross-cut surface is related to peculiar kinematics features pertaining to relative motion of disc side surface with cross-cut portions of the specimen surface. It has been shown that the intensifying impact of the specimen circular motion on the cutting process is primarily related to the changes in dynamic conditions of its interaction with the cutting edge of the disc. In contrast to conventional cutting when the process is going on under static pressure of contacting surfaces there is their periodical impact-frictional interaction due to transfer of circular motion to the specimen along elliptical trajectory. In this case the rate of the positive impact of the specimen circular motion on its cross-cut surface becomes higher while increasing vertical velocity component that concerns its sliding relative to disc side surface that is ensured by increasing oscillation frequency which is transferred to the boom suspension assembly. Moreover, the rate of positive impact of the specimen circulatory motion on the quality of its cross-cut surface becomes higher while increasing

  7. When Machines Design Machines!

    DEFF Research Database (Denmark)

    2011-01-01

    Until recently we were the sole designers, alone in the driving seat making all the decisions. But, we have created a world of complexity way beyond human ability to understand, control, and govern. Machines now do more trades than humans on stock markets, they control our power, water, gas...... and food supplies, manage our elevators, microclimates, automobiles and transport systems, and manufacture almost everything. It should come as no surprise that machines are now designing machines. The chips that power our computers and mobile phones, the robots and commercial processing plants on which we...... depend, all are now largely designed by machines. So what of us - will be totally usurped, or are we looking at a new symbiosis with human and artificial intelligences combined to realise the best outcomes possible. In most respects we have no choice! Human abilities alone cannot solve any of the major...

  8. A Study of Surrogate Parameters of Birth Weight

    Directory of Open Access Journals (Sweden)

    Kadam Y

    2005-01-01

    Full Text Available Research question : Which anthropometric parameter is correlating highly with birth weight? Can we use this parameter as a screening test for predicting birth weight? What is their cut-off value? Hypothesis: Various anthropometric parameters of newborn correlate each other positively. Objective : To find out the most effective anthropometric parameter in the newborn to assess birth weight so that newborn with LBW can be identified.. Study design: Hospital based cross-sectional study. Participants : Newborn babies born in KIMS, Karad. Results : Relatively highest correlation was observed between birth weight & thigh circumfirence (T.C. (r = 0.8637 & next with chest circumfirence (C.C.. (r = 0.8247 Cut-off values of T.C. & C.C. had better sensitivity, specificity & predictive value for identifying LBW babies. Conclusion : T.C. is the best effective parameter to predict birth weight. Next to it is C.C.

  9. A field study investigating the effects of a rebar-tying machine on trunk flexion, tool usability and productivity.

    Science.gov (United States)

    Vi, Peter

    2006-11-15

    A field study with a before-and-after experimental design was conducted to evaluate the potential reduction in the risk of musculoskeletal injuries to rodworkers when using an automatic rebar-tying machine. Eleven rodworkers participated in this experiment. All dependent variables (trunk posture, rebar-tying time and responses to a usability questionnaire) were first measured before introducing the rebar-tying machine and then after 3 months of usage all dependent variables were measured again. The results of the study indicated that working with a rebar-tying machine significantly reduced the magnitude, frequency and duration of exposure to awkward trunk posture. Tying time was reduced when participants used the machine. The usability questionnaire indicated that most participants preferred to use the rebar-tying machine for ground-level rebar construction. The field study also revealed that the rebar-tying machine is not limited to the reinforcing trade. The machine can be used for other purposes, such as tying electrical conduit and attaching radiant heat tube to steel mesh. Based on trunk posture exposure, rebar-tying time, usability and transferability, it is concluded that the rebar-tying machine can be an effective tool to reduce the frequency and duration of severe trunk flexion, improve usability and increase productivity among concrete reinforcement workers.

  10. Women, Men, and Machines.

    Science.gov (United States)

    Form, William; McMillen, David Byron

    1983-01-01

    Data from the first national study of technological change show that proportionately more women than men operate machines, are more exposed to machines that have alienating effects, and suffer more from the negative effects of technological change. (Author/SSH)

  11. Machinability of advanced materials

    CERN Document Server

    Davim, J Paulo

    2014-01-01

    Machinability of Advanced Materials addresses the level of difficulty involved in machining a material, or multiple materials, with the appropriate tooling and cutting parameters.  A variety of factors determine a material's machinability, including tool life rate, cutting forces and power consumption, surface integrity, limiting rate of metal removal, and chip shape. These topics, among others, and multiple examples comprise this research resource for engineering students, academics, and practitioners.

  12. Virtual Machines and Networks - Installation, Performance Study, Advantages and Virtualization Options

    CERN Document Server

    Ali, Ishtiaq; 10.5121/ijnsa.2011.3101

    2011-01-01

    The interest in virtualization has been growing rapidly in the IT industry because of inherent benefits like better resource utilization and ease of system manageability. The experimentation and use of virtualization as well as the simultaneous deployment of virtual software are increasingly getting popular and in use by educational institutions for research and teaching. This paper stresses on the potential advantages associated with virtualization and the use of virtual machines for scenarios, which cannot be easily implemented and/or studied in a traditional academic network environment, but need to be explored and experimented by students to meet the raising needs and knowledge-base demanded by the IT industry. In this context, we discuss various aspects of virtualization - starting from the working principle of virtual machines, installation procedure for a virtual guest operating system on a physical host operating system, virtualization options and a performance study measuring the throughput obtained ...

  13. Using machine-coded event data for the micro-level study of political violence

    Directory of Open Access Journals (Sweden)

    Jesse Hammond

    2014-07-01

    Full Text Available Machine-coded datasets likely represent the future of event data analysis. We assess the use of one of these datasets—Global Database of Events, Language and Tone (GDELT—for the micro-level study of political violence by comparing it to two hand-coded conflict event datasets. Our findings indicate that GDELT should be used with caution for geo-spatial analyses at the subnational level: its overall correlation with hand-coded data is mediocre, and at the local level major issues of geographic bias exist in how events are reported. Overall, our findings suggest that due to these issues, researchers studying local conflict processes may want to wait for a more reliable geocoding method before relying too heavily on this set of machine-coded data.

  14. Studies on the correlation of some aggregate parameters in the ...

    African Journals Online (AJOL)

    Global Journal of Pure and Applied Sciences ... Studies on the correlation of some aggregate parameters in the drains of a service facility ... coefficient of determination, R2, shows that each regression model is adequate for future prediction of

  15. The study of functional parameter of the electric coal brushes

    Directory of Open Access Journals (Sweden)

    Claudia Staşac

    2008-05-01

    Full Text Available These paper present a study about the analyzeof the functional parameters of the electrical coal brush.The analyze was made with an experimental device, andthe results was prelucrate in MathCAD software.

  16. Optimizing machining parameters of wire-EDM process to cut Al7075/SiCp composites using an integrated statistical approach

    Institute of Scientific and Technical Information of China (English)

    Thella Babu Rao

    2016-01-01

    Metal matrix composites (MMCs) as advanced materials,while producing the components with high dimensional accuracy and intricate shapes,are more complex and cost effective for machining than conventional alloys.It is due to the presence of discontinuously distributed hard ceramic with the MMCs and involvement of a large number of machining control variables.However,determination of optimal machining conditions helps the process engineer to make the process efficient and effective.In the present investigation a novel hybrid multi-response optimization approach is proposed to derive the economic machining conditions for MMCs.This hybrid approach integrates the concepts of grey relational analysis (GRA),principal component analysis (PCA) and Taguchi method (TM) to derive the optimal machining conditions.The machining experiments are planned to machine A17075/SiCp MMCs using wire-electrical discharge machining (WEDM) process.SiC particulate size and its weight percentage are explicitly considered here as the process variables along with the WEDM input variables.The derived optimal process responses are confirmed by the experimental validation tests and the results show satisfactory.The practical possibility of the derived optimal machining conditions is also analyzed and presented using scanning electron microscope (SEM) examinations.According to the growing industrial need of making high performance,low cost components,this investigation provides a simple and sequential approach to enhance the WEDM performance while machining MMCs.

  17. End mill tools integration in CNC machining for rapid manufacturing processes: simulation studies

    OpenAIRE

    Muhammed Nafis Osman Zahid; Keith Case; Darren Watts

    2015-01-01

    Computer numerical controlled (CNC) machining has been recognized as a manufacturing process that is capable of producing metal parts with high precision and reliable quality, whereas many additive manufacturing methods are less capable in these respects. The introduction of a new layer-removal methodology that utilizes an indexing device to clamp the workpiece can be used to extend CNC applications into the realm of rapid manufacturing (CNC-RM) processes. This study aims to improve the imple...

  18. End mill tools integration in CNC machining for rapid manufacturing processes: simulation studies

    OpenAIRE

    Muhammed Nafis Osman Zahid; Keith Case; Darren Watts

    2015-01-01

    Computer numerical controlled (CNC) machining has been recognized as a manufacturing process that is capable of producing metal parts with high precision and reliable quality, whereas many additive manufacturing methods are less capable in these respects. The introduction of a new layer-removal methodology that utilizes an indexing device to clamp the workpiece can be used to extend CNC applications into the realm of rapid manufacturing (CNC-RM) processes. This study aims to improve the imple...

  19. Deflecting cavity dynamics for time-resolved machine studies of SXFEL user facility

    CERN Document Server

    Song, Minghao; Liu, Bo; Wang, Dong

    2016-01-01

    Radio frequency deflectors are widely used for time-resolved electron beam energy, emittance and radiation profile measurements in modern free electron laser facilities. In this paper, we present the beam dynamics aspects of the deflecting cavity of SXFEL user facility, which is located at the exit of the undulator. With a targeted time resolution around 10 fs, it is expected to be an important tool for time-resolved commissioning and machine studies for SXFEL user facility.

  20. Characterization of machining quality attributes based on spindle probe, coordinate measuring machine, and surface roughness data

    Directory of Open Access Journals (Sweden)

    Tzu-Liang Bill Tseng

    2014-04-01

    Full Text Available This study investigates the effects of machining parameters as they relate to the quality characteristics of machined features. Two most important quality characteristics are set as the dimensional accuracy and the surface roughness. Before any newly acquired machine tool is put to use for production, it is important to test the machine in a systematic way to find out how different parameter settings affect machining quality. The empirical verification was made by conducting a Design of Experiment (DOE with 3 levels and 3 factors on a state-of-the-art Cincinnati Hawk Arrow 750 Vertical Machining Center (VMC. Data analysis revealed that the significant factor was the Hardness of the material and the significant interaction effect was the Hardness + Feed for dimensional accuracy, while the significant factor was Speed for surface roughness. Since the equally important thing is the capability of the instruments from which the quality characteristics are being measured, a comparison was made between the VMC touch probe readings and the measurements from a Mitutoyo coordinate measuring machine (CMM on bore diameters. A machine mounted touch probe has gained a wide acceptance in recent years, as it is more suitable for the modern manufacturing environment. The data vindicated that the VMC touch probe has the capability that is suitable for the production environment. The test results can be incorporated in the process plan to help maintain the machining quality in the subsequent runs.

  1. PARAMETRIC STUDY OF ELECTRICAL DISCHARGE MACHINING OF AISI 304 STAINLESS STEEL

    Directory of Open Access Journals (Sweden)

    P. SRINIVASA RAO,

    2010-08-01

    Full Text Available Electrical discharge machining (EDM is widely used process in the production of mould / dies, aerospace, automobile and electronics industries where intricate complex shapes need to be machined in very hard materials. The selection of the AISI 304 stainless steel was made taking into account its use in almost all industrial applicationsfor approximately 50% of the world’s stainless steel production and consumption. In this work, a study has been carried out on the influence of four design factors: current, open-circuit voltage, servo and dutycycle over material removal rate, tool wear rate, surface roughness and hardness on the die-sinking electrical discharge machining of AISI 304 stainless steel. This has been done using design of experiments (DOE, which allows us to carry out theabove-mentioned analysis performing a relatively small number of experiments. In this case, a 3*24-1 mixed level factorial design, whose resolution is V, has been selected due to the number of factors considered in the study. The resolution of this mixed factorial design allows us to estimate all the main effects, two-factor interactions and pure quadratic effects of the four design factors selected to perform this study.

  2. Design Parameter Studies of Emission-Based Iron Opacity Measurements

    Science.gov (United States)

    Martin, Madison E.; London, Richard A.; Goluoglu, Sedat; Whitley, Heather D.

    2016-10-01

    Opacity is a critical parameter in the transport of radiation in systems such as inertial confinement fusion capsules and stars. The resolution of current disagreements between solar models and helioseismological observations would benefit from experimental validation of theoretical opacity models. Short pulse lasers can be used to heat targets to higher temperatures and densities than long pulse lasers and pulsed power machines, thus potentially enabling access to x-ray emission spectra at conditions relevant to solar models. The radiation-hydrodynamic code HYDRA is used to investigate the effects of modifying laser energy, laser pulse length, and target dimensions on the plasma conditions, x-ray emission, and inferred opacity of a buried layer iron target. The accuracy of the opacity inference is sensitive to tamper emission and optical depth effects. An example design that reaches temperatures and densities relevant to the radiative zone of the sun while reducing optical depth and tamper emission effects will be discussed. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. Lawrence Livermore National Security, LLC.

  3. A parameter identifiability study of two chalk tracer tests

    Directory of Open Access Journals (Sweden)

    S. A. Mathias

    2006-08-01

    Full Text Available As with most fractured rock formations, Chalk is highly heterogeneous. Therefore, meaningful estimates of model parameters must be obtained at a scale comparable with the process of concern. These are frequently obtained by calibrating an appropriate model to observed concentration-time data from radially convergent tracer tests (RCTT. Arguably, an appropriate model should consider radially convergent dispersion (RCD and Fickian matrix diffusion. Such a model requires the estimation of at least four parameters. A question arises as to whether or not this level of model complexity is supported by the information contained within the calibration data. Generally modellers have not answered this question due to the calibration techniques employed. A dual-porosity model with RCD was calibrated to two tracer test datasets from different UK Chalk aquifers. A multivariate sensitivity analysis, which assumed only a priori upper and lower bounds for each model parameter, was undertaken. Rather than looking at measures of uncertainty, the shape of the multivariate objective function surface was used to determine whether a parameter was identifiable. Non-identifiable parameters were then removed and the procedure was repeated until all remaining parameters were identifiable.

    It was found that the single fracture model (SFM (which ignores mechanical dispersion obtained the best mass recovery, excellent model performance and best parameter identifiability in both the tests studied. However, there was no objective evidence suggesting that mechanical dispersion was negligible. Moreover, the SFM (with just two parameters was found to be good at approximating the Single Fracture Dispersion Model SFDM (with three parameters when different, and potentially erroneous parameters, were used. Overall, this study emphasises the importance of adequate temporal sampling of breakthrough curve data prior to peak concentrations, to ensure adequate characterisation of

  4. 一种三维磁路永磁电机的集中参数磁路模型%One lumped parameter magnetic circuit model for permanent magnet machines with three-dimensional flux paths

    Institute of Scientific and Technical Information of China (English)

    张继鹏; 陈鹏; 苏锦智; 孙立志

    2015-01-01

    为了研究一种定子采用类爪极磁极铁心形状及环形集中绕组的三维磁路结构的磁通切换型永磁电机,在对空载静磁场及电枢反应磁场进行三维有限元磁场计算的基础上,根据电机在不同定、转子相对位置时的磁场分布情况,对三维磁路结构进行集中参数磁路模型建模,并推导出节点磁动势矩阵,通过对矩阵进行解析计算以及对计算结果的分析,推导出电机各主要电磁参数的解析表达式并进行计算和分析,通过与三维磁场计算结果相对比,验证了该磁路模型计算方法的正确性。由于可采用集中参数磁路模型计算可以节省大量计算时间,可以更方便地进行三维磁路结构电机的各种参数优化,对其他三维磁路和分析工作也具有参考意义。%In order to study one flux switching permanent-magnet machine with a quasi-claw-pole stator core structure and a circular concentrate winding pattern, 3-dimentional electromagnetic field calculations were carried to analyze no-load static magnetic fields and armature reaction magnetic fields respectively. Then one 3-dimentional lumped-parameter magnetic circuit model was built based on the analysis of the magnetic field distributions at different rotor positions in the machine. Firstly the node magneto motive force matrix were derived and solved, then the analytical expressions of main electromagnetic parameters were concluded and analyzed. The correctness of the lumped parameter magnetic circuit calculation model was verified by comparing the results calculated with the corresponding 3-dimentional finite element anal-ysis results. The lumped parameter magnetic circuit model calculations take much less time than conduc-ting 3-dimentional finite element analysis, so optimizations of various parameters of the machine with three-dimensional magnetic structure can be carried out less costly, and can be a reference to analysis of other

  5. Machinability Study of Hybrid Nanoclay-Glass Fibre Reinforced Polyester Composites

    Directory of Open Access Journals (Sweden)

    P. Prabhu

    2013-01-01

    Full Text Available Glass fibre reinforced polyester composites (GRP and hybrid nanoclay and glass fibre reinforced polyester nanocomposites (CGRP are fabricated by vacuum assisted resin infusion technique. The optimum mechanical properties are obtained for CGRP with 3 wt.% nanoclay. Three types of drills (carbide twist drill D 5407060, HSS twist drill BS-328, and HSS end mill (4 flutes “N”-type end mill RH-helical flute of 6 mm diameters are used to drill holes on GRP and CGRP. Three different speeds (600, 852, and 1260 rpm and two different feeds (0.045, 0.1 mm/rev are selected as process parameters. The effect of process parameter on thrust force and delamination during drilling CGRP is analyzed for optimizing the machining parameters. The delamination factor is low for the optimum process parameter (feed = 0.1 mm/rev and speed 852 rpm. Microstructural analysis confirms that at higher feeds, delamination is low for CGRP drilled with carbide tools. In order to analyze the effect of nanoclay in CGRP on tool wear, 200 holes were drilled on CGRP samples with 3 wt.% nanoclay, and the tool wear is analyzed under optimized parametric condition. Tool wear is high in HSS twist drill compared with carbide drill. The presence of nanoclay also accelerates the tool wear.

  6. Rotary ultrasonic machining of CFRP composites: a study on power consumption.

    Science.gov (United States)

    Cong, W L; Pei, Z J; Deines, T W; Srivastava, Anil; Riley, L; Treadwell, C

    2012-12-01

    Carbon fiber reinforced plastic (CFRP) composites are very difficult to machine. A large number of holes need to be drilled in CFRP for many applications. Therefore, it is important to develop cost-effective drilling processes. CFRP has been drilled by rotary ultrasonic machining (RUM) successfully. The literature has reports about the effects of input variables on output variables (including cutting force, torque, surface roughness, tool wear, and workpiece delamination) in RUM of CFRP. However, there are no reports on power consumption in RUM of CFRP. This paper reports the first study on power consumption in RUM of CFRP. It reports an experimental investigation on effects of input variables (ultrasonic power, tool rotation speed, feedrate, and type of CFRP) on power consumption of each component (including ultrasonic power supply, spindle motor, coolant pump, and air compressor) and the entire RUM system.

  7. Geological Hazards analysis in Urban Tunneling by EPB Machine (Case study: Tehran subway line 7 tunnel

    Directory of Open Access Journals (Sweden)

    Hassan Bakhshandeh Amnieh

    2016-06-01

    Full Text Available Technological progress in tunneling has led to modern and efficient tunneling methods in vast underground spaces even under inappropriate geological conditions. Identification and access to appropriate and sufficient geological hazard data are key elements to successful construction of underground structures. Choice of the method, excavation machine, and prediction of suitable solutions to overcome undesirable conditions depend on geological studies and hazard analysis. Identifying and investigating the ground hazards in excavating urban tunnels by an EPB machine could augment the strategy for improving soil conditions during excavation operations. In this paper, challenges such as geological hazards, abrasion of the machine cutting tools, clogging around these tools and inside the chamber, diverse work front, severe water level fluctuations, existence of water, and fine-grained particles in the route were recognized in a study of Tehran subway line 7, for which solutions such as low speed boring, regular cutter head checks, application of soil improving agents, and appropriate grouting were presented and discussed. Due to the presence of fine particles in the route, foam employment was suggested as the optimum strategy where no filler is needed.

  8. QUALITY CONTROL PARAMETERS OF BRIHAT DASHAMULA TAILA: A PRELIMINARY STUDY

    Directory of Open Access Journals (Sweden)

    Sharma Vinay

    2011-05-01

    Full Text Available Standard analytical parameters of a number of Ayurvedic oils have been described in API. Brihat Dashamula Taila is one of the most commonly used oil by Ayurvedic Physicians. But there no standard analytical parameters are available in any authentic texts. Therefore this study aimed to set the quality control parameters with SOP of Brihat Dashamula Taila and found values like Refractive index (1.47 at 400C, specific gravity (0.923 at 250C Acid value (1.2, Iodine value (92.6 and Saponification value (86.34 may be considered as standard.

  9. Astrophysical parameters of ten poorly studied open star clusters

    Institute of Scientific and Technical Information of China (English)

    Ashraf Latif Tadross; Reda El-Bendary; Anas Osman; Nader Ismail; Abdel Aziz Bakry

    2012-01-01

    We present the fundamental parameters of ten open star clusters,nominated from Kronberger et al.who presented some newly discovered stellar groups on the basis of the Two Micron All Sky Survey photometry and Digitized Sky Survey visual images.Star counts and photometric parameters (radius,membership,distance,color excess,age,luminosity function,mass function,total mass,and dynamical relaxation time) have been determined for these ten clusters for the first time.In order to calibrate our procedures,the main parameters (distance,age,and color excess) have been reestimated for another five clusters,which are also studied by Kronberger et al.

  10. Machine Learning in Parliament Elections

    Directory of Open Access Journals (Sweden)

    Ahmad Esfandiari

    2012-09-01

    Full Text Available Parliament is considered as one of the most important pillars of the country governance. The parliamentary elections and prediction it, had been considered by scholars of from various field like political science long ago. Some important features are used to model the results of consultative parliament elections. These features are as follows: reputation and popularity, political orientation, tradesmen's support, clergymen's support, support from political wings and the type of supportive wing. Two parameters of reputation and popularity and the support of clergymen and religious scholars that have more impact in reducing of prediction error in election results, have been used as input parameters in implementation. In this study, the Iranian parliamentary elections, modeled and predicted using learnable machines of neural network and neuro-fuzzy. Neuro-fuzzy machine combines the ability of knowledge representation of fuzzy sets and the learning power of neural networks simultaneously. In predicting the social and political behavior, the neural network is first trained by two learning algorithms using the training data set and then this machine predict the result on test data. Next, the learning of neuro-fuzzy inference machine is performed. Then, be compared the results of two machines.

  11. A Numerical Study of the Spring-Back Phenomenon in Bending with a Rebar Bending Machine

    Directory of Open Access Journals (Sweden)

    Chang Hwan Choi

    2014-10-01

    Full Text Available Recently, the rebar bending methodology started to change from field processing to utilizing rebar bending machines at plant sites prior to transport to the construction locations. Computerized control of rebar plant bending machines provides more accurate and faster bending of rebars than the low quality inefficient field processing alternative. The bending process involves plastic deformation of rebars, where bending stress beyond the yield point of the material is applied. When the bending stress is removed, spring back is caused by the elastic restoring stress. Therefore, an accurate numerical analysis of the spring-back process is required to reduce the bending process errors. The most sensitive factors affecting the spring-back process are the bending radius, the bending angle, the diameter of the rebar, the friction coefficient, and the yielding strength of material. In this paper, we suggest a numerical modeling method using these factors. The finite element modeling of the dynamic mechanical behavior of the material during bending is performed using a commercial dynamic analysis program “DAFUL.” We use the least squares approach to derive the spring-back deflection as a function of the rebar bending parameters.

  12. Study for the electric arc of alternative current at the single phase welding machine using the Matlab/Simulink environment

    Science.gov (United States)

    Baciu, I.; Ghiormez, L.; Vasar, C.

    2017-01-01

    In this paper is presented a mathematical model of the electric arc for an alternative current welding machine of low power. The electric arc model is based on dividing the voltage-current characteristic of the electric arc in many functioning zones. For the model of the entire welding machine are used real parameters as the ones of the proper welding machine. The voltage and current harmonics spectrum that is obtained during the welding process is presented. Also, the waveforms for the current and voltage of the electric arc plotted against time and the voltage-current characteristic of the electric arc are illustrated. The electric arc is considered as being supplied by alternative voltage from the electrical power network using a single phase transformer which has the output voltage of 80 volts. The model of the welding machine is developed in Simulink and the variations of some parameters of the electric arc are obtained by modifying of them in a Matlab function. Also, in this paper is presented the total harmonic distortion for the voltage and current of the electric arc obtained during simulation of the welding machine.

  13. Distinguishing age-related cognitive decline from dementias: A study based on machine learning algorithms.

    Science.gov (United States)

    Er, Füsun; Iscen, Pınar; Sahin, Sevki; Çinar, Nilgun; Karsidag, Sibel; Goularas, Dionysis

    2017-08-01

    This study aims to examine the distinguishability of age-related cognitive decline (ARCD) from dementias based on some neurocognitive tests using machine learning. 106 subjects were divided into four groups: ARCD (n=30), probable Alzheimer's disease (AD) (n=20), vascular dementia (VD) (n=21) and amnestic mild cognitive impairment (MCI) (n=35). The following tests were applied to all subjects: The Wechsler memory scale-revised, a clock-drawing, the dual similarities, interpretation of proverbs, word fluency, the Stroop, the Boston naming (BNT), the Benton face recognition, a copying-drawings and Öktem verbal memory processes (Ö-VMPT) tests. A multilayer perceptron, a support vector machine and a classification via regression with M5-model trees were employed for classification. The pairwise classification results show that ARCD is completely separable from AD with a success rate of 100% and highly separable from MCI and VD with success rates of 95.4% and 86.30%, respectively. The neurocognitive tests with the higher merit values were Ö-VMPT recognition (ARCD vs. AD), Ö-VMPT total learning (ARCD vs. MCI) and semantic fluency, proverbs, Stroop interference and naming BNT (ARCD vs. VD). The findings show that machine learning can be successfully utilized for distinguishing ARCD from dementias based on neurocognitive tests. Copyright © 2017 Elsevier Ltd. All rights reserved.

  14. Application of machine learning algorithms to the study of noise artifacts in gravitational-wave data

    CERN Document Server

    Biswas, Rahul; Cao, Junwei; Essick, Reed; Hodge, Kari Alison; Katsavounidis, Erotokritos; Kim, Kyungmin; Kim, Young-Min; Bigot, Eric-Olivier Le; Lee, Chang-Hwan; Oh, John J; Oh, Sang Hoon; Son, Edwin J; Vaulin, Ruslan; Wang, Xiaoge; Ye, Tao

    2013-01-01

    The sensitivity of searches for astrophysical transients in data from the LIGO is generally limited by the presence of transient, non-Gaussian noise artifacts, which occur at a high-enough rate such that accidental coincidence across multiple detectors is non-negligible. Furthermore, non-Gaussian noise artifacts typically dominate over the background contributed from stationary noise. These "glitches" can easily be confused for transient gravitational-wave signals, and their robust identification and removal will help any search for astrophysical gravitational-waves. We apply Machine Learning Algorithms (MLAs) to the problem, using data from auxiliary channels within the LIGO detectors that monitor degrees of freedom unaffected by astrophysical signals. The number of auxiliary-channel parameters describing these disturbances may also be extremely large; an area where MLAs are particularly well-suited. We demonstrate the feasibility and applicability of three very different MLAs: Artificial Neural Networks, Su...

  15. A statistical study of the interdependence of solar wind parameters

    Institute of Scientific and Technical Information of China (English)

    Shollykutty John; P. J. Kurian

    2009-01-01

    Correlation analysis of solar wind parameters, namely solar wind velocity, pro- ton density, proton temperature and mean interplanetary magnetic field (IMF) from the ACE spacecraft data near Earth, was done. To our best knowledge, this study is a novel one since we consider here only the parameters inside the solar wind, including the mean IMF and, hence, the solar wind is a self consistent system. We have proposed a Multiple Linear Regression (MLR) model for the prediction of the response variable (solar wind velocity) using the parameters proton density, proton temperature and mean IMF mea- sured as dally averages. About 60% of the observed value can be predicted using this model. It is shown that, in general, the correlation between solar wind parameters is sig- nificant. A deviation from the prediction at the solar maximum is interpreted. These results are verified by a graphical method.

  16. PERFORMANCE OF COATED CUTTING TOOLS IN MACHINING HARDENED STEEL

    Directory of Open Access Journals (Sweden)

    K.Subramanyam,

    2010-10-01

    Full Text Available This paper deals with the study of the performance of coated tools in machining hardening steel under dry conditions. This paper involves of machining AISI 4340 hardened steel using coated carbide tools is studied using full factorial experiments. Many parameters influence the quality of the products in hard turning process. The objective of this study is on the effect of the cutting conditions such as cutting velocity, feed, and depth of cut on the surface finish in machining AISI 4340 hardened steel. Machining of hardened steels has become an important manufacturing process, particularly in the automotive and bearing industries.

  17. Application of Machine Learning Algorithms to the Study of Noise Artifacts in Gravitational-Wave Data

    Science.gov (United States)

    Biswas, Rahul; Blackburn, Lindy L.; Cao, Junwei; Essick, Reed; Hodge, Kari Alison; Katsavounidis, Erotokritos; Kim, Kyungmin; Young-Min, Kim; Le Bigot, Eric-Olivier; Lee, Chang-Hwan; hide

    2014-01-01

    The sensitivity of searches for astrophysical transients in data from the Laser Interferometer Gravitationalwave Observatory (LIGO) is generally limited by the presence of transient, non-Gaussian noise artifacts, which occur at a high-enough rate such that accidental coincidence across multiple detectors is non-negligible. Furthermore, non-Gaussian noise artifacts typically dominate over the background contributed from stationary noise. These "glitches" can easily be confused for transient gravitational-wave signals, and their robust identification and removal will help any search for astrophysical gravitational-waves. We apply Machine Learning Algorithms (MLAs) to the problem, using data from auxiliary channels within the LIGO detectors that monitor degrees of freedom unaffected by astrophysical signals. Terrestrial noise sources may manifest characteristic disturbances in these auxiliary channels, inducing non-trivial correlations with glitches in the gravitational-wave data. The number of auxiliary-channel parameters describing these disturbances may also be extremely large; high dimensionality is an area where MLAs are particularly well-suited. We demonstrate the feasibility and applicability of three very different MLAs: Artificial Neural Networks, Support Vector Machines, and Random Forests. These classifiers identify and remove a substantial fraction of the glitches present in two very different data sets: four weeks of LIGO's fourth science run and one week of LIGO's sixth science run. We observe that all three algorithms agree on which events are glitches to within 10% for the sixth science run data, and support this by showing that the different optimization criteria used by each classifier generate the same decision surface, based on a likelihood-ratio statistic. Furthermore, we find that all classifiers obtain similar limiting performance, suggesting that most of the useful information currently contained in the auxiliary channel parameters we extract

  18. Bone response to machined and resorbable blast material titanium implants: an experimental study in rabbits.

    Science.gov (United States)

    Piattelli, Maurizio; Scarano, Antonio; Paolantonio, Michele; Iezzi, Giovanna; Petrone, Giovanna; Piattelli, Adriano

    2002-01-01

    The aim of the present study was a comparison of implants' responses to a machined surface and to a surface sandblasted with hydroxyapatite (HA) particles (resorbable blast material [RBM]). Threaded machined and RBM, grade 3, commercially pure, titanium, screw-shaped inplants were used in this study. Twenty-four New Zealand white mature male rabbits were used. The inplants were inserted into the articular femoral knee joint according to a previously described technique. Each rabbit received 2 inplants, 1 test (RBM) and 1 control (machined). A total of 48 implants (24 control and 24 test) were inserted. The rabbits were anesthetized with intramuscular injections of fluanisone (0.7 mg/ kg body weight) and diazepam (1.5 mg/kg b.wt.), and local anesthesia was given using 1 mL of 2% lidocaine/adrenalin solution. Two rabbits died in the postoperative course. Four animals were euthanatized with an overdose of intravenous pentobarbital after 1, 2, 3, and 4 weeks; 6 rabbits were euthanatized after 8 weeks. A total of 44 implants were retrieved. The specimens were processed with the Precise 1 Automated System to obtain thin ground sections. A total of 3 slides were obtained for each implant. The slides were stained with acid and basic fuchsin and toluidine blue. The slides were observed in normal transmitted light under a Leitz Laborlux microscope, and histomorphometric analysis was performed. With the machined implants, it was possible to observe the presence of bone trabeculae near the implant surface at low magnification. At higher magnification many actively secreting alkaline phosphatasepositive (ALP+) osteoblasts were observed. In many areas, a not yet mineralized matrix was present. After 4 to 8 weeks, mature bone appeared in direct contact with the implant surface, but in many areas a not yet mineralized osteoid matrix was interposed between the mineralized bone and implant surface. In the RBM implants, many ALP+ osteoblasts were present and in direct contact with

  19. A NEW HYPERSPHERE SUPPORT VECTOR MACHINE ALGORITHM

    Institute of Scientific and Technical Information of China (English)

    Zhang Xinfeng; Shen Lansun

    2006-01-01

    The hypersphere support vector machine is a new algorithm in pattern recognition. By studying three kinds ofhypersphere support vector machines, it is found that their solutions are identical and the margin between two classes of samples is zero or is not unique. In this letter, a new kind ofhypersphere support vector machine is proposed. By introducing a parameter n(n>l), a unique solution of the margin can be obtained.Theoretical analysis and experimental results show that the proposed algorithm can achieve better generalization performance.

  20. Effect of the crown design and interface lute parameters on the stress-state of a machined crown-tooth system: a finite element analysis.

    Science.gov (United States)

    Shahrbaf, Shirin; vanNoort, Richard; Mirzakouchaki, Behnam; Ghassemieh, Elaheh; Martin, Nicolas

    2013-08-01

    The effect of preparation design and the physical properties of the interface lute on the restored machined ceramic crown-tooth complex are poorly understood. The aim of this work was to determine, by means of three-dimensional finite element analysis (3D FEA) the effect of the tooth preparation design and the elastic modulus of the cement on the stress state of the cemented machined ceramic crown-tooth complex. The three-dimensional structure of human premolar teeth, restored with adhesively cemented machined ceramic crowns, was digitized with a micro-CT scanner. An accurate, high resolution, digital replica model of a restored tooth was created. Two preparation designs, with different occlusal morphologies, were modeled with cements of 3 different elastic moduli. Interactive medical image processing software (mimics and professional CAD modeling software) was used to create sophisticated digital models that included the supporting structures; periodontal ligament and alveolar bone. The generated models were imported into an FEA software program (hypermesh version 10.0, Altair Engineering Inc.) with all degrees of freedom constrained at the outer surface of the supporting cortical bone of the crown-tooth complex. Five different elastic moduli values were given to the adhesive cement interface 1.8GPa, 4GPa, 8GPa, 18.3GPa and 40GPa; the four lower values are representative of currently used cementing lutes and 40GPa is set as an extreme high value. The stress distribution under simulated applied loads was determined. The preparation design demonstrated an effect on the stress state of the restored tooth system. The cement elastic modulus affected the stress state in the cement and dentin structures but not in the crown, the pulp, the periodontal ligament or the cancellous and cortical bone. The results of this study suggest that both the choice of the preparation design and the cement elastic modulus can affect the stress state within the restored crown

  1. Sensitivity study using machine learning algorithms on simulated r-mode gravitational wave signals from newborn neutron stars

    CERN Document Server

    Mytidis, Antonis; Panagopoulos, Orestis P; Whiting, Bernard

    2015-01-01

    This is a follow-up sensitivity study on r-mode gravitational wave signals from newborn neutron stars illustrating the applicability of machine learning algorithms for the detection of long-lived gravitational-wave transients. In this sensitivity study we examine three machine learning algorithms (MLAs): artificial neural networks (ANNs), support vector machines (SVMs) and constrained subspace classifiers (CSCs). The objective of this study is to compare the detection efficiency that MLAs can achieve with the efficiency of conventional detection algorithms discussed in an earlier paper. Comparisons are made using 2 distinct r-mode waveforms. For the training of the MLAs we assumed that some information about the distance to the source is given so that the training was performed over distance ranges not wider than half an order of magnitude. The results of this study suggest that machine learning algorithms are suitable for the detection of long-lived gravitational-wave transients and that when assuming knowle...

  2. Review Study on Runway Capacity Parameters and Improvement

    Science.gov (United States)

    Safrilah; Putra, J. C. P.

    2017-06-01

    The demand of air travel continues to increase over time, due to its short travel time, reliability and safety. Problems then arise when airport capacity, especially airside (mainly runway) capacity cannot cope with the demand. Some airports build the expensive additional infrastructure, while some others believe that manage on system is more efficient and effective. The study gathering information from various source about parameters related to runway capacity so that the improvement made in the future will solve right on target. To accommodate wide number of factors, the study classify the parameters into five categories in which operation/procedure related parameters play an important role (52%). To facilitate future research on runway capacity, the study also tabulates methods used by various scholars to improve runway capacity

  3. A study on the machining parameters optimization of micro-end ...

    African Journals Online (AJOL)

    user

    end milling is the most important micromachining process, widely used for the ... industry one of the trends is to manufacture low cost product in short time. ..... Thus using the Taguchi approach, the design of experiments and analysis of.

  4. An Approach to the Classification of Cutting Vibration on Machine Tools

    OpenAIRE

    Jeng-Fung Chen; Shih-Kuei Lo; Quang Hung Do

    2016-01-01

    Predictions of cutting vibrations are necessary for improving the operational efficiency, product quality, and safety in the machining process, since the vibration is the main factor for resulting in machine faults. “Cutting vibration” may be caused by setting incorrect parameters before machining is commenced and may affect the precision of the machined work piece. This raises the need to have an effective model that can be used to predict cutting vibrations. In this study, an artificial neu...

  5. Study on flaw identification of ultrasonic signal for large shafts based on optimal support vector machine

    Institute of Scientific and Technical Information of China (English)

    Zhao Xiufen; Yin Guofu; Tian Guiyun; Yin Ying

    2008-01-01

    Automatic identification of flaws is very important for ultrasonic nondestructive testing and evaluation of large shaft. A novel automatic defect identification system is presented. Wavelet packet analysis (WPA) was applied to feature extraction of ultrasonic signal, and optimal Support vector machine (SVM) was used to perform the identification task. Meanwhile, comparative study on convergent velocity and classified effect was done among SVM and several improved BP network models. To validate the method, some experiments were performed and the results show that the proposed system has very high identification performance for large shafts and the optimal SVM processes better classification performance and spreading potential than BP manual neural network under small study sample condition.

  6. A numerical study of ultraprecision machining of monocrystalline silicon with laser nano-structured diamond tools by atomistic simulation

    Science.gov (United States)

    Dai, Houfu; Chen, Genyu; Zhou, Cong; Fang, Qihong; Fei, Xinjiang

    2017-01-01

    Three-dimension molecular dynamics (MD) simulations is employed to investigate the ultraprecision machining of single crystal silicon with structured nanoscale diamond tool fabricated by laser. The advantages and disadvantages of diamond machining using structured tools are discussed in comparison with those of using non-structured tools. The von Mises stress distribution, hydrostatic stress distribution, atomic displacement, stress, the radial distribution function, cutting forces, frictional coefficient, subsurface temperature and potential energy during the nanometric machining process are studied. A theoretical analysis model is also established to investigate the subsurface damage mechanism by analyzing the distribution of residual stress during the nanoscale machining process. The results show that a structured nanoscale tool in machining brittle material silicon causes a smaller hydrostatic stress, a less compressive normal stress σxx and σyy , a lower temperature and a smaller cutting force. However, the structured nanoscale tool machining results in smaller chip volume and more beta-silicon phase. Besides, the friction coefficient for tool with V-shape groove is smaller than those for non-structured tools and other structured nanoscale tools. This means that the tool with V-shape groove can reduce the resistance to cutting during the nanoscale machining process. In addition, the results also point out that the potential energy of subsurface atoms and the number of other atoms for pyramid-structured tool are much smaller than those of using non-structured tools and other structured nanoscale tools.

  7. Studies on the Process Parameters of Rapid Prototyping Technique (Stereolithography for the Betterment of Part Quality

    Directory of Open Access Journals (Sweden)

    Raju Bangalore Singe Gowda

    2014-01-01

    Full Text Available Rapid prototyping (RP has evolved as frontier technology in the recent times, which allows direct transformation of CAD files into functional prototypes where it tremendously reduces the lead time to produce physical prototypes necessary for design verification, fit, and functional analysis by generating the prototypes directly from the CAD data. Part quality in the rapid prototyping process is a function of build parameters such as hatch cure depth, layer thickness, orientation, and hatch spacing. Thus an attempt was made to identify, study, and optimize the process parameters governing the system which are related to part characteristics using Taguchi experimental design techniques quality. The part characteristics can be divided into physical part and mechanical part characteristics. The physical characteristics are surface finish, dimensional accuracy, distortion, layer thickness, hatch cure, and hatch file, whereas mechanical characteristics are flexural strength, ultimate tensile strength, and impact strength. Thus, this paper proposes to characterize the influence of the physical build parameters over the part quality. An L9 orthogonal array was designed with the minimum number of experimental runs with desired parameter settings and also by analysis tools such as ANOVA (analysis of variance. Establishment of experimentally verified correlations between the physical part characteristics and mechanical part characteristics to obtain an optimal process parameter level for betterment of part quality is obtained. The process model obtained by the empirical relation can be used to determine the strength of the prototype for the given set of parameters that shows the dependency of strength, which are essential for designers and RP machine users.

  8. Comparative visualization for parameter studies of dataset series.

    Science.gov (United States)

    Malik, Muhammad Muddassir; Heinzl, Christoph; Eduard Gröller, M

    2010-01-01

    This paper proposes comparison and visualization techniques to carry out parameter studies for the special application area of dimensional measurement using 3D X-ray computed tomography (3DCT). A dataset series is generated by scanning a specimen multiple times by varying parameters of an industrial 3DCT device. A high-resolution series is explored using our planar-reformatting-based visualization system. We present a novel multi-image view and an edge explorer for comparing and visualizing gray values and edges of several datasets simultaneously. Visualization results and quantitative data are displayed side by side. Our technique is scalable and generic. It can be effective in various application areas like parameter studies of imaging modalities and dataset artifact detection. For fast data retrieval and convenient usability, we use bricking of the datasets and efficient data structures. We evaluate the applicability of the proposed techniques in collaboration with our company partners.

  9. Machine learning phases of matter

    Science.gov (United States)

    Carrasquilla, Juan; Melko, Roger G.

    2017-02-01

    Condensed-matter physics is the study of the collective behaviour of infinitely complex assemblies of electrons, nuclei, magnetic moments, atoms or qubits. This complexity is reflected in the size of the state space, which grows exponentially with the number of particles, reminiscent of the `curse of dimensionality' commonly encountered in machine learning. Despite this curse, the machine learning community has developed techniques with remarkable abilities to recognize, classify, and characterize complex sets of data. Here, we show that modern machine learning architectures, such as fully connected and convolutional neural networks, can identify phases and phase transitions in a variety of condensed-matter Hamiltonians. Readily programmable through modern software libraries, neural networks can be trained to detect multiple types of order parameter, as well as highly non-trivial states with no conventional order, directly from raw state configurations sampled with Monte Carlo.

  10. Comparative study on discharge conditions in micro-hole electrical discharge machining of tungsten carbide (WC-Co) material

    Institute of Scientific and Technical Information of China (English)

    Hyun-Seok TAK; Chang-Seung HA; Dong-Hyun KIM; Ho-Jun LEE; Hae-June LEE; Myung-Chang KANG

    2009-01-01

    WC-Co is used widely in die and mold industries due to its unique combination of hardness, strength and wear-resistance. For machining difficult-to-cut materials, such as tungsten carbide, micro-electrical discharge machining(EDM) is one of the most effective methods for making holes because the hardness is not a dominant parameter in EDM. This paper describes the characteristics of the discharge conditions for micro-hole EDM of tungsten carbide with a WC grain size of 0.5μm and Co content of 12%. The EDM process was conducted by varying the condenser and resistance values. A R-C discharge EDM device using arc erosion for micro-hole machining was suggested. Furthermore, the characteristics of the developed micro-EDM were analyzed in terms of the electro-optical observation using an oscilloscope and field emission scanning electron microscope.

  11. Optimization of machining processes using pattern search algorithm

    Directory of Open Access Journals (Sweden)

    Miloš Madić

    2014-04-01

    Full Text Available Optimization of machining processes not only increases machining efficiency and economics, but also the end product quality. In recent years, among the traditional optimization methods, stochastic direct search optimization methods such as meta-heuristic algorithms are being increasingly applied for solving machining optimization problems. Their ability to deal with complex, multi-dimensional and ill-behaved optimization problems made them the preferred optimization tool by most researchers and practitioners. This paper introduces the use of pattern search (PS algorithm, as a deterministic direct search optimization method, for solving machining optimization problems. To analyze the applicability and performance of the PS algorithm, six case studies of machining optimization problems, both single and multi-objective, were considered. The PS algorithm was employed to determine optimal combinations of machining parameters for different machining processes such as abrasive waterjet machining, turning, turn-milling, drilling, electrical discharge machining and wire electrical discharge machining. In each case study the optimization solutions obtained by the PS algorithm were compared with the optimization solutions that had been determined by past researchers using meta-heuristic algorithms. Analysis of obtained optimization results indicates that the PS algorithm is very applicable for solving machining optimization problems showing good competitive potential against stochastic direct search methods such as meta-heuristic algorithms. Specific features and merits of the PS algorithm were also discussed.

  12. Machine Learning Data Imputation and Classification in a Multicohort Hypertension Clinical Study.

    Science.gov (United States)

    Seffens, William; Evans, Chad; Taylor, Herman

    2015-01-01

    Health-care initiatives are pushing the development and utilization of clinical data for medical discovery and translational research studies. Machine learning tools implemented for Big Data have been applied to detect patterns in complex diseases. This study focuses on hypertension and examines phenotype data across a major clinical study called Minority Health Genomics and Translational Research Repository Database composed of self-reported African American (AA) participants combined with related cohorts. Prior genome-wide association studies for hypertension in AAs presumed that an increase of disease burden in susceptible populations is due to rare variants. But genomic analysis of hypertension, even those designed to focus on rare variants, has yielded marginal genome-wide results over many studies. Machine learning and other nonparametric statistical methods have recently been shown to uncover relationships in complex phenotypes, genotypes, and clinical data. We trained neural networks with phenotype data for missing-data imputation to increase the usable size of a clinical data set. Validity was established by showing performance effects using the expanded data set for the association of phenotype variables with case/control status of patients. Data mining classification tools were used to generate association rules.

  13. Micro electrical discharge machining of small hole in TC4 alloy

    Institute of Scientific and Technical Information of China (English)

    LI Mao-sheng; CHI Guan-xin; WANG Zhen-long; WANG Yu-kui; DAI Li

    2009-01-01

    Aiming at machining deeply small holes in TC4 alloy, a series of experiments were carried out on a self-developed multi-axis micro electrical discharge machining (micro-EDM) machine tool. To improve machining efficiency and decrease relative wear of electrode in machining deeply small hole in TC4 alloy, many factors in micro-EDM, such as polarity, electrical parameters and supplying ways of working fluid were studied. Experimental results show that positive polarity machining is far superior to negative polarity machining; it is more optimal when open-circuit voltage, pulse width and pulse interval are 130 V, 5 μs and 15 μs respectively on the self developed multi-axis micro-EDM machine tool; when flushing method is applied in micro-EDM, the machining efficiency is higher and relative wear of electrode is smaller.

  14. Machinability of Green Powder Metallurgy Components: Part I. Characterization of the Influence of Tool Wear

    Science.gov (United States)

    Robert-Perron, Etienne; Blais, Carl; Pelletier, Sylvain; Thomas, Yannig

    2007-06-01

    The green machining process is an interesting approach for solving the mediocre machining behavior of high-performance powder metallurgy (PM) steels. This process appears as a promising method for extending tool life and reducing machining costs. Recent improvements in binder/lubricant technologies have led to high green strength systems that enable green machining. So far, tool wear has been considered negligible when characterizing the machinability of green PM specimens. This inaccurate assumption may lead to the selection of suboptimum cutting conditions. The first part of this study involves the optimization of the machining parameters to minimize the effects of tool wear on the machinability in turning of green PM components. The second part of our work compares the sintered mechanical properties of components machined in green state with other machined after sintering.

  15. Precision machine design

    CERN Document Server

    Slocum, Alexander H

    1992-01-01

    This book is a comprehensive engineering exploration of all the aspects of precision machine design - both component and system design considerations for precision machines. It addresses both theoretical analysis and practical implementation providing many real-world design case studies as well as numerous examples of existing components and their characteristics. Fast becoming a classic, this book includes examples of analysis techniques, along with the philosophy of the solution method. It explores the physics of errors in machines and how such knowledge can be used to build an error budget for a machine, how error budgets can be used to design more accurate machines.

  16. Study on the Fruit Grading Recognition System Based on Machine Vision

    Directory of Open Access Journals (Sweden)

    Huan Ma

    2015-07-01

    Full Text Available The study proposed that the current development of fruit industry requires the fast and efficient methods to test the varieties of fruits, which can combine the image processing and computer machine vision technology together to be applied in the field of fruit varieties detection, so as to be consistent with this new trend. At present, the determination of these traits were mainly depended on visual grading and manual measurement, which existed the problems such as: slow speed, low accuracy and poor objectivity and so on.

  17. Statistical Capability Study of a Helical Grinding Machine Producing Screw Rotors

    Science.gov (United States)

    Holmes, C. S.; Headley, M.; Hart, P. W.

    2017-08-01

    Screw compressors depend for their efficiency and reliability on the accuracy of the rotors, and therefore on the machinery used in their production. The machinery has evolved over more than half a century in response to customer demands for production accuracy, efficiency, and flexibility, and is now at a high level on all three criteria. Production equipment and processes must be capable of maintaining accuracy over a production run, and this must be assessed statistically under strictly controlled conditions. This paper gives numerical data from such a study of an innovative machine tool and shows that it is possible to meet the demanding statistical capability requirements.

  18. Automated Generation of Machine Verifiable and Readable Proofs: A Case Study of Tarski's Geometry

    OpenAIRE

    Stojanovic Durdevic, Sana; Narboux, Julien; Janicic, Predrag

    2015-01-01

    International audience; The power of state-of-the-art automated and interactive the-orem provers has reached the level at which a significant portion of non-trivial mathematical contents can be formalized almost fully automat-ically. In this paper we present our framework for the formalization of mathematical knowledge that can produce machine verifiable proofs (for different proof assistants) but also human-readable (nearly textbook-like) proofs. As a case study, we focus on one of the twent...

  19. A STUDY OF SEASONAL PHYSICOCHEMICAL PARAMETERS IN RIVER USMA

    Directory of Open Access Journals (Sweden)

    A. I. Ugwu

    2012-01-01

    Full Text Available Growing populations may put stresses on natural waters by impairing both the quality of the water and the hydrological budget. Abuja, being relatively a new city and the new Federal Capital Territory of Nigeria, has scarce physicochemical data on its water resources that could assist in making robust decision in mitigating the impact of human societies on natural waters; which may not only preserve natural areas, but improve the quality of life of her growing population. A Study of Seasonal Physicochemical Parameters in River Usuma, Abuja Nigeria was carried out between 2011 and 2012. The water quality was studied at seven sites at upstream and downstream among the towns traversed by the River. Physicochemical parameters of the samples were measured; moreover, possible sources of contamination were analyzed. The parameters measured include; sodium (Na, potassium (K, Biochemical Oxygen Demand (BOD; Dissolve Oxygen (DO, pH, temperature, Electrical Conductivity (EC, Total Dissolved Solids (TDS, Total Suspended Solids (TSS, total alkalinity, Total Phosphate (TP, Total Nitrate (TN, Total Sulphate (TS and Total Chloride (TC. The mean values of the measured parameters were compared with National Standard for Drinking Water Quality (NSDWQ and U.S. Environmental Protection Agency (USEPA standards. The findings show that all the physicochemical parameters measured were within the tolerable values except TSS that exceeded with the mean values of 6.8, 4.9 and 8.4 mg L-1 respectively for all the seasons. The values of EC and TDS posed a caution that anthropogenic activities are on the daily increase within the study area. The water resources data base which could have validated the observed values is scarce. Therefore, frequent monitoring of physicochemical parameters of Abuja water resources is imperative.

  20. Developing the Parameters of Scholarship in Postgraduate Coursework Studies

    Science.gov (United States)

    McLay, Allan F.

    2013-01-01

    Scholarship parameters, in relation to postgraduate coursework studies, are developed against the expectations of the Boyer classifications of scholarship (Boyer, 1990) with particular emphasis on the role of minor thesis development. An example is presented in which postgraduate coursework students are required to undertake a three semester minor…

  1. Study on Machining Properties of Eucalyptus urophylla×E.grandis:Ⅱ.Shaping, Boring, Mortising and Turning

    Institute of Scientific and Technical Information of China (English)

    HOU Xinyi; JIANG Xiaomei; GAO Jianmin; YIN Yafang

    2006-01-01

    The research method of this paper is based on the standards of American Society for Testing and Materials(ASTM).Four items that contain boring,mortising,shaping and turning are selected to study the machining properties of E. urophylla×E. grandis plantation wood.The reasons for machining defects are analyzed.The result shows that E.urophylla×E.grandis planted in South China is a good species with great potential for solid wood utilization.

  2. A Case Study of Employing A Single Server Nonpreemptive Priority Queuing Model at ATM Machine

    Directory of Open Access Journals (Sweden)

    Abdullah Furquan

    2015-08-01

    Full Text Available This paper discusses a case study of employing a single server nonpreemptivepriorityqueuing model [1]at ATM machine which originally operates on M/M/1 model. In this study we have taken two priority classes of people in following order:- .Priority class 1- woman .Priority class 2- man Sometimea long queue is formed at ATMmachine (single serverbut the bank management don’t have enough money to invest on installing new ATM machine.In this situation we want to apply single server nonpreemptive priority queuing model.The security guard at the ATM will divide the customers in two category and arrange the customers in the above said priority order Thuspriority class 1 people willreceive theatm service ahead of priority class 2 people.This will reduce the waiting time of priority class 1 people. Of course by doing this the waiting time of priority class 2will increase. This is ok as long as the increment in waiting time of priority class2 people is reasonable and within the tolerable limitof priority class 2people.This will be true when percentage of priority class 1 people is relatively less as compared to priority class 2 people To know the attitude and tolerable limit of priority class 2 people towards the single server non preemtive priority model a sample survey has been done on the incomingpriority class 2 population at the atm machine.Against this background, the queuing process is employed with emphasis to Poisson distribution to assess the waiting time. The data for this study was collected from primary source and is limited to ATM service point of state bank of India located at Ramesh chowk, Aurangabad, bihar, India.. The assistance of three colleague was sought in collecting the data. The Interarrival time and service time data was collected during busy working hours (i.e. 10.30am to 4:00pm during the first 60 days. A sample survey was done to know the attitude and tolerable limit of priority class 2people towards the single server

  3. Experimental Studies of the Transport Parameters of Warm Dense Matter

    Energy Technology Data Exchange (ETDEWEB)

    Chouffani, Khalid [Idaho State Univ., Pocatello, ID (United States)

    2014-12-01

    There is a need to establish fundamental properties of matter and energy under extreme physical conditions. Although high energy density physics (HEDP) research spans a wide range of plasma conditions, there is one unifying regime that is of particular importance and complexity: that of warm dense matter, the transitional state between solid state condensed matter and energetic plasmas. Most laboratory experimental conditions, including inertial confinement implosion, fall into this regime. Because all aspects of laboratory-created high-energy-density plasmas transition through the warm dense matter regime, understanding the fundamental properties to determine how matter and energy interact in this regime is an important aspect of major research efforts in HEDP. Improved understanding of warm dense matter would have significant and wide-ranging impact on HEDP science, from helping to explain wire initiation studies on the Sandia Z machine to increasing the predictive power of inertial confinement fusion modeling. The central goal or objective of our proposed research is to experimentally determine the electrical resistivity, temperature, density, and average ionization state of a variety of materials in the warm dense matter regime, without the use of theoretical calculations. Since the lack of an accurate energy of state (EOS) model is primarily due to the lack of experimental data, we propose an experimental study of the transport coefficients of warm dense matter.

  4. Study of process parameter on mist lubrication of Titanium (Grade 5) alloy

    Science.gov (United States)

    Maity, Kalipada; Pradhan, Swastik

    2017-02-01

    This paper deals with the machinability of Ti-6Al-4V alloy with mist cooling lubrication using carbide inserts. The influence of process parameter on the cutting forces, evolution of tool wear, surface finish of the workpiece, material removal rate and chip reduction coefficient have been investigated. Weighted principal component analysis coupled with grey relational analysis optimization is applied to identify the optimum setting of the process parameter. Optimal condition of the process parameter was cutting speed at 160 m/min, feed at 0.16 mm/rev and depth of cut at 1.6 mm. Effects of cutting speed and depth of cut on the type of chips formation were observed. Most of the chips forms were long tubular and long helical type. Image analyses of the segmented chip were examined to study the shape and size of the saw tooth profile of serrated chips. It was found that by increasing cutting speed from 95 m/min to 160 m/min, the free surface lamella of the chips increased and the visibility of the saw tooth segment became clearer.

  5. Statistical Machines for Trauma Hospital Outcomes Research: Application to the PRospective, Observational, Multi-Center Major Trauma Transfusion (PROMMTT Study.

    Directory of Open Access Journals (Sweden)

    Sara E Moore

    Full Text Available Improving the treatment of trauma, a leading cause of death worldwide, is of great clinical and public health interest. This analysis introduces flexible statistical methods for estimating center-level effects on individual outcomes in the context of highly variable patient populations, such as those of the PRospective, Observational, Multi-center Major Trauma Transfusion study. Ten US level I trauma centers enrolled a total of 1,245 trauma patients who survived at least 30 minutes after admission and received at least one unit of red blood cells. Outcomes included death, multiple organ failure, substantial bleeding, and transfusion of blood products. The centers involved were classified as either large or small-volume based on the number of massive transfusion patients enrolled during the study period. We focused on estimation of parameters inspired by causal inference, specifically estimated impacts on patient outcomes related to the volume of the trauma hospital that treated them. We defined this association as the change in mean outcomes of interest that would be observed if, contrary to fact, subjects from large-volume sites were treated at small-volume sites (the effect of treatment among the treated. We estimated this parameter using three different methods, some of which use data-adaptive machine learning tools to derive the outcome models, minimizing residual confounding by reducing model misspecification. Differences between unadjusted and adjusted estimators sometimes differed dramatically, demonstrating the need to account for differences in patient characteristics in clinic comparisons. In addition, the estimators based on robust adjustment methods showed potential impacts of hospital volume. For instance, we estimated a survival benefit for patients who were treated at large-volume sites, which was not apparent in simpler, unadjusted comparisons. By removing arbitrary modeling decisions from the estimation process and concentrating

  6. Overview of Sustainability Studies of CNC Machining and LAM of Stainless Steel

    Science.gov (United States)

    Nyamekye, Patricia; Leino, Maija; Piili, Heidi; Salminen, Antti

    Laser additive manufacturing (LAM), known also as 3D printing, is a powder bed fusion (PBF) type of additive manufacturing (AM) technology used to fabricate metal parts out of metal powder. The development of the technology from building prototype parts to functional parts has increased remarkably in 2000s. LAM of metals is promising technology that offers new opportunities to manufacturing and to resource efficiency. However, there is only few published articles about its sustainability. Aim in this study was to create supply chain model of LAM and CNC machining and create a methodology to carry out a life cycle inventory (LCI) data collection for these techniques. The methodology of the study was literature review and scenario modeling. The acquisition of raw material, production phase and transportations were used as basis of comparison. The modelled scenarios were fictitious and created for industries, like aviation and healthcare that often require swift delivery as well as customized parts. The results of this study showed that the use of LAM offers a possibility to reduce downtime in supply chains of spare parts and reduce part inventory more effectively than CNC machining. Also the gap between customers and business is possible to be shortened with LAM thus offering a possibility to reduce emissions due to less transportation. The results also indicated weight reduction possibility with LAM due to optimized part geometry which allow lesser amount of metallic powder to be used in making parts.

  7. Experimental and Statistical Study on Machinability of the Composite Materials with Metal Matrix Al/B4C/Graphite

    Science.gov (United States)

    Nas, Engin; Gökkaya, Hasan

    2017-10-01

    In this study, four types of Al/B4C/Graphite metal matrix composites (MMCs) were produced by means of a hot-pressing technique with reinforcement elements, B4C 8 wt pct and graphite (nickel coated) 0, 3, 5, and 7 wt pct. Machinability tests of MMC materials thus produced were conducted using four different cutting speeds (100, 140, 180, and 220 m/min), three different feed rates (0.1, 0.15, and 0.20 mm/rev), and a fixed cutting depth (0.5 mm), and the effects of the cutting parameters on the average surface roughness were examined. After the machinability tests, the height of the built-up edge (BUE) formed on the cutting tools related to the cutting speed and feed rate was measured. The test results were examined by designing a matrix according to the full factorial design and the average surface roughness, and the most important factors leading to formation of the BUE were analyzed by the analysis of variance (ANOVA). As a result of analysis, it was found that the lowest surface roughness value was with 7 wt pct graphite MMC material, while the highest was without graphite powder. Based on the statistical analysis results, it was observed that the most important factor affecting average surface roughness was the type of MMC material, the second most effective factor was the feed rate, and the least effective factor was the cutting speed. Furthermore, it was found that the most important factor affecting the formation of the BUE was the type of MMC material, the second most effective factor was the cutting speed, and the least effective factor was the feed rate.

  8. Correlation of Clinicohaematological Parameters in Paediatric Dengue: A Retrospective Study

    Directory of Open Access Journals (Sweden)

    Ramakrishna Pai Jakribettu

    2015-01-01

    Full Text Available Dengue is one of the arthropod-borne (arbo viral diseases transmitted by female mosquito Aedes aegypti. Dengue fever has a wide spectrum of clinical presentation ranging from flu-like illness to severe complicated stage of dengue hemorrhagic fever leading to mortality. This was a retrospective study conducted in a tertiary care hospital in Coastal Karnataka, South India, to know the correlation between the clinical presentation and haematological parameters in the paediatric cases presented with dengue symptoms. A total of 163 paediatric cases who presented fever and dengue-like illness were included in the study. Of which, 69 were confirmed dengue patients. Critical analysis showed that there was a significant difference in the haematological parameters like total leucocyte count, percent differential leucocyte count, and platelets count, in the erythrocyte sedimentation rate (P<0.05 to 0.0001. Additionally, when compared to nondengue patients, even the liver function and renal function parameters were significantly deranged (P<0.05 to 0.0001. Stratification based on NS1, IgG, and IgM showed significant alterations in the haematological, hepatic, and renal parameters. With respect to the treatment a small percentage of patients, that is, 8% (4 patients, required platelet transfusion as their counts went below 20,000/μL. Two patients succumbed to their illness while three required ICU stay.

  9. 双面抛光机内外齿圈齿比的研究%Study on Inner and Outer Gears Ratio of Double-Sided Polishing Machine

    Institute of Scientific and Technical Information of China (English)

    金程; 李伟

    2011-01-01

    双面抛光机作为超精密加工的重要设备,它的加工质量主要由工件表面加工轨迹和抛光机的振动所决定.作为抛光机的关键因素之一,工件表面的加工轨迹和内外齿圈齿比有着直接的联系.调整内外齿圈齿比是双面抛光机进行生产之前最重要的一件事.最新的研究表明,双面抛光机的振动也与内外齿圈齿比有很大的联系,但是具体的关联理论尚不明确.文章通过具体实验调整内外齿圈齿比得到1个优化的参数使双面抛光机的振动减小,为固定内外齿圈齿比双面抛光机的制造提供参考,同时在实验中,还发现了抛光机振动与加工轨迹的1个新的关系.%The double-sided polishing machine has been considered as important equipment for ultra-precision processing, its processing quality is mainly determined by processing trail on work-piece and the vibration of polishing machine. As the key factors to the machine, it is well known that the processing trail on work-piece is direct relative with the inner and outer gears ratio. Adjusting the ratio to make the trail even is the first thing to concern before polishing machine running. However, the latest study shows that the vibration of polishing machine is also interacted with the inner and outer gears ratio. The paper carried out experiment to get an optimal parameter through adjusting inner and outer gears ratio to reduce vibration of double-sided polishing machine, thus provided a reference for manufacture double-sided polishing machine with fixed inner and outer gears ratio. Mean while, a new relationship between the trail and the vibration was discovered.

  10. 激光加热辅助引弧微爆炸加工工程陶瓷的试验研究%Experimental Study on Laser Heating-assisted Micro-detonation of Striking Arc Machining Engineering Ceramics

    Institute of Scientific and Technical Information of China (English)

    田欣利; 李富强; 张保国; 王朋晓; 吴志远

    2012-01-01

    For the purpose of proving feasibility that laser heating-assisted machining technology can improve micro-detonation of striking arc machining quality and increase efficiency of machining ceramics, and exploring the influence law of the machining parameters on the process of machining, the experimental system of laser heating-assisted micro-detonation of striking arc machining is designed and influences of process parameters to the material removal rate and edge chipping are studied. The experiment results show that machining ceramics by laser heating-assisted micro-detonation of striking arc machining can increase the material removal rate and improve the edge chipping. The machining efficiency increases with increment of laser power and decreases with the size growth of light spot. With the increase of distance, it rises in advance and then reduces. The edge chipping decreases with the increase of laser power, decreases before increases with the size growth of light spot or the increment of distance. The results provide evidences for studying machining mechanism and choosing proper process parameters of laser heating-assisted micro-detonation of striking arc.%为验证激光加热辅助技术改善引弧微爆炸加工质量和提高加工效率的可行性,探索加工工艺参数对加工过程的影响规律,设计了激光加热辅助引弧微爆炸加工试验系统,并通过试验研究了工艺参数对材料去除率和崩碎的影响规律。试验结果表明:激光加热辅助引弧微爆炸加工陶瓷可以提高材料去除率,改善崩碎情况;加工效率随激光功率的增加而提高,随光斑尺寸的增大而降低,随距离的增加先提高后降低;崩碎随激光功率的增加而减少,随光斑尺寸的增大先减少后增多,随距离的增加先减少后增多。研究结果为激光加热辅助引弧微爆炸加工机理的研究和工艺参数的优化提供了参考依据。

  11. The FERMI @ Elettra Technical Optimization Study: PreliminaryParameter Set and Initial Studies

    Energy Technology Data Exchange (ETDEWEB)

    Byrd, John; Corlett, John; Doolittle, Larry; Fawley, William; Lidia, Steven; Penn, Gregory; Ratti, Alex; Staples, John; Wilcox,Russell; Wurtele, Jonathan; Zholents, Alexander

    2005-08-01

    The goal of the FERMI {at} Elettra Technical Optimization Study is to produce a machine design and layout consistent with user needs for radiation in the approximate ranges 100 nm to 40 nm, and 40 nm to 10 nm, using seeded FEL's. The Study will involve collaboration between Italian and US physicists and engineers, and will form the basis for the engineering design and the cost estimation.

  12. Radiation Hydrodynamic Parameter Study of Inertial Fusion Energy Reactor Chambers

    Science.gov (United States)

    Sacks, Ryan; Moses, Gregory

    2014-10-01

    Inertial fusion energy reactors present great promise for the future as they are capable of providing baseline power with no carbon footprint. Simulation work regarding the chamber response and first wall insult is performed with the 1-D radiation hydrodynamics code BUCKY. Simulation with differing chamber parameters are implemented to study the effect of gas fill, gas mixtures and chamber radii. Xenon and argon gases are of particular interest as shielding for the first wall due to their high opacity values and ready availability. Mixing of the two gases is an attempt to engineer a gas cocktail to provide the maximum amount of shielding with the least amount of cost. A parameter study of different chamber radii shows a consistent relationship with that of first wall temperature (~1/r2) and overpressure (~1/r3). This work is performed under collaboration with Lawrence Livermore National Laboratory.

  13. Studying the $\\rho$ resonance parameters with staggered fermions

    CERN Document Server

    Fu, Ziwen

    2016-01-01

    We deliver a lattice study of $\\rho$ resonance parameters with p-wave $\\pi\\pi$ scattering phases, which are extracted by finite-size methods at one center-of-mass frame and four moving frames for six MILC lattice ensembles with pion masses ranging from $346$ to $ 176$ MeV. The effective range formula is applied to describe the scattering phases as a function of the energy covering the resonance region, this allows us to extract $\\rho$ resonance parameters and to investigate the quark-mass dependence. Lattice studies with three flavors of the Asqtad-improved staggered fermions enable us to use the moving-wall source technique on large lattice spatial dimensions ($L=64$) and small light $u/d$ quarks. Numerical computations are carried out at two lattice spacings, $a \\approx 0.12$ and $0.09$ fm.

  14. Studying the ρ resonance parameters with staggered fermions

    Science.gov (United States)

    Fu, Ziwen; Wang, Lingyun

    2016-08-01

    We deliver a lattice study of ρ resonance parameters with p -wave π π scattering phases, which are extracted by finite-size methods at one center-of-mass frame and four moving frames for six lattice ensembles from the MILC Collaboration with pion masses ranging from 346 to 176 MeV. The effective range formula is applied to describe the scattering phases as a function of the energy covering the resonance region; this allows us to extract ρ resonance parameters and to investigate the quark-mass dependence. Lattice studies with three flavors of Asqtad-improved staggered fermions enable us to use the moving-wall source technique on large lattice spatial dimensions (L =64 ) and small light u /d quarks. Numerical computations are carried out at two lattice spacings, a ≈0.12 and 0.09 fm.

  15. Comparative Study on Electrical Discharge Machining of Ultrafine-Grain Al, Cu, and Steel

    Science.gov (United States)

    Mahdieh, Mohammad Sajjad; Mahdavinejad, RamezanAli

    2016-12-01

    Recently, manufacturing of industrial parts out of ultrafine-grain (UFG) materials became prevalent due to their lightweight and high strength. Machining processes such as electrical discharge machining (EDM) are necessary to produce parts with accurate dimensions and tolerance. On the other hand, recast layer, heat-affected zone (HAZ), and the micro-cracks are the effects of the EDM process, reducing the surface integrity of the workpieces. These undesirable effects are more noticeable on the UFG materials because of the excess energy stored in them. This excess stored energy is because of the high strain and stress imposed on the microstructure of UFG material during severe plastic deformation processes. In this article, a comparative study is conducted about the effects of the EDM process on three applicable UFG materials: aluminum, steel, and copper. These UFG materials are produced by equal channel angular pressing, which is a well-known method in producing UFG materials. The surface integrity factors including thickness of recast layer and HAZ, cracks density, micro-hardness, and surface roughness are measured and investigated via optical microscopy, scanning electron microscopy, X-ray diffraction technique, roughness tester, and micro-hardness tester. Results show that after the EDM process, thicker recast layer, and HAZ, more cracks density and more microstructural changes are observed among the UFG aluminum samples than among the copper and steel samples.

  16. Malware Propagation on Social Time Varying Networks: A Comparative Study of Machine Learning Frameworks

    Directory of Open Access Journals (Sweden)

    A.A. Ojugo

    2014-08-01

    Full Text Available Significant research into the logarithmic analysis of complex networks yields solution to help minimize virus spread and propagation over networks. This task of virus propagation is been a recurring subject, and design of complex models will yield modeling solutions used in a number of events not limited to and include propagation, dataflow, network immunization, resource management, service distribution, adoption of viral marketing etc. Stochastic models are successfully used to predict the virus propagation processes and its effects on networks. The study employs SI-models for independent cascade and the dynamic models with Enron dataset (of e-mail addresses and presents comparative result using varied machine models. Study samples 25,000 emails of Enron dataset with Entropy and Information Gain computed to address issues of blocking targeting and extent of virus spread on graphs. Study addressed the problem of the expected spread immunization and the expected epidemic spread minimization; but not the epidemic threshold (for space constraint.

  17. New Predictive Hematologic Parameters in Chronic Rhinosinusitis: A Multicenter Study

    Directory of Open Access Journals (Sweden)

    Beyhan Yilmaz

    2016-12-01

    Full Text Available INTRODUCTION: Our aim was to investigate whether Neutrophil-Lymphocyte Ratio (NLR, Platelet-Lymphocyte Ratio (PLR and Mean Platelet Volume parameters (MPV may be utilized as inflammatory markers of chronic rhinosinusitis with nasal polyps (CRSwNP and without nasal polyps (CRSsNP. METHODS: This retrospective multicenter study was performed on 647 patients who were underwent endoscopic sinus surgery. Clinical and preoperative laboratory data of patients were screened retrospectively. The study and control groups were compared for the parameters NLR, PLR, MPV, neutrophils, lymphocytes, and platelets. RESULTS: Of the 647 patients, 313 were in the CRSwNP group, 334 were in the CRSsNP group. There were 93 individuals in the control group. NLR and PLR levels were significantly higher in study groups compared to control group (p < 0.001. But no statistically significant differences were identified between CRSwNP group and CRSsNP group in terms of NLR, PLR, MPV levels. DISCUSSION AND CONCLUSION: We speculate that high NLR and PLR values may be useful inflammatory indicator for CRSwNP and CRSsNP groups. We believe these parameters will have increasing clinical use in the future on treatment options and prognosis.

  18. Study on mechanical parameters of fractured rock masses

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    The equivalent strength parameters of fractured rock masses are prerequisite for stability analysis of geotechnical engineering projects constructed in fractured rock masses which are encountered frequently in western china.Based on generated mesh of fractured rock masses,combined with statistic damage constitutive model of intact rock and damage model of structural plane,progressive failure of fractured rock masses is studied using finite element method(FEM) .Furthermore,Scale effect and anisotropy of compressive strength of fractured rock masses are studied.Study results show that the strength decreases and tend towards stability rapidly from intact rock to fractured rock masses,and the anisotropy of strength of fractured rock masses is not significant.At last,based on numerical simulation conducted on 10 m scale rock masses under different confining pressures,the equivalent strength parameters of fractured rock masses are gained and the results are compared with Hoek-Brown criteria.The method developed is helpful for determination of strength parameters of fractured rock masses.

  19. Phase segmentation of X-ray computer tomography rock images using machine learning techniques: an accuracy and performance study

    Science.gov (United States)

    Chauhan, Swarup; Rühaak, Wolfram; Anbergen, Hauke; Kabdenov, Alen; Freise, Marcus; Wille, Thorsten; Sass, Ingo

    2016-07-01

    Performance and accuracy of machine learning techniques to segment rock grains, matrix and pore voxels from a 3-D volume of X-ray tomographic (XCT) grayscale rock images was evaluated. The segmentation and classification capability of unsupervised (k-means, fuzzy c-means, self-organized maps), supervised (artificial neural networks, least-squares support vector machines) and ensemble classifiers (bragging and boosting) were tested using XCT images of andesite volcanic rock, Berea sandstone, Rotliegend sandstone and a synthetic sample. The averaged porosity obtained for andesite (15.8 ± 2.5 %), Berea sandstone (16.3 ± 2.6 %), Rotliegend sandstone (13.4 ± 7.4 %) and the synthetic sample (48.3 ± 13.3 %) is in very good agreement with the respective laboratory measurement data and varies by a factor of 0.2. The k-means algorithm is the fastest of all machine learning algorithms, whereas a least-squares support vector machine is the most computationally expensive. Metrics entropy, purity, mean square root error, receiver operational characteristic curve and 10 K-fold cross-validation were used to determine the accuracy of unsupervised, supervised and ensemble classifier techniques. In general, the accuracy was found to be largely affected by the feature vector selection scheme. As it is always a trade-off between performance and accuracy, it is difficult to isolate one particular machine learning algorithm which is best suited for the complex phase segmentation problem. Therefore, our investigation provides parameters that can help in selecting the appropriate machine learning techniques for phase segmentation.

  20. Machine learning with neural networks - a case study of estimating thermal conductivity with ancient well-log data

    Science.gov (United States)

    Harrison, Benjamin; Sandiford, Mike; McLaren, Sandra

    2016-04-01

    Supervised machine learning algorithms attempt to build a predictive model using empirical data. Their aim is to take a known set of input data along with known responses to the data, and adaptively train a model to generate predictions for new data inputs. A key attraction to their use is the ability to perform as function approximators where the definition of an explicit relationship between variables is infeasible. We present a novel means of estimating thermal conductivity using a supervised self-organising map algorithm, trained on about 150 thermal conductivity measurements, and using a suite of five electric logs common to 14 boreholes. A key motivation of the study was to supplement the small number of direct measurements of thermal conductivity with the decades of borehole data acquired in the Gippsland Basin to produce more confident calculations of surface heat flow. A previous attempt to generate estimates from well-log data in the Gippsland Basin using classic petrophysical log interpretation methods was able to produce reasonable synthetic thermal conductivity logs for only four boreholes. The current study has extended this to a further ten boreholes. Interesting outcomes from the study are: the method appears stable at very low sample sizes (< ~100); the SOM permits quantitative analysis of essentially qualitative uncalibrated well-log data; and the method's moderate success at prediction with minimal effort tuning the algorithm's parameters.

  1. STUDI PARAMETER OSEANOGRAFI DI PERAIRAN SELAT MADURA KABUPATEN BANGKALAN

    Directory of Open Access Journals (Sweden)

    Aries Dwi Siswanto

    2014-04-01

    Full Text Available Fenomena dan dinamika di perairan laut menjadi salah satu hal penting yang harus dipertimbangkan dalam berbagai aktifitas yang dilakukan dilingkungan perairan laut. Pergerakan massa air laut dinamis sepanjang waktu memberikan pengaruh terhadap dinamika perairan. Angin menjadi salah satu parameter penting yang berpengaruh terhadap fenomena dan dinamika perairan laut. Beberapa parameter oseanografi yang dipengaruhi oleh angin adalah arus dan gelombang. Parameter lainnya yaitu pasang surut, yang dipengaruhi oleh letak bulan dan matahari menjadikan dinamika lautan semakin kompleks. Arus, gelombang, dan pasang surut diduga berpangaruh signifikan terhadap kompleksitas di lautan. Tujuan dari penelitian ini adalah untuk mengkaji karakteristik parameter oseanografi di perairan Selat Madura, Kabupaten Bangkalan. Data utama penelitian berupa data arus, pasang surut, dan gelombang. Data pasang surut diperoleh dari BMKG Perak, Surabaya. Data yang digunakan adalah data bulan September 2012. Data arus dan gelombang diolah secara deskriptif untuk mengetahui dominasi arah dan kecepatan, sedangkan data pasut diolah menggunakan metode Admiralty untuk mengetahui tipe pasang surut perairan. Hasil analisa menunjukkan kisaran arus relatif kecil (0,28-3.54 cm/detik dengan arah Timur laut, Timur dan Tenggara. Karakteristik gelombang menunjukkan kecenderungan semakin besar pada setiap minggunya dengan pola harian cenderung stabil sepanjang hari. Tipe pasang surut campuran condong ke harian ganda.Kata Kunci: hidrooseanografi, total suspended solid (TSS STUDY OF OCEANOGRAPHYC PARAMETERS IN THE MADURA STRAIT WATERS OF BANGKALAN DISTRICTABSTRACTPhenomenon and the dynamics in marine waters become important to be considered in some activities. The movement of sea water mass is dynamic along the time which gives influence toward waters dynamics. Wind become one of the important parameters influenced the phenomenon and sea waters dynamics. Some oceanography parameters were

  2. Central magnetic cooling and refrigeration machines (chiller) and their assessment. A feasibility study - Final report

    Energy Technology Data Exchange (ETDEWEB)

    Egolf, P. W.; Gonin, C. [University of Applied Sciences of Western Switzerland, HEIG-VD, Yverdon-les Bains (Switzerland); Kitanovski, A. [University of Ljubljana, Ljubljana (Slovenia)

    2010-03-15

    This final report for the Swiss Federal Office of Energy (SFOE) presents the results of a feasibility study made concerning magnetic cooling and refrigeration machines. This report presents a comprehensive thermodynamic and economic analysis of applications of rotary magnetic chillers. The study deals with magnetic chillers based on permanent magnets and superconducting magnets, respectively. The numerical design of permanent magnet assemblies with different magnetic flux densities is discussed. The authors note that superconducting magnetic chillers are feasible only in large-scale applications with over 1 MW of cooling power. This report describes new ideas for magnetic refrigeration technologies, which go beyond the state of the art. They show potential for a substantial reduction of costs and further improvements in efficiency. Rotary magnetic liquid chillers with 'wavy' structures and using micro tubes are discussed, as are superconducting magnetic chillers and future magneto-caloric technologies.

  3. Factors discriminating inventory management performance: An exploratory study of Indian machine tool SMEs

    Directory of Open Access Journals (Sweden)

    Rajeev Narayana Pillai

    2014-06-01

    Full Text Available Purpose: There are many kinds of methods to evaluate the inventory management and economic performance of small and medium enterprises, but they still have some distinct shortcomings. In order to achieve a better evaluation result, we put forward a new model based on the evidences from developing country like India.Approach: This survey study, mainly based on the evidences from machine tool SMEs in India uses statistical methods to avoid the drawbacks of qualitative techniques.Findings: Through empirical data, it is established that ‘technology’ is not the only concern, but other factors related to human resource, economic, organizational and behavioral aspects of SMEs are also vital in improving their IM performance.Originality: This study combines the role of factors such as managerial, technological, economical and contingency together for the first time in the context of SMEs.

  4. Cosmic ray driven dynamo in galactic disks. A parameter study

    CERN Document Server

    MichałHanasz,; Kowal, Grzegorz; Lesch, Harald

    2008-01-01

    We present a parameter study of the magnetohydrodynamical dynamo driven by cosmic rays in the interstellar medium (ISM) focusing on the efficiency of magnetic field amplification and the issue of energy equipartition between magnetic, kinetic and cosmic ray (CR) energies. We perform numerical CR-MHD simulations of the ISM using the extended version of ZEUS-3D code in the shearing box approximation and taking into account the presence of Ohmic resistivity, tidal forces and vertical disk gravity. CRs are supplied in randomly distributed supernova (SN) remnants and are described by the diffusion-advection equation, which incorporates an anisotropic diffusion tensor. The azimuthal magnetic flux and total magnetic energy are amplified depending on a particular choice of model parameters. We find that the most favorable conditions for magnetic field amplification correspond to magnetic diffusivity of the order of $3\\times 10^{25} \\cm^2\\s^{-1}$, SN rates close to those observed in the Milky Way, periodic SN activity...

  5. Study of some parameters interstellar transport using of magnetic umbrella

    CERN Document Server

    Čermák, Martin

    2013-01-01

    Interstellar transport is an object of interest in many sci-fi stories. In history a lot of sci-fi predictions have turned into reality, such as communications satellites, deep-sea submarines and journies to the moon. In this work we study some physical parameters of a space ship which uses a magnetic umbrella. Our spaceship generates a magnetic field in its neighborhood and captures charged protons into a magnetic trap. These particles are taken into a fusion reactor. The obtained energy and waste in form of helium are used as a fuel in an ion engine. With the help of elementary physics we can work out the basic physical parameters of the ship, e.g. maximal velocity, acceleration of the ship or acceleration time period.

  6. Key Parameter Study of 65Mn Steel in Warm Rolling

    Directory of Open Access Journals (Sweden)

    Zhi-Jie Li

    2013-02-01

    Full Text Available For study warm rolling process, warm compression experiment of ferrite combined with pearlite colony was conducted using the Gleeble-3500 thermal/mechanical simulator system. The warm deformation was carried out at temperature (500~700°C and the strain rate (0.001~10/sec. Based on the flow stress data, the key parameter was calculated. The results show that the warm-working process of carbon steel conforms to hyperbolic sine equation. The relationship of and T could be described by parameter Z (temperature compensation of strain rate factor. The value of apparent n (stress index and Q (deformation activation energy was calculated, the draught pressure calculated was 1.87×104 t during warm rolling process at 600°C.

  7. Sustainable machining

    CERN Document Server

    2017-01-01

    This book provides an overview on current sustainable machining. Its chapters cover the concept in economic, social and environmental dimensions. It provides the reader with proper ways to handle several pollutants produced during the machining process. The book is useful on both undergraduate and postgraduate levels and it is of interest to all those working with manufacturing and machining technology.

  8. Optimization of Multiple Responses of Ultrasonic Machining (USM Process: A Comparative Study

    Directory of Open Access Journals (Sweden)

    Rina Chakravorty

    2013-04-01

    Full Text Available Ultrasonic machining (USM process has multiple performance measures, e.g. material removal rate (MRR, tool wear rate (TWR, surface roughness (SR etc., which are affected by several process parameters. The researchers commonly attempted to optimize USM process with respect to individual responses, separately. In the recent past, several systematic procedures for dealing with the multi-response optimization problems have been proposed in the literature. Although most of these methods use complex mathematics or statistics, there are some simple methods, which can be comprehended and implemented by the engineers to optimize the multiple responses of USM processes. However, the relative optimization performance of these approaches is unknown because the effectiveness of different methods has been demonstrated using different sets of process data. In this paper, the computational requirements for four simple methods are presented, and two sets of past experimental data on USM processes are analysed using these methods. The relative performances of these methods are then compared. The results show that weighted signal-to-noise (WSN ratio method and utility theory (UT method usually give better overall optimisation performance for the USM process than the other approaches.

  9. A study on fluid flow simulation in the cooling systems of machine tools

    Science.gov (United States)

    Olaru, I.

    2016-08-01

    This paper aims analysing the type of coolants and the correct choice of that as well as the dispensation in the processing area to control the temperature resulted from the cutting operation and the choose of the cutting operating modes. A high temperature in the working area over a certain amount can be harmful in terms of the quality of resulting surface and that could have some influences on the life of the cutting tool. The coolant chosen can be a combination of different cooling fluids in order to achieve a better cooling of the cutting area at the same time for carrying out the proper lubrication of that area. The fluid flow parameters of coolant can be influenced by the nature of the fluid or fluids used, the geometry of the nozzle used which generally has a convergent-divergent geometry in order to achieve a better dispersion of the coolant / lubricant on the area to be processed. A smaller amount of fluid is important in terms of the economy lubricant, because they are quite expensive. A minimal amount of lubricant may have a better impact on the environment and the health of the operator because the coolants in contact with overheated machined surface may develop a substantial amount of these gases that are not always beneficial to health.

  10. GEANT4 for breast dosimetry: parameters optimization study.

    Science.gov (United States)

    Fedon, C; Longo, F; Mettivier, G; Longo, R

    2015-08-21

    Mean glandular dose (MGD) is the main dosimetric quantity in mammography. MGD evaluation is obtained by multiplying the entrance skin air kerma (ESAK) by normalized glandular dose (DgN) coefficients. While ESAK is an empirical quantity, DgN coefficients can only be estimated with Monte Carlo (MC) methods. Thus, a MC parameters benchmark is needed for effectively evaluating DgN coefficients. GEANT4 is a MC toolkit suitable for medical purposes that offers to the users several computational choices. In this work we investigate the GEANT4 performances testing the main PhysicsLists for medical applications. Four electromagnetic PhysicsLists were implemented: the linear attenuation coefficients were calculated for breast glandularity 0%, 50%, 100% in the energetic range 8-50 keV and DgN coefficients were evaluated. The results were compared with published data. Fit equations for the estimation of the G-factor parameter, introduced by the literature for converting the dose delivered in the heterogeneous medium to that in the glandular tissue, are proposed and the application of this parameter interaction-by-interaction or retrospectively is discussed. G4EmLivermorePhysicsList shows the best agreement for the linear attenuation coefficients both with theoretical values and published data. Moreover, excellent correlation factor (r2>0.99) is found for the DgN coefficients with the literature. The final goal of this study is to identify, for the first time, a benchmark of parameters that could be useful for future breast dosimetry studies with GEANT4.

  11. Machining of Metal Matrix Composites

    CERN Document Server

    2012-01-01

    Machining of Metal Matrix Composites provides the fundamentals and recent advances in the study of machining of metal matrix composites (MMCs). Each chapter is written by an international expert in this important field of research. Machining of Metal Matrix Composites gives the reader information on machining of MMCs with a special emphasis on aluminium matrix composites. Chapter 1 provides the mechanics and modelling of chip formation for traditional machining processes. Chapter 2 is dedicated to surface integrity when machining MMCs. Chapter 3 describes the machinability aspects of MMCs. Chapter 4 contains information on traditional machining processes and Chapter 5 is dedicated to the grinding of MMCs. Chapter 6 describes the dry cutting of MMCs with SiC particulate reinforcement. Finally, Chapter 7 is dedicated to computational methods and optimization in the machining of MMCs. Machining of Metal Matrix Composites can serve as a useful reference for academics, manufacturing and materials researchers, manu...

  12. Diagnosis of Dementia by Machine learning methods in Epidemiological studies: a pilot exploratory study from south India.

    Science.gov (United States)

    Bhagyashree, Sheshadri Iyengar Raghavan; Nagaraj, Kiran; Prince, Martin; Fall, Caroline H D; Krishna, Murali

    2017-07-11

    There are limited data on the use of artificial intelligence methods for the diagnosis of dementia in epidemiological studies in low- and middle-income country (LMIC) settings. A culture and education fair battery of cognitive tests was developed and validated for population based studies in low- and middle-income countries including India by the 10/66 Dementia Research Group. We explored the machine learning methods based on the 10/66 battery of cognitive tests for the diagnosis of dementia based in a birth cohort study in South India. The data sets for 466 men and women for this study were obtained from the on-going Mysore Studies of Natal effect of Health and Ageing (MYNAH), in south India. The data sets included: demographics, performance on the 10/66 cognitive function tests, the 10/66 diagnosis of mental disorders and population based normative data for the 10/66 battery of cognitive function tests. Diagnosis of dementia from the rule based approach was compared against the 10/66 diagnosis of dementia. We have applied machine learning techniques to identify minimal number of the 10/66 cognitive function tests required for diagnosing dementia and derived an algorithm to improve the accuracy of dementia diagnosis. Of 466 subjects, 27 had 10/66 diagnosis of dementia, 19 of whom were correctly identified as having dementia by Jrip classification with 100% accuracy. This pilot exploratory study indicates that machine learning methods can help identify community dwelling older adults with 10/66 criterion diagnosis of dementia with good accuracy in a LMIC setting such as India. This should reduce the duration of the diagnostic assessment and make the process easier and quicker for clinicians, patients and will be useful for 'case' ascertainment in population based epidemiological studies.

  13. 多监测参数和控制方式的种子设备控制系统%A Control System of Seeds Processing Machine with Multiple Monitoring Parameters and Control Modes

    Institute of Scientific and Technical Information of China (English)

    侯安东; 陈大跃; 赵春宇

    2014-01-01

    传统的种子处理设备还停留在以电气控制、手动操作为主的阶段,系统自动检测、控制的参量较少,控制过程的稳定性、可靠性和控制效果难以满足指标要求[1-2];且传统设备人机交互的接口单一,方式落后,用户使用过程中存在着很多不便[3]。为此,介绍了一种基于 ARM 平台的种子风力筛选机智能控制系统。该系统采用新型HMI 触摸屏为用户提供一个人性化的人机交互界面,并且设计了一款遥控器允许用户实现多角度远距离调试设备。系统可对多种参量进行实时动态监控,实现设备的精确自动控制。实践证明,该系统可靠性高,实用性强,且具有非常好的用户体验,已成功应用于种子风力筛选机。%Traditional control system of seeds processing machine still rests on the stage of electrical control and manual manipulation which doesn ’ s have enough parameters to monitor and control , so its stability , reliability and control effect can’t meet the previous guideposts[1-2].In addition, traditional machine’s man-machine interactive interface is sim-plex, behindhand and discommodious .It’ s difficult for users to operate equipments expediently [3] .This article intro-duces an intelligent control system of seeds wind-screening machine based on ARM .New type HMI touch screen could afford users a humanized human-machine interactive interface and wireless module allows users to control the machine from different angles.Enough control parameters ensure that automatic control of seeds processing machine could be rea lized .Practice indicates that this system is reliable and pragmatic and has a very good user experience which has been applied to seeds wind-screening machine succesfully .

  14. Influence of bone density on implant stability parameters and implant success: a retrospective clinical study

    Directory of Open Access Journals (Sweden)

    McGlumphy Edwin A

    2008-11-01

    Full Text Available Abstract Background The aim of the present clinical study was to determine the local bone density in dental implant recipient sites using computerized tomography (CT and to investigate the influence of local bone density on implant stability parameters and implant success. Methods A total of 300 implants were placed in 111 patients between 2003 and 2005. The bone density in each implant recipient site was determined using CT. Insertion torque and resonance frequency analysis were used as implant stability parameters. The peak insertion torque values were recorded with OsseoCare machine. The resonance frequency analysis measurements were performed with Osstell instrument immediately after implant placement, 6, and 12 months later. Results Of 300 implants placed, 20 were lost, meaning a survival rate of %. 93.3 after three years (average 3.7 ± 0.7 years. The mean bone density, insertion torque and RFA recordings of all 300 implants were 620 ± 251 HU, 36.1 ± 8 Ncm, and 65.7 ± 9 ISQ at implant placement respectively; which indicated statistically significant correlations between bone density and insertion torque values (p Conclusion CT is a useful tool to determine the bone density in the implant recipient sites, and the local bone density has a prevailing influence on primary implant stability, which is an important determinant for implant success.

  15. Studies on the key parameters in segmental lining design

    Institute of Scientific and Technical Information of China (English)

    Zhenchang Guan; Tao Deng; Gang Wang; Yujing Jiang

    2015-01-01

    The uniform ring model and the shell-spring model for segmental lining design are reviewed in this article. The former is the most promising means to reflect the real behavior of segmental lining, while the latter is the most popular means in practice due to its simplicity. To understand the relationship and the difference between these two models, both of them are applied to the engineering practice of Fuzhou Metro Line I, where the key parameters used in both models are described and compared. The effective ratio of bending rigidity h reflecting the relative stiffness between segmental lining and surrounding ground and the transfer ratio of bending moment x reflecting the relative stiffness between segment and joint, which are two key parameters used in the uniform ring model, are especially emphasized. The reasonable values for these two key parameters are calibrated by comparing the bending moments calculated from both two models. Through case studies, it is concluded that the effective ratio of bending rigidity h increases significantly with good soil properties, increases slightly with increasing overburden, and decreases slightly with increasing water head. Meanwhile, the transfer ratio of bending moment x seems to only relate to the properties of segmental lining itself and has a minor relation with the ground conditions. These results could facilitate the design practice for Fuzhou Metro Line I, and could also provide some references to other projects with respect to similar scenarios.

  16. An evaluation of the machinability of nitinol shape memory alloy by electrochemical polishing

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Eun Sang; Shin, Tae Hee [Inha University, Incheon (Korea, Republic of)

    2011-04-15

    Nitinol, a shape memory alloy (SMA), is manufactured from titanium and nickel, and is employed in various fields for use in devices such as micro sensors, ultra-precision devices and satellite wings. It is also highly recommended as a material in medical stents for insertion into the human body because it has excellent organic compatibility. However, because they are intended to be inserted into the human body, products such as medical stents require a high-quality surface. Because nitinol has more of the characteristics of titanium than of nickel, one of its drawbacks is that heat generated in nitinol during machining is not discharged smoothly and inner stress occurs when traditional machining methods are used. To overcome this difficulty, various non-traditional machining methods, including non-contact machining, have been investigated for use with nitinol. To further explore non-traditional machining methods that may be appropriate for use with nitinol, this study investigates the application of electrochemical polishing to the machining of nitinol. Characteristics of the electrochemical polishing (EP), a representative non-traditional machining, for nitinol SMA are studied. Nitinol SMA of the EP machining parameters such as electrolyte composition, applied current, machining time and inter electrode gap (IEG) are researched and the machined surface state is analyzed according to each parameters parameter. So, the most suitable EP machining conditions for nitinol SMA are derived.

  17. The Investigation of EDM Parameters on Electrode Wear Ratio

    Directory of Open Access Journals (Sweden)

    Reza Atefi

    2012-05-01

    Full Text Available Electrical Discharge Machining (EDM is a well-established machining option for manufacturing geometrically complex or hard material parts that are extremely difficult-to-machine by conventional machining processes. The non-contact machining technique has been continuously evolving from a mere tool and die making process. In this study, the influence of different electro discharge machining parameters (current, pulse on-time, pulse off-time, arc voltage on the electrode wear ratio as a result of application copper electrode to hot work steel DIN1.2344 has been investigated. Design of the experiment was chosen as full factorial. Artificial neural network has been used to choose proper machining parameters and to reach certain electrode wear ratio. Finally a hybrid model has been designed to reduce the artificial neural network errors. The experiment results indicated a good performance of proposed method in optimization of such a complex and non-linear problems.

  18. Application of machine learning algorithms to the study of noise artifacts in gravitational-wave data

    Science.gov (United States)

    Biswas, Rahul; Blackburn, Lindy; Cao, Junwei; Essick, Reed; Hodge, Kari Alison; Katsavounidis, Erotokritos; Kim, Kyungmin; Kim, Young-Min; Le Bigot, Eric-Olivier; Lee, Chang-Hwan; Oh, John J.; Oh, Sang Hoon; Son, Edwin J.; Tao, Ye; Vaulin, Ruslan; Wang, Xiaoge

    2013-09-01

    The sensitivity of searches for astrophysical transients in data from the Laser Interferometer Gravitational-wave Observatory (LIGO) is generally limited by the presence of transient, non-Gaussian noise artifacts, which occur at a high enough rate such that accidental coincidence across multiple detectors is non-negligible. These “glitches” can easily be mistaken for transient gravitational-wave signals, and their robust identification and removal will help any search for astrophysical gravitational waves. We apply machine-learning algorithms (MLAs) to the problem, using data from auxiliary channels within the LIGO detectors that monitor degrees of freedom unaffected by astrophysical signals. Noise sources may produce artifacts in these auxiliary channels as well as the gravitational-wave channel. The number of auxiliary-channel parameters describing these disturbances may also be extremely large; high dimensionality is an area where MLAs are particularly well suited. We demonstrate the feasibility and applicability of three different MLAs: artificial neural networks, support vector machines, and random forests. These classifiers identify and remove a substantial fraction of the glitches present in two different data sets: four weeks of LIGO’s fourth science run and one week of LIGO’s sixth science run. We observe that all three algorithms agree on which events are glitches to within 10% for the sixth-science-run data, and support this by showing that the different optimization criteria used by each classifier generate the same decision surface, based on a likelihood-ratio statistic. Furthermore, we find that all classifiers obtain similar performance to the benchmark algorithm, the ordered veto list, which is optimized to detect pairwise correlations between transients in LIGO auxiliary channels and glitches in the gravitational-wave data. This suggests that most of the useful information currently extracted from the auxiliary channels is already described

  19. Technical and Symbolic Knowledge in CNC Machining: A Study of Technical Workers of Different Backgrounds.

    Science.gov (United States)

    Martin, Laura M. W.; Beach, King

    Performances of 45 individuals with varying degrees of formal and informal training in machining and programming were compared on tasks designed to tap intellectual changes that may occur with the introduction of computer numerical control (CNC). Participants--30 machinists, 8 machine operators, and 7 engineers--were asked background questions and…

  20. Progress in the bionic study on anti-adhesion and resistance reduction of terrain machines

    Institute of Scientific and Technical Information of China (English)

    REN LuQuan

    2009-01-01

    The theoretical studies of bionics of machinery have great scientific significance, and the development of bionic machines has large practical values in the field of engineering and technology. Through the rigorous selection process of evolution, the survived living organisms have successfully developed outstanding abilities to adapt to their surroundings and to reproduce their offspring. In this review, we interpreted the fundamental principles of anti-adhesion and anti-resistance of soil animals by reviewing the current status in this research field and summarizing the work of the research group at Jilin Uni-versity of China in the past decades. The principles and technologies used in morphology bionics, electric-osmosis bionics, flexibility bionics, configuration bionics and coupling bionics were examined. Finally, the applications of the engineering bionics and their extensive prospects were introduced.

  1. Progress in the bionic study on anti-adhesion and resistance reduction of terrain machines

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    The theoretical studies of bionics of machinery have great scientific significance, and the development of bionic machines has large practical values in the field of engineering and technology. Through the rigorous selection process of evolution, the survived living organisms have successfully developed outstanding abilities to adapt to their surroundings and to reproduce their offspring. In this review,we interpreted the fundamental principles of anti-adhesion and anti-resistance of soil animals by reviewing the current status in this research field and summarizing the work of the research group at Jilin University of China in the past decades. The principles and technologies used in morphology bionics,electric-osmosis bionics,flexibility bionics,configuration bionics and coupling bionics were examined.Finally,the applications of the engineering bionics and their extensive prospects were introduced.

  2. Case study of a magnetic system for low-energy machines

    CERN Document Server

    Schoerling, Daniel

    2016-01-01

    The extra low-energy antiproton ring (ELENA) is a CERN particle decelerator with the purpose to deliver antiprotons at lowest energies aiming to enhance the study of antimatter. The hexagonal shaped ring with a circumference of about 30 m will decelerate antiprotons from momenta of 100 to 13.7 MeV/c. In this paper, the design approach for a magnet system for such a machine is presented. Due to the extra-low beam rigidity, the design of the magnet system is especially challenging because even small fields, arising for example from residual magnetization and hysteresis, have a major impact on beam dynamics. In total, seven prototype magnets of three different magnet types have been built and tested. This paper outlines challenges, describes solutions for the design of the magnet system and discusses the results of the prototypes.

  3. Preliminary study on rotary ultrasonic machining of CFRP/Ti stacks.

    Science.gov (United States)

    Cong, W L; Pei, Z J; Treadwell, C

    2014-08-01

    Reported drilling methods for CFRP/Ti stacks include twist drilling, end milling, core grinding, and their derived methods. The literature does not have any report on drilling of CFRP/Ti stacks using rotary ultrasonic machining (RUM). This paper, for the first time, reports a study on drilling of CFRP/Ti stacks using RUM. It also compares results on drilling of CFRP/Ti stacks using RUM with reported results on drilling of CFRP/Ti stacks using other methods. When drilling CFRP/Ti stacks using RUM, cutting force, torque, and CFRP surface roughness were lower, hole size variation was smaller, CFRP groove depth was smaller, tool life was longer, and there was no obvious Ti exit burr and CFRP entrance delamination. Ti surface roughness when drilling of CFRP/Ti stacks using RUM was about the same as those when using other methods.

  4. STUDY ON ELECTRORHEOLOGICAL FLUID DAMPER FOR APPLICATION IN MACHINING CHATTER CONTROL

    Institute of Scientific and Technical Information of China (English)

    2003-01-01

    The electrorheological fluid(ERF)is a kind of intelligent material with bright prospects for industry applications, which has viscoelastic characteristic under the applied electric field. The dynamic model of a milling system with an ERF damper is established, and the chatter suppression mechanism of the ER effect is discussed theoretically. Both the theoretical study and the experimental investigation show that the additional damping and additional stiffness produced by the ERF increase with the rise in the strength of electric field E, but their influence on the cutting stability is different. Only when both additional damping and additional stiffness cooperate, the milling chatter can be suppressed quickly and effectively. In additional, an ERF damper used on the arbor of horizontal spindle milling machine is developed, and a series of milling chatter control experiments are performed. The experimental results show that the milling chatter can be suppressed effectively by using the ER damper.

  5. Using Machine Learning to Estimate Global PM2.5 for Environmental Health Studies.

    Science.gov (United States)

    Lary, D J; Lary, T; Sattler, B

    2015-01-01

    With the increasing awareness of health impacts of particulate matter, there is a growing need to comprehend the spatial and temporal variations of the global abundance of ground-level airborne particulate matter (PM2.5). Here we use a suite of remote sensing and meteorological data products together with ground based observations of PM2.5 from 8,329 measurement sites in 55 countries taken between 1997 and 2014 to train a machine learning algorithm to estimate the daily distributions of PM2.5 from 1997 to the present. We demonstrate that the new PM2.5 data product can reliably represent global observations of PM2.5 for epidemiological studies. An analysis of Baltimore schizophrenia emergency room admissions is presented in terms of the levels of ambient pollution. PM2.5 appears to have an impact on some aspects of mental health.

  6. Case study of a magnetic system for low-energy machines

    Science.gov (United States)

    Schoerling, Daniel

    2016-08-01

    The extra low-energy antiproton ring (ELENA) is a CERN particle decelerator with the purpose to deliver antiprotons at lowest energies aiming to enhance the study of antimatter. The hexagonal shaped ring with a circumference of about 30 m will decelerate antiprotons from momenta of 100 to 13.7 MeV /c . In this paper, the design approach for a magnet system for such a machine is presented. Due to the extra-low beam rigidity, the design of the magnet system is especially challenging because even small fields, arising for example from residual magnetization and hysteresis, have a major impact on beam dynamics. In total, seven prototype magnets of three different magnet types have been built and tested. This paper outlines challenges, describes solutions for the design of the magnet system and discusses the results of the prototypes.

  7. Collisionless expansion of pulsed radio frequency plasmas. II. Parameter study

    Science.gov (United States)

    Schröder, T.; Grulke, O.; Klinger, T.; Boswell, R. W.; Charles, C.

    2016-01-01

    The plasma parameter dependencies of the dynamics during the expansion of plasma are studied with the use of a versatile particle-in-cell simulation tailored to a plasma expansion experiment [Schröder et al., J. Phys. D: Appl. Phys. 47, 055207 (2014); Schröder et al., Phys. Plasmas 23, 013511 (2016)]. The plasma expansion into a low-density ambient plasma features a propagating ion front that is preceding a density plateau. It has been shown that the front formation is entangled with a wave-breaking mechanism, i.e., an ion collapse [Sack and Schamel, Plasma Phys. Controlled Fusion 27, 717 (1985); Sack and Schamel, Phys. Lett. A 110, 206 (1985)], and the launch of an ion burst [Schröder et al., Phys. Plasmas 23, 013511 (2016)]. The systematic parameter study presented in this paper focuses on the influence on this mechanism its effect on the maximum velocity of the ion front and burst. It is shown that, apart from the well known dependency of the front propagation on the ion sound velocity, it also depends sensitively on the density ratio between main and ambient plasma density. The maximum ion velocity depends further on the initial potential gradient, being mostly influenced by the plasma density ratio in the source and expansion regions. The results of the study are compared with independent numerical studies.

  8. 液压碳石墨密封环激光辅助车削的加工性能研究%Study on machinability for laser-assisted machining of hydraulic carbon-graphite seal rings

    Institute of Scientific and Technical Information of China (English)

    薄纪康; 张海英

    2012-01-01

    为了实现液压碳石墨密封环的高效车削加工,采用激光辅助加工方法,进行了碳石墨密封环材料的激光辅助车削加工研究.考虑到碳石墨密封环材料具有高强度、高硬度等特点,利用激光束对工件进行局部加热,以提高加工效率、减小切削力和刀具磨损.针对碳石墨M104密封环的车削加工过程,进行了常规切削和激光辅助切削的对比实验研究.设计了激光辅助加工的实验流程,并进行了工艺参量的合理选择,得到了较高的切削效率.结果表明,激光辅助切削的主切削力和径向力分别比常规切削下降了23.5%和19.9%;激光辅助切削的切削区温度分布与常规切削相近;刀具磨损和破损的程度较小,能获得较好的表面加工质量.%To perform high efficient turning of hydraulic carbon-graphite seal rings, the laser-assisted machining of the material of carbon-graphite seal ring was conducted using laser pre-heating. The material of carbon-graphite seal rings has the characteristics of high strength and high hardness, and is typical non-metallic difficult-to-machine material. The laser-assisted machining heats the workpiece using laser beam, improving machining efficiency as well as reducing cutting force and tool wear. The turning process of carbon-graphite M104 seal ring was focused on, and the conventional machining was compared with the laser-assisted machining. The experimental process of laser-assisted machining was designed and reasonable process parameters were selected. A high cutting efficiency was obtained. The main cutting force and radial force decreased by 23. 5% and 19. 9% compared with conventional machining. The temperature distribution in the cutting zone of laser-assisted machining is similar to conventional machining. The laser-assisted machining has less tool wear and can get a better surface quality.

  9. Feasibility Study for Electrical Discharge Machining of Large DU-Mo Castings

    Energy Technology Data Exchange (ETDEWEB)

    Hill, Mary Ann [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). SIGMA Division; Dombrowski, David E. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). SIGMA Division; Clarke, Kester Diederik [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). SIGMA Division; Forsyth, Robert Thomas [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). SIGMA Division; Aikin, Robert M. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). SIGMA Division; Alexander, David John [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). SIGMA Division; Tegtmeier, Eric Lee [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). SIGMA Division; Robison, Jeffrey Curt [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). SIGMA Division; Beard, Timothy Vance [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). SIGMA Division; Edwards, Randall Lynn [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). SIGMA Division; Mauro, Michael Ernest [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). SIGMA Division; Scott, Jeffrey E. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). SIGMA Division; Strandy, Matthew Thomas [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). SIGMA Division

    2016-10-31

    U-10 wt. % Mo (U-10Mo) alloys are being developed as low enrichment monolithic fuel for the CONVERT program. Optimization of processing for the monolithic fuel is being pursued with the use of electrical discharge machining (EDM) under CONVERT HPRR WBS 1.2.4.5 Optimization of Coupon Preparation. The process is applicable to manufacturing experimental fuel plate specimens for the Mini-Plate-1 (MP-1) irradiation campaign. The benefits of EDM are reduced machining costs, ability to achieve higher tolerances, stress-free, burr-free surfaces eliminating the need for milling, and the ability to machine complex shapes. Kerf losses are much smaller with EDM (tenths of mm) compared to conventional machining (mm). Reliable repeatability is achievable with EDM due to its computer-generated machining programs.

  10. Machine learning techniques in disease forecasting: a case study on rice blast prediction

    Directory of Open Access Journals (Sweden)

    Kapoor Amar S

    2006-11-01

    Full Text Available Abstract Background Diverse modeling approaches viz. neural networks and multiple regression have been followed to date for disease prediction in plant populations. However, due to their inability to predict value of unknown data points and longer training times, there is need for exploiting new prediction softwares for better understanding of plant-pathogen-environment relationships. Further, there is no online tool available which can help the plant researchers or farmers in timely application of control measures. This paper introduces a new prediction approach based on support vector machines for developing weather-based prediction models of plant diseases. Results Six significant weather variables were selected as predictor variables. Two series of models (cross-location and cross-year were developed and validated using a five-fold cross validation procedure. For cross-year models, the conventional multiple regression (REG approach achieved an average correlation coefficient (r of 0.50, which increased to 0.60 and percent mean absolute error (%MAE decreased from 65.42 to 52.24 when back-propagation neural network (BPNN was used. With generalized regression neural network (GRNN, the r increased to 0.70 and %MAE also improved to 46.30, which further increased to r = 0.77 and %MAE = 36.66 when support vector machine (SVM based method was used. Similarly, cross-location validation achieved r = 0.48, 0.56 and 0.66 using REG, BPNN and GRNN respectively, with their corresponding %MAE as 77.54, 66.11 and 58.26. The SVM-based method outperformed all the three approaches by further increasing r to 0.74 with improvement in %MAE to 44.12. Overall, this SVM-based prediction approach will open new vistas in the area of forecasting plant diseases of various crops. Conclusion Our case study demonstrated that SVM is better than existing machine learning techniques and conventional REG approaches in forecasting plant diseases. In this direction, we have also

  11. Machine Learning for Big Data: A Study to Understand Limits at Scale

    Energy Technology Data Exchange (ETDEWEB)

    Sukumar, Sreenivas R. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Del-Castillo-Negrete, Carlos Emilio [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2015-12-21

    This report aims to empirically understand the limits of machine learning when applied to Big Data. We observe that recent innovations in being able to collect, access, organize, integrate, and query massive amounts of data from a wide variety of data sources have brought statistical data mining and machine learning under more scrutiny, evaluation and application for gleaning insights from the data than ever before. Much is expected from algorithms without understanding their limitations at scale while dealing with massive datasets. In that context, we pose and address the following questions How does a machine learning algorithm perform on measures such as accuracy and execution time with increasing sample size and feature dimensionality? Does training with more samples guarantee better accuracy? How many features to compute for a given problem? Do more features guarantee better accuracy? Do efforts to derive and calculate more features and train on larger samples worth the effort? As problems become more complex and traditional binary classification algorithms are replaced with multi-task, multi-class categorization algorithms do parallel learners perform better? What happens to the accuracy of the learning algorithm when trained to categorize multiple classes within the same feature space? Towards finding answers to these questions, we describe the design of an empirical study and present the results. We conclude with the following observations (i) accuracy of the learning algorithm increases with increasing sample size but saturates at a point, beyond which more samples do not contribute to better accuracy/learning, (ii) the richness of the feature space dictates performance - both accuracy and training time, (iii) increased dimensionality often reflected in better performance (higher accuracy in spite of longer training times) but the improvements are not commensurate the efforts for feature computation and training and (iv) accuracy of the learning algorithms

  12. Characterizing parameters of Jatropha curcas cell cultures for microgravity studies

    Science.gov (United States)

    Vendrame, Wagner A.; Pinares, Ania

    2013-06-01

    Jatropha (Jatropha curcas) is a tropical perennial species identified as a potential biofuel crop. The oil is of excellent quality and it has been successfully tested as biodiesel and in jet fuel mixes. However, studies on breeding and genetic improvement of jatropha are limited. Space offers a unique environment for experiments aiming at the assessment of mutations and differential gene expression of crops and in vitro cultures of plants are convenient for studies of genetic variation as affected by microgravity. However, before microgravity studies can be successfully performed, pre-flight experiments are necessary to characterize plant material and validate flight hardware environmental conditions. Such preliminary studies set the ground for subsequent spaceflight experiments. The objectives of this study were to compare the in vitro growth of cultures from three explant sources (cotyledon, leaf, and stem sections) of three jatropha accessions (Brazil, India, and Tanzania) outside and inside the petriGAP, a modified group activation pack (GAP) flight hardware to fit petri dishes. In vitro jatropha cell cultures were established in petri dishes containing a modified MS medium and maintained in a plant growth chamber at 25 ± 2 °C in the dark. Parameters evaluated were surface area of the explant tissue (A), fresh weight (FW), and dry weight (DW) for a period of 12 weeks. Growth was observed for cultures from all accessions at week 12, including subsequent plantlet regeneration. For all accessions differences in A, FW and DW were observed for inside vs. outside the PetriGAPs. Growth parameters were affected by accession (genotype), explant type, and environment. The type of explant influenced the type of cell growth and subsequent plantlet regeneration capacity. However, overall cell growth showed no abnormalities. The present study demonstrated that jatropha in vitro cell cultures are suitable for growth inside PetriGAPs for a period of 12 weeks. The parameters

  13. Experimental Study on the Machining of Inclined Holes for Thermal Barrier-Coated Nickel Superalloys by EDM

    Science.gov (United States)

    Zhang, Guowei; Guo, Yongfeng; Wang, Li

    2016-10-01

    Thermal barrier coatings (TBCs) are used to thermally insulate superalloy components from the hot gas streams in gas turbine engines. In this work, electrical discharge machining (EDM) was used to machine different inclined holes in TBC-coated nickel superalloys by integrating the inner-jet-liquid rotating electrode method and the assisting electrode method. The influences of the inclination angle (i.e., from 0° to 60°) and EDM parameters (i.e., peak current, pulse duration, duty factor and flushing pressure) on the machining time and electrode wear were investigated. The surface morphologies and elemental distribution were analyzed using a scanning electron microscope and an energy dispersive spectroscope. The results of the analysis showed that the 8YSZ ceramic coating is more prone to brittle fracture and cracking than the IN718 substrate and NiCoAlY bond coating, and pits and cracks become more pronounced as the inclination angle increases. The damage on the trailing edge is primarily caused by the thermal stress fracture, and the damage on the leading edge is mainly caused by thermal erosion. Using high-energy parameters, a delamination with dimensions of 28 μm (W) × 200 μm (L) occurs on the trailing edges of the coating/substrate interface.

  14. Study of semen parameters in male partners among infertile couples

    Directory of Open Access Journals (Sweden)

    Sheela N. Kulkarni

    2015-08-01

    Full Text Available Background: The Semen analysis provides valuable information about the etiology and fertility potential of an infertile male. The study was conducted to determine the abnormalities in semen parameters of male partners of infertile couples and to find out contribution of male factors. Methods: The descriptive study with cross sectional design was conducted in the department of Pathology at MIMSR medical college, Latur, Maharashtra, India, between January 2013 to December 2014. A total of 220 cases were analyzed during this period. Semen analysis was performed according to the methods and the standards defined by World Health Organisation (WHO 5th edition 2010. Results: Out of 220 male partners of infertile couples 96 (43.6% men had abnormal semen parameters. The male factor was responsible in 43.6% of cases. Asthenozoospermia constitutes maximum of 19.9%, followed by Oligozoospermia in 18.6%, Azoospermia in 10.9%, Oligoasthenoteratozoospermia in 7.3% and Oligoasthenozoospermia in 6.8% cases. Leucocytospermia was detected in 15.5% cases. Conclusions: Abnormal semen quality remains a significant contribution to overall infertility. Asthenozoospermia is the most common semen abnormality seen. [Int J Reprod Contracept Obstet Gynecol 2015; 4(4.000: 1016-1019

  15. Study on mild and severe wear of 7075 aluminum alloys by high-speed wire electrical discharge machining

    Science.gov (United States)

    Xu, Jinkai; Qiu, Rongxian; Xia, Kui; Wang, Zhichao; Xu, Lining; Yu, Huadong

    2017-01-01

    The recast and the carbon layers were fabricated on 7075Al alloys surface by the high-speed wire electrical discharge machining (HS-WEDM) technologyunder various working parameters. The mechanical properties and friction behaviors of the layers were investigated by UMT. 7075 Al alloys were used to do dry sliding wear tests on a pin-ondisk wear tester at room temperature under various contact pressures. 7075 Al alloys had almost the same wear regularity as a function of sliding velocity and rated frequency. The hardness of recast layer was improved. And this method can enhance durability of 7075 Al alloy effectively.The transition to severe wear occurred at a higher load (12N) for asmachined samples, compared with 7075 matrix (9N), the as-machined samples exhibited lower wear rates within the tested loading range.

  16. Study of some parameters affecting noise level in textile spinning and weaving mills.

    Science.gov (United States)

    el-Dakhakhny, A A; Noweir, M H; Kamel, N R

    1975-01-01

    Noise was evaluated in six spinning and five weaving halls located in three textile mills in Egypt. Spindle speed (rpm) and loom speed (picks per minutes) were found to be important parameters affecting the noise level in these mills. Reduction of the number of spinning machines to five spindles per square meter of floor area will probably bring the noise level below the TLV. In the weaving departments, the decrease in the number of looms will not effectively reduce the noise level.

  17. Parameter studies on flat copper and aluminum bridgefoils

    Energy Technology Data Exchange (ETDEWEB)

    Demana, T.E.; Lee, R.E.; Lee, R.S.; Von Holle, W.

    1986-10-10

    Developing models for the electrical behavior of exploding bridgewire circuits requires high-quality data of a type not usually generated in routine tests of detonator hardware. To obtain a precise measurement of the time of bridgewire burst relative to current start, one must simultaneously record the current, i, and either di/dt or the voltage across the bridgewire. To fully develop and test a model it is also necessary to vary the bridgewire cross sections and geometry, firing circuit characteristics and charging voltage for the firing circuits over as wide a range as possible. As a part of developing an electrical model for aluminum and copper bridgewires, we have conducted parameter studies on some flat copper and aluminum bridgewires. Most of the work was done on aluminum bridgewires, with a few experiments on copper. We will report the experimental results from these studies and compare them with model predictions.

  18. Comparative experimental study of machining characteristics of air-mixed EDM and conventional EDM

    Institute of Scientific and Technical Information of China (English)

    LI Li-qing; GUO Yong-feng; BAI Ji-cheng; GUO Yan-ling

    2007-01-01

    A new method of electrical discharge machining ( EDM ) in air-mixed medium-air-mixed EDM was presented, and comparative experiments were carried out to compare the machining characteristics of air-mixed EDM with conventional EDM. The experimental results showed that better machining performances were obtained with tool electrode as the cathode and workpiece as the anode. It was found that the material removal rate(MRR) was higher, the tool electrode relative wear ratio (TWR) was lower and the surface roughness (SR) quality was better in the case of air-mixed EDM than that of conventional EDM, and the reasons bringing out the results were analyzed.

  19. An Interval Analysis Based Study for the Design and the Comparison of 3-DOF Parallel Kinematic Machines

    CERN Document Server

    Chablat, Damien; Majou, Félix; Merlet, Jean-Pierre

    2004-01-01

    This paper addresses an interval analysis based study that is applied to the design and the comparison of 3-DOF parallel kinematic machines. Two design criteria are used, (i) a regular workspace shape and, (ii) a kinetostatic performance index that needs to be as homogeneous as possible throughout the workspace. The interval analysis based method takes these two criteria into account: on the basis of prescribed kinetostatic performances, the workspace is analysed to find out the largest regular dextrous workspace enclosed in the Cartesian workspace. An algorithm describing this method is introduced. Two 3-DOF translational parallel mechanisms designed for machining applications are compared using this method. The first machine features three fixed linear joints which are mounted orthogonally and the second one features three linear joints which are mounted in parallel. In both cases, the mobile platform moves in the Cartesian x-y-z space with fixed orientation.

  20. Anchorage of TiO2-blasted, HA-coated, and machined implants: an experimental study with rabbits

    DEFF Research Database (Denmark)

    Gotfredsen, K; Wennerberg, A; Johansson, C

    1995-01-01

    The purpose of this study was to evaluate the histometrical and biomechanical anchorage of TiO2-blasted implants and TiO2-blasted implants coated with hydroxyapatite. The control implants were machined. Twenty-six rabbits had a total of 156 implants placed in the proximal part of the tibia. Each...... rabbit had a machined, a TiO2-blasted, and a TiO2-blasted, HA-coated implant placed in each tibia. After a healing period of 3 and 12 weeks, respectively, the implants placed in the right tibia were used for removal torque test, and the implants placed in the left tibia were used for histomorphometrical...... measurements. Preoperatively, implants from the same batches were examined topographically with a TopScan 3D system. The TiO2-blasted implants demonstrated significantly higher removal torque values than the machined implants, and they also had a significantly more irregular surface. Furthermore, significantly...

  1. A Qualitative Study of Knowledge Exchange in an Indonesian Machine-Making Company

    Directory of Open Access Journals (Sweden)

    Indria Handoko

    2016-08-01

    Full Text Available In a supply chain, company’s ability to leverage knowledge that resides within the network of contracted and interacting firms is able to improve not only company performance but also the supply chain effectiveness as a whole. However, existing supply chain studies mostly discuss knowledge at company level, and rarely at internal-hierarchical levels. As a result, many things remain concealed, for example, how knowledge exchange between people across levels in a supply chain is influenced by the supply chain government. Moreover, most exsisting studies focus on a rigid hierarchical supply-chain mechanism, and hardly elaborate how interactions in a less-rigid mechanism. This article attempts to address these gaps, discussing how a supplier company that deals with innovation generation activities acquires knowledge that resides in its supply chain network. A qualitative case study about an Indonesian machine-making company has been chosen to represent one of supplier types in the automotive industry that deals with less-rigid mechanism. A social capital perspective is applied to shed light on how interactions between actors in a supply chain network influence knowledge exchange. The study finds out a positive relationship between social capital and knowledge exchange across levels and functions to help generate innovations, allowing the company to manage conflicting effect beliefs more effectively. The study also identifies a tendency of the company to regard intensive knowledge exchange as part of organizational learning process.

  2. Optimization of Drilling Parameters for Reducing the Burr Height in Machining the Silicon Carbide Particle (SiCp) Coated with Multi Wall Carbon Nano Tubes (MWCNT) Reinforced in Aluminum Alloy (A 356) Using Meta Modeling Approach

    Science.gov (United States)

    Sangeetha, M.; Prakash, S.

    2017-05-01

    This paper explains the optimization of drilling parameters using meta modeling approach to reduce the burr height while machining Silicon Carbide Particle (SiCp) coated with Multi Wall Carbon Nano Tubes (MWCNT) and reinforced in aluminum alloy (A 356). The specimen is prepared by the combination of sonication and stir casting processes. The volume fraction of MWCNT used is 1.5% and the volume fraction of SiCp is 10%. The combination of input parameters for drilling the holes is designed using Taguchi experimental design technique. The input parameters chosen for drilling operations are spindle speed, feed rate and drill diameter. The ranges of input parameters are listed in Table 1. The tools used for drilling operation are made up of solid carbide drill bit. Meta model is a mathematical and statistical model whose second-order model can be fitted by factorial design. The optimization model can be improved significantly by the second-order model compared to the first-order model. Twenty-seven holes are drilled using vertical machining center in the prepared specimen (A 356/MWCNT coated SiCp). Desirability function shows the optimized values of input parameters to obtain minimum burr height. Meta modeling approach is used to design a model using input parameters and output response burr height. The residuals plot shows the predicted values are closer to the measured values. This plot explains that the Meta model is adequately used to predict the burr height. The optimized values of input parameters for obtaining minimum burr height are the combination of high speed, low feed and low drill diameter. The minimum value of burr height observed in this experiment is 0.002mm and it is obtained in the optimized combination of N3, f1 and d1.

  3. Investigation of Machine-ability of Inconel 800 in EDM with Coated Electrode

    Science.gov (United States)

    Karunakaran, K.; Chandrasekaran, M.

    2017-03-01

    The Inconel 800 is a high temperature application alloy which is classified as a nickel based super alloy. It has wide scope in aerospace engineering, gas Turbine etc. The machine-ability studies were found limited on this material. Hence This research focuses on machine-ability studies on EDM of Inconel 800 with Silver Coated Electrolyte Copper Electrode. The purpose of coating on electrode is to reduce tool wear. The factors pulse on Time, Pulse off Time and Peck Current were considered to observe the responses of surface roughness, material removal rate, tool wear rate. Taguchi Full Factorial Design is employed for Design the experiment. Some specific findings were reported and the percentage of contribution of each parameter was furnished

  4. MACHINING OPTIMISATION AND OPERATION ALLOCATION FOR NC LATHE MACHINES IN A JOB SHOP MANUFACTURING SYSTEM

    Directory of Open Access Journals (Sweden)

    MUSSA I. MGWATU

    2013-08-01

    Full Text Available Numerical control (NC machines in a job shop may not be cost and time effective if the assignment of cutting operations and optimisation of machining parameters are overlooked. In order to justify better utilisation and higher productivity of invested NC machine tools, it is necessary to determine the optimum machining parameters and realize effective assignment of cutting operations on machines. This paper presents two mathematical models for optimising machining parameters and effectively allocating turning operations on NC lathe machines in a job shop manufacturing system. The models are developed as non-linear programming problems and solved using a commercial LINGO software package. The results show that the decisions of machining optimisation and operation allocation on NC lathe machines can be simultaneously made while minimising both production cost and cycle time. In addition, the results indicate that production cost and cycle time can be minimised while significantly reducing or totally eliminating idle times among machines.

  5. Simple machines

    CERN Document Server

    Graybill, George

    2007-01-01

    Just how simple are simple machines? With our ready-to-use resource, they are simple to teach and easy to learn! Chocked full of information and activities, we begin with a look at force, motion and work, and examples of simple machines in daily life are given. With this background, we move on to different kinds of simple machines including: Levers, Inclined Planes, Wedges, Screws, Pulleys, and Wheels and Axles. An exploration of some compound machines follows, such as the can opener. Our resource is a real time-saver as all the reading passages, student activities are provided. Presented in s

  6. Mortality studies of machining fluid exposure in the automobile industry. V: A case-control study of pancreatic cancer.

    Science.gov (United States)

    Bardin, J A; Eisen, E A; Tolbert, P E; Hallock, M F; Hammond, S K; Woskie, S R; Smith, T J; Monson, R R

    1997-09-01

    Results are presented from a case-control study of 97 cases of pancreatic cancer nested in a cohort of workers from three automobile manufacturing plants. Risk was examined for lifetime exposure to straight, soluble, and synthetic metalworking fluids, as used in specific machining or grinding operations, as well as for constituents of the fluids. Pancreatic cancer was associated with exposure to synthetic fluids in grinding operations, with an odds ratio of 3.0 (95% CI: 1.2-7.5) among those with more than 1.4 mg/m3-years of exposure. We were unable to examine synthetic exposure in the absence of grinding because there was virtually no exposure to synthetics in machining operations in this study population. Although a disproportionately high percent of the cases were black, no black workers had any exposure to synthetic fluids, and no other measured exposure was found to be related to risk. Thus, the previously documented excess risk of pancreatic cancer among blacks in this cohort remains unexplained.

  7. Simple Machine Junk Cars

    Science.gov (United States)

    Herald, Christine

    2010-01-01

    During the month of May, the author's eighth-grade physical science students study the six simple machines through hands-on activities, reading assignments, videos, and notes. At the end of the month, they can easily identify the six types of simple machine: inclined plane, wheel and axle, pulley, screw, wedge, and lever. To conclude this unit,…

  8. A Numerical Study of the Spring-Back Phenomenon in Bending with a Rebar Bending Machine

    OpenAIRE

    Chang Hwan Choi; Lawrence Kulinsky; Joon Soo Jun; Jin Ho Kim

    2014-01-01

    Recently, the rebar bending methodology started to change from field processing to utilizing rebar bending machines at plant sites prior to transport to the construction locations. Computerized control of rebar plant bending machines provides more accurate and faster bending of rebars than the low quality inefficient field processing alternative. The bending process involves plastic deformation of rebars, where bending stress beyond the yield point of the material is applied. When the bending...

  9. Study Of Performance Parameters Effects On OFDM Systems

    Directory of Open Access Journals (Sweden)

    M.A. Mohamed

    2012-05-01

    Full Text Available The actual and next communication schemes tend to use OFDM systems in order to provide high baud rates, less intercarrier interference, and less intersymbol interference. OFDM has become the core of most 4G communication systems as fixed Wi-Fi system (IEEE802.11a standard, mobile Wi-Fi system (IEEE802.11b standard, fixed WiMAX system (IEEE802.16a standard, mobile WiMAX system (IEEE802.16e standard, and Long Term Evolution (LTE system. In this paper the detailed simulation of different OFDM systems with different constellation mapping schemes will be obtained using MATLAB-2011 program to study the effect of various design parameters on the system performance.

  10. Studying the effects of dynamical parameters on reactor core temperature

    Directory of Open Access Journals (Sweden)

    R Khodabakhsh

    2015-01-01

    Full Text Available In order to increase productivity, reduce depreciation, and avoid possible accidents in a system such as fuel rods' melting and overpressure, control of temperature changes in the reactor core is an important factor. There are several methods for solving and analysing the stability of point kinetics equations. In most previous analyses, the effects of various factors on the temperature of the reactor core have been ignored. In this work, the effects of various dynamical parameters on the temperature of the reactor core and stability of the system in the presence of temperature feedback reactivity with external reactivity step, ramp and sinusoidal for six groups of delayed neutrons were studied using the method of Lyapunov exponent. The results proved to be in good agreement with other works

  11. Study of Operating Parameters for Accelerated Anode Degradation in SOFCs

    DEFF Research Database (Denmark)

    Ploner, Alexandra; Hagen, Anke; Hauch, Anne

    2017-01-01

    Solid oxide fuel cell (SOFC) applications require lifetimes of several years on the system level. A big challenge is to demonstrate such exceptionally long lifetimes in ongoing R&D projects. Accelerated or compressed testing are alternative methods to obtain this. Activities in this area have been...... carried out without arriving at a generally accepted methodology. This is mainly due to the complexity of degradation mechanisms on the single SOFC components as function of operating parameters. In this study, we present a detailed analysis of approx. 180 durability tests regarding degradation of single...... SOFC components as function of operating conditions. Electrochemical impedance data were collected on the fresh and long-term tested SOFCs and used to de-convolute the individual losses of single SOFC cell components – electrolyte, cathode and anode. The main findings include a time-dependent effect...

  12. A study of the influence of cutting parameters on micromilling of steel with cubic boron nitride (CBN) tools

    Science.gov (United States)

    Klocke, Fritz; Quito, Fernando; Arntz, Kristian; Souza, Alexandre

    2009-02-01

    It has been concluded in previous studies that Cubic Boron Nitride (CBN) tools have greater wear resistance and superior tool life than other tool materials used in conventional milling, due to chemically stability at high temperatures, high abrasive wear resistance and high degree of hardness; however no research has been conducted about its performance on micro milling. Burr formation has a direct negative effect on product quality and assembly automation in micro milling, therefore adoption of machining strategies and influencing factors were investigated intending to reduce burr formation. This paper also aims at analyzing the interference of cutting parameters on micro milling with CBN tools, such as the influence of cutting speed and feed per tooth on the surface quality and tool life. These outcomes enable us to know which parameters and strategies must be used to achieve better results when micro milling steel with CBN tools.

  13. Optimization of the parameter calculation the process of production historic by using Parallel Virtual Machine-PVM; Otimizacao do calculo de parametros no processo de ajuste de historicos de producao usando PVM

    Energy Technology Data Exchange (ETDEWEB)

    Vargas Cuervo, Carlos Hernan

    1997-03-01

    The main objective of this work is to develop a methodology to optimize the simultaneous computation of two parameters in the process of production history matching. This work describes a procedure to minimize an objective function established to find the values of the parameters which are modified in the process. The parameters are chosen after a sensibility analysis. Two optimization methods are tested: a Region Search Method (MBR) and Polytope Method. Both are based in direct search methods which do not require the function derivative. The software PVM (Parallel Virtual Machine) is used to parallelize the simulation runs, allowing the acceleration of the process and the search of multiple solutions. The validation of the methodology is applied to two reservoir models: one homogeneous and other heterogeneous. The advantages of each method and of the parallelization are also present. (author)

  14. Does Cigarette Smoking Affect Seminal Fluid Parameters? A Comparative Study

    Directory of Open Access Journals (Sweden)

    Zakarya Bani Meri

    2013-01-01

    Full Text Available Objective: To study the effect of cigarette smoking on seminal fluid parameters, namely; volume, sperm concentration, and motility, as well as morphology, leukocyte infiltration, among males complaining of infertility.Methods: Between August 2010 and July 2011, seminal fluid analysis was done for 1438 males who are partners of couples who visited the infertility clinic at Prince Rashid Ben Al Hassan Hospital (PRH for infertility. The men who fit the inclusion criteria (n=960 were classified into two groups: group a (non-smokers; n=564 and group B (smokers; n=396, which represents 41.25% of the study group. Seminal fluid was collected using masturbation after 3-5 days of abstinence then analyzed for volume, sperm count, sperm concentration, motility and morphology. In order to analyze whether the number of cigarettes smoked per day has an effect on the spermatogram; the smoking men were divided into two subgroups: the heavy smokers (n=266 and non-heavy smokers (n=130.Results: A total of 960 adult males were enrolled. Their age ranged between 21 and 76 years, 564 were non-smokers with mean age of 36. 45±6.27 (Mean±SD. Three-hundred-and-ninety-six were smokers with a mean age of 34.35±4.25 (Mean±SD. There was a significant effect of smoking on the motility of sperms and the ratios of abnormality (p<0.005. Concentration appeared not to be affected by smoking. Furthermore, the group of heavy smokers were found to have lower sperm concentrations and a higher percentage of abnormal sperms compared to the non-heavy smokers.Conclusion: Cigarette smoking has a deleterious effect on some of the seminal fluid parameters (motility, morphology and leukocyte count which in turn may result in male subfertility.

  15. submitter Studies of CMS data access patterns with machine learning techniques

    CERN Document Server

    De Luca, Silvia

    This thesis presents a study of the Grid data access patterns in distributed analysis in the CMS experiment at the LHC accelerator. This study ranges from the deep analysis of the historical patterns of access to the most relevant data types in CMS, to the exploitation of a supervised Machine Learning classification system to set-up a machinery able to eventually predict future data access patterns - i.e. the so-called dataset “popularity” of the CMS datasets on the Grid - with focus on specific data types. All the CMS workflows run on the Worldwide LHC Computing Grid (WCG) computing centers (Tiers), and in particular the distributed analysis systems sustains hundreds of users and applications submitted every day. These applications (or “jobs”) access different data types hosted on disk storage systems at a large set of WLCG Tiers. The detailed study of how this data is accessed, in terms of data types, hosting Tiers, and different time periods, allows to gain precious insight on storage occupancy ove...

  16. Computer vision and machine learning for robust phenotyping in genome-wide studies

    Science.gov (United States)

    Zhang, Jiaoping; Naik, Hsiang Sing; Assefa, Teshale; Sarkar, Soumik; Reddy, R. V. Chowda; Singh, Arti; Ganapathysubramanian, Baskar; Singh, Asheesh K.

    2017-01-01

    Traditional evaluation of crop biotic and abiotic stresses are time-consuming and labor-intensive limiting the ability to dissect the genetic basis of quantitative traits. A machine learning (ML)-enabled image-phenotyping pipeline for the genetic studies of abiotic stress iron deficiency chlorosis (IDC) of soybean is reported. IDC classification and severity for an association panel of 461 diverse plant-introduction accessions was evaluated using an end-to-end phenotyping workflow. The workflow consisted of a multi-stage procedure including: (1) optimized protocols for consistent image capture across plant canopies, (2) canopy identification and registration from cluttered backgrounds, (3) extraction of domain expert informed features from the processed images to accurately represent IDC expression, and (4) supervised ML-based classifiers that linked the automatically extracted features with expert-rating equivalent IDC scores. ML-generated phenotypic data were subsequently utilized for the genome-wide association study and genomic prediction. The results illustrate the reliability and advantage of ML-enabled image-phenotyping pipeline by identifying previously reported locus and a novel locus harboring a gene homolog involved in iron acquisition. This study demonstrates a promising path for integrating the phenotyping pipeline into genomic prediction, and provides a systematic framework enabling robust and quicker phenotyping through ground-based systems. PMID:28272456

  17. Computer vision and machine learning for robust phenotyping in genome-wide studies.

    Science.gov (United States)

    Zhang, Jiaoping; Naik, Hsiang Sing; Assefa, Teshale; Sarkar, Soumik; Reddy, R V Chowda; Singh, Arti; Ganapathysubramanian, Baskar; Singh, Asheesh K

    2017-03-08

    Traditional evaluation of crop biotic and abiotic stresses are time-consuming and labor-intensive limiting the ability to dissect the genetic basis of quantitative traits. A machine learning (ML)-enabled image-phenotyping pipeline for the genetic studies of abiotic stress iron deficiency chlorosis (IDC) of soybean is reported. IDC classification and severity for an association panel of 461 diverse plant-introduction accessions was evaluated using an end-to-end phenotyping workflow. The workflow consisted of a multi-stage procedure including: (1) optimized protocols for consistent image capture across plant canopies, (2) canopy identification and registration from cluttered backgrounds, (3) extraction of domain expert informed features from the processed images to accurately represent IDC expression, and (4) supervised ML-based classifiers that linked the automatically extracted features with expert-rating equivalent IDC scores. ML-generated phenotypic data were subsequently utilized for the genome-wide association study and genomic prediction. The results illustrate the reliability and advantage of ML-enabled image-phenotyping pipeline by identifying previously reported locus and a novel locus harboring a gene homolog involved in iron acquisition. This study demonstrates a promising path for integrating the phenotyping pipeline into genomic prediction, and provides a systematic framework enabling robust and quicker phenotyping through ground-based systems.

  18. Calibration of a Parallel Kinematic Machine Tool

    Institute of Scientific and Technical Information of China (English)

    HE Xiao-mei; DING Hong-sheng; FU Tie; XIE Dian-huang; XU Jin-zhong; LI Hua-feng; LIU Hui-lin

    2006-01-01

    A calibration method is presented to enhance the static accuracy of a parallel kinematic machine tool by using a coordinate measuring machine and a laser tracker. According to the established calibration model and the calibration experiment, the factual 42 kinematic parameters of BKX-I parallel kinematic machine tool are obtained. By circular tests the comparison is made between the calibrated and the uncalibrated parameters and shows that there is 80% improvement in accuracy of this machine tool.

  19. Prognostic parameters and spinal metastases: a research study.

    Directory of Open Access Journals (Sweden)

    Jefferson W Daniel

    Full Text Available OBJECT: To identify pre-operative prognostic parameters for survival in patients with spinal epidural neoplastic metastasis when the primary tumour is unknown. METHODS: This study was a retrospective chart review of patients who underwent surgery for spinal epidural neoplastic metastases between February 1997 and January 2011. The inclusion criteria were as follows: known post-operative survival period, a Karnofsky Performance Score equal to or greater than 30 points and a post-operative neoplastic metastasis histological type. The Kaplan-Meier method was used to estimate post-operative survival, and the Log-Rank test was used for statistical inference. RESULTS: A total of 52 patients who underwent 52 surgical procedures were identified. The mean age at the time of spinal surgery was 53.92 years (std. deviation, 19.09. The median survival after surgery was 70 days (95% CI 49.97-90.02, and post-operative mortality occurred within 6 months in 38 (73.07% patients. Lung cancer, prostate cancer, myeloma and lymphoma, the 4 most common primary tumour types, affected 32 (61.53% patients. The three identified prognostic parameters were the following: pre-operative walking incapacity (American Spinal Injury Association, A and B, present in 86.53% of the patients (p-value = 0.107; special care dependency (Karnofsky Performance Score, 10-40 points, present in 90.38% of the patients (p-value = 0.322; and vertebral epidural neoplastic metastases that were in contact with the thecal sac (Weinstein-Boriani-Biagini, sector D, present in 94.23% of the patients (p-value = 0.643. When the three secondary prognostic parameters were combined, the mean post-operative survival was 45 days; when at least one was present, the survival was 82 days (p-value = 0.175. CONCLUSIONS: Walking incapacity, special care dependency and contact between the neoplastic metastases and the thecal sac can help determine the ultimate survival of this patient population and

  20. Metabolomic perfusate analysis during kidney machine perfusion: the pig provides an appropriate model for human studies.

    Directory of Open Access Journals (Sweden)

    Jay Nath

    Full Text Available Hypothermic machine perfusion offers great promise in kidney transplantation and experimental studies are needed to establish the optimal conditions for this to occur. Pig kidneys are considered to be a good model for this purpose and share many properties with human organs. However it is not established whether the metabolism of pig kidneys in such hypothermic hypoxic conditions is comparable to human organs.Standard criteria human (n = 12 and porcine (n = 10 kidneys underwent HMP using the LifePort Kidney Transporter 1.0 (Organ Recovery Systems using KPS-1 solution. Perfusate was sampled at 45 minutes and 4 hours of perfusion and metabolomic analysis performed using 1-D 1H-NMR spectroscopy.There was no inter-species difference in the number of metabolites identified. Of the 30 metabolites analysed, 16 (53.3% were present in comparable concentrations in the pig and human kidney perfusates. The rate of change of concentration for 3-Hydroxybutyrate was greater for human kidneys (p<0.001. For the other 29 metabolites (96.7%, there was no difference in the rate of change of concentration between pig and human samples.Whilst there are some differences between pig and human kidneys during HMP they appear to be metabolically similar and the pig seems to be a valid model for human studies.

  1. LHC Report: machine development

    CERN Multimedia

    Rogelio Tomás García for the LHC team

    2015-01-01

    Machine development weeks are carefully planned in the LHC operation schedule to optimise and further study the performance of the machine. The first machine development session of Run 2 ended on Saturday, 25 July. Despite various hiccoughs, it allowed the operators to make great strides towards improving the long-term performance of the LHC.   The main goals of this first machine development (MD) week were to determine the minimum beam-spot size at the interaction points given existing optics and collimation constraints; to test new beam instrumentation; to evaluate the effectiveness of performing part of the beam-squeezing process during the energy ramp; and to explore the limits on the number of protons per bunch arising from the electromagnetic interactions with the accelerator environment and the other beam. Unfortunately, a series of events reduced the machine availability for studies to about 50%. The most critical issue was the recurrent trip of a sextupolar corrector circuit –...

  2. A discrete time model of a power conditioner fed permanent magnet brushless dc motor system for aerospace and electric vehicle applications for design purpose using finite elements for machine parameter determination

    Science.gov (United States)

    Nehl, T. W.

    1980-12-01

    A discrete state space model of a power conditioner fed permanent magnet brushless dc motor for aerospace and electric vehicle applications is developed. The parameters which describe that machine portion of this model are derived from a two dimensional nonlinear magnetic field analysis using the finite element method. The model predicts the instantaneous mechanical and electrical behavior of a prototype electromechanical actuator for possible use on board the shuttle orbiter. The model is also used to simulate the instantaneous performance of an advanced electric vehicle propulsion unit. The results of the computer simulations are compared with experimental test data and excellent agreement between the two is found in all cases.

  3. Electric machine

    Science.gov (United States)

    El-Refaie, Ayman Mohamed Fawzi [Niskayuna, NY; Reddy, Patel Bhageerath [Madison, WI

    2012-07-17

    An interior permanent magnet electric machine is disclosed. The interior permanent magnet electric machine comprises a rotor comprising a plurality of radially placed magnets each having a proximal end and a distal end, wherein each magnet comprises a plurality of magnetic segments and at least one magnetic segment towards the distal end comprises a high resistivity magnetic material.

  4. Preliminary Study on Machining Condition Monitoring System Using 3-Channel Force Sensor Analyzed by I-kaz Multilevel Method

    Directory of Open Access Journals (Sweden)

    Z. Karim

    2016-08-01

    Full Text Available Cutting tool wear is one of the major problems affecting the finished product in term of surface finish quality, dimensional precision and the cost of the defect. This paper discusses the preliminary study on machining condition monitoring system using force data captured using 3-channel force sensor. The data were analyzed by I-kaz multilevel method to monitor the flank wear progression during the machining. The flank wear of the cutting insert was measured using Moticom magnifier under two different operational conditions in turning process. A 3-channel Kistler force sensor was assembled to hold the tool holder to measure the force on the cutting tool in the tangential, radial and feed direction during the machining process. The signals were transmitted to the data acquisition equipment, and finally to the computer system. I-kaz multilevel method was used to identify and characterize the changes in the signals from the sensors under two different experimental set up. The values of I-kaz multilevel coefficients for all channels are strongly correlated with the cutting tool wear condition. This preliminary study can be further developed to efficiently monitor and predict flank wear level which can be used in the real machining industry.

  5. The studies of mechanical properties and structure of ADI as function of austempering parameters

    Directory of Open Access Journals (Sweden)

    A. Krzyńska

    2010-10-01

    Full Text Available The results of study of ductile iron austempered using different parameters of austempering are presented. The aim of the investigations was to look closer into mechanical properties of this very attractive cast material. The experiment was carried out with commercial EN-GJS-500-7 grade ductile iron. The specimens were first solution heat treated 1 hour in 910oC and then isothermally quenched for different time in molten tin of different temperature. The mechanical properties heat treated specimens were tested using tensile test machine to evaluate Rp,0.2, Rm and A10. Moreover Brinell hardness tests were carried out for structure investigation conventional light microscopy only was used. It was discovered, that low yield strength ADI obtained for short time quenching at 275oC exhibited high strengthening effect while tensile strained. So it was concluded that this had to by cause by large amount of untransformed austenite, which FCC lattice providing large number of glide systems.

  6. A small-sample multivariate kernel machine test for microbiome association studies.

    Science.gov (United States)

    Zhan, Xiang; Tong, Xingwei; Zhao, Ni; Maity, Arnab; Wu, Michael C; Chen, Jun

    2017-04-01

    High-throughput sequencing technologies have enabled large-scale studies of the role of the human microbiome in health conditions and diseases. Microbial community level association test, as a critical step to establish the connection between overall microbiome composition and an outcome of interest, has now been routinely performed in many studies. However, current microbiome association tests all focus on a single outcome. It has become increasingly common for a microbiome study to collect multiple, possibly related, outcomes to maximize the power of discovery. As these outcomes may share common mechanisms, jointly analyzing these outcomes can amplify the association signal and improve statistical power to detect potential associations. We propose the multivariate microbiome regression-based kernel association test (MMiRKAT) for testing association between multiple continuous outcomes and overall microbiome composition, where the kernel used in MMiRKAT is based on Bray-Curtis or UniFrac distance. MMiRKAT directly regresses all outcomes on the microbiome profiles via a semiparametric kernel machine regression framework, which allows for covariate adjustment and evaluates the association via a variance-component score test. Because most of the current microbiome studies have small sample sizes, a novel small-sample correction procedure is implemented in MMiRKAT to correct for the conservativeness of the association test when the sample size is small or moderate. The proposed method is assessed via simulation studies and an application to a real data set examining the association between host gene expression and mucosal microbiome composition. We demonstrate that MMiRKAT is more powerful than large sample based multivariate kernel association test, while controlling the type I error. A free implementation of MMiRKAT in R language is available at http://research.fhcrc.org/wu/en.html.

  7. Modeling the Financial Distress of Microenterprise StartUps Using Support Vector Machines: A Case Study

    Directory of Open Access Journals (Sweden)

    Antonio Blanco-Oliver

    2014-10-01

    Full Text Available Despite the leading role that micro-entrepreneurship plays in economic development, and the high failure rate of microenterprise start-ups in their early years, very few studies have designed financial distress models to detect the financial problems of micro-entrepreneurs. Moreover, due to a lack of research, nothing is known about whether non-financial information and nonparametric statistical techniques improve the predictive capacity of these models. Therefore, this paper provides an innovative financial distress model specifically designed for microenterprise startups via support vector machines (SVMs that employs financial, non-financial, and macroeconomic variables. Based on a sample of almost 5,500 micro- entrepreneurs from a Peruvian Microfinance Institution (MFI, our findings show that the introduction of non-financial information related to the zone in which the entrepreneurs live and situate their business, the duration of the MFI-entrepreneur relationship, the number of loans granted by the MFI in the last year, the loan destination, and the opinion of experts on the probability that microenterprise start-ups may experience financial problems, significantly increases the accuracy performance of our financial distress model. Furthermore, the results reveal that the models that use SVMs outperform those which employ traditional logistic regression (LR analysis.

  8. Machining Test Specimens from Harvested Zion RPV Segments for Through Wall Attenuation Studies

    Energy Technology Data Exchange (ETDEWEB)

    Rosseel, Thomas M [ORNL; Sokolov, Mikhail A [ORNL; Nanstad, Randy K [ORNL

    2015-01-01

    The decommissioning of the Zion Units 1 and 2 Nuclear Generating Station (NGS) in Zion, Illinois presents a special opportunity for developing a better understanding of materials degradation and other issues associated with extending the lifetime of existing Nuclear Power Plants (NPPs) beyond 60 years of service. In support of extended service and current operations of the US nuclear reactor fleet, the Oak Ridge National Laboratory (ORNL), through the Department of Energy (DOE), Light Water Reactor Sustainability (LWRS) Program, is coordinating and contracting with Zion Solutions, LLC, a subsidiary of Energy Solutions, the selective procurement of materials, structures, and components from the decommissioned reactors. In this paper, we will discuss the acquisition of segments of the Zion Unit 2 Reactor Pressure Vessel (RPV), the cutting of these segments into sections and blocks from the beltline and upper vertical welds and plate material, the current status of machining those blocks into mechanical (Charpy, compact tension, and tensile) test specimens and coupons for chemical and microstructural (TEM, APT, SANS, and nano indention) characterization, as well as the current test plans and possible collaborative projects. Access to service-irradiated RPV welds and plate sections will allow through wall attenuation studies to be performed, which will be used to assess current radiation damage models (Rosseel et al. (2012) and Rosseel et al. (2015)).

  9. Sentiment Analysis on Movie Reviews: A Comparative Study of Machine Learning Algorithms and Open Source Technologies

    Directory of Open Access Journals (Sweden)

    B. Narendra

    2016-08-01

    Full Text Available Social Networks such as Facebook, Twitter, Linked In etc… are rich in opinion data and thus Sentiment Analysis has gained a great attention due to the abundance of this ever growing opinion data. In this research paper our target set is movie reviews. There are diverge range of mechanisms to express their data which may be either subjective, objective or a mixture of both. Besides the data collected from World Wide Web consists of lot of noisy data. It is very much true that we are going to apply some pre-processing techniques and compare the accuracy using Machine Learning algorithm Naïve Bayes Classifier. With ever growing demand to mine the Big Data the open source software technologies such as Hadoop using map reducing paradigm has gained a lot of pragmatic importance. This paper illustrates a comparitive study of sentiment analysis of movie reviews using Naïve Bayes Classifier and Apache Hadoop in order to calculate the performance of the algorithms and show that Map Reduce paradigm of Apache Hadoop performed better than Naïve Bayes Classifier.

  10. Helical CT study of cerebral perfusion and related hemodynamic parameters

    Science.gov (United States)

    Cenic, Aleksa; Lee, Ting-Yim; Craen, Rosemary A.; Gelb, Adrian W.

    1997-05-01

    A convenient method for assessing cerebral perfusion and related functional parameters has been developed using a third generation slip-ring CT scanner. Dynamic contrast- enhanced scanning at the same level was employed to image the cerebral circulation at the rate of 1 image per second. Using data acquired with this non-helical mode of scanning, we have developed a method for the simultaneous in-vivo determination of cerebral blood flow (CBF), cerebral blood volume (CBV), and mean transit time (MTT). These measurements are given in the same physiological units as positron emission tomography. In order to obtain accurate measurements of these parameters, methods were also developed to correct for recirculation and partial volume averaging in imaging small blood vessels. We have used 6 New Zealand white rabbits in our studies. For each rabbit, up to 3 CT measurements of CBF, CBV, and MTT were made at normocapnia under isoflurane anesthesia. Coronal sections through the brain were imaged while simultaneously imaging either a brain artery or the ear artery. Images were acquired for 1 minute as Isovue 300 was injected intravenously. In the acquired CT images, regions of interest in brain parenchyma and an artery were drawn. For each region of interest, the mean CT number in pre-contrast images was subtracted from the mean in post-contrast images to calculate the contrast concentration curves for the brain regions Q(t) and the arterial region Ca(t). Using a robust deconvolution method, the MTT was determined. CBV was then determined from the ratio of the areas of Q(t) and Ca(t). Finally, CBF was calculated from the Central Volume Principle. The mean regional CBF, CBV and MTT values were 73.3 +/- 5.1 ml/min/100g, 1.93 +/- 0.12 ml/100g and 1.80 +/- 0.18 s respectively. IN order to validate our CT CBF measurements, we also measured CBF using the well- established technique of microspheres with each CT study. The feasibility of our CT method to measure CBF accurately was

  11. 电火花临界与加工放电间隙实验研究%Experimental Study on the Critical and Machining DisCharge Gap of EDM

    Institute of Scientific and Technical Information of China (English)

    雍耀维; 邵金龙; 邓安强

    2012-01-01

    The critical gap and practical machining continuous .gap in Electrical Discharge Machining ( EDM) based on the Tagu-chi method were studied. The main electrical parameters were peak current, open-circuit voltage and width of pulses time. Then the parameters which mainly influenced discharging gap were determined by calculation of sign-to-noise ratio and square difference. The results show that critical gap is predominantly effected by discharging voltage, whereas the continuous machining gap is predominantly effected by discharging current. And the continuous machining gap is greater than the critical gap.%基于田口法研究了电火花放电过程中的临界放电间隙和实际加工中的连续放电间隙与电参数的关系.电参数主要有峰值电流、放电电压和脉冲宽度值.然后通过计算信噪比和方差分析来判定主要影响放电间隙的参数.结果表明:临界放电间隙主要是受放电电压影响,而连续加工中的间隙主要是由放电电流决定,且连续加工放电间隙要大于临界放电间隙.

  12. Kernel machine testing for risk prediction with stratified case cohort studies.

    Science.gov (United States)

    Payne, Rebecca; Neykov, Matey; Jensen, Majken Karoline; Cai, Tianxi

    2016-06-01

    Large assembled cohorts with banked biospecimens offer valuable opportunities to identify novel markers for risk prediction. When the outcome of interest is rare, an effective strategy to conserve limited biological resources while maintaining reasonable statistical power is the case cohort (CCH) sampling design, in which expensive markers are measured on a subset of cases and controls. However, the CCH design introduces significant analytical complexity due to outcome-dependent, finite-population sampling. Current methods for analyzing CCH studies focus primarily on the estimation of simple survival models with linear effects; testing and estimation procedures that can efficiently capture complex non-linear marker effects for CCH data remain elusive. In this article, we propose inverse probability weighted (IPW) variance component type tests for identifying important marker sets through a Cox proportional hazards kernel machine (CoxKM) regression framework previously considered for full cohort studies (Cai et al., 2011). The optimal choice of kernel, while vitally important to attain high power, is typically unknown for a given dataset. Thus, we also develop robust testing procedures that adaptively combine information from multiple kernels. The proposed IPW test statistics have complex null distributions that cannot easily be approximated explicitly. Furthermore, due to the correlation induced by CCH sampling, standard resampling methods such as the bootstrap fail to approximate the distribution correctly. We, therefore, propose a novel perturbation resampling scheme that can effectively recover the induced correlation structure. Results from extensive simulation studies suggest that the proposed IPW CoxKM testing procedures work well in finite samples. The proposed methods are further illustrated by application to a Danish CCH study of Apolipoprotein C-III markers on the risk of coronary heart disease. © 2015, The International Biometric Society.

  13. Fully automatic CNC machining production system

    Directory of Open Access Journals (Sweden)

    Lee Jeng-Dao

    2017-01-01

    Full Text Available Customized manufacturing is increasing years by years. The consumption habits change has been cause the shorter of product life cycle. Therefore, many countries view industry 4.0 as a target to achieve more efficient and more flexible automated production. To develop an automatic loading and unloading CNC machining system via vision inspection is the first step in industrial upgrading. CNC controller is adopted as the main controller to command to the robot, conveyor, and other equipment in this study. Moreover, machine vision systems are used to detect position of material on the conveyor and the edge of the machining material. In addition, Open CNC and SCADA software will be utilized to make real-time monitor, remote system of control, alarm email notification, and parameters collection. Furthermore, RFID has been added to employee classification and management. The machine handshaking has been successfully proposed to achieve automatic vision detect, edge tracing measurement, machining and system parameters collection for data analysis to accomplish industrial automation system integration with real-time monitor.

  14. Study on Surface Integrity of AISI 1045 Carbon Steel when machined by Carbide Cutting Tool under wet conditions

    Directory of Open Access Journals (Sweden)

    Tamin N. Fauzi

    2017-01-01

    Full Text Available This paper presents the evaluation of surface roughness and roughness profiles when machining carbon steel under wet conditions with low and high cutting speeds. The workpiece materials and cutting tools selected in this research were AISI 1045 carbon steel and canela carbide inserts graded PM25, respectively. The cutting tools undergo machining tests by CNC turning operations and their performances were evaluated by their surface roughness value and observation of the surface roughness profile. The machining tests were held at varied cutting speeds of 35 to 53 m/min, feed rate of 0.15 to 0.50 mm/rev and a constant depth of cut of 1 mm. From the analysis, it was found that surface roughness increased as the feed rate increased. Varian of surface roughness was suspected due to interaction between cutting speeds and feed rates as well as nose radius conditions; whether from tool wear or the formation of a built-up edge. This study helps us understand the effect of cutting speed and feed rate on surface integrity, when machining AISI 1045 carbon steel using carbide cutting tools, under wet cutting conditions.

  15. Image Reconstruction Using Multi Layer Perceptron MLP And Support Vector Machine SVM Classifier And Study Of Classification Accuracy

    Directory of Open Access Journals (Sweden)

    Shovasis Kumar Biswas

    2015-02-01

    Full Text Available Abstract Support Vector Machine SVM and back-propagation neural network BPNN has been applied successfully in many areas for example rule extraction classification and evaluation. In this paper we studied the back-propagation algorithm for training the multilayer artificial neural network and a support vector machine for data classification and image reconstruction aspects. A model focused on SVM with Gaussian RBF kernel is utilized here for data classification. Back propagation neural network is viewed as one of the most straightforward and is most general methods used for supervised training of multilayered neural network. We compared a support vector machine SVM with a back-propagation neural network BPNN for the task of data classification and image reconstruction. We made a comparison between the performances of the multi-class classification of these two learning methods. Comparing with these two methods we can conclude that the classification accuracy of the support vector machine is better and algorithm is much faster than the MLP with back propagation algorithm.

  16. Acceptability of using electronic vending machines to deliver oral rapid HIV self-testing kits: a qualitative study.

    Directory of Open Access Journals (Sweden)

    Sean D Young

    Full Text Available Rates of unrecognized HIV infection are significantly higher among Latino and Black men who have sex with men (MSM. Policy makers have proposed that HIV self-testing kits and new methods for delivering self-testing could improve testing uptake among minority MSM. This study sought to conduct qualitative assessments with MSM of color to determine the acceptability of using electronic vending machines to dispense HIV self-testing kits.African American and Latino MSM were recruited using a participant pool from an existing HIV prevention trial on Facebook. If participants expressed interest in using a vending machine to receive an HIV self-testing kit, they were emailed a 4-digit personal identification number (PIN code to retrieve the test from the machine. We followed up with those who had tested to assess their willingness to participate in an interview about their experience.Twelve kits were dispensed and 8 interviews were conducted. In general, participants expressed that the vending machine was an acceptable HIV test delivery method due to its novelty and convenience.Acceptability of this delivery model for HIV testing kits was closely associated with three main factors: credibility, confidentiality, and convenience. Future research is needed to address issues, such as user-induced errors and costs, before scaling up the dispensing method.

  17. Training Restricted Boltzmann Machines

    DEFF Research Database (Denmark)

    Fischer, Asja

    Restricted Boltzmann machines (RBMs) are probabilistic graphical models that can also be interpreted as stochastic neural networks. Training RBMs is known to be challenging. Computing the likelihood of the model parameters or its gradient is in general computationally intensive. Thus, training...

  18. Efficiency of Inefficient Endoreversible Thermal Machines

    Science.gov (United States)

    Palao, José P.; Correa, Luis A.; Adesso, Gerardo; Alonso, Daniel

    2016-06-01

    We present a study of the performance of endoreversible thermal machines optimized with respect to the thermodynamic force associated with the cold bath in the regime of small thermodynamic forces. These thermal machines can work either as an engine or as a refrigerator. We analyze how the optimal performances are determined by the dependence of the thermodynamic flux on the forces. The results are motivated and illustrated with a quantum model, the three level maser, and explicit analytical expressions of the engine efficiency as a function of the system parameters are given.

  19. The little-studied cluster Berkeley 90. III. Cluster parameters

    CERN Document Server

    Marco, Amparo

    2016-01-01

    The open cluster Berkeley 90 is the home to one of the most massive binary systems in the Galaxy, LS III +46$^{\\circ}$11, formed by two identical, very massive stars (O3.5 If* + O3.5 If*), and a second early-O system (LS III +46$^{\\circ}$12 with an O4.5 IV((f)) component at least). Stars with spectral types earlier than O4 are very scarce in the Milky Way, with no more than 20 examples. The formation of such massive stars is still an open question today, and thus the study of the environments where the most massive stars are found can shed some light on this topic. To this aim, we determine the properties and characterize the population of Berkeley 90 using optical, near-infrared and WISE photometry and optical spectroscopy. This is the first determination of these parameters with accuracy. We find a distance of $3.5^{+0.5}_{-0.5}$ kpc and a maximum age of 3 Ma. The cluster mass is around $1000$ $M_{\\odot}$ (perhaps reaching $1500$ $M_{\\odot}$ if the surrounding population is added), and we do not detect cand...

  20. The little-studied cluster Berkeley 90 - III. Cluster parameters

    Science.gov (United States)

    Marco, Amparo; Negueruela, Ignacio

    2017-02-01

    The open cluster Berkeley 90 is the home to one of the most massive binary systems in the Galaxy, LS III +46°11, formed by two identical, very massive stars (O3.5 If* + O3.5 If*), and a second early-O system (LS III +46°12 with an O4.5 IV((f)) component at least). Stars with spectral types earlier than O4 are very scarce in the Milky Way, with no more than 20 examples. The formation of such massive stars is still an open question today, and thus the study of the environments where the most massive stars are found can shed some light on this topic. To this aim, we determine the properties and characterize the population of Berkeley 90 using optical, near-infrared and WISE photometry and optical spectroscopy. This is the first determination of these parameters with accuracy. We find a distance of 3.5^{+0.5}_{-0.5} kpc and a maximum age of 3 Ma. The cluster mass is around 1000 M⊙ (perhaps reaching 1500 M⊙ if the surrounding population is added), and we do not detect candidate runaway stars in the area. There is a second population of young stars to the southeast of the cluster that may have formed at the same time or slightly later, with some evidence for low-activity ongoing star formation.