WorldWideScience

Sample records for machine based operating

  1. WEB-BASED VIRTUAL CNC MACHINE MODELING AND OPERATION

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    A CNC simulation system based on internet for operation training of manufacturing facility and manufacturing process simulation is proposed. Firstly, the system framework and a rapid modeling method of CNC machine tool are studied under the virtual environment based on PolyTrans and CAD software. Then, a new method is proposed to enhance and expand the interactive ability of virtual reality modeling language(VRML) by attaining communication among VRML, JavaApplet, JavaScript and Html so as to realize the virtual operation for CNC machine tool. Moreover, the algorithm of material removed simulation based on VRML Z-map is presented. The advantages of this algorithm include less memory requirement and much higher computation. Lastly, the CNC milling machine is taken as an illustrative example for the prototype development in order to validate the feasibility of the proposed approach.

  2. Stirling machine operating experience

    Energy Technology Data Exchange (ETDEWEB)

    Ross, B. [Stirling Technology Co., Richland, WA (United States); Dudenhoefer, J.E. [Lewis Research Center, Cleveland, OH (United States)

    1994-09-01

    Numerous Stirling machines have been built and operated, but the operating experience of these machines is not well known. It is important to examine this operating experience in detail, because it largely substantiates the claim that stirling machines are capable of reliable and lengthy operating lives. The amount of data that exists is impressive, considering that many of the machines that have been built are developmental machines intended to show proof of concept, and are not expected to operate for lengthy periods of time. Some Stirling machines (typically free-piston machines) achieve long life through non-contact bearings, while other Stirling machines (typically kinematic) have achieved long operating lives through regular seal and bearing replacements. In addition to engine and system testing, life testing of critical components is also considered. The record in this paper is not complete, due to the reluctance of some organizations to release operational data and because several organizations were not contacted. The authors intend to repeat this assessment in three years, hoping for even greater participation.

  3. Energetic optimization of a piezo-based touch-operated button for man–machine interfaces

    NARCIS (Netherlands)

    Sun, Hao; Vries, de Theo J.A.; Vries, de Rene; Dalen, van Harry

    2012-01-01

    This paper discusses the optimization of a touch-operated button for man–machine interfaces based on piezoelectric energy harvesting techniques. In the mechanical button, a common piezoelectric diaphragm, is assembled to harvest the ambient energy from the source, i.e. the operator’s touch. Under to

  4. Energetic optimization of a piezo-based touch-operated button for man–machine interfaces

    NARCIS (Netherlands)

    de Vries, Theodorus J.A.; Sun, H.; de Vries, T.J.A.; de Vries, Rene; van Dalen, Harry

    2012-01-01

    This paper discusses the optimization of a touch-operated button for man–machine interfaces based on piezoelectric energy harvesting techniques. In the mechanical button, a common piezoelectric diaphragm, is assembled to harvest the ambient energy from the source, i.e. the operator’s touch. Under

  5. Operating Comfort Prediction Model of Human-Machine Interface Layout for Cabin Based on GEP.

    Science.gov (United States)

    Deng, Li; Wang, Guohua; Chen, Bo

    2015-01-01

    In view of the evaluation and decision-making problem of human-machine interface layout design for cabin, the operating comfort prediction model is proposed based on GEP (Gene Expression Programming), using operating comfort to evaluate layout scheme. Through joint angles to describe operating posture of upper limb, the joint angles are taken as independent variables to establish the comfort model of operating posture. Factor analysis is adopted to decrease the variable dimension; the model's input variables are reduced from 16 joint angles to 4 comfort impact factors, and the output variable is operating comfort score. The Chinese virtual human body model is built by CATIA software, which will be used to simulate and evaluate the operators' operating comfort. With 22 groups of evaluation data as training sample and validation sample, GEP algorithm is used to obtain the best fitting function between the joint angles and the operating comfort; then, operating comfort can be predicted quantitatively. The operating comfort prediction result of human-machine interface layout of driller control room shows that operating comfort prediction model based on GEP is fast and efficient, it has good prediction effect, and it can improve the design efficiency.

  6. Operator functional state classification using least-square support vector machine based recursive feature elimination technique.

    Science.gov (United States)

    Yin, Zhong; Zhang, Jianhua

    2014-01-01

    This paper proposed two psychophysiological-data-driven classification frameworks for operator functional states (OFS) assessment in safety-critical human-machine systems with stable generalization ability. The recursive feature elimination (RFE) and least square support vector machine (LSSVM) are combined and used for binary and multiclass feature selection. Besides typical binary LSSVM classifiers for two-class OFS assessment, two multiclass classifiers based on multiclass LSSVM-RFE and decision directed acyclic graph (DDAG) scheme are developed, one used for recognizing the high mental workload and fatigued state while the other for differentiating overloaded and base-line states from the normal states. Feature selection results have revealed that different dimensions of OFS can be characterized by specific set of psychophysiological features. Performance comparison studies show that reasonable high and stable classification accuracy of both classification frameworks can be achieved if the RFE procedure is properly implemented and utilized.

  7. Virtual Planning, Control, and Machining for a Modular-Based Automated Factory Operation in an Augmented Reality Environment.

    Science.gov (United States)

    Pai, Yun Suen; Yap, Hwa Jen; Md Dawal, Siti Zawiah; Ramesh, S; Phoon, Sin Ye

    2016-06-07

    This study presents a modular-based implementation of augmented reality to provide an immersive experience in learning or teaching the planning phase, control system, and machining parameters of a fully automated work cell. The architecture of the system consists of three code modules that can operate independently or combined to create a complete system that is able to guide engineers from the layout planning phase to the prototyping of the final product. The layout planning module determines the best possible arrangement in a layout for the placement of various machines, in this case a conveyor belt for transportation, a robot arm for pick-and-place operations, and a computer numerical control milling machine to generate the final prototype. The robotic arm module simulates the pick-and-place operation offline from the conveyor belt to a computer numerical control (CNC) machine utilising collision detection and inverse kinematics. Finally, the CNC module performs virtual machining based on the Uniform Space Decomposition method and axis aligned bounding box collision detection. The conducted case study revealed that given the situation, a semi-circle shaped arrangement is desirable, whereas the pick-and-place system and the final generated G-code produced the highest deviation of 3.83 mm and 5.8 mm respectively.

  8. Virtual Planning, Control, and Machining for a Modular-Based Automated Factory Operation in an Augmented Reality Environment

    Science.gov (United States)

    Pai, Yun Suen; Yap, Hwa Jen; Md Dawal, Siti Zawiah; Ramesh, S.; Phoon, Sin Ye

    2016-06-01

    This study presents a modular-based implementation of augmented reality to provide an immersive experience in learning or teaching the planning phase, control system, and machining parameters of a fully automated work cell. The architecture of the system consists of three code modules that can operate independently or combined to create a complete system that is able to guide engineers from the layout planning phase to the prototyping of the final product. The layout planning module determines the best possible arrangement in a layout for the placement of various machines, in this case a conveyor belt for transportation, a robot arm for pick-and-place operations, and a computer numerical control milling machine to generate the final prototype. The robotic arm module simulates the pick-and-place operation offline from the conveyor belt to a computer numerical control (CNC) machine utilising collision detection and inverse kinematics. Finally, the CNC module performs virtual machining based on the Uniform Space Decomposition method and axis aligned bounding box collision detection. The conducted case study revealed that given the situation, a semi-circle shaped arrangement is desirable, whereas the pick-and-place system and the final generated G-code produced the highest deviation of 3.83 mm and 5.8 mm respectively.

  9. Machine Tool Operation, Course Description.

    Science.gov (United States)

    Denny, Walter E.; Anderson, Floyd L.

    Prepared by an instructor and curriculum specialists, this course of study was designed to meet the individual needs of the dropout and/or hard-core unemployed youth by providing them skill training, related information, and supportive services knowledge in machine tool operation. The achievement level of each student is determined at entry, and…

  10. Machine function based control code algebras

    NARCIS (Netherlands)

    Bergstra, J.A.

    2008-01-01

    Machine functions have been introduced by Earley and Sturgis in [6] in order to provide a mathematical foundation of the use of the T-diagrams proposed by Bratman in [5]. Machine functions describe the operation of a machine at a very abstract level. A theory of hardware and software based on machin

  11. Standardized Curriculum for Machine Tool Operation/Machine Shop.

    Science.gov (United States)

    Mississippi State Dept. of Education, Jackson. Office of Vocational, Technical and Adult Education.

    Standardized vocational education course titles and core contents for two courses in Mississippi are provided: machine tool operation/machine shop I and II. The first course contains the following units: (1) orientation; (2) shop safety; (3) shop math; (4) measuring tools and instruments; (5) hand and bench tools; (6) blueprint reading; (7)…

  12. Machine Protection and Operation for LHC

    CERN Document Server

    Wenninger, J.

    2016-01-01

    Since 2010 the Large Hadron Collider (LHC) is the accelerator with the highest stored energy per beam, with a record of 140 MJ at a beam energy of 4 TeV, almost a factor of 50 higher than other accelerators. With such a high stored energy, machine protection aspects set the boundary conditions for operation during all phases of the machine cycle. Only the low-intensity commissioning beams can be considered as relatively safe. This document discusses the interplay of machine operation and machine protection at the LHC, from commissioning to regular operation.

  13. Machine Learning with Operational Costs

    CERN Document Server

    Tulabandhula, Theja

    2011-01-01

    This work concerns the way that statistical models are used to make decisions. In particular, we aim to merge the way estimation algorithms are designed with how they are used for a subsequent task. Our methodology considers the operational cost of carrying out a policy, based on a predictive model. The operational cost becomes a regularization term in the learning algorithm's objective function, allowing either an \\textit{optimistic} or \\textit{pessimistic} view of possible costs. Limiting the operational cost reduces the hypothesis space for the predictive model, and can thus improve generalization. We show that different types of operational problems can lead to the same type of restriction on the hypothesis space, namely the restriction to an intersection of an $\\ell_{q}$ ball with a halfspace. We bound the complexity of such hypothesis spaces by proposing a technique that involves counting integer points in polyhedrons.

  14. Mississippi Curriculum Framework for Machine Tool Operation/Machine Shop (Program CIP: 48.0503--Machine Shop Assistant). Secondary Programs.

    Science.gov (United States)

    Mississippi Research and Curriculum Unit for Vocational and Technical Education, State College.

    This document, which reflects Mississippi's statutory requirement that instructional programs be based on core curricula and performance-based assessment, contains outlines of the instructional units required in local instructional management plans and daily lesson plans for machine tool operation/machine shop I and II. Presented first are a…

  15. Fault tolerant operation of switched reluctance machine

    Science.gov (United States)

    Wang, Wei

    The energy crisis and environmental challenges have driven industry towards more energy efficient solutions. With nearly 60% of electricity consumed by various electric machines in industry sector, advancement in the efficiency of the electric drive system is of vital importance. Adjustable speed drive system (ASDS) provides excellent speed regulation and dynamic performance as well as dramatically improved system efficiency compared with conventional motors without electronics drives. Industry has witnessed tremendous grow in ASDS applications not only as a driving force but also as an electric auxiliary system for replacing bulky and low efficiency auxiliary hydraulic and mechanical systems. With the vast penetration of ASDS, its fault tolerant operation capability is more widely recognized as an important feature of drive performance especially for aerospace, automotive applications and other industrial drive applications demanding high reliability. The Switched Reluctance Machine (SRM), a low cost, highly reliable electric machine with fault tolerant operation capability, has drawn substantial attention in the past three decades. Nevertheless, SRM is not free of fault. Certain faults such as converter faults, sensor faults, winding shorts, eccentricity and position sensor faults are commonly shared among all ASDS. In this dissertation, a thorough understanding of various faults and their influence on transient and steady state performance of SRM is developed via simulation and experimental study, providing necessary knowledge for fault detection and post fault management. Lumped parameter models are established for fast real time simulation and drive control. Based on the behavior of the faults, a fault detection scheme is developed for the purpose of fast and reliable fault diagnosis. In order to improve the SRM power and torque capacity under faults, the maximum torque per ampere excitation are conceptualized and validated through theoretical analysis and

  16. Machine learning-based receiver operating characteristic (ROC) curves for crisp and fuzzy classification of DNA microarrays in cancer research.

    Science.gov (United States)

    Peterson, Leif E; Coleman, Matthew A

    2008-01-01

    Receiver operating characteristic (ROC) curves were generated to obtain classification area under the curve (AUC) as a function of feature standardization, fuzzification, and sample size from nine large sets of cancer-related DNA microarrays. Classifiers used included k nearest neighbor (kNN), näive Bayes classifier (NBC), linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), learning vector quantization (LVQ1), logistic regression (LOG), polytomous logistic regression (PLOG), artificial neural networks (ANN), particle swarm optimization (PSO), constricted particle swarm optimization (CPSO), kernel regression (RBF), radial basis function networks (RBFN), gradient descent support vector machines (SVMGD), and least squares support vector machines (SVMLS). For each data set, AUC was determined for a number of combinations of sample size, total sum[-log(p)] of feature t-tests, with and without feature standardization and with (fuzzy) and without (crisp) fuzzification of features. Altogether, a total of 2,123,530 classification runs were made. At the greatest level of sample size, ANN resulted in a fitted AUC of 90%, while PSO resulted in the lowest fitted AUC of 72.1%. AUC values derived from 4NN were the most dependent on sample size, while PSO was the least. ANN depended the most on total statistical significance of features used based on sum[-log(p)], whereas PSO was the least dependent. Standardization of features increased AUC by 8.1% for PSO and -0.2% for QDA, while fuzzification increased AUC by 9.4% for PSO and reduced AUC by 3.8% for QDA. AUC determination in planned microarray experiments without standardization and fuzzification of features will benefit the most if CPSO is used for lower levels of feature significance (i.e., sum[-log(p)] ~ 50) and ANN is used for greater levels of significance (i.e., sum[-log(p)] ~ 500). When only standardization of features is performed, studies are likely to benefit most by using CPSO for low levels

  17. Operating System For Numerically Controlled Milling Machine

    Science.gov (United States)

    Ray, R. B.

    1992-01-01

    OPMILL program is operating system for Kearney and Trecker milling machine providing fast easy way to program manufacture of machine parts with IBM-compatible personal computer. Gives machinist "equation plotter" feature, which plots equations that define movements and converts equations to milling-machine-controlling program moving cutter along defined path. System includes tool-manager software handling up to 25 tools and automatically adjusts to account for each tool. Developed on IBM PS/2 computer running DOS 3.3 with 1 MB of random-access memory.

  18. Operating System For Numerically Controlled Milling Machine

    Science.gov (United States)

    Ray, R. B.

    1992-01-01

    OPMILL program is operating system for Kearney and Trecker milling machine providing fast easy way to program manufacture of machine parts with IBM-compatible personal computer. Gives machinist "equation plotter" feature, which plots equations that define movements and converts equations to milling-machine-controlling program moving cutter along defined path. System includes tool-manager software handling up to 25 tools and automatically adjusts to account for each tool. Developed on IBM PS/2 computer running DOS 3.3 with 1 MB of random-access memory.

  19. Machine Operator Training Program and Curriculum.

    Science.gov (United States)

    St. Cyr, David; And Others

    This curriculum contains materials for use in duplicating the 11-week course for machine operators that was implemented at New Hampshire Vocational-Technical College in Nashua, New Hampshire. Addressed in the course, which is designed to prepare entry-level employees, are the following topics: basic math, blueprint reading, layout tools and…

  20. Accessible engineering drawings for visually impaired machine operators.

    Science.gov (United States)

    Ramteke, Deepak; Kansal, Gayatri; Madhab, Benu

    2014-01-01

    An engineering drawing provides manufacturing information to a machine operator. An operator plans and executes machining operations based on this information. A visually impaired (VI) operator does not have direct access to the drawings. Drawing information is provided to them verbally or by using sample parts. Both methods have limitations that affect the quality of output. Use of engineering drawings is a standard practice for every industry; this hampers employment of a VI operator. Accessible engineering drawings are required to increase both independence, as well as, employability of VI operators. Today, Computer Aided Design (CAD) software is used for making engineering drawings, which are saved in CAD files. Required information is extracted from the CAD files and converted into Braille or voice. The authors of this article propose a method to make engineering drawings information directly accessible to a VI operator.

  1. Ensuring Machine and Tractor Aggregates Operability

    Science.gov (United States)

    Redreev, G. V.

    2016-08-01

    the operability of the machine and tractor aggregates is ensured by processes which occur in machine units and considered as technical systems. In order to develop theoretical understanding of the processes in technical systems as the basis and purpose of the repairserving actions, the author's concept is presented which relies on on the basic concepts of "processes in technical systems", "maintenance and repair of performers", "maintenance and repair of technology" "objectives of the maintenance and repair". Analysis of the basic concepts of "processes in technical systems" made possible to distinguishing four types of relations: of order, stipulation, exactingness, and non-contradiction. It is shown that the implementation of maintenance and repair of technology should be conducted according to the assessment of the effectiveness of processes in technical systems, revealed in complex diagnosis. The perfection of the design of the machine in terms of its technical operation can be estimated according to the degree of consistency of processes in technical systems, purposes of maintenance and repair. In order to increase the efficiency of the lubrication system,the modernised design of the centrifugal oil filter with permanent control of its cleaning power is offered, which allows changing the technology of the maintenance of engine lubrication system by separating the operations of crankcase oil replacement and the rotor filter cleaning.

  2. 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.

  3. Local Search Method for a Parallel Machine Scheduling Problemof Minimizing the Number of Machines Operated

    Science.gov (United States)

    Yamana, Takashi; Iima, Hitoshi; Sannomiya, Nobuo

    Although there have been many studies on parallel machine scheduling problems, the number of machines operated is fixed in these studies. It is desirable to generate a schedule with fewer machines operated from the viewpoint of the operation cost of machines. In this paper, we cope with a problem of minimizing the number of parallel machines subject to the constraint that the total tardiness is not greater than the value given in advance. For this problem, we introduce a local search method in which the number of machines operated is changed efficiently and appropriately in a short time as well as reducing the total tardiness.

  4. Agent Based Computing Machine

    Science.gov (United States)

    2005-12-09

    be used in Phase 2 to accomplish the following enhancements. Due to the speed and support of MPI for C/C++ on Beowulf clusters , these languages could...1.7 ABC Machine Formal Definition 24 1.8 Computational Analysis 31 1.9 Programming Concepts 34 1.10 Cluster Mapping 38 1.11 Phase 1 Results 43 2...options for hardware implementation are explored including an emulation with a high performance cluster , a high performance silicon chip and the

  5. Measuring laser power as a force: a new paradigm to accurately monitor optical power during laser-based machining operations

    Science.gov (United States)

    Williams, Paul; Simonds, Brian; Sowards, Jeffrey; Hadler, Joshua

    2016-03-01

    In laser manufacturing operations, accurate measurement of laser power is important for product quality, operational repeatability, and process validation. Accurate real-time measurement of high-power lasers, however, is difficult. Typical thermal power meters must absorb all the laser power in order to measure it. This constrains power meters to be large, slow and exclusive (that is, the laser cannot be used for its intended purpose during the measurement). To address these limitations, we have developed a different paradigm in laser power measurement where the power is not measured according to its thermal equivalent but rather by measuring the laser beam's momentum (radiation pressure). Very simply, light reflecting from a mirror imparts a small force perpendicular to the mirror which is proportional to the optical power. By mounting a high-reflectivity mirror on a high-sensitivity force transducer (scale), we are able to measure laser power in the range of tens of watts up to ~ 100 kW. The critical parameters for such a device are mirror reflectivity, angle of incidence, and scale sensitivity and accuracy. We will describe our experimental characterization of a radiation-pressure-based optical power meter. We have tested it for modulated and CW laser powers up to 92 kW in the laboratory and up to 20 kW in an experimental laser welding booth. We will describe present accuracy, temporal response, sources of measurement uncertainty, and hurdles which must be overcome to have an accurate power meter capable of routine operation as a turning mirror within a laser delivery head.

  6. Simulation Modeling and Analysis of Operator-Machine Ratio

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Based on a simulation model of a semiconductor manufacturer, operator-machine ratio (OMR) analysis is made using work study and time study. Through sensitivity analysis, it is found that labor utilization decreases with the increase of lot size.Meanwhile, it is able to identify that the OMR for this company should be improved from 1∶3 to 1∶5. An application result shows that the proposed model can effectively improve the OMR by 33%.

  7. MONITORING DIAGNOSTIC INDICATORS DURING OPERATION OF A PRINT MACHIN

    Directory of Open Access Journals (Sweden)

    Jozef Dobránsky

    2015-11-01

    Full Text Available This article deals with monitoring diagnostic indicators during the operation of a machine used for production of packing materials with a print. It analyses low-frequency vibrations measured in individual spherical roller bearings in eight print positions. The rollers in these positions have a different pressure based on positioning these rollers in relation to the central roller. As a result, the article also deals with a correlation of pressure and level of measured low-frequency vibrations. The speed of the print machine (the speed of a line in meters per minute is a very important variable during its operation, this is why it is important to verify the values of vibrations in various speeds of the line, what can lead to revelation of one or more resonance areas. Moreover, it examines vibrations of the central roller drive and measurement of backlash of transmission cogs of this drive. Based on performed analyses recommendations for an operator of the machine have been conceived.

  8. Job Grading Standard for Machine Tool Operator, WG-3431.

    Science.gov (United States)

    Civil Service Commission, Washington, DC. Bureau of Policies and Standards.

    The standard covers nonsupervisory work involved in the set up, adjustment, and operation of conventional machine tools to perform machining operations in the manufacture and repair of castings, forgings, or parts from raw stock made of various metals, metal alloys, and other materials. A general description of the job at both the WG-8 and WG-9…

  9. Refrigerating machine operating characteristics under various mixed refrigerant mass charges

    Energy Technology Data Exchange (ETDEWEB)

    Rozhentsev, Andrey [Far Eastern State Transport University of the Russian Federation, Seryshev street, 47, 680021 Khabarovsk (Russian Federation)

    2008-11-15

    This paper reports the results of experimental investigation of a low-temperature Joule-Thomson refrigerating machine, working by use of a non-azeotropic mixture of refrigerants and with a single-stage hermetic compressor. The temperature, hydraulic and power performance of the machine are determined experimentally in relation to the mixed refrigerant (MR) mass charge. Variations of the MR refrigerating machine operating performance with the working mixture mass charge are found to be considerably different from the analogous performance variations of a refrigerating machine charged with a pure refrigerant. The peculiarities of those relationships are analyzed theoretically. The specific value of a minimum acceptable MR mass charge for the investigated system and its correlation with internal processes in the machine loop are established as well. If the refrigerant mixture mass charges are below the minimum ones, the temperature and power performance of the MR machine differ essentially from the design performance and such operating modes are considered inadmissible. (author)

  10. Temperature based Restricted Boltzmann Machines.

    Science.gov (United States)

    Li, Guoqi; Deng, Lei; Xu, Yi; Wen, Changyun; Wang, Wei; Pei, Jing; Shi, Luping

    2016-01-13

    Restricted Boltzmann machines (RBMs), which apply graphical models to learning probability distribution over a set of inputs, have attracted much attention recently since being proposed as building blocks of multi-layer learning systems called deep belief networks (DBNs). Note that temperature is a key factor of the Boltzmann distribution that RBMs originate from. However, none of existing schemes have considered the impact of temperature in the graphical model of DBNs. In this work, we propose temperature based restricted Boltzmann machines (TRBMs) which reveals that temperature is an essential parameter controlling the selectivity of the firing neurons in the hidden layers. We theoretically prove that the effect of temperature can be adjusted by setting the parameter of the sharpness of the logistic function in the proposed TRBMs. The performance of RBMs can be improved by adjusting the temperature parameter of TRBMs. This work provides a comprehensive insights into the deep belief networks and deep learning architectures from a physical point of view.

  11. Machining operations using Yamaha YK 400 robot

    Science.gov (United States)

    Pop, A.; Pop, A.; Savu, D.; Dolga, V.

    2016-08-01

    This paper addresses the topic of industrial robots built for handling processes used in cutting machining applications. The study discourses the machining of a globe calotte made of komatex using a Yamaha YK 400 SCARA robot. Are presented aspects regarding the capabilities of Yamaha YK 400 robot, the development of the robot program, analyses of the proposed system and methods of improvement. A set of experimental analyses was conducted in order to identify correlations between the robot speed variation and distance between the points that describe the trajectory of the motion.

  12. 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.

  13. AUTOMATING FACING OPERATION ON A CNC MACHINING CENTRE

    Directory of Open Access Journals (Sweden)

    S. K. SINHA

    2010-12-01

    Full Text Available Facing is usually the first and an essential process on a CNC machining centre, using a face-milling cutter, on any workpiece, because many a time, the workpiece is obtained through a “rough” casting process. The advantage of a cast part is that a workpiece with slightly oversize dimensions is made available, usuallyrequiring very little machining. This saves machining costs. However, the inherent limitation of common casting processes is inaccuracy in dimensions as well as surface roughness. Because of this reason, facing becomes the first machining operation. On a CNC milling machine, this requires a facing program written in terms of Gcodes.Since dimensions of different workpieces are likely to be different, offering different areas to be faced, the same program would not work on all workpieces. The present paper uses the latest macro-programmingtechnique, available on modern CNC machines, to develop a single program for workpieces of all dimensions.

  14. Development of an Electrically Operated Cassava Peeling and Slicing Machine

    Directory of Open Access Journals (Sweden)

    I. S. Aji

    2017-08-01

    Full Text Available The development and construction of an electrically operated cassava peeling and slicing machine was described in this paper. The objective was to design, construct and test an electrically operated machine that will peel and slice cassava root into chips, to aid the processes of drying, pelletizing and storage. The methodology adopted includes; design, construction, calculation, specification, assembly of component parts and performance test. The machine was able to Peel and slice cassava to fairly similar sizes. Performance test reveals that 7 kg of cassava tuber was peeled and chipped in one minute, which shows that, the machine developed can significantly reduce the cost of labour and time wastage associated with traditional processing of cassava tubers into dried cassava pellets, and finished products, such as; garri, and cassava flour. The machine has a capacity of 6.72 kg/min, with peeling and chipping efficiency of 66.2% and 84.0% respectively. The flesh loss of the peeled tuber was 8.52%, while overall machine efficiency obtained as 82.4%. The machine is recommended for use by small scale industries and by cassava farmers in the rural areas. It has an overall cost of N46100 ($150. The machine can easily be operated by an individual and maintained, by using warm water to wash the component parts, and sharpening of the chipping disc when required.

  15. Improving machine operation management efficiency via improving the vehicle park structure and using the production operation information database

    Science.gov (United States)

    Koptev, V. Yu

    2017-02-01

    The work represents the results of studying basic interconnected criteria of separate equipment units of the transport network machines fleet, depending on production and mining factors to improve the transport systems management. Justifying the selection of a control system necessitates employing new methodologies and models, augmented with stability and transport flow criteria, accounting for mining work development dynamics on mining sites. A necessary condition is the accounting of technical and operating parameters related to vehicle operation. Modern open pit mining dispatching systems must include such kinds of the information database. An algorithm forming a machine fleet is presented based on multi-variation task solution in connection with defining reasonable operating features of a machine working as a part of a complex. Proposals cited in the work may apply to mining machines (drilling equipment, excavators) and construction equipment (bulldozers, cranes, pile-drivers), city transport and other types of production activities using machine fleet.

  16. 76 FR 174 - International Business Machines (IBM), Global Sales Operations Organization, Sales and...

    Science.gov (United States)

    2011-01-03

    ... Employment and Training Administration International Business Machines (IBM), Global Sales Operations...; International Business Machines (IBM), Global Sales Operations Organization, Sales and Distribution Business..., applicable to workers of International Business Machines (IBM), Global Sales Operations Organization,...

  17. Improved Operating Performance of Mining Machine Picks

    Science.gov (United States)

    Prokopenko, S.; Li, A.; Kurzina, I.; Sushko, A.

    2016-08-01

    The reasons of low performance of mining machine picks are stated herein. In order to improve the wear resistance and the cutting ability of picks a new design of a cutting carbide tip insert to be fixed on a removable and rotating pick head is developed. Owing to the new design, the tool ensures a twofold increase in the cutting force maintained longer, a twofold reduction in the specific power consumption of the breaking process, and extended service life of picks and the possibility of their multiple use.

  18. Development of Cassava Grating Machine: A Dual-Operational Mode

    Directory of Open Access Journals (Sweden)

    Mohammed B. NDALIMAN

    2006-07-01

    Full Text Available Design of a Cassava grating machine which has two modes of operation was made. It can be powered either electrically or manually. It takes care of power failure problems, and can be used in rural settlements where electricity supply is not in existence. Cassava is fed with the Machine through the hopper made of metal sheet to the granting drum, which rotates at a constant speed. This process grates the cassava into cassava pulp. The chute constructed of metal sheet accepts the pulp and send it out because of its inclination which operated manually, the efficiency of the machine was found to be 92.4%, which the efficiency of the electrically powered machine was found to be 91.9%.

  19. 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.

  20. Principles of machine operation and maintenance

    CERN Document Server

    Jeffrey, Dick

    2013-01-01

    This book explains how rotating machinery works, and the role of the maintenance engineer in ensuring its proper operation. Stress is laid on the need for the trainee engineer to develop skills in diagnosis and troubleshooting as well as practicalexpertise in maintenance procedures.

  1. A survey of machine readable data bases

    Science.gov (United States)

    Matlock, P.

    1981-01-01

    Forty-two of the machine readable data bases available to the technologist and researcher in the natural sciences and engineering are described and compared with the data bases and date base services offered by NASA.

  2. STEP based Finish Machining CAPP system

    OpenAIRE

    A Arivazhagan; Mehta, NK; Jain, PK

    2012-01-01

    This research paper presents various methodologies developed in a STEP based Computer Aided Process Planning (CAPP) system named "Finish Machining – CAPP" (FM-CAPP). It is developed to generate automatic process plans for finish machining prismatic parts. It is designed in a modular fashion consisting of three main modules, namely (i) Feature Recognition module (FRM) (ii) Machining Planning Module (MPM) and (iii) Setup Planning Module (SPM). The FRM Module analyses the geometrical and topolog...

  3. Shaper and Milling Machine Operation, Machine Shop Work 2: 9555.04.

    Science.gov (United States)

    Dade County Public Schools, Miami, FL.

    The course outline has been prepared to assist the student in learning the basic skills and safety for shaper and milling operations. The course presents the various types of machines, work holding devices, cutting tools and feeds and speeds, and instruction designed to enable the student to obtain the manipulative skills and related knowledge…

  4. USE OF GENETIC ALGORITHMS TO SEQUENCE THE MACHINING OPERATIONS OF PARTS

    Institute of Scientific and Technical Information of China (English)

    1998-01-01

    Genetic algorithms are used to determine the sequence of parts\\' machining operations.First, the feature operation units are encoded to a genetic string with natural digits, and the sequencing constraint knowledge is represented by the fitness functions based on four types of constraints, and then, through the implementation of the genetic operators including reproduction, crossover and mutation, a rational sequence of operations is being searched and can be found finally.Such sequence is also optimal.

  5. Critical Machine Based Scheduling -A Review

    Science.gov (United States)

    Vivek, P.; Saravanan, R.; Chandrasekaran, M.; Pugazhenthi, R.

    2017-03-01

    This article aims to identify the natural occurrence of the critical machines in scheduling. The exciting scheduling in the real time manufacturing environment is focused on considering equal weight-age of all the machines, but very few researchers were considered the real time constraint(s) like processor/ machine/ workstation availability, etc.,. This article explores the gap between the theory and practices by identifying the critical machine in scheduling and helps the researcher to find the suitable problem in their case study environment. Through the literature survey, it is evident that, in scheduling the occurrence of the critical machine is in nature. The critical machine is found in various names and gives a various range of weight-age based on the particular manufacturing environment and it plays a vital role in scheduling which includes one or more circumstances of occurrence in the production environment. Very few researchers were reported that in manufacturing environment, the critical machine occurrence is in nature, but most of the researchers were focused to optimize the manufacturing environment by only reducing the cycle time. In real-time manufacturing environment, the scheduling of critical machine(s) was keenly monitored and some weight-age was considered.

  6. Development of Web-based Virtual Training Environment for Machining

    Science.gov (United States)

    Yang, Zhixin; Wong, S. F.

    2010-05-01

    With the booming in the manufacturing sector of shoe, garments and toy, etc. in pearl region, training the usage of various facilities and design the facility layout become crucial for the success of industry companies. There is evidence that the use of virtual training may provide benefits in improving the effect of learning and reducing risk in the physical work environment. This paper proposed an advanced web-based training environment that could demonstrate the usage of a CNC machine in terms of working condition and parameters selection. The developed virtual environment could provide training at junior level and advanced level. Junior level training is to explain machining knowledge including safety factors, machine parameters (ex. material, speed, feed rate). Advanced level training enables interactive programming of NG coding and effect simulation. Operation sequence was used to assist the user to choose the appropriate machining condition. Several case studies were also carried out with animation of milling and turning operations.

  7. Development of Prediction System for Environmental Burden for Machine Tool Operation

    Science.gov (United States)

    Narita, Hirohisa; Kawamura, Hiroshi; Norihisa, Takashi; Chen, Lian-Yi; Fujimoto, Hideo; Hasebe, Takao

    Recently, some activities for environmental protection have been attempted to reduce environmental burdens in many fields. The manufacturing field also requires such reduction. Hence, a prediction system for environmental burden for machining operation is proposed based on the Life Cycle Assessment (LCA) policy for the future manufacturing system in this research. This system enables the calculation of environmental burden (equivalent CO2 emission) due to the electric consumption of machine tool components, cutting tool status, coolant quantity, lubricant oil quantity and metal chip quantity, and provides accurate information of environmental burden of the machining process by considering some activities related to machine tool operation. In this paper, the development of the prediction system is described. As a case study, two Numerical Control (NC) programs that manufacture a simple shape are evaluated to show the feasibility of the proposed system.

  8. Lane Detection Based on Machine Learning Algorithm

    National Research Council Canada - National Science Library

    Chao Fan; Jingbo Xu; Shuai Di

    2013-01-01

    In order to improve accuracy and robustness of the lane detection in complex conditions, such as the shadows and illumination changing, a novel detection algorithm was proposed based on machine learning...

  9. Molecular machines operating on the nanoscale: from classical to quantum

    Directory of Open Access Journals (Sweden)

    Igor Goychuk

    2016-03-01

    Full Text Available The main physical features and operating principles of isothermal nanomachines in the microworld, common to both classical and quantum machines, are reviewed. Special attention is paid to the dual, constructive role of dissipation and thermal fluctuations, the fluctuation–dissipation theorem, heat losses and free energy transduction, thermodynamic efficiency, and thermodynamic efficiency at maximum power. Several basic models are considered and discussed to highlight generic physical features. This work examines some common fallacies that continue to plague the literature. In particular, the erroneous beliefs that one should minimize friction and lower the temperature for high performance of Brownian machines, and that the thermodynamic efficiency at maximum power cannot exceed one-half are discussed. The emerging topic of anomalous molecular motors operating subdiffusively but very efficiently in the viscoelastic environment of living cells is also discussed.

  10. Operation Range of Brushless Doubly-fed Machine Based on Slot-harmonics%齿谐波法设计的无刷双馈发电机运行范围

    Institute of Scientific and Technical Information of China (English)

    阚超豪; 王雪帆

    2011-01-01

    Wound rotor brushless doubly-fed machine (WRBDFM) based on slot-harmonics have wide application in variable speed constant frequency power generation, and the reliability of the machine is the key factor for the applications of WRBDFM. In order to achieve safely operate for the machine, the working area was defined as the zone in which brushless doubly-fest machine could safely be operated without exceeding its material and stability limits. It meant that there were some restrictions needed, such as electric loadings, magnetic loadings and capacity of converter. Based on the field of marine shaft actual working conditions and the full circuit model of slot-harmonics WRBDFM, It had been analyzed that the electric loadings composition and temperature rising of the machine, the select of magnetic loadings and the selection of converter-inverter capacity. The stability operation range was obtained. Finally, the correctness of results and theoretical analysis gained from researching was verified through the experiment of laboratory WRBDFM.%转子绕组采用齿谐波法设计的无刷双馈电机在变速恒频发电领域有着广泛的应用前景,而影响其应用的关键在于电机运行的可靠性。要实现电机可靠运行,则必须考虑电机能可靠运行的约束条件。约束条件主要包含运行时电机的电负荷、磁负荷和变频器容量等。根据齿谐波法绕线转子无刷双馈发电机在船用轴带领域的实际工况,依据绕线转子无刷双馈电机全电路模型,对轴带发电机电负荷的组成及其对电机温升的影响、磁负荷选择的依据和变频器容量的选择等进行了分析,推导了绕线转子无刷双馈发电机可靠运行的范围。计算和样机实验对比验证了结论的正确性。

  11. Operating point resolved loss computation in electrical machines

    Directory of Open Access Journals (Sweden)

    Pfingsten Georg Von

    2016-03-01

    Full Text Available Magnetic circuits of electromagnetic energy converters, such as electrical machines, are nowadays highly utilized. This proposition is intrinsic for the magnetic as well as the electric circuit and depicts that significant enhancements of electrical machines are difficult to achieve in the absence of a detailed understanding of underlying effects. In order to improve the properties of electrical machines the accurate determination of the locally distributed iron losses based on idealized model assumptions solely is not sufficient. Other loss generating effects have to be considered and the possibility being able to distinguish between the causes of particular loss components is indispensable. Parasitic loss mechanisms additionally contributing to the total losses originating from field harmonics, non-linear material behaviour, rotational magnetizations, and detrimental effects caused by the manufacturing process or temperature, are not explicitly considered in the common iron-loss models, probably even not specifically contained in commonly used calibration factors. This paper presents a methodology being able to distinguish between different loss mechanisms and enables to individually consider particular loss mechanisms in the model of the electric machine. A sensitivity analysis of the model parameters can be performed to obtain information about which decisive loss origin for which working point has to be manipulated by the electromagnetic design or the control of the machine.

  12. A Low-Cost Easy-Operation Hexapod Walking Machine

    Directory of Open Access Journals (Sweden)

    Giuseppe Carbone

    2008-06-01

    Full Text Available This paper presents the mechanical design of an hybrid hexapod walking machine that has been designed and built at LARM: Laboratory of Robotics and Mechatronics in Cassino. Basic characteristics are investigated in order to design a leg system with suitable low-cost modular components. Moreover, special care has been addressed in proposing an architecture that can be easily operated by a PLC with on-off logic. Experimental tests are reported in order to show feasibility and operational capability of proposed design.

  13. Optimization of Operation Sequence in CNC Machine Tools Using Genetic Algorithm

    Science.gov (United States)

    Abu Qudeiri, Jaber; Yamamoto, Hidehiko; Ramli, Rizauddin

    The productivity of machine tools is significantly improved by using microcomputer based CAD/CAM systems for NC program generation. Currently, many commercial CAD/CAM packages that provide automatic NC programming have been developed and applied to various cutting processes. Many cutting processes machined by CNC machine tools. In this paper, we attempt to find an efficient solution approach to determine the best sequence of operations for a set of operations that located in asymmetrical locations and different levels. In order to find the best sequence of operations that achieves the shortest cutting tool travel path (CTTP), genetic algorithm is introduced. After the sequence is optimized, the G-codes that use to code for the travel time is created. CTTP can be formulated as a special case of the traveling salesman problem (TSP). The incorporation of genetic algorithm and TSP can be included in the commercial CAD/CAM packages to optimize the CTTP during automatic generation of NC programs.

  14. Chunk Alignment for Corpus-Based Machine Translation

    Science.gov (United States)

    Kim, Jae Dong

    2011-01-01

    Since sub-sentential alignment is critically important to the translation quality of an Example-Based Machine Translation (EBMT) system, which operates by finding and combining phrase-level matches against the training examples, we developed a new alignment algorithm for the purpose of improving the EBMT system's performance. This new…

  15. Job Analysis Schedule--Offset Press Operator (Multilith 1250 W) or Offset Duplicating Machine Operator.

    Science.gov (United States)

    Feyock, Anthony J.

    This paper presents an analysis of the job performed by an offset press operator (alternate title is offset duplicating machine operator) of a Multilith 1250 W. First covered is work performed, as follows: prepares dampening unit for printing run, prepares inking unit for printing, readies printing plate for printing, sets up press for running,…

  16. Basic Operation of Cryocoolers and Related Thermal Machines

    Science.gov (United States)

    de Waele, A. T. A. M.

    2011-09-01

    This paper deals with the basics of cryocoolers and related thermodynamic systems. The treatment is based on the first and second law of thermodynamics for inhomogeneous, open systems using enthalpy flow, entropy flow, and entropy production. Various types of machines, which use an oscillating gas flow, are discussed such as: Stirling refrigerators, GM coolers, pulse-tube refrigerators, and thermoacoustic coolers and engines. Furthermore the paper deals with Joule-Thomson and dilution refrigerators which use a constant flow of the working medium.

  17. 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

  18. Correlation of cutting fluid performance in different machining operations

    DEFF Research Database (Denmark)

    De Chiffre, Leonardo; Belluco, Walter

    2001-01-01

    An analysis of cutting fluid performance in different metal cutting operations is presented, based on experimental investigations in which type of operation, performance criteria, work material, and fluid type are considered. Cutting fluid performance was evaluated in turning, drilling, reaming...

  19. Machine-Tractor Aggregates Operation Assurance by Mobile Maintenance Teams

    Science.gov (United States)

    Redreev, G. V.; Myalo, O. V.; Prokopov, S. P.; Solomkin, A. P.; Okunev, G. A.

    2017-07-01

    operability of machine-tractor aggregates (MTA) is ensured by purposeful activity of maintenance and repair performers. MTAs operation assurance can provide achievement of absolutely different goals. For further development of technical service formation concept concretization in the part of determining locations of maintenance and repair performers and their area of expertise is suggested, as well as of arising peculiarities of equipment. The theoretical task is reduced to the type of tasks of distribution of recourses or transportation tasks. Mobile maintenance teams of regional agricultural equipment manufacturers’ dealers have experience of technical service performance. The formed stream of requests from agricultural plants determines the direction of correcting of existing theoretical provisions, confirming necessity of further development of centralized method of technical service by efforts and means of manufacturers’ dealers.

  20. Efficient operation of anisotropic synchronous machines for wind energy systems

    Science.gov (United States)

    Eldeeb, Hisham; Hackf, Christoph M.; Kullick, Julian

    2016-09-01

    This paper presents an analytical solution for the Maximum-Torque-per-Ampere (MTPA) operation of synchronous machines (SM) with anisotropy and magnetic cross-coupling for the application in wind turbine systems and airborne wind energy systems. For a given reference torque, the analytical MTPA solution provides the optimal stator current references which produce the desired torque while minimizing the stator copper losses. From an implementation point of view, the proposed analytical method is appealing in terms of its fast online computation (compared to classical numerical methods) and its efficiency enhancement of the electrical drive system. The efficiency of the analytical MTPA operation, with and without consideration of cross-coupling, is compared to the conventional method with zero direct current.

  1. Prototype-based models in machine learning

    NARCIS (Netherlands)

    Biehl, Michael; Hammer, Barbara; Villmann, Thomas

    2016-01-01

    An overview is given of prototype-based models in machine learning. In this framework, observations, i.e., data, are stored in terms of typical representatives. Together with a suitable measure of similarity, the systems can be employed in the context of unsupervised and supervised analysis of poten

  2. Prototype-based models in machine learning

    NARCIS (Netherlands)

    Biehl, Michael; Hammer, Barbara; Villmann, Thomas

    2016-01-01

    An overview is given of prototype-based models in machine learning. In this framework, observations, i.e., data, are stored in terms of typical representatives. Together with a suitable measure of similarity, the systems can be employed in the context of unsupervised and supervised analysis of

  3. A nanoplasmonic switch based on molecular machines

    KAUST Repository

    Zheng, Yue Bing

    2009-06-01

    We aim to develop a molecular-machine-driven nanoplasmonic switch for its use in future nanophotonic integrated circuits (ICs) that have applications in optical communication, information processing, biological and chemical sensing. Experimental data show that an Au nanodisk array, coated with rotaxane molecular machines, switches its localized surface plasmon resonances (LSPR) reversibly when it is exposed to chemical oxidants and reductants. Conversely, bare Au nanodisks and disks coated with mechanically inert control compounds, do not display the same switching behavior. Along with calculations based on time-dependent density functional theory (TDDFT), these observations suggest that the nanoscale movements within surface-bound "molecular machines" can be used as the active components in plasmonic devices. ©2009 IEEE.

  4. Optimization of Surface Finish in Turning Operation by Considering the Machine Tool Vibration using Taguchi Method

    Directory of Open Access Journals (Sweden)

    Muhammad Munawar

    2012-01-01

    Full Text Available Optimization of surface roughness has been one of the primary objectives in most of the machining operations. Poor control on the desired surface roughness generates non conforming parts and results into increase in cost and loss of productivity due to rework or scrap. Surface roughness value is a result of several process variables among which machine tool condition is one of the significant variables. In this study, experimentation was carried out to investigate the effect of machine tool condition on surface roughness. Variable used to represent machine tool\\'s condition was vibration amplitude. Input parameters used, besides vibration amplitude, were feed rate and insert nose radius. Cutting speed and depth of cut were kept constant. Based on Taguchi orthogonal array, a series of experimentation was designed and performed on AISI 1040 carbon steel bar at default and induced machine tool\\'s vibration amplitudes. ANOVA (Analysis of Variance, revealed that vibration amplitude and feed rate had moderate effect on the surface roughness and insert nose radius had the highest significant effect on the surface roughness. It was also found that a machine tool with low vibration amplitude produced better surface roughness. Insert with larger nose radius produced better surface roughness at low feed rate.

  5. Synthetic recombinase-based state machines in living cells.

    Science.gov (United States)

    Roquet, Nathaniel; Soleimany, Ava P; Ferris, Alyssa C; Aaronson, Scott; Lu, Timothy K

    2016-07-22

    State machines underlie the sophisticated functionality behind human-made and natural computing systems that perform order-dependent information processing. We developed a recombinase-based framework for building state machines in living cells by leveraging chemically controlled DNA excision and inversion operations to encode states in DNA sequences. This strategy enables convenient readout of states (by sequencing and/or polymerase chain reaction) as well as complex regulation of gene expression. We validated our framework by engineering state machines in Escherichia coli that used one, two, or three chemical inputs to control up to 16 DNA states. These state machines were capable of recording the temporal order of all inputs and performing multi-input, multi-output control of gene expression. We also developed a computational tool for the automated design of gene regulation programs using recombinase-based state machines. Our scalable framework should enable new strategies for recording and studying how combinational and temporal events regulate complex cell functions and for programming sophisticated cell behaviors.

  6. Design and manufacturing of abrasive jet machine for drilling operation

    Directory of Open Access Journals (Sweden)

    Mittal Divyansh

    2016-01-01

    Full Text Available Wide application of Abrasive Jet Machine (AJM is found in machining hard and brittle materials. Machining of brittle materials by AJM is due to brittle fracture and removal of micro chips from the work piece. Embedment of the abrasive particles in the brittle materials results in decrease of machining efficiency. In this paper design and manufacturing of AJM has been presented. Various parts of AJM have been designed using ANSYS 16.2 software. The parts are then manufactured indigenously as per designed parameters. The machine fabricated in this work will be used further for process optimization of AJM parameters for machining of glass and ceramics.

  7. Outlier Mining Based Abnormal Machine Detection in Intelligent Maintenance

    Institute of Scientific and Technical Information of China (English)

    ZHANG Lei; CAO Qi-xin; LEE Jay

    2009-01-01

    Assessing machine's performance through comparing the same or similar machines is important to implement intelligent maintenance for swarm machine. In this paper, an outlier mining based abnormal machine detection algorithm is proposed for this purpose. Firstly, the outlier mining based on clustering is introduced and the definition of cluster-based global outlier factor (CBGOF) is presented. Then the modified swarm intelligence clustering(MSIC) algorithm is suggested and the outlier mining algorithm based on MSIC is proposed. The algorithm can not only cluster machines according to their performance but also detect possible abnormal machines. Finally, a comparison of mobile soccer robots' performance proves the algorithm is feasible and effective.

  8. Investigations of Cutting Fluid Performance Using Different Machining Operations

    DEFF Research Database (Denmark)

    De Chiffre, Leonardo; Belluco, Walter

    2002-01-01

    An analysis of cutting fluid performance in dif-ferent metal cutting operations is presented based on performance criteria, work material and fluid type. Cutting fluid performance was evaluated in turning, drilling, reaming and tapping operations, with respect to tool life, cutting forces and prod......-gated. In the case of austenitic stainless steel as the workpiece material, results using the different operations under different cutting conditions show that the performance of vegetable oil based prod-ucts is superior or equal to that of mineral oil based products. The hypothesis was investigated that one...

  9. Investigations of Cutting Fluid Performance Using Different Machining Operations

    DEFF Research Database (Denmark)

    De Chiffre, Leonardo; Belluco, Walter

    2002-01-01

    An analysis of cutting fluid performance in dif-ferent metal cutting operations is presented based on performance criteria, work material and fluid type. Cutting fluid performance was evaluated in turning, drilling, reaming and tapping operations, with respect to tool life, cutting forces and prod...

  10. 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.

  11. Applying Multi-Class Support Vector Machines for performance assessment of shipping operations: The case of tanker vessels

    DEFF Research Database (Denmark)

    Pagoropoulos, Aris; Møller, Anders H.; McAloone, Tim C.

    2017-01-01

    efficient operations. Positive and negative patterns of energy efficient operations were identified and verified through discussions with senior officers and technical superintendents. Based on this data, the high dimensional parameter space that describes vessel operations was first reduced by means...... of feature selection algorithms. Afterwards, a model based on Multi- Class Support Vector Machines (SVM) was constructed and the efficacy of the approach is shown through the application of a test set. The results demonstrate the importance and benefits of machine learning algorithms in driving energy...... efficiency on board, as well as the impact of power management on energy costs throughout the life cycle of the ships....

  12. Pre-use anesthesia machine check; certified anesthesia technician based quality improvement audit

    Science.gov (United States)

    Al Suhaibani, Mazen; Al Malki, Assaf; Al Dosary, Saad; Al Barmawi, Hanan; Pogoku, Mahdhav

    2014-01-01

    Context: Quality assurance of providing a work ready machine in multiple theatre operating rooms in a tertiary modern medical center in Riyadh. Aims: The aim of the following study is to keep high quality environment for workers and patients in surgical operating rooms. Settings and Design: Technicians based audit by using key performance indicators to assure inspection, passing test of machine worthiness for use daily and in between cases and in case of unexpected failure to provide quick replacement by ready to use another anesthetic machine. Materials and Methods: The anesthetic machines in all operating rooms are daily and continuously inspected and passed as ready by technicians and verified by anesthesiologist consultant or assistant consultant. The daily records of each machines were collected then inspected for data analysis by quality improvement committee department for descriptive analysis and report the degree of staff compliance to daily inspection as “met” items. Replaced machine during use and overall compliance. Statistical Analysis Used: Distractive statistic using Microsoft Excel 2003 tables and graphs of sums and percentages of item studied in this audit. Results: Audit obtained highest compliance percentage and low rate of replacement of machine which indicate unexpected machine state of use and quick machine switch. Conclusions: The authors are able to conclude that following regular inspection and running self-check recommended by the manufacturers can contribute to abort any possibility of hazard of anesthesia machine failure during operation. Furthermore in case of unexpected reason to replace the anesthesia machine in quick maneuver contributes to high assured operative utilization of man machine inter-phase in modern surgical operating rooms. PMID:25886335

  13. Finite State Machine based Vending Machine Controller with Auto-Billing Features

    Directory of Open Access Journals (Sweden)

    Ana Monga

    2012-04-01

    Full Text Available Nowadays, Vending Machines are well known among Japan, Malaysia and Singapore. The quantity of machines in these countries is on the top worldwide. This is due to the modern lifestyles which require fast food processing with high quality. This paper describes the designing of multi select machine using Finite State Machine Model with Auto-Billing Features. Finite State Machine (FSM modelling is the most crucial part in developing proposed model as this reduces the hardware. In this paper the process of four state (user Selection, Waiting for money insertion, product delivery and servicing has been modelled using MEALY Machine Model. The proposed model is tested using Spartan 3 development board and its performance is compared with CMOS based machine.

  14. Finite State Machine based Vending Machine Controller with Auto-Billing Features

    Directory of Open Access Journals (Sweden)

    Balwinder Singh

    2012-05-01

    Full Text Available Nowadays, Vending Machines are well known among Japan, Malaysia and Singapore. The quantity of machines in these countries is on the top worldwide. This is due to the modern lifestyles which require fast food processing with high quality. This paper describes the designing of multi select machine using Finite State Machine Model with Auto-Billing Features. Finite State Machine (FSM modelling is the most crucial part in developing proposed model as this reduces the hardware. In this paper the process of four state (user Selection, Waiting for money insertion, product delivery and servicing has been modelled using MEALY Machine Model. The proposed model is tested using Spartan 3 development board and its performance is compared with CMOS based machine.

  15. Finite State Machine based Vending Machine Controller with Auto-Billing Features

    CERN Document Server

    Monga, Ana; 10.5121/vlsic.2012.3202

    2012-01-01

    Nowadays, Vending Machines are well known among Japan, Malaysia and Singapore. The quantity of machines in these countries is on the top worldwide. This is due to the modern lifestyles which require fast food processing with high quality. This paper describes the designing of multi select machine using Finite State Machine Model with Auto-Billing Features. Finite State Machine (FSM) modelling is the most crucial part in developing proposed model as this reduces the hardware. In this paper the process of four state (user Selection, Waiting for money insertion, product delivery and servicing) has been modelled using MEALY Machine Model. The proposed model is tested using Spartan 3 development board and its performance is compared with CMOS based machine.

  16. Support vector machine-based multi-model predictive control

    Institute of Scientific and Technical Information of China (English)

    Zhejing BA; Youxian SUN

    2008-01-01

    In this paper,a support vector machine-based multi-model predictive control is proposed,in which SVM classification combines well with SVM regression.At first,each working environment is modeled by SVM regression and the support vector machine network-based model predictive control(SVMN-MPC)algorithm corresponding to each environment is developed,and then a multi-class SVM model is established to recognize multiple operating conditions.As for control,the current environment is identified by the multi-class SVM model and then the corresponding SVMN.MPCcontroller is activated at each sampling instant.The proposed modeling,switching and controller design is demonstrated in simulation results.

  17. 基于人机工程学的机械操作面板设计研究%The machinery operation panel design and study based on man-machine engineering

    Institute of Scientific and Technical Information of China (English)

    孟庆强

    2011-01-01

    Staring from the man-machine interface design concept, fully consider people's factors, the mechanical operation interface design principles and human environment relationship is studied. The operation panel maximum limit match with human body structure. For the operator to create a safe, healthy and comfortable environment. Makes the man-machine system to play out maximum efficiency.%从人机界面设计的概念入手,充分考虑人的因素,对机械操作界面的设计原则和人机环境关系进行了研究,最终使操作面板最大限度地与人体结构相匹配,为操作者创造一个安全、健康、舒适的操作环境,使人机系统发挥出最大的效率.

  18. Alternative Models of Service, Centralized Machine Operations. Phase II Report. Volume II.

    Science.gov (United States)

    Technology Management Corp., Alexandria, VA.

    A study was conducted to determine if the centralization of playback machine operations for the national free library program would be feasible, economical, and desirable. An alternative model of playback machine services was constructed and compared with existing network operations considering both cost and service. The alternative model was…

  19. Rule based systems for big data a machine learning approach

    CERN Document Server

    Liu, Han; Cocea, Mihaela

    2016-01-01

    The ideas introduced in this book explore the relationships among rule based systems, machine learning and big data. Rule based systems are seen as a special type of expert systems, which can be built by using expert knowledge or learning from real data. The book focuses on the development and evaluation of rule based systems in terms of accuracy, efficiency and interpretability. In particular, a unified framework for building rule based systems, which consists of the operations of rule generation, rule simplification and rule representation, is presented. Each of these operations is detailed using specific methods or techniques. In addition, this book also presents some ensemble learning frameworks for building ensemble rule based systems.

  20. Passivity-Based Control of Electric Machines

    Energy Technology Data Exchange (ETDEWEB)

    Nicklasson, P.J.

    1996-12-31

    This doctoral thesis presents new results on the design and analysis of controllers for a class of electric machines. Nonlinear controllers are derived from a Lagrangian model representation using passivity techniques, and previous results on induction motors are improved and extended to Blondel-Park transformable machines. The relation to conventional techniques is discussed, and it is shown that the formalism introduced in this work facilitates analysis of conventional methods, so that open questions concerning these methods may be resolved. In addition, the thesis contains the following improvements of previously published results on the control of induction motors: (1) Improvement of a passivity-based speed/position controller, (2) Extension of passivity-based (observer-less and observer-based) controllers from regulation to tracking of rotor flux norm, (3) An extension of the classical indirect FOC (Field-Oriented Control) scheme to also include global rotor flux norm tracking, instead of only torque tracking and rotor flux norm regulation. The design is illustrated experimentally by applying the proposed control schemes to a squirrel-cage induction motor. The results show that the proposed methods have advantages over previous designs with respect to controller tuning, performance and robustness. 145 refs., 21 figs.

  1. Multi-Response Ergonomic Evaluation of Higher Age Group CNC Machine Operators

    Directory of Open Access Journals (Sweden)

    Imtiaz Ali Khan

    2014-08-01

    Full Text Available This work contributes to research on improving performance in a human-CNC machine interface (HCMI environment. A salient contribution of this study is the use of a load cell to measure human performance. The developed novel system can measure cognitive and motor action responses simultaneously. The performance measurement system designed for this work may be used in other fields where systems are operated using control panels and for observing and evaluating the responses of mentally retarded persons (or persons with symptoms of Alzheimer‟s disease. The search time, motor action time and applied force were selected as response variables to accurately evaluate a computer numerically controlled (CNC machine operator‟s performance. Based on a Taguchi experimental design, a full factorial design consisting of 27 (33 experiments was used to collect data on human performance. The collected data were analyzed using grey relational analysis, analysis of variance (ANOVA and the F-test. ANOVA was performed using Design-Expert software. The designed research was shown to have a reasonable degree of validity via a confirmation test. This study represents an effective approach for the optimization of a higher age group operator-CNC machine interface environment with multi-performance characteristics based on a combination of the Taguchi method and grey relational analysis.

  2. Neural Network Based Color Recognition for Bobbin Sorting Machine

    Directory of Open Access Journals (Sweden)

    Mu Zhang

    2013-07-01

    Full Text Available Winding is a key process in the manufacturing process of textile industry. The normal and effective operation of winding process plays a very important role on the textiles’ quality and economic effects. At present, a large proportion of bobbins which collected from winder still have yarn left over. The bobbin recycling is severely limited and quick running of winder is seriously restricted, the invention of the the automatic bobbin sorting machine has solved this problem. The ability to distinguish bobbin which has yarn left over from the rest and the classification accuracy of color are the two important performance indicators for bobbin sorting machine. According to the development and application of the color recognition technology and the artificial intelligence method, this study proposes a novel color recognition method that based on BP neural networks. The result shows that the accuracy of color recognition reaches 98%.  

  3. THE INFLUENCE SEWING MACHINE ON FOOTWEAR MOCCASIN ECONOMIC INDICATORS AI ASSEMBLY OPERATIONS

    Directory of Open Access Journals (Sweden)

    MALCOCI Marina

    2014-05-01

    Full Text Available With the evolution of time changes, grows and improves, construction, form, rationality and argumentation usefulness of various types of footwear, namely machines. In the present paper analyzes a number of sewing machines, bound for achieving moccasin shoes. With sewing machines can perform a wide variety of stitches, they create an aesthetically pleasing, but all at once enable product diversification with minimum expenses. Sewing machines moccasins are distinguished by technological parameters, number of stitches, design and affordability. Sewing operation carried out in these machines is carried out within 72 seconds to manual operation - 22 minutes. A flow diagram mechanical requires a reduced number of workers (e.g., 3 workers, to a manual flow diagram - 38 workers. Labour productivity in the use of sewing machines increase by 10 times, and operation cost decreases from 3,7 to 5,7 lei. Regardless of the sewing moccasins construction company helps to increase productivity, quality completion of the operation, ie products, reducing the time required to manufacture the products, shortening manufacturing cycle. Among the cars analyzed, the most recommended sewing machine as OS 7700 P Global company because it represents the best technical features. Sewing machines for manufacturing footwear moccasin were implemented in Moldova in 2010, at the "Cristina Mold Rom Simpex" in Chisinau. Because, company management understood beneficial role of sewing moccasins on quality operation, but also on other economic indicators. Currently the majority of footwear enterprises in Moldova sewing moccasins are done manually. One problem is the high price of sewing machines moccasins.

  4. Audio Signal Generator System Based On State Machines

    Institute of Scientific and Technical Information of China (English)

    王维喜

    2009-01-01

    A state machine can make program designing quicker, simpler and more efficient. This paper describes in detail the model for a state machine and the idea for its designing and gives the design process of the state machine through an example of audio signal generator system based on Labview. The result shows that the introduction of the state machine can make complex design processes more clear and the revision of programs easier.

  5. A Knowledge base model for complex forging die machining

    OpenAIRE

    Mawussi, Kwamiwi; Tapie, Laurent

    2011-01-01

    International audience; Recent evolutions on forging process induce more complex shape on forging die. These evolutions, combined with High Speed Machining (HSM) process of forging die lead to important increase in time for machining preparation. In this context, an original approach for generating machining process based on machining knowledge is proposed in this paper. The core of this approach is to decompose a CAD model of complex forging die in geometric features. Technological data and ...

  6. Advanced Electrical Machines and Machine-Based Systems for Electric and Hybrid Vehicles

    Directory of Open Access Journals (Sweden)

    Ming Cheng

    2015-09-01

    Full Text Available The paper presents a number of advanced solutions on electric machines and machine-based systems for the powertrain of electric vehicles (EVs. Two types of systems are considered, namely the drive systems designated to the EV propulsion and the power split devices utilized in the popular series-parallel hybrid electric vehicle architecture. After reviewing the main requirements for the electric drive systems, the paper illustrates advanced electric machine topologies, including a stator permanent magnet (stator-PM motor, a hybrid-excitation motor, a flux memory motor and a redundant motor structure. Then, it illustrates advanced electric drive systems, such as the magnetic-geared in-wheel drive and the integrated starter generator (ISG. Finally, three machine-based implementations of the power split devices are expounded, built up around the dual-rotor PM machine, the dual-stator PM brushless machine and the magnetic-geared dual-rotor machine. As a conclusion, the development trends in the field of electric machines and machine-based systems for EVs are summarized.

  7. A Knowledge base model for complex forging die machining

    CERN Document Server

    Mawussi, Kwamiwi; 10.1016/j.cie.2011.02.016

    2011-01-01

    Recent evolutions on forging process induce more complex shape on forging die. These evolutions, combined with High Speed Machining (HSM) process of forging die lead to important increase in time for machining preparation. In this context, an original approach for generating machining process based on machining knowledge is proposed in this paper. The core of this approach is to decompose a CAD model of complex forging die in geometric features. Technological data and topological relations are aggregated to a geometric feature in order to create machining features. Technological data, such as material, surface roughness and form tolerance are defined during forging process and dies design. These data are used to choose cutting tools and machining strategies. Topological relations define relative positions between the surfaces of the die CAD model. After machining features identification cutting tools and machining strategies currently used in HSM of forging die, are associated to them in order to generate mac...

  8. Density Based Support Vector Machines for Classification

    Directory of Open Access Journals (Sweden)

    Zahra Nazari

    2015-04-01

    Full Text Available Support Vector Machines (SVM is the most successful algorithm for classification problems. SVM learns the decision boundary from two classes (for Binary Classification of training points. However, sometimes there are some less meaningful samples amongst training points, which are corrupted by noises or misplaced in wrong side, called outliers. These outliers are affecting on margin and classification performance, and machine should better to discard them. SVM as a popular and widely used classification algorithm is very sensitive to these outliers and lacks the ability to discard them. Many research results prove this sensitivity which is a weak point for SVM. Different approaches are proposed to reduce the effect of outliers but no method is suitable for all types of data sets. In this paper, the new method of Density Based SVM (DBSVM is introduced. Population Density is the basic concept which is used in this method for both linear and non-linear SVM to detect outliers. Experiments on artificial data sets, real high-dimensional benchmark data sets of Liver disorder and Heart disease, and data sets of new and fatigued banknotes’ acoustic signals can prove the efficiency of this method on noisy data classification and the better generalization that it can provide compared to the standard SVM.

  9. A Novel Framework for Agent-Based Production Remote Monitoring System Design: A Case Study of Injection Machines

    Directory of Open Access Journals (Sweden)

    Yun-Yao Chen

    2013-01-01

    Full Text Available Currently, many injection machine controllers in the market involve PC-based architecture, so engineers can conduct simple and quick operation on the controller via a human-machine interface. However, when there are too many machines in a factory, mining algorithms for multimachines and development of rear-end applications are often trivial and complicated. The operation systems of the machines in factories are different, and different machine models need different transfer protocols for data mining. Therefore, we need to develop different information platforms and machine production information mining systems for cross platform controllers. This research proposed an agent based remote monitoring system for injection machines to solve this problem. The agent-based production remote monitor system framework in this research has the following advantages. (1 It can transmit machine information cross platforms regard of constraints of different operating systems. Controlling frameworks can process data mining and transmission. (2 It can send back machine information actively to the manager without operation of machine operators, mine specific information effectively, and screen unnecessary machine information. (3 It can categorize the required information, filter extra information, and elicit data the user needs.

  10. Pre-use anesthesia machine check; certified anesthesia technician based quality improvement audit

    OpenAIRE

    2014-01-01

    Context: Quality assurance of providing a work ready machine in multiple theatre operating rooms in a tertiary modern medical center in Riyadh. Aims: The aim of the following study is to keep high quality environment for workers and patients in surgical operating rooms. Settings and Design: Technicians based audit by using key performance indicators to assure inspection, passing test of machine worthiness for use daily and in between cases and in case of unexpected failure to provide quick re...

  11. Predictive modeling of human operator cognitive state via sparse and robust support vector machines.

    Science.gov (United States)

    Zhang, Jian-Hua; Qin, Pan-Pan; Raisch, Jörg; Wang, Ru-Bin

    2013-10-01

    The accurate prediction of the temporal variations in human operator cognitive state (HCS) is of great practical importance in many real-world safety-critical situations. However, since the relationship between the HCS and electrophysiological responses of the operator is basically unknown, complicated and uncertain, only data-based modeling method can be employed. This paper is aimed at constructing a data-driven computationally intelligent model, based on multiple psychophysiological and performance measures, to accurately estimate the HCS in the context of a safety-critical human-machine system. The advanced least squares support vector machines (LS-SVM), whose parameters are optimized by grid search and cross-validation techniques, are adopted for the purpose of predictive modeling of the HCS. The sparse and weighted LS-SVM (WLS-SVM) were proposed by Suykens et al. to overcome the deficiency of the standard LS-SVM in lacking sparseness and robustness. This paper adopted those two improved LS-SVM algorithms to model the HCS based solely on a set of physiological and operator performance data. The results showed that the sparse LS-SVM can obtain HCS models with sparseness with almost no loss of modeling accuracy, while the WLS-SVM leads to models which are robust in case of noisy training data. Both intelligent system modeling approaches are shown to be capable of capturing the temporal fluctuation trends of the HCS because of their superior generalization performance.

  12. Energy-saving operation of a converter-fed synchronous machine

    Energy Technology Data Exchange (ETDEWEB)

    Schmidt, I.; Veszpremi, K. [Technical University of Budapest, Department of Electrical Machines and Drives, Budapest (Hungary)

    1997-12-31

    In the Converter-Fed Synchronous Machine (CFSM) there is no need for forced commutation the CL and CF converters operate with line commutation, the CM is commutated by the machine voltages. This drive is applied mainly for large power and high speed controlled drives. Considering the large power, the investigation of energy-saving operation is important. As in the DC and the induction motor drives the energy-saving operation is implemented by flux control. (orig.) 6 refs.

  13. Machine-vision based optofluidic cell sorting

    DEFF Research Database (Denmark)

    Glückstad, Jesper; Bañas, Andrew

    In contemporary life science there is an increasing emphasis on sorting rare disease-indicating cells within small dilute quantities such as in the confines of optofluidic lab-on-chip devices. Our approach to this is based on the use of optical forces to isolate red blood cells detected by advanc...... the available light and creating 2D or 3D beam distributions aimed at the positions of the detected cells. Furthermore, the beam shaping freedom provided by GPC can allow optimizations in the beam’s propagation and its interaction with the laser catapulted and sorted cells....... machine vision1. This approach is gentler, less invasive and more economical compared to conventional FACS-systems. As cells are less responsive to plastic or glass objects commonly used in the optical manipulation literature2, and since laser safety would be an issue in clinical use, we develop efficient...

  14. Lane Detection Based on Machine Learning Algorithm

    Directory of Open Access Journals (Sweden)

    Chao Fan

    2013-09-01

    Full Text Available In order to improve accuracy and robustness of the lane detection in complex conditions, such as the shadows and illumination changing, a novel detection algorithm was proposed based on machine learning. After pretreatment, a set of haar-like filters were used to calculate the eigenvalue in the gray image f(x,y and edge e(x,y. Then these features were trained by using improved boosting algorithm and the final class function g(x was obtained, which was used to judge whether the point x belonging to the lane or not. To avoid the over fitting in traditional boosting, Fisher discriminant analysis was used to initialize the weights of samples. After testing by many road in all conditions, it showed that this algorithm had good robustness and real-time to recognize the lane in all challenging conditions.

  15. Support vector machine based on chaos particle swarm optimization for fault diagnosis of rotating machine

    Institute of Scientific and Technical Information of China (English)

    TANG Xian-lun; ZHUANG Ling; QIU Guo-qing; CAI Jun

    2009-01-01

    The performance of the support vector machine models depends on a proper setting of its parameters to a great extent. A novel method of searching the optimal parameters of support vector machine based on chaos particle swarm optimization is proposed. A multi-fault classification model based on SVM optimized by chaos particle swarm optimization is established and applied to the fault diagnosis of rotating machines. The results show that the proposed fault classification model outperforms the neural network trained by chaos particle swarm optimization and least squares support vector machine, and the precision and reliability of the fault classification results can meet the requirement of practical application. It indicates that chaos particle swarm optimization is a suitable method for searching the optimal parameters of support vector machine.

  16. Earth-moving equipment as base machines in forest work. Final report of an NSR project

    Energy Technology Data Exchange (ETDEWEB)

    Johansson, Jerry [ed.

    1997-12-31

    Excavators have been used for forest draining for a long time in the Nordic countries. Only during the 1980s they were introduced as base machines for other forest operations, such as mounding, processing, harvesting, and road construction and road maintenance. Backhoe loaders were introduced in forestry at a somewhat later stage and to a smaller degree. The number of this type of base machines in forestry is so far small and is increasing very slowly. The NSR project `Earth moving equipment as base machines in forest work` started in 1993 and the project ended in 1995. The objective of the project was to obtain an overall picture of this type of machines up to a point where the logs are at landing site, ready for transportation to the industry. The project should cover as many aspects as possible. In order to obtain this picture, the main project was divided into sub projects. The sub projects separately described in this volume are (1) Excavators in ditching operations and site preparation, (2) Backhoe loaders in harvesting operations, (3) Excavators in wood cutting operations, (4) Tracked excavators in forestry operations, (5) Crawler versus wheeled base machines for single-grip harvester, and (6) Soil changes - A comparison between a wheeled and a tracked forest machine

  17. Modification and Performance Evaluation of a Low Cost Electro-Mechanically Operated Creep Testing Machine

    Directory of Open Access Journals (Sweden)

    John J. MOMOH

    2010-12-01

    Full Text Available Existing mechanically operated tensile and creep testing machine was modified to a low cost, electro-mechanically operated creep testing machine capable of determining the creep properties of aluminum, lead and thermoplastic materials as a function of applied stress, time and temperature. The modification of the testing machine was necessitated by having an electro-mechanically operated creep testing machine as a demonstration model ideal for use and laboratory demonstrations, which will provide an economical means of performing standard creep experiments. The experimental result is a more comprehensive understanding of the laboratory experience, as the technology behind the creep testing machine, the test methodology and the response of materials loaded during experiment are explored. The machine provides a low cost solution for Mechanics of Materials laboratories interested in creep testing experiment and demonstration but not capable of funding the acquisition of commercially available creep testing machines. Creep curves of strain versus time on a thermoplastic material were plotted at a stress level of 1.95MPa, 3.25MPa and 4.55MPa and temperature of 20oC, 40oC and 60oC respectively. The machine is satisfactory since it is always ready for operation at any given time.

  18. A Review of Virtual Machine Attack Based on Xen

    Directory of Open Access Journals (Sweden)

    Ren xun-yi

    2016-01-01

    Full Text Available Virtualization technology as the foundation of cloud computing gets more and more attention because the cloud computing has been widely used. Analyzing the threat with the security of virtual machine and summarizing attack about virtual machine based on XEN to predict visible security hidden recently. Base on this paper can provide a reference for the further research on the security of virtual machine.

  19. Quantum Neural Network Based Machine Translator for Hindi to English

    OpenAIRE

    Ravi Narayan; V. P. Singh; S. Chakraverty

    2014-01-01

    This paper presents the machine learning based machine translation system for Hindi to English, which learns the semantically correct corpus. The quantum neural based pattern recognizer is used to recognize and learn the pattern of corpus, using the information of part of speech of individual word in the corpus, like a human. The system performs the machine translation using its knowledge gained during the learning by inputting the pair of sentences of Devnagri-Hindi and English. To analyze t...

  20. Quantum Neural Network Based Machine Translator for Hindi to English

    OpenAIRE

    Ravi Narayan; Singh, V. P.; S. Chakraverty

    2014-01-01

    This paper presents the machine learning based machine translation system for Hindi to English, which learns the semantically correct corpus. The quantum neural based pattern recognizer is used to recognize and learn the pattern of corpus, using the information of part of speech of individual word in the corpus, like a human. The system performs the machine translation using its knowledge gained during the learning by inputting the pair of sentences of Devnagri-Hindi and English. To analyze t...

  1. Methods, systems and apparatus for controlling third harmonic voltage when operating a multi-space machine in an overmodulation region

    Energy Technology Data Exchange (ETDEWEB)

    Perisic, Milun; Kinoshita, Michael H; Ranson, Ray M; Gallegos-Lopez, Gabriel

    2014-06-03

    Methods, system and apparatus are provided for controlling third harmonic voltages when operating a multi-phase machine in an overmodulation region. The multi-phase machine can be, for example, a five-phase machine in a vector controlled motor drive system that includes a five-phase PWM controlled inverter module that drives the five-phase machine. Techniques for overmodulating a reference voltage vector are provided. For example, when the reference voltage vector is determined to be within the overmodulation region, an angle of the reference voltage vector can be modified to generate a reference voltage overmodulation control angle, and a magnitude of the reference voltage vector can be modified, based on the reference voltage overmodulation control angle, to generate a modified magnitude of the reference voltage vector. By modifying the reference voltage vector, voltage command signals that control a five-phase inverter module can be optimized to increase output voltages generated by the five-phase inverter module.

  2. Coherence-Induced Reversibility and Collective Operation of Quantum Heat Machines via Coherence Recycling

    Science.gov (United States)

    Uzdin, Raam

    2016-08-01

    Collective behavior, where a set of elements interact and generate effects that are beyond the reach of the individual noninteracting elements, is always of great interest in physics. Quantum collective effects that have no classical analog are even more intriguing. In this work, we show how to construct collective quantum heat machines and explore their performance boosts with respect to regular machines. Without interactions between the machines, the individual units operate in a stochastic, nonquantum manner. The construction of the collective machine becomes possible by introducing two simple quantum operations: coherence extraction and coherence injection. Together, these operations can harvest coherence from one engine and use it to boost the performance of a slightly different engine. For weakly driven engines, we show that the collective work output scales quadratically with the number of engines rather than linearly. Eventually, the boost saturates and then becomes linear. Nevertheless, even in saturation, work is still significantly boosted compared to individual operation. To study the reversibility of the collective machine, we introduce the "entropy-pollution" measure. It is shown that there is a regime where the collective machine is N times more reversible while producing N times more work, compared to the individual operation of N units. Moreover, the collective machine can even be more reversible than the most reversible unit in the collective. This high level of reversibility becomes possible due to a special symbiotic mechanism between engine pairs.

  3. Improvement of Machinability of Mild Steel during Turning Operation by Magnetic Cutting

    Directory of Open Access Journals (Sweden)

    Anayet U. Patwari

    2012-01-01

    Full Text Available This paper presents the details of improvement of machinability of mild steel using magnetic cutting during turning operation. Improvement of machinability was evaluated in terms of tool life, surface roughness and chip morphology. Machine tool chatter is a type of intensive self-excited vibrations of individual components of Machine-Tool-Fixture-Work (MTFW system. Chatter causes unwanted excessive vibratory motion in between the tool and the work-piece causing adverse effects on the product quality and machine-tool and tool life. In addition to the damage of the work-piece surface due to chatter marks, the occurrence of severe chatter results in many adverse effects, which include poor dimensional accuracy of the work-piece, reduction of tool life, and damage to the machine. Chatter is formed as resonance phenomena during machining because of the instability of the closed-loop system formed by machine tool structure and metal-cutting process. In this study, magnets were used to avoid the chatter formation zone and its effect on machinability was investigated. Improvements in tool life and surface finish were observed during magnetic cutting of the mild steel. An obvious change in the chip behaviour was also present. These observations further enhance the possibility of using this magnetic cutting to eliminate the chatter formation zones and hence eliminate the adverse effect of chatter on machinability.

  4. Brake Pedal Displacement Measuring System based on Machine Vision

    Directory of Open Access Journals (Sweden)

    Chang Wang

    2013-10-01

    Full Text Available Displacement of brake pedal was an important characteristic of driving behavior. This paper proposed a displacement measure algorithm based on machine vision. Image of brake pedal was captured by camera from left side, and images were processed in industry computer. Firstly, average smooth algorithm and wavelet transform algorithm were used to smooth the original image consecutively. Then, edge extracting method which combined Roberts’s operator with wavelet analysis was used to identify the edge of brake pedal. At last, least square method was adopted to recognize the characteristic line of brake pedal’s displacement. The experimental results demonstrated that the proposed method takes the advantages of Roberts’s operator and wavelet transform, it can obtain better measurement result as well as linear displacement sensors

  5. The Abstract Machine Model for Transaction-based System Control

    Energy Technology Data Exchange (ETDEWEB)

    Chassin, David P.

    2003-01-31

    Recent work applying statistical mechanics to economic modeling has demonstrated the effectiveness of using thermodynamic theory to address the complexities of large scale economic systems. Transaction-based control systems depend on the conjecture that when control of thermodynamic systems is based on price-mediated strategies (e.g., auctions, markets), the optimal allocation of resources in a market-based control system results in an emergent optimal control of the thermodynamic system. This paper proposes an abstract machine model as the necessary precursor for demonstrating this conjecture and establishes the dynamic laws as the basis for a special theory of emergence applied to the global behavior and control of complex adaptive systems. The abstract machine in a large system amounts to the analog of a particle in thermodynamic theory. The permit the establishment of a theory dynamic control of complex system behavior based on statistical mechanics. Thus we may be better able to engineer a few simple control laws for a very small number of devices types, which when deployed in very large numbers and operated as a system of many interacting markets yields the stable and optimal control of the thermodynamic system.

  6. Threat Assessment of Targets Based on Support Vector Machine

    Institute of Scientific and Technical Information of China (English)

    CAI Huai-ping; LIU Jing-xu; CHEN Ying-wu

    2006-01-01

    In the context of cooperative engagement of armored vehicles, the threat factors of offensive targets are analyzed, and a threat assessment (TA) model is built based on a support v.ector machine (SVM) method. The SVM-based model has some advantages over the traditional method-based models: the complex factors of threat are considered in the cooperative engagement; the shortcomings of neural networks, such as local minimum and "over fitting", are overcome to improve the generalization ability; its operation speed is high and meets the needs of real time C2 of cooperative engagement; the assessment results could be more reasonable because of its self-learning capability. The analysis and simulation indicate that the SVM method is an effective method to resolve the TA problems.

  7. Vane Pump Casing Machining of Dumpling Machine Based on CAD/CAM

    Science.gov (United States)

    Huang, Yusen; Li, Shilong; Li, Chengcheng; Yang, Zhen

    Automatic dumpling forming machine is also called dumpling machine, which makes dumplings through mechanical motions. This paper adopts the stuffing delivery mechanism featuring the improved and specially-designed vane pump casing, which can contribute to the formation of dumplings. Its 3D modeling in Pro/E software, machining process planning, milling path optimization, simulation based on UG and compiling post program were introduced and verified. The results indicated that adoption of CAD/CAM offers firms the potential to pursue new innovative strategies.

  8. Structural Optimization of Machine Gun Based on Dynamic Stability Concept

    Institute of Scientific and Technical Information of China (English)

    LI Yong-jian; WANG Rui-lin; ZHANG Ben-jun

    2008-01-01

    Improving the firing accuracy is a final goal of structural optimization of machine guns. The main factors which affect the dispersion accuracy of machine gun are analyzed. Based on the concept of dynamic stability, a structural optimization model is built up, and the sensitivity of dispersion accuracy to design variables is analyzed. The optimization results of a type of machine gun show that the method is valid, feasible, and can be used as a guide to the structural optimization of other automatic weapons.

  9. Improved AAG based recognization of machining feature

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    The lost information caused by feature interaction is restored by using auxiliary faces(AF)and virtual links(VL).The delta volume of the interacted features represented by concave attachable connected graph (CACG)can be decomposed into several isolated features represented by complete concave adjacency graph (CCAG).We can recognize the features sketchy type by using CCAG as a hint; the exact type of the feature can be attained by deleting the auxiliary faces from the isolated feature.United machining feature(UMF)is used to represent the features that can be machined in the same machining process.It is important to the rationalizing of the process plans and reduce the time costing in machining.An example is given to demonstrate the effectiveness of this method.

  10. Optimal interference code based on machine learning

    Science.gov (United States)

    Qian, Ye; Chen, Qian; Hu, Xiaobo; Cao, Ercong; Qian, Weixian; Gu, Guohua

    2016-10-01

    In this paper, we analyze the characteristics of pseudo-random code, by the case of m sequence. Depending on the description of coding theory, we introduce the jamming methods. We simulate the interference effect or probability model by the means of MATLAB to consolidate. In accordance with the length of decoding time the adversary spends, we find out the optimal formula and optimal coefficients based on machine learning, then we get the new optimal interference code. First, when it comes to the phase of recognition, this study judges the effect of interference by the way of simulating the length of time over the decoding period of laser seeker. Then, we use laser active deception jamming simulate interference process in the tracking phase in the next block. In this study we choose the method of laser active deception jamming. In order to improve the performance of the interference, this paper simulates the model by MATLAB software. We find out the least number of pulse intervals which must be received, then we can make the conclusion that the precise interval number of the laser pointer for m sequence encoding. In order to find the shortest space, we make the choice of the greatest common divisor method. Then, combining with the coding regularity that has been found before, we restore pulse interval of pseudo-random code, which has been already received. Finally, we can control the time period of laser interference, get the optimal interference code, and also increase the probability of interference as well.

  11. Numerical Ergonomics Analysis in Operation Environment of CNC Machine

    Science.gov (United States)

    Wong, S. F.; Yang, Z. X.

    2010-05-01

    The performance of operator will be affected by different operation environments [1]. Moreover, poor operation environment may cause health problems of the operator [2]. Physical and psychological considerations are two main factors that will affect the performance of operator under different conditions of operation environment. In this paper, applying scientific and systematic methods find out the pivot elements in the field of physical and psychological factors. There are five main factors including light, temperature, noise, air flow and space that are analyzed. A numerical ergonomics model has been built up regarding the analysis results which can support to advance the design of operation environment. Moreover, the output of numerical ergonomic model can provide the safe, comfortable, more productive conditions for the operator.

  12. Accurate measurement method for tube's endpoints based on machine vision

    Science.gov (United States)

    Liu, Shaoli; Jin, Peng; Liu, Jianhua; Wang, Xiao; Sun, Peng

    2017-01-01

    Tubes are used widely in aerospace vehicles, and their accurate assembly can directly affect the assembling reliability and the quality of products. It is important to measure the processed tube's endpoints and then fix any geometric errors correspondingly. However, the traditional tube inspection method is time-consuming and complex operations. Therefore, a new measurement method for a tube's endpoints based on machine vision is proposed. First, reflected light on tube's surface can be removed by using photometric linearization. Then, based on the optimization model for the tube's endpoint measurements and the principle of stereo matching, the global coordinates and the relative distance of the tube's endpoint are obtained. To confirm the feasibility, 11 tubes are processed to remove the reflected light and then the endpoint's positions of tubes are measured. The experiment results show that the measurement repeatability accuracy is 0.167 mm, and the absolute accuracy is 0.328 mm. The measurement takes less than 1 min. The proposed method based on machine vision can measure the tube's endpoints without any surface treatment or any tools and can realize on line measurement.

  13. Accurate Measurement Method for Tube's Endpoints Based on Machine Vision

    Institute of Scientific and Technical Information of China (English)

    LIU Shaoli; JIN Peng; LIU Jianhua; WANG Xiao; SUN Peng

    2017-01-01

    Tubes are used widely in aerospace vehicles,and their accurate assembly can directly affect the assembling reliability and the quality of products.It is important to measure the processed tube's endpoints and then fix any geometric errors correspondingly.However,the traditional tube inspection method is time-consuming and complex operations.Therefore,a new measurement method for a tube's endpoints based on machine vision is proposed.First,reflected light on tube's surface can be removed by using photometric linearization.Then,based on the optimization model for the tube's endpoint measurements and the principle of stereo matching,the global coordinates and the relative distance of the tube's endpoint are obtained.To confirm the feasibility,11 tubes are processed to remove the reflected light and then the endpoint's positions of tubes are measured.The experiment results show that the measurement repeatability accuracy is 0.167 mm,and the absolute accuracy is 0.328 mm.The measurement takes less than 1 min.The proposed method based on machine vision can measure the tube's endpoints without any surface treatment or any tools and can realize on line measurement.

  14. Accurate measurement method for tube's endpoints based on machine vision

    Science.gov (United States)

    Liu, Shaoli; Jin, Peng; Liu, Jianhua; Wang, Xiao; Sun, Peng

    2016-08-01

    Tubes are used widely in aerospace vehicles, and their accurate assembly can directly affect the assembling reliability and the quality of products. It is important to measure the processed tube's endpoints and then fix any geometric errors correspondingly. However, the traditional tube inspection method is time-consuming and complex operations. Therefore, a new measurement method for a tube's endpoints based on machine vision is proposed. First, reflected light on tube's surface can be removed by using photometric linearization. Then, based on the optimization model for the tube's endpoint measurements and the principle of stereo matching, the global coordinates and the relative distance of the tube's endpoint are obtained. To confirm the feasibility, 11 tubes are processed to remove the reflected light and then the endpoint's positions of tubes are measured. The experiment results show that the measurement repeatability accuracy is 0.167 mm, and the absolute accuracy is 0.328 mm. The measurement takes less than 1 min. The proposed method based on machine vision can measure the tube's endpoints without any surface treatment or any tools and can realize on line measurement.

  15. State Machine Framework And Its Use For Driving LHC Operational states

    CERN Document Server

    Misiowiec, M; Solfaroli Camilloci, M

    2011-01-01

    The LHC follows a complex operational cycle with 12 major phases that include equipment tests, preparation, beam injection, ramping and squeezing, finally followed by the physics phase. This cycle is modelled and enforced with a state machine, whereby each operational phase is represented by a state. On each transition, before entering the next state, a series of conditions is verified to make sure the LHC is ready to move on. The State Machine framework was developed to cater for building independent or embedded state machines. They safely drive between the states executing tasks bound to transitions and broadcast related information to interested parties. The framework encourages users to program their own actions. Simple configuration management allows the operators to define and maintain complex models themselves. An emphasis was also put on easy interaction with the remote state machine instances through standard communication protocols. On top of its core functionality, the framework offers a transparen...

  16. Entanglement-based machine learning on a quantum computer.

    Science.gov (United States)

    Cai, X-D; Wu, D; Su, Z-E; Chen, M-C; Wang, X-L; Li, Li; Liu, N-L; Lu, C-Y; Pan, J-W

    2015-03-20

    Machine learning, a branch of artificial intelligence, learns from previous experience to optimize performance, which is ubiquitous in various fields such as computer sciences, financial analysis, robotics, and bioinformatics. A challenge is that machine learning with the rapidly growing "big data" could become intractable for classical computers. Recently, quantum machine learning algorithms [Lloyd, Mohseni, and Rebentrost, arXiv.1307.0411] were proposed which could offer an exponential speedup over classical algorithms. Here, we report the first experimental entanglement-based classification of two-, four-, and eight-dimensional vectors to different clusters using a small-scale photonic quantum computer, which are then used to implement supervised and unsupervised machine learning. The results demonstrate the working principle of using quantum computers to manipulate and classify high-dimensional vectors, the core mathematical routine in machine learning. The method can, in principle, be scaled to larger numbers of qubits, and may provide a new route to accelerate machine learning.

  17. Scientific Bases of Human-Machine Communication by Voice

    Science.gov (United States)

    Schafer, Ronald W.

    1995-10-01

    The scientific bases for human-machine communication by voice are in the fields of psychology, linguistics, acoustics, signal processing, computer science, and integrated circuit technology. The purpose of this paper is to highlight the basic scientific and technological issues in human-machine communication by voice and to point out areas of future research opportunity. The discussion is organized around the following major issues in implementing human-machine voice communication systems: (i) hardware/software implementation of the system, (ii) speech synthesis for voice output, (iii) speech recognition and understanding for voice input, and (iv) usability factors related to how humans interact with machines.

  18. Method of change management based on dynamic machining error propagation

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    In multistage machining processes(MMPs),the final quality of a part is influenced by a series of machining processes,which are complex correlations.So it is necessary to research the rule of machin-ing error propagation to ensure the machining quality.For this issue,a change management method of quality control nodes(i.e.,QC-nodes) for machining error propagation is proposed.A new framework of QC-nodes is proposed including association analysis of quality attributes,quality closed-loop control,error tracing and error coordination optimization.And the weighted directed network is introduced to describe and analyze the correlativity among the machining processes.In order to establish the dynamic machining error propagation network(D-MEPN),QC-nodes are defined as the network nodes,and the correlation among the QC-nodes is mapped onto the network.Based on the network analysis,the dynamic characteristics of machining error propagation are explored.An adaptive control method based on the stability theory is introduced for error coordination optimization.At last,a simple example is used to verify the proposed method.

  19. Nontraditional manufacturing technique-Nano machining technique based on SPM

    Institute of Scientific and Technical Information of China (English)

    DONG; Shen; YAN; Yongda; SUN; Tao; LIANG; Yingchun; CHENG

    2004-01-01

    Nano machining based on SPM is a novel, nontraditional advanced manufacturing technique. There are three main machining methods based on SPM, i.e.single atom manipulation, surface modification using physical or chemical actions and mechanical scratching. The current development of this technique is summarized. Based on the analysis of mechanical scratching mechanism, a 5 μm micro inflation hole is fabricated on the surface of inertial confinement fusion (ICF) target. The processing technique is optimized. The machining properties of brittle material, single crystal Ge, are investigated. A micro machining system combining SPM and a high accuracy stage is developed. Some 2D and 3D microstructures are fabricated using the system. This method has broad applications in the field of nano machining.

  20. Non-machined Surface Protection Process of Electrochemical Machining Based on Repaired Turbine Blade

    Directory of Open Access Journals (Sweden)

    LIU Wei-dong

    2016-11-01

    Full Text Available In order to improve the efficiency of turbine blade repairing, protection processes of non-machined surface in Electrochemical Machining (ECM based on blade repairing were studied. Mathematical model of electric field was developed to obtain current density distribution on anode surface, and to study the repairing principle and consequently analyze the defects forming mechanism by conventional electrolytic repair process. Sacrificial layer process was proposed to protect the non-machined surface in this work and an experimental system was developed to shape overlay welded TC4 blades. The results show that directly shaping process and insulated layer process produce stray dissolution and "stair" defects respectively,while sacrificial layer process achieves acceptable machining performance. With shaping time of 60s, the efficiency is improved; shaped blades have higher precision and surface roughness is Ra≤0.6μm, and with higher repeatability, the design requirements can be met.

  1. A GA-Based Approach for FMS Machine Loading Planing

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    The machine loading problem in flexible manufacturing system isaddressed in this paper. The problem is modelled as a mixed integer program. A Genetic Algorithm (GA) approach is developed to yield an optimal solution. In the genetic algorithm, chromosomes are encoded in term of operation routes. A point-to-point crossover search operator together with a Cyclic Shifting Mutation (CSM) operator is designed to adapt to the problem. At last computational experience with the model is presented, and the results show that our genetic algorithms are very powerful and suitable to machine loading problems.

  2. Agricultural Safety. FMO: Fundamentals of Machine Operation. Second Edition.

    Science.gov (United States)

    John Deere Co., Moline, IL.

    This manual is intended to provide students with basic information on the safe operation of farm machinery. The following topics are covered in the individual chapters: safe farm machinery operation (the importance of safety, the role of communication in safety, and types of farm accidents); human factors (human limitations and capabilities;…

  3. A Rational Deconstruction of Landin's SECD Machine with the J Operator

    DEFF Research Database (Denmark)

    Danvy, Olivier; Millikin, Kevin

    2008-01-01

    to this extension of the SECD machine, using a series of elementary transformations (transformation into continuation-passing style (CPS) and defunctionalization, chiefly) and their left inverses (transformation into direct style and refunctionalization). To this end, we modernize the SECD machine into a bisimilar...... one that operates in lockstep with the original one but that (1) does not use a data stack and (2) uses the caller-save rather than the callee-save convention for environments. We also identify that the dump component of the SECD machine is managed in a callee-save way. The caller-save counterpart...... as well as the expressive power of the CPS hierarchy (1) to account for the first control operator and the first abstract machine for functional languages and (2) to connect them to their successors. Our work also illustrates the value of Danvy and Nielsen's refocusing technique to connect environment...

  4. Metrological Aspects of Surface Topographies Produced by Different Machining Operations Regarding Their Potential Functionality

    Directory of Open Access Journals (Sweden)

    Żak Krzysztof

    2017-06-01

    Full Text Available This paper presents a comprehensive methodology for measuring and characterizing the surface topographies on machined steel parts produced by precision machining operations. The performed case studies concern a wide spectrum of topographic features of surfaces with different geometrical structures but the same values of the arithmetic mean height Sa. The tested machining operations included hard turning operations performed with CBN tools, grinding operations with Al2O3 ceramic and CBN wheels and superfinish using ceramic stones. As a result, several characteristic surface textures with the Sa roughness parameter value of about 0.2 μm were thoroughly characterized and compared regarding their potential functional capabilities. Apart from the standard 2D and 3D roughness parameters, the fractal, motif and frequency parameters were taken in the consideration.

  5. Rule-based machine translation for Aymara

    NARCIS (Netherlands)

    Coler, Matthew; Homola, Petr; Jones, Mari

    2014-01-01

    This paper presents the ongoing result of an approach developed by the collaboration of a computational linguist with a field linguist that addresses one of the oft-overlooked keys to language maintenance: the development of modern language-learning tools. Although machine translation isn’t commonly

  6. Design of Maritime Satellite Navigation Equipment Man-Machine Interactive Software Based on ReWorks Operating System%基于ReWorks操作系统海用卫星导航设备人机交互软件开发

    Institute of Scientific and Technical Information of China (English)

    2015-01-01

    针对海用卫星导航设备人机交互软件,引入了ReWorks操作系统,研究了基于ReWorks的应用软件开发方法,使用ReDe开发环境和DirectX工具实现了海用卫星导航设备人机交互软件的设计开发,最后工程实践表明其正确性和有效性。%According to maritime satellite navigation equipment man-machine interactive software, ReWorks operating system is introduced, software development methods Based on ReWorks operating system is studied, maritime satellite navigation equipment man-machine interactive software design is realized by using the development environment of ReDe and DirectX tool. The final project application proved its correctness and effectiveness.

  7. Method of change management based on dynamic machining error propagation

    Institute of Scientific and Technical Information of China (English)

    FENG Jia; JIANG PingYu

    2009-01-01

    In multistage machining processes (MMPs), the final quality of a part is influenced by a series of machining processes, which are complex correlations. So it is necessary to research the rule of machining error propagation to ensure the machining quality. For this issue, a change management method of quality control nodes (i.e., QC-nodes) for machining error propagation is proposed. A new framework of QC-nodes is proposed including association analysis of quality attributes, quality closed-loop control,error tracing and error coordination optimization. And the weighted directed network is introduced to describe and analyze the correlativity among the machining processes. In order to establish the dynamic machining error propagation network (D-MEPN), QC-nodes are defined as the network nodes,and the correlation among the QC-nodes is mapped onto the network. Based on the network analysis,the dynamic characteristics of machining error propagation are explored. An adaptive control method based on the stability theory is introduced for error coordination optimization. At last, a simple example is used to verify the proposed method.

  8. Sparsity-based algorithm for detecting faults in rotating machines

    Science.gov (United States)

    He, Wangpeng; Ding, Yin; Zi, Yanyang; Selesnick, Ivan W.

    2016-05-01

    This paper addresses the detection of periodic transients in vibration signals so as to detect faults in rotating machines. For this purpose, we present a method to estimate periodic-group-sparse signals in noise. The method is based on the formulation of a convex optimization problem. A fast iterative algorithm is given for its solution. A simulated signal is formulated to verify the performance of the proposed approach for periodic feature extraction. The detection performance of comparative methods is compared with that of the proposed approach via RMSE values and receiver operating characteristic (ROC) curves. Finally, the proposed approach is applied to single fault diagnosis of a locomotive bearing and compound faults diagnosis of motor bearings. The processed results show that the proposed approach can effectively detect and extract the useful features of bearing outer race and inner race defect.

  9. 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.

  10. Design of an ARM-based Automatic Rice-Selling Machine for Cafeterias

    Directory of Open Access Journals (Sweden)

    Zhiliang Kang

    2016-02-01

    Full Text Available To address the problems of low selling efficiency, poor sanitation conditions, labor-intensive requirement, and quick rice cooling speed in manual rice selling in cafeterias, especially in colleges and secondary schools, this paper presented an Advanced RISC Machines (ARM microprocessor-based rice-selling machine for cafeterias. The machines consisted of a funnel-shaped rice bin, a thermal insulation box, and a conveying and scattering mechanism. Moreover, this machine exerts fuzzy control over stepper motor rpm, and the motor drives the conveyor belt with a scraper to scatter rice, deliver it, and keep it warm. Apart from an external 4*4 keyboard, a point of sale (POS machine, an ARM process and a pressure sensor, the machine is also equipped with card swiping and weighting mechanisms to achieve functions of card swiping payment and precise measurement, respectively. In addition, detection of the right amount of rice and the alarm function are achieved using an ultrasonic sensor and a beeper, respectively. The presence of the rice container on the rice outlet is detected by an optoelectronic switch. Results show that this rice-selling machine achieves precise measurement, quick card swiping, fast rice selling, stable operation, and good rice heat preservation. Therefore, the mechanical design enables the machine to achieve its goals.

  11. Digital controlling for GMA welding machine based on DSP

    Institute of Scientific and Technical Information of China (English)

    华学明; 吴毅雄; 张勇; 焦馥杰; 于乾波

    2003-01-01

    This paper introduced a welding machine for GMAW using digital controlling method based on DSP (Digital Signal Process). By means of flexible programming according to welding technologies and experiences the suitable characteristics of welding machine, such as line compensation, welding voltage and current feedback, wire-feed driving, SCR trigging and so on, can be controlled and self-adjusted using digital signals. Through the designing based on DSP it is put out that the traditional hardware of control circuit is decreased greatly which can enhance the stability and reliability of welding machine. Finally, the welding experiment using CO2 shielding gas proves that the welding process is stable.

  12. DNA regulatory motif selection based on support vector machine ...

    African Journals Online (AJOL)

    DNA regulatory motif selection based on support vector machine (SVM) and its application in microarray ... African Journal of Biotechnology ... experiments to explore the underlying relationships between motif types and gene functions.

  13. Correlation of cutting fluid performance in different machining operations

    DEFF Research Database (Denmark)

    De Chiffre, Leonardo; Belluco, Walter

    2001-01-01

    investigated. Results show that correlation of cutting fluid performance in different operations exists, within the same group of cutting fluids, in the case of stainless steel as workpiece material. Under the tested conditions, the average correlation coefficients between efficiency parameters with different...... operations on austenitic stainless steel lied in the range 0.87-0.97 for waterbased fluids and 0.79-0.89 for straight oils. A similar correlation could not be found for the other workpiece materials investigated in this work. A rationalisation of cutting fluid performance tests is suggested....

  14. Research on Manufacturing Technology Based on Machine Vision

    Institute of Scientific and Technical Information of China (English)

    HU Zhanqi; ZHENG Kuijing

    2006-01-01

    The concept of machine vision based manufacturing technology is proposed first, and the key algorithms used in two-dimensional and three-dimensional machining are discussed in detail. Machining information can be derived from the binary images and gray picture after processing and transforming the picture. Contour and the parallel cutting method about two-dimensional machining are proposed. Polygon approximating algorithm is used to cutting the profile of the workpiece. Fill Scanning algorithm used to machining inner part of a pocket. The improved Shape From Shading method with adaptive pre-processing is adopted to reconstruct the three-dimensional model. Layer cutting method is adopted for three-dimensional machining. The tool path is then gotten from the model, and NC code is formed subsequently. The model can be machined conveniently by the lathe, milling machine or engraver. Some examples are given to demonstrate the results of ImageCAM system, which is developed by the author to implement the algorithms previously mentioned.

  15. Discharge estimation based on machine learning

    Institute of Scientific and Technical Information of China (English)

    Zhu JIANG; Hui-yan WANG; Wen-wu SONG

    2013-01-01

    To overcome the limitations of the traditional stage-discharge models in describing the dynamic characteristics of a river, a machine learning method of non-parametric regression, the locally weighted regression method was used to estimate discharge. With the purpose of improving the precision and efficiency of river discharge estimation, a novel machine learning method is proposed:the clustering-tree weighted regression method. First, the training instances are clustered. Second, the k-nearest neighbor method is used to cluster new stage samples into the best-fit cluster. Finally, the daily discharge is estimated. In the estimation process, the interference of irrelevant information can be avoided, so that the precision and efficiency of daily discharge estimation are improved. Observed data from the Luding Hydrological Station were used for testing. The simulation results demonstrate that the precision of this method is high. This provides a new effective method for discharge estimation.

  16. Image Segmentation Based on Support Vector Machine

    Institute of Scientific and Technical Information of China (English)

    XU Hai-xiang; ZHU Guang-xi; TIAN Jin-wen; ZHANG Xiang; PENG Fu-yuan

    2005-01-01

    Image segmentation is a necessary step in image analysis. Support vector machine (SVM) approach is proposed to segment images and its segmentation performance is evaluated.Experimental results show that: the effects of kernel function and model parameters on the segmentation performance are significant; SVM approach is less sensitive to noise in image segmentation; The segmentation performance of SVM approach is better than that of back-propagation multi-layer perceptron (BP-MLP) approach and fuzzy c-means (FCM) approach.

  17. Prevalence of persistent neck and upper limb pain in a historical cohort of sewing machine operators.

    Science.gov (United States)

    Andersen, J H; Gaardboe, O

    1993-12-01

    Four hundred and twenty-four sewing machine operators from a historical cohort of garment industry workers answered questionnaires concerning musculoskeletal symptoms and job exposure. They were compared with 781 women from the general population of the region and an internal control group of 89 women from the garment industry. The risk for persistent neck and shoulder complaints increased with years of being a sewing machine operator: (up to seven years, eight to fifteen years, and more than fifteen years: prevalence proportion ratio 1.8, 3.5 and 4.4 [neck] and 1.5, 4 and 6.8 [shoulder] compared with the controls [n = 781]). The exposure-response relationships remained when adjusted for potential confounders, of which age, current shoulder-neck exposure, and child bearing were the most contributing. The study revealed that work for more than eight years as a sewing machine operator probably has a cumulative deleterious effect on the neck and shoulders.

  18. An extensible operating system design for large-scale parallel machines.

    Energy Technology Data Exchange (ETDEWEB)

    Riesen, Rolf E.; Ferreira, Kurt Brian

    2009-04-01

    Running untrusted user-level code inside an operating system kernel has been studied in the 1990's but has not really caught on. We believe the time has come to resurrect kernel extensions for operating systems that run on highly-parallel clusters and supercomputers. The reason is that the usage model for these machines differs significantly from a desktop machine or a server. In addition, vendors are starting to add features, such as floating-point accelerators, multicore processors, and reconfigurable compute elements. An operating system for such machines must be adaptable to the requirements of specific applications and provide abstractions to access next-generation hardware features, without sacrificing performance or scalability.

  19. A reliability assessment method based on support vector machines for CNC equipment

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    With the applications of high technology,a catastrophic failure of CNC equipment rarely occurs at normal operation conditions.So it is difficult for traditional reliability assessment methods based on time-to-failure distributions to deduce the reliability level.This paper presents a novel reliability assessment methodology to estimate the reliability level of equipment with machining performance degradation data when only a few samples are available.The least squares support vector machines(LS-SVM) are introduced to analyze the performance degradation process on the equipment.A two-stage parameter optimization and searching method is proposed to improve the LS-SVM regression performance and a reliability assessment model based on the LS-SVM is built.A machining performance degradation experiment has been carried out on an OTM650 machine tool to validate the effectiveness of the proposed reliability assessment methodology.

  20. A reliability assessment method based on support vector machines for CNC equipment

    Institute of Scientific and Technical Information of China (English)

    WU Jun; DENG Chao; SHAO XinYu; XIE S Q

    2009-01-01

    With the applications of high technology, a catastrophic failure of CNC equipment rarely occurs at normal operation conditions. So it is difficult for traditional reliability assessment methods based on time-to-failure distributions to deduce the reliability level. This paper presents a novel reliability assessment methodology to estimate the reliability level of equipment with machining performance degradation data when only a few samples are available. The least squares support vector machines(LS-SVM) are introduced to analyze the performance degradation process on the equipment. A two-stage parameter optimization and searching method is proposed to improve the LS-SVM regression performance and a reliability assessment model based on the LS-SVM is built. A machining performance degradation experiment has been carried out on an OTM650 machine tool to validate the effectiveness of the proposed reliability assessment methodology.

  1. Quantum Neural Network Based Machine Translator for Hindi to English

    Directory of Open Access Journals (Sweden)

    Ravi Narayan

    2014-01-01

    Full Text Available This paper presents the machine learning based machine translation system for Hindi to English, which learns the semantically correct corpus. The quantum neural based pattern recognizer is used to recognize and learn the pattern of corpus, using the information of part of speech of individual word in the corpus, like a human. The system performs the machine translation using its knowledge gained during the learning by inputting the pair of sentences of Devnagri-Hindi and English. To analyze the effectiveness of the proposed approach, 2600 sentences have been evaluated during simulation and evaluation. The accuracy achieved on BLEU score is 0.7502, on NIST score is 6.5773, on ROUGE-L score is 0.9233, and on METEOR score is 0.5456, which is significantly higher in comparison with Google Translation and Bing Translation for Hindi to English Machine Translation.

  2. Quantum neural network based machine translator for Hindi to English.

    Science.gov (United States)

    Narayan, Ravi; Singh, V P; Chakraverty, S

    2014-01-01

    This paper presents the machine learning based machine translation system for Hindi to English, which learns the semantically correct corpus. The quantum neural based pattern recognizer is used to recognize and learn the pattern of corpus, using the information of part of speech of individual word in the corpus, like a human. The system performs the machine translation using its knowledge gained during the learning by inputting the pair of sentences of Devnagri-Hindi and English. To analyze the effectiveness of the proposed approach, 2600 sentences have been evaluated during simulation and evaluation. The accuracy achieved on BLEU score is 0.7502, on NIST score is 6.5773, on ROUGE-L score is 0.9233, and on METEOR score is 0.5456, which is significantly higher in comparison with Google Translation and Bing Translation for Hindi to English Machine Translation.

  3. RSI in forest-machine operators in Scandinavia; Belastningsskador bland skogsmaskinfoerare i Norden

    Energy Technology Data Exchange (ETDEWEB)

    Eriksson, Goeran

    1995-08-01

    Repetitive stress (or strain) injury (RSI) is a widespread complaint among forest-machine operators. The most common complaints are those afflicting the neck and shoulders as a result of muscular tension due to sustained, intensive and repetitive operation of the machine`s controls. Muscular tension leads to reduced circulation which, in turn, gives rise to chemical and physiological disorders in the muscle cells. RSI not only causes considerable personal suffering but can also be costly to the afflicted individuals, their employers and to society. Despite the substantial ergonomic improvements that have been made to forest machinery, the percentage of operators suffering from RSI has not declined. The ergonomic standard of cab design and controls on farm tractors used in forestry, however, is still very poor, although the risk of RSI on tractor drivers is offset by the fact that they work much shorter hours than the operator of forest machines. Action taken to stimulate the circulation of blood through the muscles reduces the risk of RSI among operators. However, if real and lasting progress is to be made, a comprehensive programme of technological, organizational and personal measures needs to be established. This report describes the extent, causes and consequences of RSI and also highlights some of the measures that can be taken to prevent it. Refs, 12 figs, 1 tab

  4. Change-Exchange Currency based Vending Machine using VHDL

    Directory of Open Access Journals (Sweden)

    Nikita Khandelwal

    2013-01-01

    Full Text Available A vending machine is a coin-operated, automatic device which dispenses items such as snacks, beverages, lottery tickets, consumer products and even gold and gems to customers automatically, after the customer inserts currency or credit into the machine. These are more accessible and practical than the convention purchasing method. It is for the reason that vending machines provide us for our necessities almost instantly and with high quality, that people consider it as a very much reliable choice. In this paper a new approach is proposed to design a Vending Machine with automatic currency change or exchange multi select feature using which user can get a change of its currency or can exchange its currency to other available currency options. The machine also supports a cancel feature which means that the user can withdraw the request and the money will be returned back to him. This machine can be used at various places like Hotels, Restaurants, Stations and shopping centers. This reduces the time and cost. The proposed model is implemented using FPGA, the simulation results and circuit parameters are also presented.

  5. Support vector machines optimization based theory, algorithms, and extensions

    CERN Document Server

    Deng, Naiyang; Zhang, Chunhua

    2013-01-01

    Support Vector Machines: Optimization Based Theory, Algorithms, and Extensions presents an accessible treatment of the two main components of support vector machines (SVMs)-classification problems and regression problems. The book emphasizes the close connection between optimization theory and SVMs since optimization is one of the pillars on which SVMs are built.The authors share insight on many of their research achievements. They give a precise interpretation of statistical leaning theory for C-support vector classification. They also discuss regularized twi

  6. Design of Sugarcane Peeling Machine Based on Motion Controller

    Directory of Open Access Journals (Sweden)

    Zhang Dehui

    2015-04-01

    Full Text Available Sugarcane is a common raw material for sugar, but in the process of machining, there will be suspended solids in the cane juice, in order to process better, the sugarcane should be peeled. Traditional way of peeling is by man, production efficiency is low. In this study, a kind of sugarcane peeling machine was designed based on motion controller, it can realize the automation of input, peeling and output. It can make certain contribution for sugarcane processing.

  7. Creating Situational Awareness in Spacecraft Operations with the Machine Learning Approach

    Science.gov (United States)

    Li, Z.

    2016-09-01

    This paper presents a machine learning approach for the situational awareness capability in spacecraft operations. There are two types of time dependent data patterns for spacecraft datasets: the absolute time pattern (ATP) and the relative time pattern (RTP). The machine learning captures the data patterns of the satellite datasets through the data training during the normal operations, which is represented by its time dependent trend. The data monitoring compares the values of the incoming data with the predictions of machine learning algorithm, which can detect any meaningful changes to a dataset above the noise level. If the difference between the value of incoming telemetry and the machine learning prediction are larger than the threshold defined by the standard deviation of datasets, it could indicate the potential anomaly that may need special attention. The application of the machine-learning approach to the Advanced Himawari Imager (AHI) on Japanese Himawari spacecraft series is presented, which has the same configuration as the Advanced Baseline Imager (ABI) on Geostationary Environment Operational Satellite (GOES) R series. The time dependent trends generated by the data-training algorithm are in excellent agreement with the datasets. The standard deviation in the time dependent trend provides a metric for measuring the data quality, which is particularly useful in evaluating the detector quality for both AHI and ABI with multiple detectors in each channel. The machine-learning approach creates the situational awareness capability, and enables engineers to handle the huge data volume that would have been impossible with the existing approach, and it leads to significant advances to more dynamic, proactive, and autonomous spacecraft operations.

  8. The reduction methods of operator's radiation dose for portable dental X-ray machines.

    Science.gov (United States)

    Cho, Jeong-Yeon; Han, Won-Jeong

    2012-08-01

    This study was aimed to investigate the methods to reduce operator's radiation dose when taking intraoral radiographs with portable dental X-ray machines. Two kinds of portable dental X-ray machines (DX3000, Dexcowin and Rextar, Posdion) were used. Operator's radiation dose was measured with an 1,800 cc ionization chamber (RadCal Corp.) at the hand level of X-ray tubehead and at the operator's chest and waist levels with and without the backscatter shield. The operator's radiation dose at the hand level was measured with and without lead gloves and with long and short cones. The backscatter shield reduced operator's radiation dose at the hand level of X-ray tubehead to 23 - 32%, the lead gloves to 26 - 31%, and long cone to 48 - 52%. And the backscatter shield reduced operator's radiation dose at the operator's chest and waist levels to 0.1 - 37%. When portable dental X-ray systems are used, it is recommended to select X-ray machine attached with a backscatter shield and a long cone and to wear the lead gloves.

  9. The reduction methods of operator's radiation dose for portable dental X-ray machines

    Directory of Open Access Journals (Sweden)

    Jeong-Yeon Cho

    2012-08-01

    Full Text Available Objectives This study was aimed to investigate the methods to reduce operator's radiation dose when taking intraoral radiographs with portable dental X-ray machines. Materials and Methods Two kinds of portable dental X-ray machines (DX3000, Dexcowin and Rextar, Posdion were used. Operator's radiation dose was measured with an 1,800 cc ionization chamber (RadCal Corp. at the hand level of X-ray tubehead and at the operator's chest and waist levels with and without the backscatter shield. The operator's radiation dose at the hand level was measured with and without lead gloves and with long and short cones. Results The backscatter shield reduced operator's radiation dose at the hand level of X-ray tubehead to 23 - 32%, the lead gloves to 26 - 31%, and long cone to 48 - 52%. And the backscatter shield reduced operator's radiation dose at the operator's chest and waist levels to 0.1 - 37%. Conclusions When portable dental X-ray systems are used, it is recommended to select X-ray machine attached with a backscatter shield and a long cone and to wear the lead gloves.

  10. Technology and Jobs: Computer-Aided Design. Numerical-Control Machine-Tool Operators. Office Automation.

    Science.gov (United States)

    Stanton, Michael; And Others

    1985-01-01

    Three reports on the effects of high technology on the nature of work include (1) Stanton on applications and implications of computer-aided design for engineers, drafters, and architects; (2) Nardone on the outlook and training of numerical-control machine tool operators; and (3) Austin and Drake on the future of clerical occupations in automated…

  11. MACHINE TOOL OPERATOR--GENERAL, ENTRY, SUGGESTED GUIDE FOR A TRAINING COURSE.

    Science.gov (United States)

    RONEY, MAURICE W.; AND OTHERS

    THE PURPOSE OF THIS CURRICULUM GUIDE IS TO ASSIST THE ADMINISTRATOR AND INSTRUCTOR IN PLANNING AND DEVELOPING MANPOWER DEVELOPMENT AND TRAINING PROGRAMS TO PREPARE MACHINE TOOL OPERATORS FOR ENTRY-LEVEL POSITIONS. THE COURSE OUTLINE PROVIDES UNITS IN -- (1) ORIENTATION, (2) BENCH WORK, (3) SHOP MATHEMATICS, (4) BLUEPRINT READING AND SKETCHING, (5)…

  12. Musculoskeletal disorders of the neck and shoulders in female sewing machine operators: prevalence, incidence, and prognosis

    DEFF Research Database (Denmark)

    Kaergaard, A.; Andersen, JH

    2000-01-01

    OBJECTIVES: To assess the occurrence and persistence of two restrictively defined neck-shoulder disorders among sewing machine operators. To assess factors associated with the development of neck-shoulder disorder and prognostic factors for remaining a case, when disorders were already present. M...

  13. Sewing machine operation : workstation adjustment, working posture, and workers’ perceptions

    NARCIS (Netherlands)

    Delleman, N.J.; Dul, J.

    2002-01-01

    At a traditional sewing machine workstation professional operators worked at ten different combined adjustments of table height, desk slope, and pedal position. Working posture and workers’ perceptions were measured. Two recommendations were formulated in order to minimize the load on the musculoske

  14. Embedded Based Electronic Voting Machine Using Password

    Directory of Open Access Journals (Sweden)

    Varkala Vinay,

    2015-04-01

    Full Text Available The Electronic voting machine plays a key role in elections. The Earlier EVM’S needs more man power, time and mislead the voting scenario due to influence of local people vote and after voting the other may vote only after the Password is set then the system gets ready to accept the polling. After completion of the polling we may make the system to reset .If the person is authenticated then the vote is issued and the polling process is done using buzzer system, else that denies the process. At every regular intervals of time the polled votes are recorded and give the count that how many votes are casted through LCD. This system gives an efficient way to conduct elections and display the results on the same day.

  15. A discourse based approach in text-based machine translation

    CERN Document Server

    Ullah, Sana; Kwak, Kyung Sup

    2009-01-01

    This paper presents a theoretical research based approach to ellipsis resolution in machine translation. Moreover, the formula of discourse is applied in order to resolve ellipses. The validity of the discourse formula is analyzed by applying it to the real world text i.e. newspaper fragments. The source text is converted into mono-sentential discourses where complex discourses require further dissection either directly into primitive discourses or first into compound discourses and later into primitive ones. The procedure of dissection needs further improvement i.e. discovering as many primitive discourse forms as possible [1]. This work is further improvement to the concepts presented by Khan (Khan, 1995). Likewise, an attempt has been made to investigate new primitive discourses i.e. patterns from the given text.

  16. Factors influencing the microbial composition of metalworking fluids and potential implications for machine operator's lung.

    Science.gov (United States)

    Murat, Jean-Benjamin; Grenouillet, Frédéric; Reboux, Gabriel; Penven, Emmanuelle; Batchili, Adam; Dalphin, Jean-Charles; Thaon, Isabelle; Millon, Laurence

    2012-01-01

    Hypersensitivity pneumonitis, also known as "machine operator's lung" (MOL), has been related to microorganisms growing in metalworking fluids (MWFs), especially Mycobacterium immunogenum. We aimed to (i) describe the microbiological contamination of MWFs and (ii) look for chemical, physical, and environmental parameters associated with variations in microbiological profiles. We microbiologically analyzed 180 MWF samples from nonautomotive plants (e.g., screw-machining or metal-cutting plants) in the Franche-Comté region in eastern France and 165 samples from three French automotive plants in which cases of MOL had been proven. Our results revealed two types of microbial biomes: the first was from the nonautomotive industry, showed predominantly Gram-negative rods (GNR), and was associated with a low risk of MOL, and the second came from the automotive industry that was affected by cases of MOL and showed predominantly Gram-positive rods (GPR). Traces of M. immunogenum were sporadically detected in the first type, while it was highly prevalent in the automotive sector, with up to 38% of samples testing positive. The use of chromium, nickel, or iron was associated with growth of Gram-negative rods; conversely, growth of Gram-positive rods was associated with the absence of these metals. Synthetic MWFs were more frequently sterile than emulsions. Vegetable oil-based emulsions were associated with GNR, while mineral ones were associated with GPR. Our results suggest that metal types and the nature of MWF play a part in MWF contamination, and this work shall be followed by further in vitro simulation experiments on the kinetics of microbial populations, focusing on the phenomena of inhibition and synergy.

  17. A Cataloguing System for Machine Readable Data Bases.

    Science.gov (United States)

    Lauterbach, Guy

    With the fantastic growth in computerized data processing and management, there arises a great need for improved techniques in cataloging of machine readable data bases. The purpose of this report is to define a system by which computerized data bases may be cataloged for easy reference and availability. Developed from a computer scientist's…

  18. Machine learning versus knowledge based classification of legal texts

    NARCIS (Netherlands)

    de Maat, E.; Krabben, K.; Winkels, R.

    2010-01-01

    This paper presents results of an experiment in which we used machine learning (ML) techniques to classify sentences in Dutch legislation. These results are compared to the results of a pattern-based classifier. Overall, the ML classifier performs as accurate (>90%) as the pattern based one, but

  19. Support Vector Machine-Based Nonlinear System Modeling and Control

    Institute of Scientific and Technical Information of China (English)

    张浩然; 韩正之; 冯瑞; 于志强

    2003-01-01

    This paper provides an introduction to a support vector machine, a new kernel-based technique introduced in statistical learning theory and structural risk minimization, then presents a modeling-control framework based on SVM.At last a numerical experiment is taken to demonstrate the proposed approach's correctness and effectiveness.

  20. Study of pulmonary (lung) functioning of commercial wheat grinding machine operators in India using spirometric testing.

    Science.gov (United States)

    Agashe, Abhijeet; Deshpande, V S

    2010-04-01

    In ancient times, in India each household had a chakki to mill the wheat. There was no concept of getting wheat grounded from outside. With the fast changing lifestyle, this tradition has almost disappeared now. Today every city of India has numerous commercial wheat grinding machine shops located at various places. Other than states like Punjab, this occupation is mostly unorganized and little has been done to look into the welfare and health of these machine operators. Like most of the occupations, this occupation of wheat grinding also has several occupational hazards and injuries associated with it. The most obvious of them all in this case is due to the continuous exposure of the operators to the rising dust wheat particles, commonly called atta). This perpetual inhaling ofpollutants exposes the operators to risks of pulmonary malfunctioning. Therefore, this paper attempts to determine the pulmonary functioning of the commercial wheat grinding machine operators in India using spirometric testing. On the basis of the anthropometric data, effort has been done to develop the expected lung performance. Further, the actual lung performance of the operators is measured and compared with expected performance.

  1. Direction Identification System of Garlic Clove Based on Machine Vision

    Directory of Open Access Journals (Sweden)

    Gao Chi

    2013-05-01

    Full Text Available In order to fulfill the requirements of seeding direction of garlic cloves, the paper proposed a research method of garlic clove direction identification based on machine vision, it expounded the theory of garlic clove direction identification, stated the arithmetic of it, designed the direction identification device of it, then developed the control system of garlic clove direction identification based on machine vision, at last tested the garlic clove direction identification, and the result of the experiment certificated that the rate of garlic clove direction identification could reach to more than 97%, and it demonstrated that the research is of high feasibility and technological values.

  2. Control of seismic and operational vibrations of rotating machines using semi-active mounts

    Institute of Scientific and Technical Information of China (English)

    R.Rana; T.T.Soong

    2004-01-01

    A dual isolation problem for rotating machines consists of isolation of housing structures from the machine vibrations and protection of machines during an earthquake to maintain their functionality. Desirable characteristics of machine mounts for the above two purposes can differ significantly due to difference in nature of the excitation and performance criteria in the two situations. In this paper, relevant response quantities are identified that may be used to quantify performancc and simplified models of rotating machines are presented using which these relevant response quantities may be calculated. Using random vibration approach with a stationary excitation, it is shown that significant improvement in seismic performance is achievable by proper mount design. Results of shaking table experiments performed with a realistic setup using a centrifugal pump are presented. It is concluded that a solution to this dual isolation problem lies in a semi-active.mount capable of switching its properties from‘operation-optimum'to‘seismic-optimum'at the omset of a seismic event.

  3. Based on B/S structure of the tunnel boring machine operation simulation and fault diagnosis system%基于B/S架构的掘进机运行仿真与故障诊断系统研究

    Institute of Scientific and Technical Information of China (English)

    汤其建

    2015-01-01

    Yongcheng Vocational College developed to run the simulation and fault diagnosis system based on In‐ternet technology roadheader .The system uses advanced computer simulation technology virtual Tunneling sud‐den disposal and roadheader typical faults to troubleshoot .Teachers can set a variety of unexpected situations and failures on a server or superuser machine;Students can be performed on the brow ser side virtual training to deal with unexpected situations , troubleshooting , the status process and troubleshooting process , you can choose a variety of simulation tools and test equipment ,process automatic record .The system was applied to the teaching and training ,so that students can not only deepen the Tunneling relevant expertise to understand ,and can exercise their ability to handle emergencies and Diagnostics boring machine failure .The system is to improve student interest in learning and learning efficiency w hile reducing costs and time costs of teaching in schools and training institutions .%永城职业学院开发了基于网络技术的掘进机运行仿真与故障诊断系统。该系统利用先进的计算机虚拟仿真技术实现巷道掘进突发状况处置和掘进机典型故障诊断排除。教师可以在服务器或超级用户机上设置各种突发状况和故障;学生可以在浏览器端上进行虚拟实训,应对突发状况、排除故障,在状况处理和排除故障过程中,可选用各种仿真工具和检测仪器,过程自动记录。将该系统运用到教学和培训中,不但可以使学员加深对巷道掘进相关专业知识的理解,而且可以锻炼其处置突发状况和诊断掘进机故障的能力。该系统在提高学员学习兴趣和学习效率的同时,还能降低学校和培训机构的教学成本和时间成本。

  4. Modeling powder encapsulation in dosator-based machines: I. Theory.

    Science.gov (United States)

    Khawam, Ammar

    2011-12-15

    Automatic encapsulation machines have two dosing principles: dosing disc and dosator. Dosator-based machines compress the powder to plugs that are transferred into capsules. The encapsulation process in dosator-based capsule machines was modeled in this work. A model was proposed to predict the weight and length of produced plugs. According to the model, the plug weight is a function of piston dimensions, powder-bed height, bulk powder density and precompression densification inside dosator while plug length is a function of piston height, set piston displacement, spring stiffness and powder compressibility. Powder densification within the dosator can be achieved by precompression, compression or both. Precompression densification depends on the powder to piston height ratio while compression densification depends on piston displacement against powder. This article provides the theoretical basis of the encapsulation model, including applications and limitations. The model will be applied to experimental data separately.

  5. Molecular Machine-Based Active Plasmonics

    Science.gov (United States)

    2011-07-21

    integrated multifunctional sensors and devices based on switchable molecules. This outcome is essential for the development of carbon nanotube...constitutes a seminal step towards functional nanoelectromechanical systems ( NEMS ) based on artificial molecular muscles. In addition, we have published a

  6. Power distribution of a co-axial dual-mechanical-port flux-switching permanent magnet machine for fuel-based extended range electric vehicles

    Science.gov (United States)

    Zhou, Lingkang; Hua, Wei; Zhang, Gan

    2017-05-01

    In this paper, power distribution between the inner and outer machines of a co-axial dual-mechanical-port flux-switching permanent magnet (CADMP-FSPM) machine is investigated for fuel-based extended range electric vehicle (ER-EV). Firstly, the topology and operation principle of the CADMP-FSPM machine are introduced, which consist of an inner FSPM machine used for high-speed, an outer FSPM machine for low-speed, and a magnetic isolation ring between them. Then, the magnetic field coupling of the inner and outer FSPM machines is analyzed with more attention paid to the optimization of the isolation ring thickness. Thirdly, the power-dimension (PD) equations of the inner and outer FSPM machines are derived, respectively, and thereafter, the PD equation of the whole CADMP-FSPM machine can be given. Finally, the PD equations are validated by finite element analysis, which supplies the guidance on the design of this type of machines.

  7. Technology development for remote, computer-assisted operation of a continuous mining machine

    Energy Technology Data Exchange (ETDEWEB)

    Schnakenberg, G.H. [Pittsburgh Research Center, PA (United States)

    1993-12-31

    The U.S. Bureau of Mines was created to conduct research to improve the health, safety, and efficiency of the coal and metal mining industries. In 1986, the Bureau embarked on a new, major research effort to develop the technology that would enable the relocation of workers from hazardous areas to areas of relative safety. This effort is in contrast to historical efforts by the Bureau of controlling or reducing the hazardous agent or providing protection to the worker. The technologies associated with automation, robotics, and computer software and hardware systems had progressed to the point that their use to develop computer-assisted operation of mobile mining equipment appeared to be a cost-effective and accomplishable task. At the first International Symposium of Mine Mechanization and Automation, an overview of the Bureau`s computer-assisted mining program for underground coal mining was presented. The elements included providing computer-assisted tele-remote operation of continuous mining machines, haulage systems and roof bolting machines. Areas of research included sensors for machine guidance and for coal interface detection. Additionally, the research included computer hardware and software architectures which are extremely important in developing technology that is transferable to industry and is flexible enough to accommodate the variety of machines used in coal mining today. This paper provides an update of the research under the computer-assisted mining program.

  8. Machine Learning Based Diagnosis of Lithium Batteries

    Science.gov (United States)

    Ibe-Ekeocha, Chinemerem Christopher

    The depletion of the world's current petroleum reserve, coupled with the negative effects of carbon monoxide and other harmful petrochemical by-products on the environment, is the driving force behind the movement towards renewable and sustainable energy sources. Furthermore, the growing transportation sector consumes a significant portion of the total energy used in the United States. A complete electrification of this sector would require a significant development in electric vehicles (EVs) and hybrid electric vehicles (HEVs), thus translating to a reduction in the carbon footprint. As the market for EVs and HEVs grows, their battery management systems (BMS) need to be improved accordingly. The BMS is not only responsible for optimally charging and discharging the battery, but also monitoring battery's state of charge (SOC) and state of health (SOH). SOC, similar to an energy gauge, is a representation of a battery's remaining charge level as a percentage of its total possible charge at full capacity. Similarly, SOH is a measure of deterioration of a battery; thus it is a representation of the battery's age. Both SOC and SOH are not measurable, so it is important that these quantities are estimated accurately. An inaccurate estimation could not only be inconvenient for EV consumers, but also potentially detrimental to battery's performance and life. Such estimations could be implemented either online, while battery is in use, or offline when battery is at rest. This thesis presents intelligent online SOC and SOH estimation methods using machine learning tools such as artificial neural network (ANN). ANNs are a powerful generalization tool if programmed and trained effectively. Unlike other estimation strategies, the techniques used require no battery modeling or knowledge of battery internal parameters but rather uses battery's voltage, charge/discharge current, and ambient temperature measurements to accurately estimate battery's SOC and SOH. The developed

  9. Development of High-speed Machining Database with Case-based Reasoning

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    Applying high-speed machining technology in shop floor has many benefits, such as manufacturing more accurate parts with better surface finishes. The selection of the appropriate machining parameters plays a very important role in the implementation of high-speed machining technology. The case-based reasoning is used in the developing of high-speed machining database to overcome the shortage of available high-speed cutting parameters in machining data handbooks and shop floors. The high-speed machining data...

  10. 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.

  11. Prediction of the Functional Performance of Machined Components Based on Surface Topography: State of the Art

    Science.gov (United States)

    Grzesik, Wit

    2016-10-01

    This survey overviews the functional performance of manufactured components produced by typical finishing machining operations in terms of their topographical characteristics. Surface topographies were characterized using both profile (2D) and 3D (areal) surface roughness parameters. The prediction of typical functional properties such as fatigue, friction, wear, bonding and corrosion is discussed based on appropriate surface roughness parameters. Some examples of real 3D surface topographies produced with desired functional characteristics are provided. This survey highlights technological possibilities of producing surfaces with enhanced functional properties by machining processes.

  12. Prediction Based Proactive Thermal Virtual Machine Scheduling in Green Clouds

    OpenAIRE

    Supriya Kinger; Rajesh Kumar; Anju Sharma

    2014-01-01

    Cloud computing has rapidly emerged as a widely accepted computing paradigm, but the research on Cloud computing is still at an early stage. Cloud computing provides many advanced features but it still has some shortcomings such as relatively high operating cost and environmental hazards like increasing carbon footprints. These hazards can be reduced up to some extent by efficient scheduling of Cloud resources. Working temperature on which a machine is currently running can be taken as a crit...

  13. An Analysis of Hardware-Assisted Virtual Machine Based Rootkits

    Science.gov (United States)

    2014-06-01

    NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS Approved for public release; distribution is unlimited AN ANALYSIS OF...34 [Online]. Available: http://www.delorie.com/djgpp/doc/ug /basics/protected.html. [10] G. Duarte . (2008, Aug.). “CPU rings, privilege, and...Vitualization” in ASPLOS’06, San Jose, California , 2006. [21] G. Heiser et al, “Are virtual-machine monitors microkernels done right?” SIGOPS Oper

  14. Multi-machine power system stabilizer design by rule based bacteria foraging

    Energy Technology Data Exchange (ETDEWEB)

    Mishra, S.; Tripathy, M.; Nanda, J. [Department of Electrical Engineering, Indian Institute of Technology, Delhi (India)

    2007-10-15

    Several power system stabilizers (PSS) connected in number of machines in a multi-machine power systems, pose the problem of appropriate tuning of their parameters so that overall system dynamic stability can be improved in a robust way. Based on the foraging behavior of Escherichia coli bacteria in human intestine, this paper attempts to optimize simultaneously three constants each of several PSS present in a multi-machine power system. The tuning is done taking an objective function that incorporates a multi-operative condition, consisting of nominal and various changed conditions, into it. The convergence with the proposed rule based bacteria foraging (RBBF) optimization technique is superior to the conventional and genetic algorithm (GA) techniques. Robustness of tuning with the proposed method was verified, with transient stability analysis of the system by time domain simulations subjecting the power system to different types of disturbances. (author)

  15. Performance Analysis of Kernel-Based Virtual Machine

    Directory of Open Access Journals (Sweden)

    Usha J

    2013-03-01

    Full Text Available Rapid advancement in computing technology has put forth Cloud computing as a paramount paradigm indistributed systems. It is very much essential and important too to fully understand the underlyingtechnologies that makes clouds possible. One key technology that make makes the cloud popular isvirtualization. Even though virtualization technology isnot new, the concept of hypervisors withvirtualization is getting popular and also well understood by many. There are a good number ofhypervisors. This paper discusses the types of Virtualization Technologies, hypervisors and configurationof the VMs and analyse the performance of Virtual Machines using Kernel Based Virtual Machine-KVM,a Type2 hypervisor.

  16. Machine Learning for Vision-Based Motion Analysis

    CERN Document Server

    Wang, Liang; Cheng, Li; Pietikainen, Matti

    2011-01-01

    Techniques of vision-based motion analysis aim to detect, track, identify, and generally understand the behavior of objects in image sequences. With the growth of video data in a wide range of applications from visual surveillance to human-machine interfaces, the ability to automatically analyze and understand object motions from video footage is of increasing importance. Among the latest developments in this field is the application of statistical machine learning algorithms for object tracking, activity modeling, and recognition. Developed from expert contributions to the first and second In

  17. Prediction of Banking Systemic Risk Based on Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Shouwei Li

    2013-01-01

    Full Text Available Banking systemic risk is a complex nonlinear phenomenon and has shed light on the importance of safeguarding financial stability by recent financial crisis. According to the complex nonlinear characteristics of banking systemic risk, in this paper we apply support vector machine (SVM to the prediction of banking systemic risk in an attempt to suggest a new model with better explanatory power and stability. We conduct a case study of an SVM-based prediction model for Chinese banking systemic risk and find the experiment results showing that support vector machine is an efficient method in such case.

  18. Syntactic Reordering for Arabic- English Phrase-Based Machine Translation

    Science.gov (United States)

    Hatem, Arwa; Omar, Nazlia

    Machine Translation (MT) refers to the use of a machine for performing translation task which converts text or speech in one Natural Language (Source Language (SL)) into another Natural Language (Target Language (TL)). The translation from Arabic to English is difficult task due to the Arabic languages are highly inflectional, rich morphology and relatively free word order. Word ordering plays an important part in the translation process. The paper proposes a transfer-based approach in Arabic to English MT to handle the word ordering problem. Preliminary tested indicate that our system, AE-TBMT is competitive when compared against other approaches from the literature.

  19. Limitations Of The Current State Space Modelling Approach In Multistage Machining Processes Due To Operation Variations

    Science.gov (United States)

    Abellán-Nebot, J. V.; Liu, J.; Romero, F.

    2009-11-01

    The State Space modelling approach has been recently proposed as an engineering-driven technique for part quality prediction in Multistage Machining Processes (MMP). Current State Space models incorporate fixture and datum variations in the multi-stage variation propagation, without explicitly considering common operation variations such as machine-tool thermal distortions, cutting-tool wear, cutting-tool deflections, etc. This paper shows the limitations of the current State Space model through an experimental case study where the effect of the spindle thermal expansion, cutting-tool flank wear and locator errors are introduced. The paper also discusses the extension of the current State Space model to include operation variations and its potential benefits.

  20. Computational Principle and Performance Evaluation of Coherent Ising Machine Based on Degenerate Optical Parametric Oscillator Network

    Directory of Open Access Journals (Sweden)

    Yoshitaka Haribara

    2016-04-01

    Full Text Available We present the operational principle of a coherent Ising machine (CIM based on a degenerate optical parametric oscillator (DOPO network. A quantum theory of CIM is formulated, and the computational ability of CIM is evaluated by numerical simulation based on c-number stochastic differential equations. We also discuss the advanced CIM with quantum measurement-feedback control and various problems which can be solved by CIM.

  1. Machine learning for network-based malware detection

    DEFF Research Database (Denmark)

    Stevanovic, Matija

    and based on different, mutually complementary, principles of traffic analysis. The proposed approaches rely on machine learning algorithms (MLAs) for automated and resource-efficient identification of the patterns of malicious network traffic. We evaluated the proposed methods through extensive evaluations...

  2. Exact Decoding for Phrase-Based Statistical Machine Translation

    NARCIS (Netherlands)

    Aziz, W.; Dymetman, M.; Specia, L.

    2014-01-01

    The combinatorial space of translation derivations in phrase-based statistical machine translation is given by the intersection between a translation lattice and a target language model. We replace this intractable intersection by a tractable relaxation which incorporates a low-order upperbound on t

  3. Runtime Optimizations for Tree-Based Machine Learning Models

    NARCIS (Netherlands)

    N. Asadi; J.J.P. Lin (Jimmy); A.P. de Vries (Arjen)

    2014-01-01

    htmlabstractTree-based models have proven to be an effective solution for web ranking as well as other machine learning problems in diverse domains. This paper focuses on optimizing the runtime performance of applying such models to make predictions, specifically using gradient-boosted regression

  4. Finite State Machine based Vending Machine Controller with Auto-Billing Features

    OpenAIRE

    2012-01-01

    Nowadays, Vending Machines are well known among Japan, Malaysia and Singapore. The quantity of machines in these countries is on the top worldwide. This is due to the modern lifestyles which require fast food processing with high quality. This paper describes the designing of multi select machine using Finite State Machine Model with Auto-Billing Features. Finite State Machine (FSM) modelling is the most crucial part in developing proposed model as this reduces the hardware. In this paper th...

  5. Fast Affinity Propagation Clustering based on Machine Learning

    OpenAIRE

    Shailendra Kumar Shrivastava; J. L. Rana; DR.R.C.JAIN

    2013-01-01

    Affinity propagation (AP) was recently introduced as an un-supervised learning algorithm for exemplar based clustering. In this paper a novel Fast Affinity Propagation clustering Approach based on Machine Learning (FAPML) has been proposed. FAPML tries to put data points into clusters based on the history of the data points belonging to clusters in early stages. In FAPML we introduce affinity learning constant and dispersion constant which supervise the clustering process. FAPML also enforces...

  6. OPTIMIZATION OF OPERATING PARAMETERS FOR EDM PROCESS BASED ON THE TAGUCHI METHOD AND ARTIFICIAL NEURAL NETWORK

    Directory of Open Access Journals (Sweden)

    A.Thillaivanan,

    2010-12-01

    Full Text Available In this paper the complexity of electrical discharge machining process which is very difficult to determine optimal cutting parameters for improving cutting performance has been reported. Optimization of operating parameters is an important step in machining, particularly for operating unconventional machiningprocedure like EDM. A suitable selection of machining parameters for the electrical discharge machining process relies heavily on the operators’ technologies and experience because of their numerous and diverse range. Machining parameters tables provided by the machine tool builder can not meet the operators’ requirements, since for anarbitrary desired machining time for a particular job, they do not provide the optimal machining conditions. An approach to determine parameters setting is proposed. Based on the Taguchi parameter design method and the analysis of variance, the significant factors affecting the machining performance such as total machining time, oversize and taper for a hole machined by EDM process, are determined.Artificial neural networks are highly flexible modeling tools with an ability to learn the mapping between input variables and output feature spaces. The superiority of using artificial neural networks inmodeling machining processes make easier to model the EDM process with dimensional input and output spaces. On the basis of the developed neural network model, for a required total machining time, oversize and taper the corresponding process parameters to be set in EDM by using the developed and trained ANN are determined.

  7. "Machine" consciousness and "artificial" thought: an operational architectonics model guided approach.

    Science.gov (United States)

    Fingelkurts, Andrew A; Fingelkurts, Alexander A; Neves, Carlos F H

    2012-01-05

    Instead of using low-level neurophysiology mimicking and exploratory programming methods commonly used in the machine consciousness field, the hierarchical operational architectonics (OA) framework of brain and mind functioning proposes an alternative conceptual-theoretical framework as a new direction in the area of model-driven machine (robot) consciousness engineering. The unified brain-mind theoretical OA model explicitly captures (though in an informal way) the basic essence of brain functional architecture, which indeed constitutes a theory of consciousness. The OA describes the neurophysiological basis of the phenomenal level of brain organization. In this context the problem of producing man-made "machine" consciousness and "artificial" thought is a matter of duplicating all levels of the operational architectonics hierarchy (with its inherent rules and mechanisms) found in the brain electromagnetic field. We hope that the conceptual-theoretical framework described in this paper will stimulate the interest of mathematicians and/or computer scientists to abstract and formalize principles of hierarchy of brain operations which are the building blocks for phenomenal consciousness and thought. Copyright © 2010 Elsevier B.V. All rights reserved.

  8. OpenCL based machine learning labeling of biomedical datasets

    Science.gov (United States)

    Amoros, Oscar; Escalera, Sergio; Puig, Anna

    2011-03-01

    In this paper, we propose a two-stage labeling method of large biomedical datasets through a parallel approach in a single GPU. Diagnostic methods, structures volume measurements, and visualization systems are of major importance for surgery planning, intra-operative imaging and image-guided surgery. In all cases, to provide an automatic and interactive method to label or to tag different structures contained into input data becomes imperative. Several approaches to label or segment biomedical datasets has been proposed to discriminate different anatomical structures in an output tagged dataset. Among existing methods, supervised learning methods for segmentation have been devised to easily analyze biomedical datasets by a non-expert user. However, they still have some problems concerning practical application, such as slow learning and testing speeds. In addition, recent technological developments have led to widespread availability of multi-core CPUs and GPUs, as well as new software languages, such as NVIDIA's CUDA and OpenCL, allowing to apply parallel programming paradigms in conventional personal computers. Adaboost classifier is one of the most widely applied methods for labeling in the Machine Learning community. In a first stage, Adaboost trains a binary classifier from a set of pre-labeled samples described by a set of features. This binary classifier is defined as a weighted combination of weak classifiers. Each weak classifier is a simple decision function estimated on a single feature value. Then, at the testing stage, each weak classifier is independently applied on the features of a set of unlabeled samples. In this work, we propose an alternative representation of the Adaboost binary classifier. We use this proposed representation to define a new GPU-based parallelized Adaboost testing stage using OpenCL. We provide numerical experiments based on large available data sets and we compare our results to CPU-based strategies in terms of time and

  9. Neural Operant Conditioning as a Core Mechanism of Brain-Machine Interface Control

    Directory of Open Access Journals (Sweden)

    Yoshio Sakurai

    2016-08-01

    Full Text Available The process of changing the neuronal activity of the brain to acquire rewards in a broad sense is essential for utilizing brain-machine interfaces (BMIs, which is essentially operant conditioning of neuronal activity. Currently, this is also known as neural biofeedback, and it is often referred to as neurofeedback when human brain activity is targeted. In this review, we first illustrate biofeedback and operant conditioning, which are methodological background elements in neural operant conditioning. Then, we introduce research models of neural operant conditioning in animal experiments and demonstrate that it is possible to change the firing frequency and synchronous firing of local neuronal populations in a short time period. We also debate the possibility of the application of neural operant conditioning and its contribution to BMIs.

  10. ARABIC-MALAY MACHINE TRANSLATION USING RULE-BASED APPROACH

    Directory of Open Access Journals (Sweden)

    Ahmed Jumaa Alsaket

    2014-01-01

    Full Text Available Arabic machine translation has been taking place in machine translation projects in recent years. This study concentrates on the translation of Arabic text to its equivalent in Malay language. The problem of this research is the syntactic and morphological differences between Arabic and Malay adjective sentences. The main aim of this study is to design and develop Arabic-Malay machine translation model. First, we analyze the adjective role in the Arabic and Malay languages. Based on this analysis, we identify the transfer bilingual rules form source language to target language so that the translation of source language to target language can be performed by computers successfully. Then, we build and implement a machine translation prototype called AMTS to translate from Arabic to Malay based on rule based approach. The system is evaluated on set of simple Arabic sentences. The techniques used to evaluate the correctness of the system translation are the BLEU metric algorithm and the human judgment. The results of the BLEU algorithm show that the AMTS system performs better than Google in the translation of Arabic sentences into Malay. In addition, the average accuracy given by human judges is 92.3% for our system and 75.3% for Google.

  11. Methods, systems and apparatus for controlling operation of two alternating current (AC) machines

    Science.gov (United States)

    Gallegos-Lopez, Gabriel; Nagashima, James M.; Perisic, Milun; Hiti, Silva

    2012-02-14

    A system is provided for controlling two AC machines. The system comprises a DC input voltage source that provides a DC input voltage, a voltage boost command control module (VBCCM), a five-phase PWM inverter module coupled to the two AC machines, and a boost converter coupled to the inverter module and the DC input voltage source. The boost converter is designed to supply a new DC input voltage to the inverter module having a value that is greater than or equal to a value of the DC input voltage. The VBCCM generates a boost command signal (BCS) based on modulation indexes from the two AC machines. The BCS controls the boost converter such that the boost converter generates the new DC input voltage in response to the BCS. When the two AC machines require additional voltage that exceeds the DC input voltage required to meet a combined target mechanical power required by the two AC machines, the BCS controls the boost converter to drive the new DC input voltage generated by the boost converter to a value greater than the DC input voltage.

  12. Machine Learning

    Energy Technology Data Exchange (ETDEWEB)

    Chikkagoudar, Satish; Chatterjee, Samrat; Thomas, Dennis G.; Carroll, Thomas E.; Muller, George

    2017-04-21

    The absence of a robust and unified theory of cyber dynamics presents challenges and opportunities for using machine learning based data-driven approaches to further the understanding of the behavior of such complex systems. Analysts can also use machine learning approaches to gain operational insights. In order to be operationally beneficial, cybersecurity machine learning based models need to have the ability to: (1) represent a real-world system, (2) infer system properties, and (3) learn and adapt based on expert knowledge and observations. Probabilistic models and Probabilistic graphical models provide these necessary properties and are further explored in this chapter. Bayesian Networks and Hidden Markov Models are introduced as an example of a widely used data driven classification/modeling strategy.

  13. Energy Analysis of Contention Tree-Based Access Protocols in Dense Machine-to-Machine Area Networks

    Directory of Open Access Journals (Sweden)

    Francisco Vázquez-Gallego

    2015-01-01

    Full Text Available Machine-to-Machine (M2M area networks aim at connecting an M2M gateway with a large number of energy-constrained devices that must operate autonomously for years. Therefore, attaining high energy efficiency is essential in the deployment of M2M networks. In this paper, we consider a dense M2M area network composed of hundreds or thousands of devices that periodically transmit data upon request from a gateway or coordinator. We theoretically analyse the devices’ energy consumption using two Medium Access Control (MAC protocols which are based on a tree-splitting algorithm to resolve collisions among devices: the Contention Tree Algorithm (CTA and the Distributed Queuing (DQ access. We have carried out computer-based simulations to validate the accuracy of the theoretical models and to compare the energy performance using DQ, CTA, and Frame Slotted-ALOHA (FSA in M2M area networks with devices in compliance with the IEEE 802.15.4 physical layer. Results show that the performance of DQ is totally independent of the number of contending devices, and it can reduce the energy consumed per device in more than 35% with respect to CTA and in more than 80% with respect to FSA.

  14. An Android malware detection system based on machine learning

    Science.gov (United States)

    Wen, Long; Yu, Haiyang

    2017-08-01

    The Android smartphone, with its open source character and excellent performance, has attracted many users. However, the convenience of the Android platform also has motivated the development of malware. The traditional method which detects the malware based on the signature is unable to detect unknown applications. The article proposes a machine learning-based lightweight system that is capable of identifying malware on Android devices. In this system we extract features based on the static analysis and the dynamitic analysis, then a new feature selection approach based on principle component analysis (PCA) and relief are presented in the article to decrease the dimensions of the features. After that, a model will be constructed with support vector machine (SVM) for classification. Experimental results show that our system provides an effective method in Android malware detection.

  15. Dynamic Bayesian Network Based Prognosis in Machining Processes

    Institute of Scientific and Technical Information of China (English)

    DONG Ming; YANG Zhi-bo

    2008-01-01

    Condition based maintenance (CBM) is becoming more and more popular in equipment main-tenance. A prerequisite to widespread deployment of CBM technology and practice in industry is effectivediagnostics and prognostics. A dynamic Bayesian network (DBN) based prognosis method was investigated topredict the remaining useful life (RUL) for an equipment. First, a DBN based prognosis framework and specificsteps for building a DBN based prognosis model were presented. Then, the corresponding inference algorithmsfor DBN based prognosis were provided. Finally, a prognosis procedure based on particle filtering algorithmswas used to predict the RUL of drill-bits of a vertical drilling machine, which is commonly used in industrialprocess. Preliminary experimental results are promising.

  16. Physics-Based Haptic Simulation of Bone Machining.

    Science.gov (United States)

    Arbabtafti, M; Moghaddam, M; Nahvi, A; Mahvash, M; Richardson, B; Shirinzadeh, B

    2011-01-01

    We present a physics-based training simulator for bone machining. Based on experimental studies, the energy required to remove a unit volume of bone is a constant for every particular bone material. We use this physical principle to obtain the forces required to remove bone material with a milling tool rotating at high speed. The rotating blades of the tool are modeled as a set of small cutting elements. The force of interaction between a cutting element and bone is calculated from the energy required to remove a bone chip with an estimated thickness and known material stiffness. The total force acting on the cutter at a particular instant is obtained by integrating the differential forces over all cutting elements engaged. A voxel representation is used to represent the virtual bone and removed chips for calculating forces of machining. We use voxels that carry bone material properties to represent the volumetric haptic body and to apply underlying physical changes during machining. Experimental results of machining samples of a real bone confirm the force model. A real-time haptic implementation of the method in a dental training simulator is described.

  17. 冷冻机及操作%Refrigerating Machine and Operation

    Institute of Scientific and Technical Information of China (English)

    叶常琼

    2012-01-01

    随着社会的发展、生产的扩大,为了实现更好地生产,化工操作工要熟练操作设备,并且做好设备的维护,减少生产损失,这样就可以减少检修带来的人力物力及停滞生产所带来的利润损失.在化工生产中主要有换热器、压缩机、冷冻机及泵,在此主要以冷冻机为例,介绍冷冻机的原理、组成、开车准备、操作、遇到积液的判断与处理,不断提高操作人员对冷冻机的操作,保护好设备并减少对设备的损伤.%With the development of society, the expansion of production, in order to achieve better production, chemical operators must operate equipment expertly, and do a good job on equipment maintenance to reduce the production loss, which can reduce the manpower and material resources as well as loss of profit brought about by the stagnation production. In the chemical production, it mainly has heat exchanger, compressor, refrigerating machine and pump. In this paper, taking refrigerating machine as the example, its principle, composition, preparation of driving, operation, as well as judgment and treatment when encountering hydrops were introduced, so as to constantly improve the operation of operators to refrigerating machine, protect the equipment and reduce the damage to the equipment

  18. 29 CFR 570.63 - Occupations involved in the operation of paper-products machines, scrap paper balers, and paper...

    Science.gov (United States)

    2010-07-01

    ... machines, scrap paper balers, and paper box compactors (Order 12). 570.63 Section 570.63 Labor Regulations... involved in the operation of paper-products machines, scrap paper balers, and paper box compactors (Order..., scrap paper baler, paper box compactor, or vertical slotter. (ii) Platen die-cutting press,...

  19. Real-Time Simulation and Analysis of the Induction Machine Performances Operating at Flux Constant

    Directory of Open Access Journals (Sweden)

    Aziz Derouich

    2014-05-01

    Full Text Available In this paper, we are interested, in a first time, at the study and the implementation of a V/f control for induction machine in real time. After, We are attached to a comparison of the results by simulation and experiment for, speed responses, flux and currents of the real machine, with a DSPACE card and model established by classical identification (Direct Current test , blocked-rotor test, no-load test , synchronous test, to ensure the validity of the established model. The scalar controlled induction motor allows operation of the motor with the maximum torque by simultaneous action on the frequency and amplitude of the stator voltage, with conservation of the ratio V/f. Speed reference imposes a frequency at the inverter supplying the voltages needed to power the motor, which determines the speed of rotation. The maximum torque of the machine is proportional to the square of the supply voltage and inversely proportional to the frequency voltage. So, Keep V/f constant implies a operating with maximum constant torque. The results obtained for the rotor flux and the stator currents are especially satisfactory steady.

  20. The Remote Monitoring System Based on Wireless Digital Radio Portal Crane Machine Operation%基于无线数传电台的门机操作远程监控系统

    Institute of Scientific and Technical Information of China (English)

    熊见林; 刘清; 沈成建; 刘光明

    2011-01-01

    基于港口装卸作业过程中操作监控系统的远程实时监控和分析,提出了基于数传电台的解决方案.系统主要由后台管理计算机平台、系统支撑软件(Windows 2000 Server操作系统、SQL Server2008商业数据库等)和采用C8051F020单片机研制的门机操作记录终端构成,通过数传电台的无线数据通信,实现门机操作记录的数据实时发送到后台管理计算机,从而便于管理人员实时掌握门机司机的作业情况,以便及时做出相应的调度和调配.系统经过实际应用,安装和维护成本低、可扩展性强,数据传输实时性好.%This article is the process of loading and unloading port operations monitoring system, remote real-time monitoring and analysis is proposed based on digital radio solutions. The system is composed of background management computer platform, system support software (Windows 2000 Server operating system, SQL Server2000 commercial databases, etc. ) and developed using C8051F020 microcontroller operating records of the terminal gate structure, through digital radio wireless data communications, to achieve Portal Crane operation real-time data record sent to the admin computer, thus facilitating management of drivers to real-time control door operating conditions in order to make appropriate and timely scheduling and deployment. The system is practical, low cost installation and maintenance, scalability, strong, good real-time data transmission.

  1. Selected Operations, Algorithms, and Applications of n-Tape Weighted Finite-State Machines

    CERN Document Server

    Kempe, André

    2011-01-01

    A weighted finite-state machine with n tapes (n-WFSM) defines a rational relation on n strings. It is a generalization of weighted acceptors (one tape) and transducers (two tapes). After recalling some basic definitions about n-ary weighted rational relations and n-WFSMs, we summarize some central operations on these relations and machines, such as join and auto-intersection. Unfortunately, due to Post's Correspondence Problem, a fully general join or auto-intersection algorithm cannot exist. We recall a restricted algorithm for a class of n-WFSMs. Through a series of practical applications, we finally investigate the augmented descriptive power of n-WFSMs and their join, compared to classical transducers and their composition. Some applications are not feasible with the latter. The series includes: the morphological analysis of Semitic languages, the preservation of intermediate results in transducer cascades, the induction of morphological rules from corpora, the alignment of lexicon entries, the automatic ...

  2. Towards intelligent environments: an augmented reality-brain-machine interface operated with a see-through head-mount display

    Directory of Open Access Journals (Sweden)

    Kouji eTakano

    2011-04-01

    Full Text Available The brain-machine interface (BMI or brain-computer interface (BCI is a new interface technology that uses neurophysiological signals from the brain to control external machines or computers. This technology is expected to support daily activities, especially for persons with disabilities. To expand the range of activities enabled by this type of interface, here, we added augmented reality (AR to a P300-based BMI. In this new system, we used a see-through head-mount display (HMD to create control panels with flicker visual stimuli to support the user in areas close to controllable devices. When the attached camera detects an AR marker, the position and orientation of the marker are calculated, and the control panel for the pre-assigned appliance is created by the AR system and superimposed on the HMD. The participants were required to control system-compatible devices, and they successfully operated them without significant training. Online performance with the HMD was not different from that using an LCD monitor. Posterior and lateral (right or left channel selections contributed to operation of the AR-BMI with both the HMD and LCD monitor. Our results indicate that AR-BMI systems operated with a see-through HMD may be useful in building advanced intelligent environments.

  3. Prediction based proactive thermal virtual machine scheduling in green clouds.

    Science.gov (United States)

    Kinger, Supriya; Kumar, Rajesh; Sharma, Anju

    2014-01-01

    Cloud computing has rapidly emerged as a widely accepted computing paradigm, but the research on Cloud computing is still at an early stage. Cloud computing provides many advanced features but it still has some shortcomings such as relatively high operating cost and environmental hazards like increasing carbon footprints. These hazards can be reduced up to some extent by efficient scheduling of Cloud resources. Working temperature on which a machine is currently running can be taken as a criterion for Virtual Machine (VM) scheduling. This paper proposes a new proactive technique that considers current and maximum threshold temperature of Server Machines (SMs) before making scheduling decisions with the help of a temperature predictor, so that maximum temperature is never reached. Different workload scenarios have been taken into consideration. The results obtained show that the proposed system is better than existing systems of VM scheduling, which does not consider current temperature of nodes before making scheduling decisions. Thus, a reduction in need of cooling systems for a Cloud environment has been obtained and validated.

  4. Prediction Based Proactive Thermal Virtual Machine Scheduling in Green Clouds

    Directory of Open Access Journals (Sweden)

    Supriya Kinger

    2014-01-01

    Full Text Available Cloud computing has rapidly emerged as a widely accepted computing paradigm, but the research on Cloud computing is still at an early stage. Cloud computing provides many advanced features but it still has some shortcomings such as relatively high operating cost and environmental hazards like increasing carbon footprints. These hazards can be reduced up to some extent by efficient scheduling of Cloud resources. Working temperature on which a machine is currently running can be taken as a criterion for Virtual Machine (VM scheduling. This paper proposes a new proactive technique that considers current and maximum threshold temperature of Server Machines (SMs before making scheduling decisions with the help of a temperature predictor, so that maximum temperature is never reached. Different workload scenarios have been taken into consideration. The results obtained show that the proposed system is better than existing systems of VM scheduling, which does not consider current temperature of nodes before making scheduling decisions. Thus, a reduction in need of cooling systems for a Cloud environment has been obtained and validated.

  5. 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.

  6. Building a Large-Scale Knowledge Base for Machine Translation

    CERN Document Server

    Knight, K; Knight, Kevin; Luk, Steve K.

    1994-01-01

    Knowledge-based machine translation (KBMT) systems have achieved excellent results in constrained domains, but have not yet scaled up to newspaper text. The reason is that knowledge resources (lexicons, grammar rules, world models) must be painstakingly handcrafted from scratch. One of the hypotheses being tested in the PANGLOSS machine translation project is whether or not these resources can be semi-automatically acquired on a very large scale. This paper focuses on the construction of a large ontology (or knowledge base, or world model) for supporting KBMT. It contains representations for some 70,000 commonly encountered objects, processes, qualities, and relations. The ontology was constructed by merging various online dictionaries, semantic networks, and bilingual resources, through semi-automatic methods. Some of these methods (e.g., conceptual matching of semantic taxonomies) are broadly applicable to problems of importing/exporting knowledge from one KB to another. Other methods (e.g., bilingual match...

  7. Machine Translation Based on Translation Corresponding Tree Structure

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    A representation schema called translation corresponding tree (TCT) has been applied to a Portuguese to Chinese example-based machine translation system. The translation examples are annotated by the representation of the TCT structure. Each TCT describes not only the syntactic structure of the source sentence (i.e., Portuguese in our system) but also the translation correspondences (i.e., Chinese translation). In addition, the TCT nodes describe the corresponding linguistic relationships between the source and target languages. The translation examples can be effectively represented with this annotation schema and organized in the bilingual knowledge database or example base. In the real machine translation process, the target language is synthesized with higher quality by referring to the TCT translation information.

  8. A new support vector machine based multiuser detection scheme

    Institute of Scientific and Technical Information of China (English)

    WANG Yong-jian; ZHAO Hong-lin

    2008-01-01

    In order to suppress the multiple access interference(MAI)in 3G,which limits the capacity of a CDMA communication system,a fast relevance vector machine(FRVM)is employed in the muhinser detection (MUD)scheme.This method aims to overcome the shortcomings of many ordinary support vector machine (SVM)based MUD schemes,such as the long training time and the inaccuracy of the decision data,and enhance the performance of a CDMA communication system.Computer simulation results demonstrate that the proposed FRVM based muhiuser detection has lower bit error rate,costs short training time,needs fewer kernel functions and possesses better near-far resistance.

  9. English to Sanskrit Machine Translation Using Transfer Based approach

    Science.gov (United States)

    Pathak, Ganesh R.; Godse, Sachin P.

    2010-11-01

    Translation is one of the needs of global society for communicating thoughts and ideas of one country with other country. Translation is the process of interpretation of text meaning and subsequent production of equivalent text, also called as communicating same meaning (message) in another language. In this paper we gave detail information on how to convert source language text in to target language text using Transfer Based Approach for machine translation. Here we implemented English to Sanskrit machine translator using transfer based approach. English is global language used for business and communication but large amount of population in India is not using and understand the English. Sanskrit is ancient language of India most of the languages in India are derived from Sanskrit. Sanskrit can be act as an intermediate language for multilingual translation.

  10. Memory Based Machine Intelligence Techniques in VLSI hardware

    OpenAIRE

    James, Alex Pappachen

    2012-01-01

    We briefly introduce the memory based approaches to emulate machine intelligence in VLSI hardware, describing the challenges and advantages. Implementation of artificial intelligence techniques in VLSI hardware is a practical and difficult problem. Deep architectures, hierarchical temporal memories and memory networks are some of the contemporary approaches in this area of research. The techniques attempt to emulate low level intelligence tasks and aim at providing scalable solutions to high ...

  11. Saudi License Plate Recognition Algorithm Based on Support Vector Machine

    Institute of Scientific and Technical Information of China (English)

    Khaled Suwais; Rana Al-Otaibi; Ali Alshahrani

    2013-01-01

    License plate recognition (LPR) is an image processing technology that is used to identify vehicles by their license plates. This paper presents a license plate recognition algorithm for Saudi car plates based on the support vector machine (SVM) algorithm. The new algorithm is efficient in recognizing the vehicles from the Arabic part of the plate. The performance of the system has been investigated and analyzed. The recognition accuracy of the algorithm is about 93.3%.

  12. Successful attack on permutation-parity-machine-based neural cryptography.

    Science.gov (United States)

    Seoane, Luís F; Ruttor, Andreas

    2012-02-01

    An algorithm is presented which implements a probabilistic attack on the key-exchange protocol based on permutation parity machines. Instead of imitating the synchronization of the communicating partners, the strategy consists of a Monte Carlo method to sample the space of possible weights during inner rounds and an analytic approach to convey the extracted information from one outer round to the next one. The results show that the protocol under attack fails to synchronize faster than an eavesdropper using this algorithm.

  13. Memory Based Machine Intelligence Techniques in VLSI hardware

    CERN Document Server

    James, Alex Pappachen

    2012-01-01

    We briefly introduce the memory based approaches to emulate machine intelligence in VLSI hardware, describing the challenges and advantages. Implementation of artificial intelligence techniques in VLSI hardware is a practical and difficult problem. Deep architectures, hierarchical temporal memories and memory networks are some of the contemporary approaches in this area of research. The techniques attempt to emulate low level intelligence tasks and aim at providing scalable solutions to high level intelligence problems such as sparse coding and contextual processing.

  14. Development of a finite state machine for the automates operation of the LLRF control at FLASH

    Energy Technology Data Exchange (ETDEWEB)

    Brandt, A.

    2007-07-15

    The entry of digital signal processors in modern control systems not only allows for extended diagnostics compared to analog systems but also for sophisticated and tricky extensions of the control algorithms. With modern DSP- and FPGA-technology, the processing speed of digital systems is no longer inferior to analog systems in many applications. A higher degree of digitalization leads to an increased complexity of the systems and hence to higher requirements on their operators. The focus of research and development in the field of high frequency control has changed in the last few years and moved towards the direction of software development and complexity management. In the presented thesis, a frame for an automation concept of modern high frequency control systems is developed. The developed automation is based on the concept of finite state machines (FSM), which is established in industry for years. A flexible framework was developed, in which procedures communicate using standardized interfaces and can be exchanged easily. With that, the developer of high frequency control components as well as the operator on shift shall be empowered to improve and adapt the automation to changed conditions without special programming skills required. Along the automation concept a number of algorithms addressing various problems were developed which satisfy the needs of modern high frequency control systems. Among the developed and successfully tested algorithms are the calibration of incident and reflected wave of resonators without antennas, the fast adaptive compensation of repetitive errors, the robust estimation of the phase advance in the control loop and the latency adjustment for the rejection of instabilities caused by passband modes. During the development of the resonator theory, high value was set on the usability of the equation in algorithms for high frequency control. The usage of the common nomenclature of control theory emphasizes the underlying mathematical

  15. Performance Improvement of Servo Machine Low Speed Operation Using RBFN Disturbance Observer

    DEFF Research Database (Denmark)

    Lee, Kyo-Beum; Blaabjerg, Frede

    2004-01-01

    A new scheme to estimate the moment of inertia in the servo motor drive system in very low speed is proposed in this paper. The typical speed estimation scheme in most servo system for low speed operation is sensitive to the variation of machine parameters, especially the moment of inertia....... To estimate the motor inertia value, the observer using the Radial Basis Function Networks (RBFN) is applied. The effectiveness of the proposed inertia estimation method is verified by experiments. It is concluded that the speed control performance in the low speed region is improved with the proposed...

  16. 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

  17. Machine Translation Using Constraint-Based Synchronous Grammar

    Institute of Scientific and Technical Information of China (English)

    WONG Fai; DONG Mingchui; HU Dongcheng

    2006-01-01

    A synchronous grammar based on the formalism of context-free grammar was developed by generalizing the first component of production that models the source text. Unlike other synchronous grammars,the grammar allows multiple target productions to be associated to a single production rule which can be used to guide a parser to infer different possible translational equivalences for a recognized input string according to the feature constraints of symbols in the pattern. An extended generalized LR algorithm was adapted to the parsing of the proposed formalism to analyze the syntactic structure of a language. The grammar was used as the basis for building a machine translation system for Portuguese to Chinese translation. The empirical results show that the grammar is more expressive when modeling the translational equivalences of parallel texts for machine translation and grammar rewriting applications.

  18. Machine learning based Intelligent cognitive network using fog computing

    Science.gov (United States)

    Lu, Jingyang; Li, Lun; Chen, Genshe; Shen, Dan; Pham, Khanh; Blasch, Erik

    2017-05-01

    In this paper, a Cognitive Radio Network (CRN) based on artificial intelligence is proposed to distribute the limited radio spectrum resources more efficiently. The CRN framework can analyze the time-sensitive signal data close to the signal source using fog computing with different types of machine learning techniques. Depending on the computational capabilities of the fog nodes, different features and machine learning techniques are chosen to optimize spectrum allocation. Also, the computing nodes send the periodic signal summary which is much smaller than the original signal to the cloud so that the overall system spectrum source allocation strategies are dynamically updated. Applying fog computing, the system is more adaptive to the local environment and robust to spectrum changes. As most of the signal data is processed at the fog level, it further strengthens the system security by reducing the communication burden of the communications network.

  19. Yarn Properties Prediction Based on Machine Learning Method

    Institute of Scientific and Technical Information of China (English)

    YANG Jian-guo; L(U) Zhi-jun; LI Bei-zhi

    2007-01-01

    Although many works have been done to constructprediction models on yarn processing quality, the relationbetween spinning variables and yam properties has not beenestablished conclusively so far. Support vector machines(SVMs), based on statistical learning theory, are gainingapplications in the areas of machine learning and patternrecognition because of the high accuracy and goodgeneralization capability. This study briefly introduces theSVM regression algorithms, and presents the SVM basedsystem architecture for predicting yam properties. Model.selection which amounts to search in hyper-parameter spaceis performed for study of suitable parameters with grid-research method. Experimental results have been comparedwith those of artificial neural network(ANN) models. Theinvestigation indicates that in the small data sets and real-life production, SVM models are capable of remaining thestability of predictive accuracy, and more suitable for noisyand dynamic spinning process.

  20. Extending the features of RBMK refuelling machine simulator with a training tool based on virtual reality

    Energy Technology Data Exchange (ETDEWEB)

    Khoudiakov, M.; Slonimsky, V.; Mitrofanov, S. (and others)

    2004-07-01

    The paper describes a continuation of efforts of an international Russian - Norwegian joint team to improve operational safety during the refuelling process of an RBMK-type reactor by implementing a training simulator based on an innovative Virtual Reality (VR) approach. During the preceding 1st stage of the project a display-based simulator was extended with VR models of the real Refuelling Machine (RM) and its environment in order to improve both the learning process and operation's effectiveness. The simulator's challenge is to support the performance (operational activity) of RM operational staff firstly by helping them to develop basic knowledge and skills as well as to keep skilled staff in close touch with the complex machinery of the Refuelling Machine. During the 2nd stage of the joint project the functional scope of the VR-simulator was greatly enhanced - firstly, by connecting to the RBMK-unit full-scope simulator, and, secondly, by including a training program and simulator model upgrade. The present 3rd stage of the Project is primarily oriented towards the improvement of the training process for maintenance and operational personnel by means of a development of the Training Support Methodology and Courses (TSMC) to be based on Virtual Reality and enlarged functionality of 3D and process modelling. The TMSC development is based on Russian and International Regulatory Bodies requirements and recommendations. Design, development and creation of a specialised VR-based Training System for RM Maintenance Personnel are very important for the Russian RBMK plants. The main goal is to create a powerful, autonomous VR-based simulator for training technical maintenance personnel on the Refuelling Machine. VR based training is expected to improve the effect of training compared to the current training based on traditional methods using printed documentation. The LNPP management and the Regulatory Bodies supported this goal. The VR-based Training System

  1. The Research of CNC Machining Cutter Choice Based on CAXA

    Institute of Scientific and Technical Information of China (English)

    RUAN Xiao-guang; YUAN Si-cong; CAI An-jiang; ZHANG Dang-fei

    2011-01-01

    The article introduces the unique characteristics of CNC machining center cutter compared to traditional cutters, analyzes the choice of CNC machining cutter and factors of choice. Meanwhile, proved by the examples with manufacture software CAXA2004, the correct choice of CNC machining center cutter can give full play to the advantages of CNC machining and improve the economic efficiency and production levels of enterprises.

  2. Machine Learning Based Statistical Prediction Model for Improving Performance of Live Virtual Machine Migration

    Directory of Open Access Journals (Sweden)

    Minal Patel

    2016-01-01

    Full Text Available Service can be delivered anywhere and anytime in cloud computing using virtualization. The main issue to handle virtualized resources is to balance ongoing workloads. The migration of virtual machines has two major techniques: (i reducing dirty pages using CPU scheduling and (ii compressing memory pages. The available techniques for live migration are not able to predict dirty pages in advance. In the proposed framework, time series based prediction techniques are developed using historical analysis of past data. The time series is generated with transferring of memory pages iteratively. Here, two different regression based models of time series are proposed. The first model is developed using statistical probability based regression model and it is based on ARIMA (autoregressive integrated moving average model. The second one is developed using statistical learning based regression model and it uses SVR (support vector regression model. These models are tested on real data set of Xen to compute downtime, total number of pages transferred, and total migration time. The ARIMA model is able to predict dirty pages with 91.74% accuracy and the SVR model is able to predict dirty pages with 94.61% accuracy that is higher than ARIMA.

  3. 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.

  4. FARE device operational characteristics of remote controlled fuelling machine at Wolsong NPP

    Energy Technology Data Exchange (ETDEWEB)

    Namgung, I. [Korea Power Engineering Co., Taejon (Korea, Republic of); Kim, Y. B.; Lee, S. K. [Korea Electric Power Research Institute, Taejon (Korea, Republic of)

    2002-10-01

    There are 4 CANDU6 type reactors operating at Wolsong site. For fuelling operation of certain fuel channels (with flow less than 21.5 kg/s) a FARE (flow Assist Ram Extension) device is used. During the refuelling operation, two remote controlled F/Ms (Fuelling Machines) are attached to a designated fuel channel and carry out refuelling job. The upstream F/M inserts new fuel bundles into the fuel channel while the downstream F/M discharges spent fuel bundles. In order to assist fuelling operation of channels that has lower coolant flow rate, the FARE device is used instead of F/M C-ram to push the fuel bundle string. The FARE device is essentially a flow restricting element that produces enough drag force to push the fuel bundle string toward downstream F/M. Channels that require the use of FARE device for refuelling are located along the outside perimeter of reactor. This paper presents the FARE device design feature, steady state hydraulic and operational characteristics and behavior of the device when coupled with fuel bundle string during fuelling operation. The study showed that the steady state performance of Fare device meets the design objective that was confirmed by downstream F/M C-ram force to be positive.

  5. An Approach to Realizing Process Control for Underground Mining Operations of Mobile Machines.

    Directory of Open Access Journals (Sweden)

    Zhen Song

    Full Text Available The excavation and production in underground mines are complicated processes which consist of many different operations. The process of underground mining is considerably constrained by the geometry and geology of the mine. The various mining operations are normally performed in series at each working face. The delay of a single operation will lead to a domino effect, thus delay the starting time for the next process and the completion time of the entire process. This paper presents a new approach to the process control for underground mining operations, e.g. drilling, bolting, mucking. This approach can estimate the working time and its probability for each operation more efficiently and objectively by improving the existing PERT (Program Evaluation and Review Technique and CPM (Critical Path Method. If the delay of the critical operation (which is on a critical path inevitably affects the productivity of mined ore, the approach can rapidly assign mucking machines new jobs to increase this amount at a maximum level by using a new mucking algorithm under external constraints.

  6. Electromagnetic power absorption and temperature changes due to brain machine interface operation.

    Science.gov (United States)

    Ibrahim, Tamer S; Abraham, Doney; Rennaker, Robert L

    2007-05-01

    To fully understand neural function, chronic neural recordings must be made simultaneously from 10s or 100s of neurons. To accomplish this goal, several groups are developing brain machine interfaces. For these devices to be viable for chronic human use, it is likely that they will need to be operated and powered externally via a radiofrequency (RF) source. However, RF exposure can result in tissue heating and is regulated by the FDA/FCC. This paper provides an initial estimate of the amount of tissue heating and specific absorption rate (SAR) associated with the operation of a brain-machine interface (BMI). The operation of a brain machine interface was evaluated in an 18-tissue anatomically detailed human head mesh using simulations of electromagnetics and bio-heat phenomena. The simulations were conducted with a single chip, as well as with eight chips, placed on the surface of the human brain and each powered at four frequencies (13.6 MHz, 1.0 GHz, 2.4 GHz, and 5.8 GHz). The simulated chips consist of a wire antenna on a silicon chip covered by a Teflon dura patch. SAR values were calculated using the finite-difference time-domain method and used to predict peak temperature changes caused by electromagnetic absorption in the head using two-dimensional bio-heat equation. Results due to SAR alone show increased heating at higher frequencies, with a peak temperature change at 5.8 GHz of approximately 0.018 degrees C in the single-chip configuration and 0.06 degrees C in the eight-chip configuration with 10 mW of power absorption (in the human head) per chip. In addition, temperature elevations due to power dissipation in the chip(s) were studied. Results show that for the neural tissue, maximum temperature rises of 3.34 degrees C in the single-chip configuration and 7.72 degrees C in the eight-chip configuration were observed for 10 mW dissipation in each chip. Finally, the maximum power dissipation allowable in each chip before a 1.0 degrees C temperature

  7. Professional risk of developing diseases of the peripheral nervous system in tractor drivers – machine operators of agricultural production

    Directory of Open Access Journals (Sweden)

    G.A. Bezrukova

    2015-09-01

    Full Text Available Based on the results of the hygienic assessment of working conditions in the domestic agricultural machinery of old and new models when performing the main types of seasonal agricultural work during the annual production cycle and analysis of accumulated occupational diseases’ nosology structure in agricultural workers of the Saratov region over the period from 2004 to 2014, the estimation of professional risk diseases of the peripheral nervous system in tractor drivers – machine operators of agricultural production is given. Professional risk assessment carried out under the procedure set forth in P2.2.1766-03 has shown that the category of a priori risk to their health during an annual production cycle ranged from high to very high (unbearable. It was revealed that the most important factors shaping the harmful working conditions when working on agricultural machinery that can act as a trigger in the formation of vertebral diseases of the peripheral nervous system, are general and local vibration, adverse micro-climatic conditions, long uncomfortable static working posture and physical stress. The risk of diseases in the peripheral uneven system in machine operators of agriculture was attributed to the high risk category with an index of professional diseases (IPD equal to 0,5 %.

  8. Kernel-based machine learning techniques for infrasound signal classification

    Science.gov (United States)

    Tuma, Matthias; Igel, Christian; Mialle, Pierrick

    2014-05-01

    Infrasound monitoring is one of four remote sensing technologies continuously employed by the CTBTO Preparatory Commission. The CTBTO's infrasound network is designed to monitor the Earth for potential evidence of atmospheric or shallow underground nuclear explosions. Upon completion, it will comprise 60 infrasound array stations distributed around the globe, of which 47 were certified in January 2014. Three stages can be identified in CTBTO infrasound data processing: automated processing at the level of single array stations, automated processing at the level of the overall global network, and interactive review by human analysts. At station level, the cross correlation-based PMCC algorithm is used for initial detection of coherent wavefronts. It produces estimates for trace velocity and azimuth of incoming wavefronts, as well as other descriptive features characterizing a signal. Detected arrivals are then categorized into potentially treaty-relevant versus noise-type signals by a rule-based expert system. This corresponds to a binary classification task at the level of station processing. In addition, incoming signals may be grouped according to their travel path in the atmosphere. The present work investigates automatic classification of infrasound arrivals by kernel-based pattern recognition methods. It aims to explore the potential of state-of-the-art machine learning methods vis-a-vis the current rule-based and task-tailored expert system. To this purpose, we first address the compilation of a representative, labeled reference benchmark dataset as a prerequisite for both classifier training and evaluation. Data representation is based on features extracted by the CTBTO's PMCC algorithm. As classifiers, we employ support vector machines (SVMs) in a supervised learning setting. Different SVM kernel functions are used and adapted through different hyperparameter optimization routines. The resulting performance is compared to several baseline classifiers. All

  9. An alternative hybrid evolutionary technique focused on allocating machines and sequencing operations

    Directory of Open Access Journals (Sweden)

    Mariano Frutos

    2016-09-01

    Full Text Available We present here a hybrid algorithm for the Flexible Job-Shop Scheduling Problem (FJSSP. This problem involves the optimal use of resources in a flexible production environment in which each operation can be carried out by more than a single machine. Our algorithm allocates, in a first step, the machines to operations and in a second stage it sequences them by integrating a Multi-Objective Evolutionary Algorithm (MOEA and a path-dependent search algorithm (Multi-Objective Simulated Annealing, which is enacted at the genetic phase of the procedure. The joint interaction of those two components yields a very efficient procedure for solving the FJSSP. An important step in the development of the algorithm was the selection of the right MOEA. Candidates were tested on problems of low, medium and high complexity. Further analyses showed the relevance of the search algorithm in the hybrid structure. Finally, comparisons with other algorithms in the literature indicate that the performance of our alternative is good.

  10. Modulated Tool-Path Chip Breaking For Depleted Uranium Machining Operations

    Energy Technology Data Exchange (ETDEWEB)

    Barkman, W. E.; Babelay Jr., E. F.; Smith, K. S.; Assaid T. S.; McFarland, J. T.; Tursky, D. A.

    2010-04-15

    Turning operations involving depleted uranium frequently generate long, stringy chips that present a hazard to both the machinist and the machine tool. While a variety of chip-breaking techniques are available, they generally depend on a mechanism that increases the bending of the chip or the introduction of a one dimensional vibration that produces an interrupted cutting pattern. Unfortunately, neither of these approaches is particularly effective when making a 'light depth-of-cut' on a contoured workpiece. The historical solution to this problem has been for the machinist to use long-handled tweezers to 'pull the chip' and try to keep it submerged in the chip pan; however, this approach is not practical for all machining operations. This paper discusses a research project involving the Y-12 National Security Complex and the University of North Carolina at Charlotte in which unique, oscillatory part programs are used to continuously create an interrupted cut that generates pre-defined, user-selectable chip lengths.

  11. Analysis of doubly-fed induction machine operating at motoring mode subjected to voltage sag

    Directory of Open Access Journals (Sweden)

    Navneet Kumar

    2016-09-01

    Full Text Available Variable Speed (VS Pumped Storage Plants (PSP equipped with large asynchronous (Doubly-Fed Induction machines are emerging now in hydropower applications. Motoring mode of operation of Doubly-Fed Induction Machine (DFIM is essential and techno-economical in this application due to: (1 its uniqueness in active power controllability, (2 bulk power handing capability with less rated power converters in rotor circuit, and (3 integrating Renewable Energy Sources (RES. This paper investigates the performance of two DFIMs at different power ratings (2.2 kW and 2 MW under voltage sag with different attribute. The test results are analyzed in terms of the peaks in torque, speed, power taken and transient currents in rotor and stator circuits. During sag, stable region for DFIM operation along with speed and stator side reactive power input control is also illustrated. The negative effects of voltage sag are briefly discussed. MATLAB simulation is validated with experimentation. The various observations during simulation and experimental analysis are also supported by the theoretical explanations.

  12. Comparison of Multiobjective Evolutionary Algorithms for Operations Scheduling under Machine Availability Constraints

    Directory of Open Access Journals (Sweden)

    M. Frutos

    2013-01-01

    Full Text Available Many of the problems that arise in production systems can be handled with multiobjective techniques. One of those problems is that of scheduling operations subject to constraints on the availability of machines and buffer capacity. In this paper we analyze different Evolutionary multiobjective Algorithms (MOEAs for this kind of problems. We consider an experimental framework in which we schedule production operations for four real world Job-Shop contexts using three algorithms, NSGAII, SPEA2, and IBEA. Using two performance indexes, Hypervolume and R2, we found that SPEA2 and IBEA are the most efficient for the tasks at hand. On the other hand IBEA seems to be a better choice of tool since it yields more solutions in the approximate Pareto frontier.

  13. Considerations for NSLS-II Synchrotron Radiation Protection When Operating Damping Wigglers at Low Machine Energy

    Energy Technology Data Exchange (ETDEWEB)

    Seletskiy, S. [Brookhaven National Lab. (BNL), Upton, NY (United States). Photon Sciences Dept.; Podobedov, B. [Brookhaven National Lab. (BNL), Upton, NY (United States). Photon Sciences Dept.

    2015-12-30

    The NSLS-II storage ring vacuum chamber, including frontends (FE) and beamlines (BL), is protected from possible damage from synchrotron radiation (SR) emitted from insertion devices (IDs) by a dedicated active interlock system (AIS). The system monitors electron beam position and angle and triggers a beam dump if the beam orbit is outside of the active interlock envelope (AIE). The AIE was calculated under the assumptions of 3 GeV beam energy and ID gaps set to their minimum operating values (i.e. “fully closed”). Recently it was proposed to perform machine studies that would ramp the stored beam energy significantly below the nominal operational value of 3 GeV. These studies may potentially include the use of NSLS-II damping wigglers (DWs) for electron beam emittance reduction and control.

  14. 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.

  15. JACOS: AI-based simulation system for man-machine system behavior in NPP

    Energy Technology Data Exchange (ETDEWEB)

    Yoshida, Kazuo; Yokobayashi, Masao; Tanabe, Fumiya [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment; Kawase, Katsumi [CSK Corp., Tokyo (Japan); Komiya, Akitoshi [Computer Associated Laboratory, Inc., Hitachinaka, Ibaraki (Japan)

    2001-08-01

    A prototype of a computer simulation system named JACOS (JAERI COgnitive Simulation system) has been developed at JAERI (Japan Atomic Energy Research Institute) to simulate the man-machine system behavior in which both the cognitive behavior of a human operator and the plant behavior affect each other. The objectives of this system development is to provide man-machine system analysts with detailed information on the cognitive process of an operator and the plant behavior affected by operator's actions in accidental situations of a nuclear power plant. The simulation system consists of an operator model and a plant model which are coupled dynamically. The operator model simulates an operator's cognitive behavior in accidental situations based on the decision ladder model of Rasmussen, and is implemented using the AI-techniques of the distributed cooperative inference method with the so-called blackboard architecture. Rule-based behavior is simulated using knowledge representation with If-Then type of rules. Knowledge-based behavior is simulated using knowledge representation with MFM (Multilevel Flow Modeling) and qualitative reasoning method. Cognitive characteristics of attentional narrowing, limitation of short-term memory, and knowledge recalling from long-term memory are also taken into account. The plant model of a 3-loop PWR is also developed using a best estimate thermal-hydraulic analysis code RELAP5/MOD2. This report is prepared as User's Manual for JACOS. The first chapter of this report describes both operator and plant models in detail. The second chapter includes instructive descriptions for program installation, building of a knowledge base for operator model, execution of simulation and analysis of simulation results. The examples of simulation with JACOS are shown in the third chapter. (author)

  16. Novel Sensorless Vector Control System of Induction Machine Based on Flux Observer in Field Weakening

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    A speed-sensorless vector control system for induction machines (IMs) is presented. According to the vector control theory of IMs, the rotor flux is estimated based on a flux observer,and the speed is estimated through the method of q-axis rotor flux converging on zero with proportional integral regulator. A 0.75 kW,50 Hz,two-pole induction machine was used in the simulation and experimental verification. The simulation model was constructed in Matlab. A series of tests were performed in the field weakening region, for both no-load and loaded operation. The estimated speed tracks the actual speed well in the based speed region and field weakening region (1 per unit value to 4 per unit value). The small estimation error of residual speed is due to the existence of slip.

  17. A Parallel Decision Model Based on Support Vector Machines and Its Application to Fault Diagnosis

    Institute of Scientific and Technical Information of China (English)

    Yan Weiwu(阎威武); Shao Huihe

    2004-01-01

    Many industrial process systems are becoming more and more complex and are characterized by distributed features. To ensure such a system to operate under working order, distributed parameter values are often inspected from subsystems or different points in order to judge working conditions of the system and make global decisions. In this paper, a parallel decision model based on Support Vector Machine (PDMSVM) is introduced and applied to the distributed fault diagnosis in industrial process. PDMSVM is convenient for information fusion of distributed system and it performs well in fault diagnosis with distributed features. PDMSVM makes decision based on synthetic information of subsystems and takes the advantage of Support Vector Machine. Therefore decisions made by PDMSVM are highly reliable and accurate.

  18. Study and implementation high speed operating of induced magnetization machines; Etude et mise en oeuvre de machines a aimantation induite fonctionnant a haute vitesse

    Energy Technology Data Exchange (ETDEWEB)

    Alhassoun, Y.

    2005-05-15

    Actually, electromechanical machines are characterized by their low cost and reduced maintenance. Therefore, new types of magnetic materials such as soft magnetic composites (SMC), have to be considered not only for multiple applications (small motors for automotive) for cost reduction, but also when considering other special requirements such as high speed drive (aircraft and space applications). Our report of thesis is articulated around four chapters: The first chapter show the various types of magnetic interactions used in the electromagnetic actuators. The second chapter is devoted to the modelling of the induced magnetic machines by analytical resolution of equations of the field in two dimensions. The third chapter presents the four configurations prototypes of switched reluctance machine which mix the exploitation of laminated materials and the soft magnetic powders. The fourth chapter discusses the critical conditions of this machines operating at high speed. We conclude, insisting on the efforts carried out in term of analytical modelling of the induced magnetization machines for their dimensions and exploited in this same structure, the soft magnetic composite materials. The results show the potential of soft magnetic powders when considering in particular the high frequency losses and their ability to favour the heat dissipation in this structure. (author)

  19. Incidence of MSDs and neck and back pain among logging machine operators in the southern U.S.

    Science.gov (United States)

    Lynch, S M; Smidt, M F; Merrill, P D; Sesek, R F

    2014-07-01

    There are limited data about the incidence and prevalence of musculoskeletal disorders (MSDs) among loggers in the southern U.S. despite the risk factors associated with these occupations. Risk factors are both personal (age, body mass index, etc.) and job-related (awkward postures, repetitive hand and foot movements, vibration, etc.). A survey was conducted to estimate the incidence of self-reported pain and diagnosed MSDs and to study the relationship with known risk factors. Respondents were loggers attending training and continuing education classes. Respondents were asked to identify personal attributes, machine use, awkward postures, repetitive movements, and recent incidence of pain and medical diagnoses. All were male with an average age of 44 (range of 19-67) and an average body mass index of 31.3. Most were machine operators (97%) who have worked in the logging industry for an average of 22.9 years. Most machines identified were manufactured within the past ten years (average machine age 6.7 years). For machine operators, 10.5% (16) reported an MSD diagnosis, 74.3% (113) reported at least mild back pain, and 71.7% (109) reported at least mild neck pain over the past year. Further analysis attempted to identify an association between personal attributes, machine use, posture, and pain. Risk factors related to machine use may be biased since most survey respondents had considerable choice or control in working conditions, as they were firm owners and/or supervisors.

  20. Fully digital controlled A.C. servo engraving machine based on DEC4DA

    Science.gov (United States)

    Shu, Zhibing; Chen, Xianfeng; Zhang, Hairong; Huang, Yiqun; Yan, Caizhong

    2005-12-01

    A novel engraving machine (NUT-1A) is presented, in which fully digital controlled AC system based on DEC4DA was used to improve the machining precision and sensitivity. This engraving machine was constructed around AC servo motor with encoder, controlled by a servo motor control card - DEC4DA. As the upper unit of AC servo motor, DEC4DA was a numerical control generator, which received pulses form CPU by ISA bus, and these pulses were amplified and converted to drive AC servo actuator. This novel engraving machine can achieve a higher positioning accuracy of +/-0.01mm and positioning repetition of +/-0.005mm, and its resolution is 0.001mm/0.0001mm. Moreover, because of multi-closed loops were used in the system, the steady and transient performances are more excellent. This system ensures a much quicker current regulation in closed-loop operation, of acceleration and braking in both directions, as well as stable speed characteristics. Amplifier boards are protected against excessive current, excessive temperature and short circuiting of the motor supply cables.

  1. Debris Flow Hazard Assessment Based on Support Vector Machine

    Institute of Scientific and Technical Information of China (English)

    YUAN Lifeng; ZHANG Youshui

    2006-01-01

    Seven factors, including the maximum volume of once flow , occurrence frequency of debris flow , watershed area , main channel length , watershed relative height difference , valley incision density and the length ratio of sediment supplement are chosen as evaluation factors of debris flow hazard degree. Using support vector machine (SVM) theory, we selected 259 basic data of 37 debris flow channels in Yunnan Province as learning samples in this study. We create a debris flow hazard assessment model based on SVM. The model was validated though instance applications and showed encouraging results.

  2. A Machine Learning Based Framework for Adaptive Mobile Learning

    Science.gov (United States)

    Al-Hmouz, Ahmed; Shen, Jun; Yan, Jun

    Advances in wireless technology and handheld devices have created significant interest in mobile learning (m-learning) in recent years. Students nowadays are able to learn anywhere and at any time. Mobile learning environments must also cater for different user preferences and various devices with limited capability, where not all of the information is relevant and critical to each learning environment. To address this issue, this paper presents a framework that depicts the process of adapting learning content to satisfy individual learner characteristics by taking into consideration his/her learning style. We use a machine learning based algorithm for acquiring, representing, storing, reasoning and updating each learner acquired profile.

  3. Estimation of underdetermined mixing matrix based on support vector machine

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    In underdetermined blind source separation (BSS), a novel algorithm based on extended support vector machine(SVM) is proposed to estimate the mixing matrix in this paper, including the number of the active sources. Instead of traditional clustering algorithms, it mainly takes the modulus of observations and the number in each direction of arrival, without any prior knowledge about the sources except for sparsity, and it is not sensitive to the initial values. Simulations are given to illustrate availability and robustness of our algorithm.

  4. Slope Deformation Prediction Based on Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Lei JIA

    2013-07-01

    Full Text Available This paper principally studies the prediction of slope deformation based on Support Vector Machine (SVM. In the prediction process,explore how to reconstruct the phase space. The geological body’s displacement data obtained from chaotic time series are used as SVM’s training samples. Slope displacement caused by multivariable coupling is predicted by means of single variable. Results show that this model is of high fitting accuracy and generalization, and provides reference for deformation prediction in slope engineering.

  5. 基于最小二乘支持向量回归建模方法的人机系统操作员功能状态分析%Analysis on Operator Functional State of Human-Machine System Based on Approach of LSSVM Regressive Model

    Institute of Scientific and Technical Information of China (English)

    秦攀攀; 张建华

    2012-01-01

    Objective To construct an optimum mathematical model to estimate Operator Functional State (OFS) in a human-machine system. Methods This paper adopted Least Squares Support Vector Machine ( LSSVM) approach to construct OFS models with their multiple physiological and performance data. The model parameters were optimized with grid-search and 10-fold cross validation techniques. The modeling results of the LSSVM approach was compared with those of Genetic-Algorithms-based Mamdani ( GA-Mamdani) -type fuzzy modeling method. Results The LSSVM model was shown to be capable of capturing the actual fluctuations of the OFS over time. In general, the overall modeling error (indicated by the RMSE index) of the LSSVM model was accepted and smaller than that of GA-Mamdani model. Conclusion The data-driven LSSVM modeling approach is effective for OFS estimation thanks to its superior generalization performance.%目的 建立具有很强预测能力的数学模型来准确评估人机系统操作员功能状态( Operator Functional States,OFS).方法 基于采集到的一系列操作员电生理信号及性能数据,采用最小二乘支持向量机(Least Squares Support Vector Machine,LSSVM)方法对OFS建模.通过网格搜索和10-折交叉验证方法对模型参数进行优化,并将LSSVM与基于遗传算法的模糊建模方法进行比较.结果 模型基本能反映OFS的实际变化趋势,输出误差在可接受的范围之内且与基于遗传算法的模糊建模方法得到的模型输出误差相比较小.结论 LSSVM方法具有更好的泛化性能,将其用于OFS评估是有效的.

  6. Software Aging Prediction Based on Extreme Learning Machine

    Directory of Open Access Journals (Sweden)

    Xiaozhi Du

    2013-11-01

    Full Text Available In the research on software aging and rejuvenation, one of the most important questions is when to trigger the rejuvenation action. And it is useful to predict the system resource utilization state efficiently for determining the rejuvenation time. In this paper, we propose software aging prediction model based on extreme learning machine (ELM for a real VOD system. First, the data on the parameters of system resources and application server are collected. Then, the data is preprocessed by normalization and principal component analysis (PCA. Then, ELMs are constructed to model the extracted data series of systematic parameters. Finally, we get the predicted data of system resource by computing the sum of the outputs of these ELMs. Experiments show that the proposed software aging prediction method based on wavelet transform and ELM is superior to the artificial neural network (ANN and support vector machine (SVM in the aspects of prediction precision and efficiency. Based on the models employed here, software rejuvenation policies can be triggered by actual measurements.  

  7. Vision-Based People Detection System for Heavy Machine Applications

    Directory of Open Access Journals (Sweden)

    Vincent Fremont

    2016-01-01

    Full Text Available This paper presents a vision-based people detection system for improving safety in heavy machines. We propose a perception system composed of a monocular fisheye camera and a LiDAR. Fisheye cameras have the advantage of a wide field-of-view, but the strong distortions that they create must be handled at the detection stage. Since people detection in fisheye images has not been well studied, we focus on investigating and quantifying the impact that strong radial distortions have on the appearance of people, and we propose approaches for handling this specificity, adapted from state-of-the-art people detection approaches. These adaptive approaches nevertheless have the drawback of high computational cost and complexity. Consequently, we also present a framework for harnessing the LiDAR modality in order to enhance the detection algorithm for different camera positions. A sequential LiDAR-based fusion architecture is used, which addresses directly the problem of reducing false detections and computational cost in an exclusively vision-based system. A heavy machine dataset was built, and different experiments were carried out to evaluate the performance of the system. The results are promising, in terms of both processing speed and performance.

  8. Human machine interface to manually drive rhombic like vehicles in remote handling operations

    Energy Technology Data Exchange (ETDEWEB)

    Lopes, Pedro; Vale, Alberto [Instituto de Plasmas e Fusao Nuclear, Instituto Superior Tecnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa (Portugal); Ventura, Rodrigo [Institute for Systems and Robotics, Instituto Superior Tecnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa (Portugal)

    2015-07-01

    In the thermonuclear experimental reactor ITER, a vehicle named CTS is designed to transport a container with activated components inside the buildings. In nominal operations, the CTS is autonomously guided under supervision. However, in some unexpected situations, such as in rescue and recovery operations, the autonomous mode must be overridden and the CTS must be remotely guided by an operator. The CTS is a rhombic-like vehicle, with two drivable and steerable wheels along its longitudinal axis, providing omni-directional capabilities. The rhombic kinematics correspond to four control variables, which are difficult to manage in manual mode operation. This paper proposes a Human Machine Interface (HMI) to remotely guide the vehicle in manual mode. The proposed solution is implemented using a HMI with an encoder connected to a micro-controller and an analog 2-axis joystick. Experimental results were obtained comparing the proposed solution with other controller devices in different scenarios and using a software platform that simulates the kinematics and dynamics of the vehicle. (authors)

  9. Control of soft machines using actuators operated by a Braille display.

    Science.gov (United States)

    Mosadegh, Bobak; Mazzeo, Aaron D; Shepherd, Robert F; Morin, Stephen A; Gupta, Unmukt; Sani, Idin Zhalehdoust; Lai, David; Takayama, Shuichi; Whitesides, George M

    2014-01-07

    One strategy for actuating soft machines (e.g., tentacles, grippers, and simple walkers) uses pneumatic inflation of networks of small channels in an elastomeric material. Although the management of a few pneumatic inputs and valves to control pressurized gas is straightforward, the fabrication and operation of manifolds containing many (>50) independent valves is an unsolved problem. Complex pneumatic manifolds-often built for a single purpose-are not easily reconfigured to accommodate the specific inputs (i.e., multiplexing of many fluids, ranges of pressures, and changes in flow rates) required by pneumatic systems. This paper describes a pneumatic manifold comprising a computer-controlled Braille display and a micropneumatic device. The Braille display provides a compact array of 64 piezoelectric actuators that actively close and open elastomeric valves of a micropneumatic device to route pressurized gas within the manifold. The positioning and geometries of the valves and channels in the micropneumatic device dictate the functionality of the pneumatic manifold, and the use of multi-layer soft lithography permits the fabrication of networks in a wide range of configurations with many possible functions. Simply exchanging micropneumatic devices of different designs enables rapid reconfiguration of the pneumatic manifold. As a proof of principle, a pneumatic manifold controlled a soft machine containing 32 independent actuators to move a ball above a flat surface.

  10. To investigate the influence of machine operating variables on formulations derived from lactose types in capsule filling: part 2.

    Science.gov (United States)

    Moolchandani, Vikas; Augsburger, Larry L; Gupta, Abhay; Khan, Mansoor A; Langridge, John; Hoag, Stephen W

    2016-01-01

    This study is the second in a series that examines the characterizing and selection of suitable grades of lactose for capsule formulation development. Based upon the previous study, four grades were selected for further study. The effects of drug load and operational variables on formulations derived from these four lactose types were evaluated for physicochemical and mechanical attributes of plugs and their capsules on an instrumented dosing-disc capsule filling machine (H&H KFM/3) using acetaminophen as a model, highly soluble and poorly compressible drug. The results obtained were as follows: (1) flowability reduced upon increasing drug load; (2) powder bed height (PBH) and compression force (CF) had positive significant effect on plug weight (p < 0.05); (3) ejection force was positively and significantly correlated with increasing speed and CF (p < 0.05); (4) AL capsule plugs had the highest plug crushing force which was followed by DCL15; (5) the crushing strength of plugs made from DCL11 increased with increasing acetaminophen concentration; (6) higher CF had a significant negative impact on acetaminophen release at 15 min time point (p < 0.05); (7) at 10% and 40% drug load, formulations containing AL showed the quickest drug release; and (8) increased drug load had a significant negative impact on the release rate at 15 and 45 min time points (p < 0.05). Overall, the results from this study provides information on risk based assessment of filler selection based on drug load and the range of machine operating variables which will help in defining criteria for meeting key quality attributes for capsule formulation development.

  11. A discrete event simulation design for block-based maintenance planning under random machine usage

    NARCIS (Netherlands)

    de Jonge, Bram

    2015-01-01

    Existing research on block-based preventive maintenance planning generally assumes that machines are either used continuously, or that times until failure do not depend on the actual usage of machines. In practice, however, it is often more realistic to assume that machines are not used continuously

  12. Prediction of Surface Roughness Based on Machining Condition and Tool Condition in Boring EN31 Steel

    Directory of Open Access Journals (Sweden)

    P. Mohanaraman

    2016-04-01

    Full Text Available Prediction of Surface roughness plays a vital role in manufacturing process. In manufacturing industries, productions of metallic materials require high surface finish in various components. In the present work, the effect of spindle speed, feed rate, depth of cut and flank wear of the tool on the surface roughness has been studied. Carbide tipped insert was used for boring operation. Experiments were conducted in CNC lathe. The experimental setup was prepared with sixteen levels of cutting parameters and was conducted with two tool tip conditions in dry machining. A piezoelectric accelerometer was used to measure the vibrational signals while machining. The data acquisition card which connected between accelerometer and lab-view software to record the signals. Simple linear and least median regression models were used for prediction of surface roughness. The models were developed by weka analysis software. The best suitable regression model is implemented based on maximum correlation coefficient and the minimum error values.

  13. Vibration reliability analysis for aeroengine compressor blade based on support vector machine response surface method

    Institute of Scientific and Technical Information of China (English)

    GAO Hai-feng; BAI Guang-chen

    2015-01-01

    To ameliorate reliability analysis efficiency for aeroengine components, such as compressor blade, support vector machine response surface method (SRSM) is proposed. SRSM integrates the advantages of support vector machine (SVM) and traditional response surface method (RSM), and utilizes experimental samples to construct a suitable response surface function (RSF) to replace the complicated and abstract finite element model. Moreover, the randomness of material parameters, structural dimension and operating condition are considered during extracting data so that the response surface function is more agreeable to the practical model. The results indicate that based on the same experimental data, SRSM has come closer than RSM reliability to approximating Monte Carlo method (MCM); while SRSM (17.296 s) needs far less running time than MCM (10958 s) and RSM (9840 s). Therefore, under the same simulation conditions, SRSM has the largest analysis efficiency, and can be considered a feasible and valid method to analyze structural reliability.

  14. 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.

  15. Fast Affinity Propagation Clustering based on Machine Learning

    Directory of Open Access Journals (Sweden)

    Shailendra Kumar Shrivastava

    2013-01-01

    Full Text Available Affinity propagation (AP was recently introduced as an un-supervised learning algorithm for exemplar based clustering. In this paper a novel Fast Affinity Propagation clustering Approach based on Machine Learning (FAPML has been proposed. FAPML tries to put data points into clusters based on the history of the data points belonging to clusters in early stages. In FAPML we introduce affinity learning constant and dispersion constant which supervise the clustering process. FAPML also enforces the exemplar consistency and one of 'N constraints. Experiments conducted on many data sets such as Olivetti faces, Mushroom, Documents summarization, Thyroid, Yeast, Wine quality Red, Balance etc. show that FAPML is up to 54 % faster than the original AP with better Net Similarity.

  16. Image-based object recognition in man, monkey and machine.

    Science.gov (United States)

    Tarr, M J; Bülthoff, H H

    1998-07-01

    Theories of visual object recognition must solve the problem of recognizing 3D objects given that perceivers only receive 2D patterns of light on their retinae. Recent findings from human psychophysics, neurophysiology and machine vision provide converging evidence for 'image-based' models in which objects are represented as collections of viewpoint-specific local features. This approach is contrasted with 'structural-description' models in which objects are represented as configurations of 3D volumes or parts. We then review recent behavioral results that address the biological plausibility of both approaches, a well as some of their computational advantages and limitations. We conclude that, although the image-based approach holds great promise, it has potential pitfalls that may be best overcome by including structural information. Thus, the most viable model of object recognition may be one that incorporates the most appealing aspects of both image-based and structural description theories.

  17. A review on conventional and laser assisted machining of Aluminium based metal matrix composites

    OpenAIRE

    2014-01-01

    Aluminum based Metal Matrix Composites (Al-MMC) have been found in different industrial applications due its excellent properties compared to conventional materials. Machining of these composites is difficult due to the hard particle reinforcements. The wider usage of these composites is limited due high machining cost and excessive tool wear with conventional machining. Because of increasing demands in industries, any improvement of conventional machining process or any other deployment of a...

  18. Mechanical properties of white layers formed by different machining processes on nickel-based superalloy

    Science.gov (United States)

    Proust, Edouard

    Nickel-based superalloys are widely used in the aerospace industry in the production of turbine discs and blades because of their good mechanical properties and great corrosion resistance at high temperature. Although very useful, these alloys are hard to machine. Their structure is responsible for rapid wear of cutting tools. Moreover, under certain machining conditions, near-surface regions of the material undergo a phase transformation resulting in the formation of a thin layer called "white etching layer" at the surface of the machined workpiece. Because turbine discs are safety critical components, no defects can be tolerated on the workpiece. Therefore, efforts should be made to ensure that this white etching layer can't influence the operating life of the workpiece and make its operation unsafe. Even if the existence of the white etching layer is well known, its mechanical properties have never been assessed in detail. In this thesis, we present a study of the mechanical (hardness and Young's modulus) and microstructural properties of white etching layers formed at the surface of nickel-based superalloy IN100 turbine discs fabricated by different machining processes. This work aims at evaluating the impact of the machining process and of fatigue on the properties of the white etching layers under study. The originality of this study primarily lies in the employed characterization technique. Using nanoindentation has allowed us to very precisely assess the variations of both the hardness and the Young's modulus along the white etching layers. Also, the use of a sophisticated indentation system has enabled the acquisition of very precise surface images of the samples and therefore to study the microstructure of the white etching layers. This research has demonstrated that the mechanical and microstructural properties of the white etching layers are closely linked to the machining conditions of the material. Therefore, our study will help researchers gain a

  19. A Cooperative Approach to Virtual Machine Based Fault Injection

    Energy Technology Data Exchange (ETDEWEB)

    Naughton III, Thomas J [ORNL; Engelmann, Christian [ORNL; Vallee, Geoffroy R [ORNL; Aderholdt, William Ferrol [ORNL; Scott, Stephen L [Tennessee Technological University (TTU)

    2017-01-01

    Resilience investigations often employ fault injection (FI) tools to study the effects of simulated errors on a target system. It is important to keep the target system under test (SUT) isolated from the controlling environment in order to maintain control of the experiement. Virtual machines (VMs) have been used to aid these investigations due to the strong isolation properties of system-level virtualization. A key challenge in fault injection tools is to gain proper insight and context about the SUT. In VM-based FI tools, this challenge of target con- text is increased due to the separation between host and guest (VM). We discuss an approach to VM-based FI that leverages virtual machine introspection (VMI) methods to gain insight into the target s context running within the VM. The key to this environment is the ability to provide basic information to the FI system that can be used to create a map of the target environment. We describe a proof- of-concept implementation and a demonstration of its use to introduce simulated soft errors into an iterative solver benchmark running in user-space of a guest VM.

  20. Hybrid Support Vector Machines-Based Multi-fault Classification

    Institute of Scientific and Technical Information of China (English)

    GAO Guo-hua; ZHANG Yong-zhong; ZHU Yu; DUAN Guang-huang

    2007-01-01

    Support Vector Machines (SVM) is a new general machine-learning tool based on structural risk minimization principle. This characteristic is very signific ant for the fault diagnostics when the number of fault samples is limited. Considering that SVM theory is originally designed for a two-class classification, a hybrid SVM scheme is proposed for multi-fault classification of rotating machinery in our paper. Two SVM strategies, 1-v-1 (one versus one) and 1-v-r (one versus rest), are respectively adopted at different classification levels. At the parallel classification level, using 1-v-1 strategy, the fault features extracted by various signal analysis methods are transferred into the multiple parallel SVM and the local classification results are obtained. At the serial classification level, these local results values are fused by one serial SVM based on 1-v-r strategy. The hybrid SVM scheme introduced in our paper not only generalizes the performance of signal binary SVMs but improves the precision and reliability of the fault classification results. The actually testing results show the availability suitability of this new method.

  1. Artificial emotional model based on finite state machine

    Institute of Scientific and Technical Information of China (English)

    MENG Qing-mei; WU Wei-guo

    2008-01-01

    According to the basic emotional theory, the artificial emotional model based on the finite state machine(FSM) was presented. In finite state machine model of emotion, the emotional space included the basic emotional space and the multiple emotional spaces. The emotion-switching diagram was defined and transition function was developed using Markov chain and linear interpolation algorithm. The simulation model was built using Stateflow toolbox and Simulink toolbox based on the Matlab platform.And the model included three subsystems: the input one, the emotion one and the behavior one. In the emotional subsystem, the responses of different personalities to the external stimuli were described by defining personal space. This model takes states from an emotional space and updates its state depending on its current state and a state of its input (also a state-emotion). The simulation model realizes the process of switching the emotion from the neutral state to other basic emotions. The simulation result is proved to correspond to emotion-switching law of human beings.

  2. Large A.C. machines theory and investigation methods of currents and losses in stator and rotor meshes including operation with nonlinear loads

    CERN Document Server

    Boguslawsky, Iliya; Hayakawa, Masashi

    2017-01-01

    In this monograph the authors solve the modern scientific problems connected with A.C. motors and generators, based first on the detailed consideration of their physical phenomena. The authors describe the theory and investigative methods they developed and applied in practice, which are considered to be of essential interest for specialists in the field of the electrical engineering industry in European countries, the USA, Argentina, and Brazil, as well as in such countries as India, China, and Iran. This book will be of interest to engineers specialized in the field of the manufacture, operation, and repair of A.C. machines (motors and generators) as well as electric drives; to professors, lecturers, and post-graduate students of technical universities, who are specializing in the field of electric machine engineering and electric drives; and to students who are engaged in the field of high current techniques, electric drives, and electric machine engineering.

  3. Duality-based algorithms for scheduling unrelated parallel machines

    NARCIS (Netherlands)

    S.L. van de Velde (Steef)

    1993-01-01

    textabstractWe consider the following parallel machine scheduling problem. Each of n independent jobs has to be scheduled on one of m unrelated parallel machines. The processing of job J[sub l] on machine Mi requires an uninterrupted period of positive length p[sub lj]. The objective is to find an a

  4. Graph-based formalism for Machine-to-Machine self-managed communications

    OpenAIRE

    2013-01-01

    International audience; Machine-to-Machine communications comprise a large number of intelligent devices sharing information and making cooperative decisions without any human intervention. To support M2M requirements and applications which are in perpetual evolution, many standards are designed, updated and rendered obsolete. Among these, arise from The European Telecommunications Standards Institute (ETSI) a promising standard for M2M communications. The ETSI M2M provides in particular a st...

  5. Motor proteins and molecular motors: how to operate machines at the nanoscale.

    Science.gov (United States)

    Kolomeisky, Anatoly B

    2013-11-20

    Several classes of biological molecules that transform chemical energy into mechanical work are known as motor proteins or molecular motors. These nanometer-sized machines operate in noisy stochastic isothermal environments, strongly supporting fundamental cellular processes such as the transfer of genetic information, transport, organization and functioning. In the past two decades motor proteins have become a subject of intense research efforts, aimed at uncovering the fundamental principles and mechanisms of molecular motor dynamics. In this review, we critically discuss recent progress in experimental and theoretical studies on motor proteins. Our focus is on analyzing fundamental concepts and ideas that have been utilized to explain the non-equilibrium nature and mechanisms of molecular motors.

  6. Alternative Vibration Protecting Systems for Men-Operators of Transport Machines: Modern Level and Prospects

    Science.gov (United States)

    LEE, C.-M.; GOVERDOVSKIY, V. N.

    2002-01-01

    The up-to-date level and a few of the prospects are considered in transport biomechanical vibration protection systems. An experimental estimation of the maximum capabilities of traditional vibration protecting mechanisms (VPMs) used in driver seats is given. Some of the points of synthesis and research for the adaptive VPMs, called mechanisms of elastic links with small stiffness (ELSS-mechanisms) are presented. They contain a novel object of control: non-linear elastic elements with variable torsion “negative” stiffness (TNS). These TNS-elements help to optimize VPMs according to certain criteria and give them invariant structural and functional properties. Some experimental results are presented, and they correspond well with theoretical predictions. An approach is demonstrated for grade of quality of vibration protection of the men-operators of land unsuspended machines and pilots of helicopters.

  7. A Vectorial modeling for the pentaphase Permanent Magnet Synchronous Machine based on multimachine approach

    Directory of Open Access Journals (Sweden)

    Abdelkrim Sellam

    2012-12-01

    Full Text Available The polyphase [1] machines are developed mainly in the field of variable speed drives of high power because increasing the number of phases on the one hand allows to reduce the dimensions of the components in power modulators energy and secondly to improve the operating safety. By a vector approach (vector space, it is possible to find a set of single-phase machine and / or two-phase fictitious equivalent to polyphase synchronous machine.These fictitious machines are coupled electrically and mechanically but decoupled magnetically. This approach leads to introduce the concept of the equivalent machine (multimachine multiconverter system MMS which aims to analyze systems composed of multiple machines (or multiple converters in electric drives. A first classification multimachine multiconverter system follows naturally from MMS formalism. We present an example of a synchronous machine pent phase.

  8. Fabrication of large scale nanostructures based on a modified atomic force microscope nanomechanical machining system.

    Science.gov (United States)

    Hu, Z J; Yan, Y D; Zhao, X S; Gao, D W; Wei, Y Y; Wang, J H

    2011-12-01

    The atomic force microscope (AFM) tip-based nanomechanical machining has been demonstrated to be a powerful tool for fabricating complex 2D∕3D nanostructures. But the machining scale is very small, which holds back this technique severely. How to enlarge the machining scale is always a major concern for the researches. In the present study, a modified AFM tip-based nanomechanical machining system is established through combination of a high precision X-Y stage with the moving range of 100 mm × 100 mm and a commercial AFM in order to enlarge the machining scale. It is found that the tracing property of the AFM system is feasible for large scale machining by controlling the constant normal load. Effects of the machining parameters including the machining direction and the tip geometry on the uniform machined depth with a large scale are evaluated. Consequently, a new tip trace and an increasing load scheme are presented to achieve a uniform machined depth. Finally, a polymer nanoline array with the dimensions of 1 mm × 0.7 mm, the line density of 1000 lines/mm and the average machined depth of 150 nm, and a 20 × 20 polymer square holes array with the scale of 380 μm × 380 μm and the average machined depth of 250 nm are machined successfully. The uniform of the machined depths for all the nanostructures is acceptable. Therefore, it is verified that the AFM tip-based nanomechanical machining method can be used to machine millimeter scale nanostructures.

  9. Insight into mechanics of AFM tip-based nanomachining: bending of cantilevers and machined grooves

    Science.gov (United States)

    Al-Musawi, R. S. J.; Brousseau, E. B.; Geng, Y.; Borodich, F. M.

    2016-09-01

    Atomic force microscope (AFM) tip-based nanomachining is currently the object of intense research investigations. Values of the load applied to the tip at the free end of the AFM cantilever probe used for nanomachining are always large enough to induce plastic deformation on the specimen surface contrary to the small load values used for the conventional contact mode AFM imaging. This study describes an important phenomenon specific for AFM nanomachining in the forward direction: under certain processing conditions, the deformed shape of the cantilever probe may change from a convex to a concave orientation. The phenomenon can principally change the depth and width of grooves machined, e.g. the grooves machined on a single crystal copper specimen may increase by 50% on average following such a change in the deformed shape of the cantilever. It is argued that this phenomenon can take place even when the AFM-based tool is operated in the so-called force-controlled mode. The study involves the refined theoretical analysis of cantilever probe bending, the analysis of experimental signals monitored during the backward and forward AFM tip-based machining and the inspection of the topography of produced grooves.

  10. Insight into mechanics of AFM tip-based nanomachining: bending of cantilevers and machined grooves.

    Science.gov (United States)

    Al-Musawi, R S J; Brousseau, E B; Geng, Y; Borodich, F M

    2016-09-23

    Atomic force microscope (AFM) tip-based nanomachining is currently the object of intense research investigations. Values of the load applied to the tip at the free end of the AFM cantilever probe used for nanomachining are always large enough to induce plastic deformation on the specimen surface contrary to the small load values used for the conventional contact mode AFM imaging. This study describes an important phenomenon specific for AFM nanomachining in the forward direction: under certain processing conditions, the deformed shape of the cantilever probe may change from a convex to a concave orientation. The phenomenon can principally change the depth and width of grooves machined, e.g. the grooves machined on a single crystal copper specimen may increase by 50% on average following such a change in the deformed shape of the cantilever. It is argued that this phenomenon can take place even when the AFM-based tool is operated in the so-called force-controlled mode. The study involves the refined theoretical analysis of cantilever probe bending, the analysis of experimental signals monitored during the backward and forward AFM tip-based machining and the inspection of the topography of produced grooves.

  11. A data-based technique for monitoring of wound rotor induction machines: A simulation study

    Directory of Open Access Journals (Sweden)

    Fouzi Harrou

    2016-09-01

    Full Text Available Detecting faults induction machines is crucial for a safe operation of these machines. The aim of this paper is to present a statistical fault detection methodology for the detection of faults in three-phase wound rotor induction machines (WRIM. The proposed fault detection approach is based on the use of principal components analysis (PCA. However, conventional PCA-based detection indices, such as the T2 and the Q statistics, are not well suited to detect small faults because these indices only use information from the most recent available samples. Detection of small faults is one of the most crucial and challenging tasks in the area of fault detection and diagnosis. In this paper, a new statistical system monitoring strategy is proposed for detecting changes resulting from small shifts in several variables associated with WRIM. The proposed approach combines modeling using PCA modeling with the exponentially weighted moving average (EWMA control scheme. In the proposed approach, EWMA control scheme is applied on the ignored principal components to detect the presence of faults. The performance of the proposed method is compared with those of the traditional PCA-based fault detection indices. The simulation results clearly show the effectiveness of the proposed method over the conventional ones, especially in the presence of faults with small magnitudes.

  12. A data-based technique for monitoring of wound rotor induction machines: A simulation study

    KAUST Repository

    Harrou, Fouzi

    2016-05-09

    Detecting faults induction machines is crucial for a safe operation of these machines. The aim of this paper is to present a statistical fault detection methodology for the detection of faults in three-phase wound rotor induction machines (WRIM). The proposed fault detection approach is based on the use of principal components analysis (PCA). However, conventional PCA-based detection indices, such as the T2T2 and the Q statistics, are not well suited to detect small faults because these indices only use information from the most recent available samples. Detection of small faults is one of the most crucial and challenging tasks in the area of fault detection and diagnosis. In this paper, a new statistical system monitoring strategy is proposed for detecting changes resulting from small shifts in several variables associated with WRIM. The proposed approach combines modeling using PCA modeling with the exponentially weighted moving average (EWMA) control scheme. In the proposed approach, EWMA control scheme is applied on the ignored principal components to detect the presence of faults. The performance of the proposed method is compared with those of the traditional PCA-based fault detection indices. The simulation results clearly show the effectiveness of the proposed method over the conventional ones, especially in the presence of faults with small magnitudes.

  13. Research advances in coupling bionic optimization design method for CNC machine tools based on ergonomics

    Directory of Open Access Journals (Sweden)

    Shihao LIU

    2015-06-01

    Full Text Available Currently, most Chinese CNC machine tools' dynamic and static performances have large gap comparing with the similar foreign products, and the CNC machine tools users' human-centered design demand are ignored, which results in that the domestic CNC machine tools' overall competitiveness is relatively low. In order to solve the above problem, the ergonomics and coupling bionics are adopted to study collaborative optimization design method for CNC machine tools based on the domestic and foreign machine tool design method research achievement. The CNC machine tools' "man-machine-environment" interaction mechanism can be built by combining with ergonomic, and then the CNC ergonomic design criteria is obtained. Taking the coupling bionics as theoretical basis, the biological structures "morphology-structure-function-adaptive growth" multiple coupling mechanism can be studied, and the mechanical performance benefits structure can be extracted, then the CNC machine tools structural coupling bionic design technology is obtained by combining with the similarity principle. Combination of CNC machine tools' ergonomic design criteria and coupling bionic design technology, and considering the CNC machine tool performance's interaction and coupling mechanisms, a new multi-objective optimization design method can be obtained, which is verified through CNC machine tools' prototype experiments. The new optimization design method for CNC machine tools can not only help improve the whole machine's dynamic and static performance, but also has a bright prospect because of the "man-oriented" design concept.

  14. New generation of human machine interfaces for controlling UAV through depth-based gesture recognition

    Science.gov (United States)

    Mantecón, Tomás.; del Blanco, Carlos Roberto; Jaureguizar, Fernando; García, Narciso

    2014-06-01

    New forms of natural interactions between human operators and UAVs (Unmanned Aerial Vehicle) are demanded by the military industry to achieve a better balance of the UAV control and the burden of the human operator. In this work, a human machine interface (HMI) based on a novel gesture recognition system using depth imagery is proposed for the control of UAVs. Hand gesture recognition based on depth imagery is a promising approach for HMIs because it is more intuitive, natural, and non-intrusive than other alternatives using complex controllers. The proposed system is based on a Support Vector Machine (SVM) classifier that uses spatio-temporal depth descriptors as input features. The designed descriptor is based on a variation of the Local Binary Pattern (LBP) technique to efficiently work with depth video sequences. Other major consideration is the especial hand sign language used for the UAV control. A tradeoff between the use of natural hand signs and the minimization of the inter-sign interference has been established. Promising results have been achieved in a depth based database of hand gestures especially developed for the validation of the proposed system.

  15. Numerical investigation of refrigeration machine compressor operation considering single-phase electric motor dynamic characteristics

    Science.gov (United States)

    Baidak, Y.; Smyk, V.

    2017-08-01

    Using as the base the differential equations system which was presented in relative units for generalized electric motor of hermetic refrigeration compressor, mathematical model of the software for dynamic performance calculation of refrigeration machine compressors drive low-power asynchronous motors was developed. Performed on its ground calculations of the basic model of two-phase electric motor drive of hermetic compressor and the proposed newly developed model of the motor with single-phase stator winding, which is an alternative to the industrial motor winding, have confirmed the benefits of the motor with innovative stator winding over the base engine. Given calculations of the dynamic characteristics of compressor drive motor have permitted to determine the value of electromagnetic torque swinging for coordinating compressor and motor mechanical characteristics, and for taking them into consideration in choosing compressor elements construction materials. Developed and used in the process of investigation of refrigeration compressor drive asynchronous single-phase motor mathematical and software can be considered as an element of computer-aided design system for design of the aggregate of refrigeration compression unit refrigerating machine.

  16. RM-structure alignment based statistical machine translation model

    Institute of Scientific and Technical Information of China (English)

    Sun Jiadong; Zhao Tiejun

    2008-01-01

    A novel model based on structure alignments is proposed for statistical machine translation in this paper.Meta-structure and sequence of meta-structure for a parse tree are defined.During the translation process, a parse tree is decomposed to deal with the structure divergence and the alignments can be constructed at different levels of recombination of meta-structure (RM).This method can perform the structure mapping across the sub-tree structure between languages.As a result, we get not only the translation for the target language, but sequence of meta-structure of its parse tree at the same time.Experiments show that the model in the framework of log-linear model has better generative ability and significantly outperforms Pharaoh, a phrase-based system.

  17. Reinforced Angle-based Multicategory Support Vector Machines

    Science.gov (United States)

    Zhang, Chong; Liu, Yufeng; Wang, Junhui; Zhu, Hongtu

    2015-01-01

    The Support Vector Machine (SVM) is a very popular classification tool with many successful applications. It was originally designed for binary problems with desirable theoretical properties. Although there exist various Multicategory SVM (MSVM) extensions in the literature, some challenges remain. In particular, most existing MSVMs make use of k classification functions for a k-class problem, and the corresponding optimization problems are typically handled by existing quadratic programming solvers. In this paper, we propose a new group of MSVMs, namely the Reinforced Angle-based MSVMs (RAMSVMs), using an angle-based prediction rule with k − 1 functions directly. We prove that RAMSVMs can enjoy Fisher consistency. Moreover, we show that the RAMSVM can be implemented using the very efficient coordinate descent algorithm on its dual problem. Numerical experiments demonstrate that our method is highly competitive in terms of computational speed, as well as classification prediction performance. Supplemental materials for the article are available online. PMID:27891045

  18. An Efficient Audio Classification Approach Based on Support Vector Machines

    Directory of Open Access Journals (Sweden)

    Lhoucine Bahatti

    2016-05-01

    Full Text Available In order to achieve an audio classification aimed to identify the composer, the use of adequate and relevant features is important to improve performance especially when the classification algorithm is based on support vector machines. As opposed to conventional approaches that often use timbral features based on a time-frequency representation of the musical signal using constant window, this paper deals with a new audio classification method which improves the features extraction according the Constant Q Transform (CQT approach and includes original audio features related to the musical context in which the notes appear. The enhancement done by this work is also lay on the proposal of an optimal features selection procedure which combines filter and wrapper strategies. Experimental results show the accuracy and efficiency of the adopted approach in the binary classification as well as in the multi-class classification.

  19. Alumina Concentration Detection Based on the Kernel Extreme Learning Machine.

    Science.gov (United States)

    Zhang, Sen; Zhang, Tao; Yin, Yixin; Xiao, Wendong

    2017-09-01

    The concentration of alumina in the electrolyte is of great significance during the production of aluminum. The amount of the alumina concentration may lead to unbalanced material distribution and low production efficiency and affect the stability of the aluminum reduction cell and current efficiency. The existing methods cannot meet the needs for online measurement because industrial aluminum electrolysis has the characteristics of high temperature, strong magnetic field, coupled parameters, and high nonlinearity. Currently, there are no sensors or equipment that can detect the alumina concentration on line. Most companies acquire the alumina concentration from the electrolyte samples which are analyzed through an X-ray fluorescence spectrometer. To solve the problem, the paper proposes a soft sensing model based on a kernel extreme learning machine algorithm that takes the kernel function into the extreme learning machine. K-fold cross validation is used to estimate the generalization error. The proposed soft sensing algorithm can detect alumina concentration by the electrical signals such as voltages and currents of the anode rods. The predicted results show that the proposed approach can give more accurate estimations of alumina concentration with faster learning speed compared with the other methods such as the basic ELM, BP, and SVM.

  20. MACHINING OF NICKEL BASED ALLOYS USING DIFFERENT CEMENTED CARBIDE TOOLS

    Directory of Open Access Journals (Sweden)

    BASIM A. KHIDHIR

    2010-09-01

    Full Text Available This paper presents the results of experimental work in dry turning of nickel based alloys (Haynes – 276 using Deferent tool geometer of cemented carbide tools. The turning tests were conducted at three different cutting speeds (112, 152, 201and 269 m/min while feed rate and depth of cut were kept constant at 0.2 mm/rev and 1.5 mm, respectively. The tool holders used were SCLCR with insert CCMT-12 and CCLNR – M12-4 with insert CNGN-12. The influence of cutting speed, tool inserts type and workpiece material was investigated on the machined surface roughness. The worn parts of the cutting tools were also examined under scanning electron microscope (SEM. The results showed that cutting speed significantly affected the machined surface finish values in related with the tool insert geometry. Insert type CCMT-12 showed better surface finish for cutting speed to 201 m/min, while insert type CNGN-12 surface roughness increased dramatically with increasing of speed to a limit completely damage of insert geometer beyond 152 m/min.

  1. Fuzzy support vector machines based on linear clustering

    Science.gov (United States)

    Xiong, Shengwu; Liu, Hongbing; Niu, Xiaoxiao

    2005-10-01

    A new Fuzzy Support Vector Machines (FSVMs) based on linear clustering is proposed in this paper. Its concept comes from the idea of linear clustering, selecting the data points near to the preformed hyperplane, which is formed on the training set including one positive and one negative training samples respectively. The more important samples near to the preformed hyperplane are selected by linear clustering technique, and the new FSVMs are formed on the more important data set. It integrates the merit of two kinds of FSVMs. The membership functions are defined using the relative distance between the data points and the preformed hyperplane during the training process. The fuzzy membership decision functions of multi-class FSVMs adopt the minimal value of all the decision functions of two-class FSVMs. To demonstrate the superiority of our methods, the benchmark data sets of machines learning databases are selected to verify the proposed FSVMs. The experimental results indicate that the proposed FSVMs can reduce the training data and running time, and its recognition rate is greater than or equal to that of FSVMs through selecting a suitable linear clustering parameter.

  2. A Bayesian least squares support vector machines based framework for fault diagnosis and failure prognosis

    Science.gov (United States)

    Khawaja, Taimoor Saleem

    A high-belief low-overhead Prognostics and Health Management (PHM) system is desired for online real-time monitoring of complex non-linear systems operating in a complex (possibly non-Gaussian) noise environment. This thesis presents a Bayesian Least Squares Support Vector Machine (LS-SVM) based framework for fault diagnosis and failure prognosis in nonlinear non-Gaussian systems. The methodology assumes the availability of real-time process measurements, definition of a set of fault indicators and the existence of empirical knowledge (or historical data) to characterize both nominal and abnormal operating conditions. An efficient yet powerful Least Squares Support Vector Machine (LS-SVM) algorithm, set within a Bayesian Inference framework, not only allows for the development of real-time algorithms for diagnosis and prognosis but also provides a solid theoretical framework to address key concepts related to classification for diagnosis and regression modeling for prognosis. SVM machines are founded on the principle of Structural Risk Minimization (SRM) which tends to find a good trade-off between low empirical risk and small capacity. The key features in SVM are the use of non-linear kernels, the absence of local minima, the sparseness of the solution and the capacity control obtained by optimizing the margin. The Bayesian Inference framework linked with LS-SVMs allows a probabilistic interpretation of the results for diagnosis and prognosis. Additional levels of inference provide the much coveted features of adaptability and tunability of the modeling parameters. The two main modules considered in this research are fault diagnosis and failure prognosis. With the goal of designing an efficient and reliable fault diagnosis scheme, a novel Anomaly Detector is suggested based on the LS-SVM machines. The proposed scheme uses only baseline data to construct a 1-class LS-SVM machine which, when presented with online data is able to distinguish between normal behavior

  3. Comparison of stator-mounted permanent-magnet machines based on a general power equation

    DEFF Research Database (Denmark)

    Chen, Zhe; Hua, Wei; Cheng, Ming

    2009-01-01

    The stator-mounted permanent-magnet (SMPM) machines have some advantages compared with its counterparts, such as simple rotor, short winding terminals, and good thermal dissipation conditions for magnets. In this paper, a general power equation for three types of SMPM machine is introduced first......, and then, power equations considering the specific topologies are derived. Based on these power equations, theoretical comparisons are carried out between various types of the SMPM machines. In all, eight topologies have been presented and benchmarked. It reveals that the flux switching permanent......-magnet (PM) machine owns higher power density than the flux reversal PM machine and the doubly salient PM machine under same outer diameter. The comparison based on the power equation has established a foundation for optimizing the SMPM machines....

  4. Prediction of Backbreak in Open-Pit Blasting Operations Using the Machine Learning Method

    Science.gov (United States)

    Khandelwal, Manoj; Monjezi, M.

    2013-03-01

    Backbreak is an undesirable phenomenon in blasting operations. It can cause instability of mine walls, falling down of machinery, improper fragmentation, reduced efficiency of drilling, etc. The existence of various effective parameters and their unknown relationships are the main reasons for inaccuracy of the empirical models. Presently, the application of new approaches such as artificial intelligence is highly recommended. In this paper, an attempt has been made to predict backbreak in blasting operations of Soungun iron mine, Iran, incorporating rock properties and blast design parameters using the support vector machine (SVM) method. To investigate the suitability of this approach, the predictions by SVM have been compared with multivariate regression analysis (MVRA). The coefficient of determination (CoD) and the mean absolute error (MAE) were taken as performance measures. It was found that the CoD between measured and predicted backbreak was 0.987 and 0.89 by SVM and MVRA, respectively, whereas the MAE was 0.29 and 1.07 by SVM and MVRA, respectively.

  5. Fourier transform based dynamic error modeling method for ultra-precision machine tool

    Science.gov (United States)

    Chen, Guoda; Liang, Yingchun; Ehmann, Kornel F.; Sun, Yazhou; Bai, Qingshun

    2014-08-01

    In some industrial fields, the workpiece surface need to meet not only the demand of surface roughness, but the strict requirement of multi-scale frequency domain errors. Ultra-precision machine tool is the most important carrier for the ultra-precision machining of the parts, whose errors is the key factor to influence the multi-scale frequency domain errors of the machined surface. The volumetric error modeling is the important bridge to link the relationship between the machine error and machined surface error. However, the available error modeling method from the previous research is hard to use to analyze the relationship between the dynamic errors of the machine motion components and multi-scale frequency domain errors of the machined surface, which plays the important reference role in the design and accuracy improvement of the ultra-precision machine tool. In this paper, a fourier transform based dynamic error modeling method is presented, which is also on the theoretical basis of rigid body kinematics and homogeneous transformation matrix. A case study is carried out, which shows the proposed method can successfully realize the identical and regular numerical description of the machine dynamic errors and the volumetric errors. The proposed method has strong potential for the prediction of the frequency domain errors on the machined surface, extracting of the information of multi-scale frequency domain errors, and analysis of the relationship between the machine motion components and frequency domain errors of the machined surface.

  6. BEHAVIOR BASED CREDIT CARD FRAUD DETECTION USING SUPPORT VECTOR MACHINES

    Directory of Open Access Journals (Sweden)

    V. Dheepa

    2012-07-01

    Full Text Available Along with the great increase of internet and e-commerce, the use of credit card is an unavoidable one. Due to the increase of credit card usage, the frauds associated with this have also increased. There are a lot of approaches used to detect the frauds. In this paper, behavior based classification approach using Support Vector Machines are employed and efficient feature extraction method also adopted. If any discrepancies occur in the behaviors transaction pattern then it is predicted as suspicious and taken for further consideration to find the frauds. Generally credit card fraud detection problem suffers from a large amount of data, which is rectified by the proposed method. Achieving finest accuracy, high fraud catching rate and low false alarms are the main tasks of this approach.

  7. Machine learning based global particle indentification algorithms at LHCb experiment

    CERN Multimedia

    Derkach, Denis; Likhomanenko, Tatiana; Rogozhnikov, Aleksei; Ratnikov, Fedor

    2017-01-01

    One of the most important aspects of data processing at LHC experiments is the particle identification (PID) algorithm. In LHCb, several different sub-detector systems provide PID information: the Ring Imaging CHerenkov (RICH) detector, the hadronic and electromagnetic calorimeters, and the muon chambers. To improve charged particle identification, several neural networks including a deep architecture and gradient boosting have been applied to data. These new approaches provide higher identification efficiencies than existing implementations for all charged particle types. It is also necessary to achieve a flat dependency between efficiencies and spectator variables such as particle momentum, in order to reduce systematic uncertainties during later stages of data analysis. For this purpose, "flat” algorithms that guarantee the flatness property for efficiencies have also been developed. This talk presents this new approach based on machine learning and its performance.

  8. Temperature prediction control based on least squares support vector machines

    Institute of Scientific and Technical Information of China (English)

    Bin LIU; Hongye SU; Weihua HUANG; Jian CHU

    2004-01-01

    A prediction control algorithm is presented based on least squares support vector machines (LS-SVM) model for a class of complex systems with strong nonlinearity.The nonlinear off-line model of the controlled plant is built by LS-SVM with radial basis function (RBF) kernel.In the process of system running,the off-line model is linearized at each sampling instant,and the generalized prediction control (GPC) algorithm is employed to implement the prediction control for the controlled plant.The obtained algorithm is applied to a boiler temperature control system with complicated nonlinearity and large time delay.The results of the experiment verify the effectiveness and merit of the algorithm.

  9. METAPHOR: Probability density estimation for machine learning based photometric redshifts

    Science.gov (United States)

    Amaro, V.; Cavuoti, S.; Brescia, M.; Vellucci, C.; Tortora, C.; Longo, G.

    2017-06-01

    We present METAPHOR (Machine-learning Estimation Tool for Accurate PHOtometric Redshifts), a method able to provide a reliable PDF for photometric galaxy redshifts estimated through empirical techniques. METAPHOR is a modular workflow, mainly based on the MLPQNA neural network as internal engine to derive photometric galaxy redshifts, but giving the possibility to easily replace MLPQNA with any other method to predict photo-z's and their PDF. We present here the results about a validation test of the workflow on the galaxies from SDSS-DR9, showing also the universality of the method by replacing MLPQNA with KNN and Random Forest models. The validation test include also a comparison with the PDF's derived from a traditional SED template fitting method (Le Phare).

  10. Machine vision inspection of rice seed based on Hough transform

    Institute of Scientific and Technical Information of China (English)

    成芳; 应义斌

    2004-01-01

    A machine vision system was developed to inspect the quality of rice seeds. Five varieties of Jinyou402, Shanyou10, Zhongyou207, Jiayou and IIyou were evaluated. The images of both sides of rice seed with black background and white background were acquired with the image processing system for identifying external features of rice seeds. Five image sets consisting of 600 original images each were obtained. Then a digital image processing algorithm based on Hough transform was developed to inspect the rice seeds with incompletely closed glumes. The algorithm was implemented with all image sets using a Matlab 6.5 procedure. The results showed that the algorithm achieved an average accuracy of 96% for normal seeds, 92% for seeds with fine fissure and 87% for seeds with incompletely closed glumes. The algorithm was proved to be applicable to different seed varieties and insensitive to the color of the background.

  11. SENSITIVITY ANALYSIS FOR ROLLING PROCESS BASED ON SUPPORT VECTOR MACHINE

    Institute of Scientific and Technical Information of China (English)

    Huang Yanwei; Wu Tihua; Zhao Jingyi; Wang Yiqun

    2005-01-01

    A method for the calculation of the sensitivity factors of the rolling process has been obtained by differentiating the roll force model based on support vector machine. It can eliminate the algebraic loop of the analytical model of the rolling process. The simulations in the first stand of five stand cold tandem rolling mill indicate that the calculation for sensitivities by this proposed method can obtain a good accuracy, and an appropriate adjustment on the control variables determined directly by the sensitivity has an excellent compensation accuracy. Moreover, the roll gap has larger effect on the exit thickness than both front tension and back tension, and it is more efficient to select the roll gap as the controlvariable of the thickness control system in the first stand.

  12. Machine vision inspection of rice seed based on Hough transform

    Institute of Scientific and Technical Information of China (English)

    成芳; 应义斌

    2004-01-01

    A machine vision system was developed to inspect the quality of rice seeds. Five varieties of Jinyou402,Shanyou 10, Zhongyou207, Jiayou and Ilyou were evaluated. The images of both sides of rice seed with black background and white background were acquired with the image processing system for identifying external features of rice seeds. Five image sets consisting of 600 original images each were obtained. Then a digital image processing algorithm based on Hough transform was developed to inspect the rice seeds with incompletely closed glumes. The algorithm was implemented with all image sets using a Matlab 6.5 procedure. The results showed that the algorithm achieved an average accuracy of 96% for normal seeds, 92% for seeds with fine fissure and 87% for seeds with incompletely closed glumes. The algorithm was proved to be applicable to different seed varieties and insensitive to the color of the background.

  13. TYRE DYNAMICS MODELLING OF VEHICLE BASED ON SUPPORT VECTOR MACHINES

    Institute of Scientific and Technical Information of China (English)

    ZHENG Shuibo; TANG Houjun; HAN Zhengzhi; ZHANG Yong

    2006-01-01

    Various methods of tyre modelling are implemented from pure theoretical to empirical or semi-empirical models based on experimental results. A new way of representing tyre data obtained from measurements is presented via support vector machines (SVMs). The feasibility of applying SVMs to steady-state tyre modelling is investigated by comparison with three-layer backpropagation(BP) neural network at pure slip and combined slip. The results indicate SVMs outperform the BP neural network in modelling the tyre characteristics with better generalization performance. The SVMs-tyre is implemented in 8-DOF vehicle model for vehicle dynamics simulation by means of the PAC 2002 Magic Formula as reference. The SVMs-tyre can be a competitive and accurate method to model a tyre for vehicle dynamics simulation.

  14. Explaining Support Vector Machines: A Color Based Nomogram

    Science.gov (United States)

    Van Belle, Vanya; Van Calster, Ben; Van Huffel, Sabine; Suykens, Johan A. K.; Lisboa, Paulo

    2016-01-01

    Problem setting Support vector machines (SVMs) are very popular tools for classification, regression and other problems. Due to the large choice of kernels they can be applied with, a large variety of data can be analysed using these tools. Machine learning thanks its popularity to the good performance of the resulting models. However, interpreting the models is far from obvious, especially when non-linear kernels are used. Hence, the methods are used as black boxes. As a consequence, the use of SVMs is less supported in areas where interpretability is important and where people are held responsible for the decisions made by models. Objective In this work, we investigate whether SVMs using linear, polynomial and RBF kernels can be explained such that interpretations for model-based decisions can be provided. We further indicate when SVMs can be explained and in which situations interpretation of SVMs is (hitherto) not possible. Here, explainability is defined as the ability to produce the final decision based on a sum of contributions which depend on one single or at most two input variables. Results Our experiments on simulated and real-life data show that explainability of an SVM depends on the chosen parameter values (degree of polynomial kernel, width of RBF kernel and regularization constant). When several combinations of parameter values yield the same cross-validation performance, combinations with a lower polynomial degree or a larger kernel width have a higher chance of being explainable. Conclusions This work summarizes SVM classifiers obtained with linear, polynomial and RBF kernels in a single plot. Linear and polynomial kernels up to the second degree are represented exactly. For other kernels an indication of the reliability of the approximation is presented. The complete methodology is available as an R package and two apps and a movie are provided to illustrate the possibilities offered by the method. PMID:27723811

  15. A 128-Channel Extreme Learning Machine-Based Neural Decoder for Brain Machine Interfaces.

    Science.gov (United States)

    Chen, Yi; Yao, Enyi; Basu, Arindam

    2016-06-01

    Currently, state-of-the-art motor intention decoding algorithms in brain-machine interfaces are mostly implemented on a PC and consume significant amount of power. A machine learning coprocessor in 0.35- μm CMOS for the motor intention decoding in the brain-machine interfaces is presented in this paper. Using Extreme Learning Machine algorithm and low-power analog processing, it achieves an energy efficiency of 3.45 pJ/MAC at a classification rate of 50 Hz. The learning in second stage and corresponding digitally stored coefficients are used to increase robustness of the core analog processor. The chip is verified with neural data recorded in monkey finger movements experiment, achieving a decoding accuracy of 99.3% for movement type. The same coprocessor is also used to decode time of movement from asynchronous neural spikes. With time-delayed feature dimension enhancement, the classification accuracy can be increased by 5% with limited number of input channels. Further, a sparsity promoting training scheme enables reduction of number of programmable weights by ≈ 2X.

  16. 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.

  17. An Interactive Web-based Learning System for Assisting Machining Technology Education

    Directory of Open Access Journals (Sweden)

    Min Jou

    2008-05-01

    Full Text Available The key technique of manufacturing methods is machining. The degree of technique of machining directly affects the quality of the product. Therefore, the machining technique is of primary importance in promoting student practice ability during the training process. Currently, practical training is applied in shop floor to discipline student’s practice ability. Much time and cost are used to teach these techniques. Particularly, computerized machines are continuously increasing in use. The development of educating engineers on computerized machines becomes much more difficult than with traditional machines. This is because of the limitation of the extremely expensive cost of teaching. The quality and quantity of teaching cannot always be promoted in this respect. The traditional teaching methods can not respond well to the needs of the future. Therefore, this research aims to the following topics; (1.Propose the teaching strategies for the students to learning machining processing planning through web-based learning system. (2.Establish on-line teaching material for the computer-aided manufacturing courses including CNC coding method, CNC simulation. (3.Develop the virtual machining laboratory to bring the machining practical training to web-based learning system. (4.Integrate multi-media and virtual laboratory in the developed e-learning web-based system to enhance the effectiveness of machining education through web-based system.

  18. Machine intelligence and signal processing

    CERN Document Server

    Vatsa, Mayank; Majumdar, Angshul; Kumar, Ajay

    2016-01-01

    This book comprises chapters on key problems in machine learning and signal processing arenas. The contents of the book are a result of a 2014 Workshop on Machine Intelligence and Signal Processing held at the Indraprastha Institute of Information Technology. Traditionally, signal processing and machine learning were considered to be separate areas of research. However in recent times the two communities are getting closer. In a very abstract fashion, signal processing is the study of operator design. The contributions of signal processing had been to device operators for restoration, compression, etc. Applied Mathematicians were more interested in operator analysis. Nowadays signal processing research is gravitating towards operator learning – instead of designing operators based on heuristics (for example wavelets), the trend is to learn these operators (for example dictionary learning). And thus, the gap between signal processing and machine learning is fast converging. The 2014 Workshop on Machine Intel...

  19. Expected energy-based restricted Boltzmann machine for classification.

    Science.gov (United States)

    Elfwing, S; Uchibe, E; Doya, K

    2015-04-01

    In classification tasks, restricted Boltzmann machines (RBMs) have predominantly been used in the first stage, either as feature extractors or to provide initialization of neural networks. In this study, we propose a discriminative learning approach to provide a self-contained RBM method for classification, inspired by free-energy based function approximation (FE-RBM), originally proposed for reinforcement learning. For classification, the FE-RBM method computes the output for an input vector and a class vector by the negative free energy of an RBM. Learning is achieved by stochastic gradient-descent using a mean-squared error training objective. In an earlier study, we demonstrated that the performance and the robustness of FE-RBM function approximation can be improved by scaling the free energy by a constant that is related to the size of network. In this study, we propose that the learning performance of RBM function approximation can be further improved by computing the output by the negative expected energy (EE-RBM), instead of the negative free energy. To create a deep learning architecture, we stack several RBMs on top of each other. We also connect the class nodes to all hidden layers to try to improve the performance even further. We validate the classification performance of EE-RBM using the MNIST data set and the NORB data set, achieving competitive performance compared with other classifiers such as standard neural networks, deep belief networks, classification RBMs, and support vector machines. The purpose of using the NORB data set is to demonstrate that EE-RBM with binary input nodes can achieve high performance in the continuous input domain. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

  20. 3-D measuring of engine camshaft based on machine vision

    Science.gov (United States)

    Qiu, Jianxin; Tan, Liang; Xu, Xiaodong

    2008-12-01

    The non-touch 3D measuring based on machine vision is introduced into camshaft precise measuring. Currently, because CCD 3-dimensional measuring can't meet requirements for camshaft's measuring precision, it's necessary to improve its measuring precision. In this paper, we put forward a method to improve the measuring method. A Multi-Character Match method based on the Polygonal Non-regular model is advanced with the theory of Corner Extraction and Corner Matching .This method has solved the problem of the matching difficulty and a low precision. In the measuring process, the use of the Coded marked Point method and Self-Character Match method can bring on this problem. The 3D measuring experiment on camshaft, which based on the Multi-Character Match method of the Polygonal Non-regular model, proves that the normal average measuring precision is increased to a new level less than 0.04mm in the point-clouds photo merge. This measuring method can effectively increase the 3D measuring precision of the binocular CCD.

  1. Case-Based Reasoning for Explaining Probabilistic Machine Learning

    Directory of Open Access Journals (Sweden)

    T omas Olsson

    2014-04-01

    Full Text Available This paper describes a generic fram e w ork for e xplaining the prediction of probabilistic machine learning algorithms using cases. The fram e w ork consists of t w o components: a similarity metric between cases th at is defined relat i v e to a probability model and an n ov el case - based approach to justifying the probabilistic prediction by estimating the prediction error using case - based reasoning. As basis for der i ving similarity metrics, we define similarity in terms of the principle of inte r c han g eability that t w o cases are considered similar or identical if t w o probability distri b utions, der i v ed from e xcluding either one or the other case in the case base, are identical. Lastl y , we sh o w the applicability of the propo sed approach by der i ving a metric for linear r e gression, and apply the proposed approach for e xplaining predictions of the ene r gy performance of households

  2. Support Vector Machine Ensemble Based on Genetic Algorithm

    Institute of Scientific and Technical Information of China (English)

    LI Ye; YIN Ru-po; CAI Yun-ze; XU Xiao-ming

    2006-01-01

    Support vector machines (SVMs) have been introduced as effective methods for solving classification problems.However, due to some limitations in practical applications,their generalization performance is sometimes far from the expected level. Therefore, it is meaningful to study SVM ensemble learning. In this paper, a novel genetic algorithm based ensemble learning method, namely Direct Genetic Ensemble (DGE), is proposed. DGE adopts the predictive accuracy of ensemble as the fitness function and searches a good ensemble from the ensemble space. In essence, DGE is also a selective ensemble learning method because the base classifiers of the ensemble are selected according to the solution of genetic algorithm. In comparison with other ensemble learning methods, DGE works on a higher level and is more direct. Different strategies of constructing diverse base classifiers can be utilized in DGE.Experimental results show that SVM ensembles constructed by DGE can achieve better performance than single SVMs,bagged and boosted SVM ensembles. In addition, some valuable conclusions are obtained.

  3. Operator representations in Kramers bases

    DEFF Research Database (Denmark)

    Aucar, G. A.; Jensen, H. J Aa; Oddershede, J.

    1995-01-01

    Using the time-reversal symmetry operations, we introduce the time-reversal adapted Kramers basis operators Xpq± which are the natural expansion set for any relativistic Hermitian or anti-Hermitian one-electron operator and thus replace the spin-adapted basis operators of non-relativistic quantum...... mechanics. Depending on the time-reversal symmetry or Hermiticity of the one-electron operator, either X+ or X-, but never both of them, appear in the expansion, thus causing the symmetry blocking that is important for computational saving in relativistic electronic structure calculations. We determine...

  4. Effect of tube-electrode inner diameter on electrochemical discharge machining of nickel-based superalloy

    Institute of Scientific and Technical Information of China (English)

    Zhang Yan; Xu Zhengyang; Xing Jun; Zhu Di

    2016-01-01

    Nickel-based superalloys are widely employed in modern aircraft engines because of their excellent material characteristics, particularly in the fabrication of film cooling holes. How-ever, the high machining requirement of a large number of film cooling holes can be extremely chal-lenging. The hybrid machining technique of tube electrode high-speed electrochemical discharge drilling (TEHECDD) has been considered as a promising method for the production of film cooling holes. Compared with any single machining process, this hybrid technique requires the removal of more complex machining by-products, including debris produced in the electrical discharge machin-ing process and hydroxide and bubbles generated in the electrochemical machining process. These by-products significantly affect the machining efficiency and surface quality of the machined prod-ucts. In this study, tube electrodes in different inner diameters are designed and fabricated, and the effects of inner diameter on the machining efficiency and surface quality of TEHECDD are inves-tigated. The results show that larger inner diameters could effectively improve the flushing condi-tion and facilitate the removal of machining by-products. Therefore, higher material removal efficiency, surface quality, and electrode wear rate could be achieved by increasing the inner diam-eter of the tube electrode.

  5. MERGING OPTIMALITY CONDITIONS WITH GENETIC ALGORITHM OPERATORS TO SOLVE SINGLE MACHINE TOTAL WEIGHTED TARDINESS PROBLEM

    Institute of Scientific and Technical Information of China (English)

    Ibrahim M.AL-HARKAN

    2005-01-01

    In this paper, a constrained genetic algorithm (CGA) is proposed to solve the single machine total weighted tardiness problem. The proposed CGA incorporates dominance rules for the problem under consideration into the GA operators. This incorporation should enable the proposed CGA to obtain close to optimal solutions with much less deviation and much less computational effort than the conventional GA (UGA). Several experiments were performed to compare the quality of solutions obtained by the three versions of both the CGA and the UGA with the results obtained by a dynamic programming approach. The computational results showed that the CGA was better than the UGA in both quality of solutions obtained and the CPU time needed to obtain the close to optimal solutions.The three versions of the CGA reduced the percentage deviation by 15.6%, 61.95%, and 25% respectively and obtained close to optimal solutions with 59% lower CPU time than what the three versions of the UGA demanded. The CGA performed better than the UGA in terms of quality of solutions and computational effort when the population size and the number of generations are smaller.

  6. Operation of a quantum dot in the finite-state machine mode: Single-electron dynamic memory

    Energy Technology Data Exchange (ETDEWEB)

    Klymenko, M. V. [Department of Chemistry, University of Liège, B4000 Liège (Belgium); Klein, M. [The Fritz Haber Center for Molecular Dynamics and the Institute of Chemistry, The Hebrew University of Jerusalem, Jerusalem 91904 (Israel); Levine, R. D. [The Fritz Haber Center for Molecular Dynamics and the Institute of Chemistry, The Hebrew University of Jerusalem, Jerusalem 91904 (Israel); Crump Institute for Molecular Imaging and Department of Molecular and Medical Pharmacology, David Geffen School of Medicine and Department of Chemistry and Biochemistry, University of California, Los Angeles, California 90095 (United States); Remacle, F., E-mail: fremacle@ulg.ac.be [Department of Chemistry, University of Liège, B4000 Liège (Belgium); The Fritz Haber Center for Molecular Dynamics and the Institute of Chemistry, The Hebrew University of Jerusalem, Jerusalem 91904 (Israel)

    2016-07-14

    A single electron dynamic memory is designed based on the non-equilibrium dynamics of charge states in electrostatically defined metallic quantum dots. Using the orthodox theory for computing the transfer rates and a master equation, we model the dynamical response of devices consisting of a charge sensor coupled to either a single and or a double quantum dot subjected to a pulsed gate voltage. We show that transition rates between charge states in metallic quantum dots are characterized by an asymmetry that can be controlled by the gate voltage. This effect is more pronounced when the switching between charge states corresponds to a Markovian process involving electron transport through a chain of several quantum dots. By simulating the dynamics of electron transport we demonstrate that the quantum box operates as a finite-state machine that can be addressed by choosing suitable shapes and switching rates of the gate pulses. We further show that writing times in the ns range and retention memory times six orders of magnitude longer, in the ms range, can be achieved on the double quantum dot system using experimentally feasible parameters, thereby demonstrating that the device can operate as a dynamic single electron memory.

  7. Operation of a quantum dot in the finite-state machine mode: Single-electron dynamic memory

    Science.gov (United States)

    Klymenko, M. V.; Klein, M.; Levine, R. D.; Remacle, F.

    2016-07-01

    A single electron dynamic memory is designed based on the non-equilibrium dynamics of charge states in electrostatically defined metallic quantum dots. Using the orthodox theory for computing the transfer rates and a master equation, we model the dynamical response of devices consisting of a charge sensor coupled to either a single and or a double quantum dot subjected to a pulsed gate voltage. We show that transition rates between charge states in metallic quantum dots are characterized by an asymmetry that can be controlled by the gate voltage. This effect is more pronounced when the switching between charge states corresponds to a Markovian process involving electron transport through a chain of several quantum dots. By simulating the dynamics of electron transport we demonstrate that the quantum box operates as a finite-state machine that can be addressed by choosing suitable shapes and switching rates of the gate pulses. We further show that writing times in the ns range and retention memory times six orders of magnitude longer, in the ms range, can be achieved on the double quantum dot system using experimentally feasible parameters, thereby demonstrating that the device can operate as a dynamic single electron memory.

  8. Towards a Standard-based Domain-specific Platform to Solve Machine Learning-based Problems

    Directory of Open Access Journals (Sweden)

    Vicente García-Díaz

    2015-12-01

    Full Text Available Machine learning is one of the most important subfields of computer science and can be used to solve a variety of interesting artificial intelligence problems. There are different languages, framework and tools to define the data needed to solve machine learning-based problems. However, there is a great number of very diverse alternatives which makes it difficult the intercommunication, portability and re-usability of the definitions, designs or algorithms that any developer may create. In this paper, we take the first step towards a language and a development environment independent of the underlying technologies, allowing developers to design solutions to solve machine learning-based problems in a simple and fast way, automatically generating code for other technologies. That can be considered a transparent bridge among current technologies. We rely on Model-Driven Engineering approach, focusing on the creation of models to abstract the definition of artifacts from the underlying technologies.

  9. Airline Passenger Profiling Based on Fuzzy Deep Machine Learning.

    Science.gov (United States)

    Zheng, Yu-Jun; Sheng, Wei-Guo; Sun, Xing-Ming; Chen, Sheng-Yong

    2016-09-27

    Passenger profiling plays a vital part of commercial aviation security, but classical methods become very inefficient in handling the rapidly increasing amounts of electronic records. This paper proposes a deep learning approach to passenger profiling. The center of our approach is a Pythagorean fuzzy deep Boltzmann machine (PFDBM), whose parameters are expressed by Pythagorean fuzzy numbers such that each neuron can learn how a feature affects the production of the correct output from both the positive and negative sides. We propose a hybrid algorithm combining a gradient-based method and an evolutionary algorithm for training the PFDBM. Based on the novel learning model, we develop a deep neural network (DNN) for classifying normal passengers and potential attackers, and further develop an integrated DNN for identifying group attackers whose individual features are insufficient to reveal the abnormality. Experiments on data sets from Air China show that our approach provides much higher learning ability and classification accuracy than existing profilers. It is expected that the fuzzy deep learning approach can be adapted for a variety of complex pattern analysis tasks.

  10. 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.

  11. International Workshop on Advanced Dynamics and Model Based Control of Structures and Machines

    CERN Document Server

    Belyaev, Alexander; Krommer, Michael

    2017-01-01

    The papers in this volume present and discuss the frontiers in the mechanics of controlled machines and structures. They are based on papers presented at the International Workshop on Advanced Dynamics and Model Based Control of Structures and Machines held in Vienna in September 2015. The workshop continues a series of international workshops held in Linz (2008) and St. Petersburg (2010).

  12. The Body of Knowledge & Content Framework. Identifying the Important Knowledge Required for Productive Performance of a Plastics Machine Operator. Blow Molding, Extrusion, Injection Molding, Thermoforming.

    Science.gov (United States)

    Society of the Plastics Industry, Inc., Washington, DC.

    Designed to guide training and curriculum development to prepare machine operators for the national certification exam, this publication identifies the important knowledge required for productive performance by a plastics machine operator. Introductory material discusses the rationale for a national standard, uses of the Body of Knowledge,…

  13. Generating Fuzzy Rule-based Systems from Examples Based on Robust Support Vector Machine

    Institute of Scientific and Technical Information of China (English)

    JIA Jiong; ZHANG Hao-ran

    2006-01-01

    This paper firstly proposes a new support vector machine regression (SVR) with a robust loss function, and designs a gradient based algorithm for implementation of the SVR,then uses the SVR to extract fuzzy rules and designs fuzzy rule-based system. Simulations show that fuzzy rule-based system technique based on robust SVR achieves superior performance to the conventional fuzzy inference method, the proposed method provides satisfactory performance with excellent approximation and generalization property than the existing algorithm.

  14. A system framework of inter-enterprise machining quality control based on fractal theory

    Science.gov (United States)

    Zhao, Liping; Qin, Yongtao; Yao, Yiyong; Yan, Peng

    2014-03-01

    In order to meet the quality control requirement of dynamic and complicated product machining processes among enterprises, a system framework of inter-enterprise machining quality control based on fractal was proposed. In this system framework, the fractal-specific characteristic of inter-enterprise machining quality control function was analysed, and the model of inter-enterprise machining quality control was constructed by the nature of fractal structures. Furthermore, the goal-driven strategy of inter-enterprise quality control and the dynamic organisation strategy of inter-enterprise quality improvement were constructed by the characteristic analysis on this model. In addition, the architecture of inter-enterprise machining quality control based on fractal was established by means of Web service. Finally, a case study for application was presented. The result showed that the proposed method was available, and could provide guidance for quality control and support for product reliability in inter-enterprise machining processes.

  15. Influence of Chatter of VMC Arising During End Milling Operation and Cutting Conditions on Quality of Machined Surface

    Directory of Open Access Journals (Sweden)

    A.K.M.N. Amin, M.A. Rizal, and M. Razman

    2012-08-01

    Full Text Available Machine tool chatter is a dynamic instability of the cutting process. Chatter results in poor part surface finish, damaged cutting tool, and an irritating and unacceptable noise. Exten¬sive research has been undertaken to study the mechanisms of chatter formation. Efforts have been also made to prevent the occurrence of chatter vibration. Even though some progress have been made, fundamental studies on the mechanics of metal cutting are necessary to achieve chatter free operation of CNC machine tools to maintain their smooth operating cycle. The same is also true for Vertical Machining Centres (VMC, which operate at high cutting speeds and are capable of offering high metal removal rates. The present work deals with the effect of work materials, cutting conditions and diameter of end mill cutters on the frequency-amplitude characteristics of chatter and on machined surface roughness. Vibration data were recorded using an experimental rig consisting of KISTLER 3-component dynamometer model 9257B, amplifier, scope meters and a PC.  Three different types of vibrations were observed. The first type was a low frequency vibration, associated with the interrupted nature of end mill operation. The second type of vibration was associated with the instability of the chip formation process and the third type was due to chatter. The frequency of the last type remained practically unchanged over a wide range of cutting speed.  It was further observed that chip-tool contact processes had considerable effect on the roughness of the machined surface.Key Words: Chatter, Cutting Conditions, Stable Cutting, Surface Roughness.

  16. Feed Drive Based upon Linear Motor for Ultraprecision Turning Machine

    Institute of Scientific and Technical Information of China (English)

    2003-01-01

    The characteristics of several different linear motors have been investigated, and the feed drive system with linear motor instead of screw-nut mechanism has been built for a submicro ultraprecision turning machine. In the control system for the feed drive system arranged as "T", both P-position and PI-speed control loops are used. The feedback variable is obtained from a double frequecy laser interferometor. Experiments show that the feed drive with linear motor is simple in construction, and that its dynamics is better than others. So the machining accuracy of the workpiece machined has been successfully improved.

  17. Fast Training of Support Vector Machines Using Error-Center-Based Optimization

    Institute of Scientific and Technical Information of China (English)

    L. Meng; Q. H. Wu

    2005-01-01

    This paper presents a new algorithm for Support Vector Machine (SVM) training, which trains a machine based on the cluster centers of errors caused by the current machine. Experiments withvarious training sets show that the computation time of this new algorithm scales almost linear with training set size and thus may be applied to much larger training sets, in comparison to standard quadratic programming (QP) techniques.

  18. Advances in Fully-Automatic and Interactive Phrase-Based Statistical Machine Translation

    OpenAIRE

    Ortiz Martínez, Daniel

    2011-01-01

    This thesis presents different contributions in the fields of fully-automatic statistical machine translation and interactive statistical machine translation. In the field of statistical machine translation there are three problems that are to be addressed, namely, the modelling problem, the training problem and the search problem. In this thesis we present contributions regarding these three problems. Regarding the modelling problem, an alternative derivation of phrase-based s...

  19. Feature Based Machining Process Planning Modeling and Integration for Life Cycle Engineering

    Institute of Scientific and Technical Information of China (English)

    LIU Changyi

    2006-01-01

    Machining process data is the core of computer aided process planning application systems. It is also provides essential content for product life cycle engineering. The character of CAPP that supports product LCE and virtual manufacturing is analyzed. The structure and content of machining process data concerning green manufacturing is also examined. A logic model of Machining Process Data has been built based on an object oriented approach, using UML technology and a physical model of machining process data that utilizes XML technology. To realize the integration of design and process, an approach based on graph-based volume decomposition was apposed. Instead, to solve the problem of generation in the machining process, case-based reasoning and rule-based reasoning have been applied synthetically. Finally, the integration framework and interface that deal with the CAPP integration with CAD, CAM, PDM, and ERP are discussed.

  20. Layout Design of Human-Machine Interaction Interface of Cabin Based on Cognitive Ergonomics and GA-ACA.

    Science.gov (United States)

    Deng, Li; Wang, Guohua; Yu, Suihuai

    2016-01-01

    In order to consider the psychological cognitive characteristics affecting operating comfort and realize the automatic layout design, cognitive ergonomics and GA-ACA (genetic algorithm and ant colony algorithm) were introduced into the layout design of human-machine interaction interface. First, from the perspective of cognitive psychology, according to the information processing process, the cognitive model of human-machine interaction interface was established. Then, the human cognitive characteristics were analyzed, and the layout principles of human-machine interaction interface were summarized as the constraints in layout design. Again, the expression form of fitness function, pheromone, and heuristic information for the layout optimization of cabin was studied. The layout design model of human-machine interaction interface was established based on GA-ACA. At last, a layout design system was developed based on this model. For validation, the human-machine interaction interface layout design of drilling rig control room was taken as an example, and the optimization result showed the feasibility and effectiveness of the proposed method.

  1. Layout Design of Human-Machine Interaction Interface of Cabin Based on Cognitive Ergonomics and GA-ACA

    Directory of Open Access Journals (Sweden)

    Li Deng

    2016-01-01

    Full Text Available In order to consider the psychological cognitive characteristics affecting operating comfort and realize the automatic layout design, cognitive ergonomics and GA-ACA (genetic algorithm and ant colony algorithm were introduced into the layout design of human-machine interaction interface. First, from the perspective of cognitive psychology, according to the information processing process, the cognitive model of human-machine interaction interface was established. Then, the human cognitive characteristics were analyzed, and the layout principles of human-machine interaction interface were summarized as the constraints in layout design. Again, the expression form of fitness function, pheromone, and heuristic information for the layout optimization of cabin was studied. The layout design model of human-machine interaction interface was established based on GA-ACA. At last, a layout design system was developed based on this model. For validation, the human-machine interaction interface layout design of drilling rig control room was taken as an example, and the optimization result showed the feasibility and effectiveness of the proposed method.

  2. Layout Design of Human-Machine Interaction Interface of Cabin Based on Cognitive Ergonomics and GA-ACA

    Science.gov (United States)

    Deng, Li; Wang, Guohua; Yu, Suihuai

    2016-01-01

    In order to consider the psychological cognitive characteristics affecting operating comfort and realize the automatic layout design, cognitive ergonomics and GA-ACA (genetic algorithm and ant colony algorithm) were introduced into the layout design of human-machine interaction interface. First, from the perspective of cognitive psychology, according to the information processing process, the cognitive model of human-machine interaction interface was established. Then, the human cognitive characteristics were analyzed, and the layout principles of human-machine interaction interface were summarized as the constraints in layout design. Again, the expression form of fitness function, pheromone, and heuristic information for the layout optimization of cabin was studied. The layout design model of human-machine interaction interface was established based on GA-ACA. At last, a layout design system was developed based on this model. For validation, the human-machine interaction interface layout design of drilling rig control room was taken as an example, and the optimization result showed the feasibility and effectiveness of the proposed method. PMID:26884745

  3. The systematic development of a machine vision based milking robot.

    NARCIS (Netherlands)

    Gouws, J.

    1993-01-01

    Agriculture involves unique interactions between man, machines, and various elements from nature. Therefore the implementation of advanced technology in agriculture holds different challenges than in other sectors of the economy. This dissertation stems from research into the application of advanced

  4. HYBRID CONTROL OF HYDRAULIC PRESS MACHINE BASED ON ROBUST CONTROL

    Institute of Scientific and Technical Information of China (English)

    FANG Yu; YANG Jian; CHAI Xiaodong

    2008-01-01

    A robust control algorithm is proposed to focus on the non-linearity and variables of the hydraulic press machine with the proportional valve. The proposed robust controller does not need to design stable compensator in advance, which is simple in design and has large scope of uncertainty applications. The feedback gains of the proposed robust controller are small, so it is easily implemented in engineering applications. The theoretical and experimental research on the position and speed control of the hydraulic press machine is carried out. The control requirements of the hydraulic press machine during the working process are met in the position and speed at the same time. Experimental results show that the proposed controller has better robustness subject to load variables and adaptability of parameter variations of the hydraulic press machine with the proportional valve.

  5. Fault Diagnosis of Machine Based on Fuzzy Reliability Theory

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    According to life analysis in reliability theory, certain diagnosis rules can be used to diagnose machines' faults. On this basis, considering the indefiniteness in machine working states, the accurate diagnosis rule was extended to fuzzy diagnosis rule by using basic concepts and methods of fuzzy mathematics. The formulas of fault probability under different conditions were deduced. In the end, an example is given and the results of two methods were compared.

  6. A machine learning-based automatic currency trading system

    OpenAIRE

    Brvar, Anže

    2012-01-01

    The main goal of this thesis was to develop an automated trading system for Forex trading, which would use machine learning methods and their prediction models for deciding about trading actions. A training data set was obtained from exchange rates and values of technical indicators, which describe conditions on currency market. We estimated selected machine learning algorithms and their parameters with validation with sampling. We have prepared a set of automated trading systems with various...

  7. The Acceleration/Deceleration Control Algorithm Based on Trapezoid-Curve Jerk in CNC Machining

    Directory of Open Access Journals (Sweden)

    Guoyong Zhao

    2013-02-01

    Full Text Available In this study, we propose the acceleration/deceleration control algorithm based on trapezoid-curve jerk in CNC machining. In aviation and mould and die industry, it is much significant to achieve high accuracy CNC machining on complex profile parts. The unsmooth Acceleration/Deceleration (ab. Acc/Dec control in feed movement is one of the main reasons to bring about machine tools impact and vibration in practical machining. After analyzing the CNC machine tools dynamic model, an Acc/Dec control algorithm based on trapezoid-curve jerk is put forward in order to avoid step change in jerk curve in the study; Moreover, the motion profile smooth control approach based on continuous jerk is developed in details to decrease machine tools impact according to various kinematics constraint conditions, such as the maximum acceleration, the maximum jerk, the machining program segment displacement, the instruction feedrate and so on; Finally, the developed Acc/Dec approach and the traditional linear Acc/Dec approach are compared in the CNC experimental table. The results reveal that the developed approach can achieve more smooth and flexible motion profile, which is helpful to minish machine tools impact and enhance parts machining surface quality.

  8. Effect of tube-electrode inner diameter on electrochemical discharge machining of nickel-based superalloy

    Directory of Open Access Journals (Sweden)

    Zhang Yan

    2016-08-01

    Full Text Available Nickel-based superalloys are widely employed in modern aircraft engines because of their excellent material characteristics, particularly in the fabrication of film cooling holes. However, the high machining requirement of a large number of film cooling holes can be extremely challenging. The hybrid machining technique of tube electrode high-speed electrochemical discharge drilling (TEHECDD has been considered as a promising method for the production of film cooling holes. Compared with any single machining process, this hybrid technique requires the removal of more complex machining by-products, including debris produced in the electrical discharge machining process and hydroxide and bubbles generated in the electrochemical machining process. These by-products significantly affect the machining efficiency and surface quality of the machined products. In this study, tube electrodes in different inner diameters are designed and fabricated, and the effects of inner diameter on the machining efficiency and surface quality of TEHECDD are investigated. The results show that larger inner diameters could effectively improve the flushing condition and facilitate the removal of machining by-products. Therefore, higher material removal efficiency, surface quality, and electrode wear rate could be achieved by increasing the inner diameter of the tube electrode.

  9. Classification of Regional Ionospheric Disturbances Based on Support Vector Machines

    Science.gov (United States)

    Begüm Terzi, Merve; Arikan, Feza; Arikan, Orhan; Karatay, Secil

    2016-07-01

    Ionosphere is an anisotropic, inhomogeneous, time varying and spatio-temporally dispersive medium whose parameters can be estimated almost always by using indirect measurements. Geomagnetic, gravitational, solar or seismic activities cause variations of ionosphere at various spatial and temporal scales. This complex spatio-temporal variability is challenging to be identified due to extensive scales in period, duration, amplitude and frequency of disturbances. Since geomagnetic and solar indices such as Disturbance storm time (Dst), F10.7 solar flux, Sun Spot Number (SSN), Auroral Electrojet (AE), Kp and W-index provide information about variability on a global scale, identification and classification of regional disturbances poses a challenge. The main aim of this study is to classify the regional effects of global geomagnetic storms and classify them according to their risk levels. For this purpose, Total Electron Content (TEC) estimated from GPS receivers, which is one of the major parameters of ionosphere, will be used to model the regional and local variability that differs from global activity along with solar and geomagnetic indices. In this work, for the automated classification of the regional disturbances, a classification technique based on a robust machine learning technique that have found wide spread use, Support Vector Machine (SVM) is proposed. SVM is a supervised learning model used for classification with associated learning algorithm that analyze the data and recognize patterns. In addition to performing linear classification, SVM can efficiently perform nonlinear classification by embedding data into higher dimensional feature spaces. Performance of the developed classification technique is demonstrated for midlatitude ionosphere over Anatolia using TEC estimates generated from the GPS data provided by Turkish National Permanent GPS Network (TNPGN-Active) for solar maximum year of 2011. As a result of implementing the developed classification

  10. Visual tracking based on extreme learning machine and sparse representation.

    Science.gov (United States)

    Wang, Baoxian; Tang, Linbo; Yang, Jinglin; Zhao, Baojun; Wang, Shuigen

    2015-10-22

    The existing sparse representation-based visual trackers mostly suffer from both being time consuming and having poor robustness problems. To address these issues, a novel tracking method is presented via combining sparse representation and an emerging learning technique, namely extreme learning machine (ELM). Specifically, visual tracking can be divided into two consecutive processes. Firstly, ELM is utilized to find the optimal separate hyperplane between the target observations and background ones. Thus, the trained ELM classification function is able to remove most of the candidate samples related to background contents efficiently, thereby reducing the total computational cost of the following sparse representation. Secondly, to further combine ELM and sparse representation, the resultant confidence values (i.e., probabilities to be a target) of samples on the ELM classification function are used to construct a new manifold learning constraint term of the sparse representation framework, which tends to achieve robuster results. Moreover, the accelerated proximal gradient method is used for deriving the optimal solution (in matrix form) of the constrained sparse tracking model. Additionally, the matrix form solution allows the candidate samples to be calculated in parallel, thereby leading to a higher efficiency. Experiments demonstrate the effectiveness of the proposed tracker.

  11. Prolog-based prototyping software for machine vision

    Science.gov (United States)

    Batchelor, Bruce G.; Hack, Ralf; Jones, Andrew C.

    1996-10-01

    Prolog image processing (PIP) is a multi-media prototyping tool, intended to assist designers of intelligent industrial machine vision systems. This is the latest in a series of prolog-based systems that have been implemented at Cardiff, specifically for this purpose. The software package provides fully integrated facilities for both interactive and programmed image processing, 'smart' documentation, guidance about which lighting/viewing set-up to use, speech/natural language input and speech output. It can also be used to control a range of electro-mechanical devices, such as lamps, cameras, lenses, pneumatic positioning mechanisms, robots, etc., via a low-cost hardware interfacing module. The software runs on a standard computer, with no predecessors in that the image processing is carried out entirely in software. This article concentrates on the design and implementation of the PIP system, and presents programs for two demonstration applications: (a) recognizing a non-picture playing card; (b) recognizing a well laid table place setting.

  12. Machine learning based interatomic potential for amorphous carbon

    Science.gov (United States)

    Deringer, Volker L.; Csányi, Gábor

    2017-03-01

    We introduce a Gaussian approximation potential (GAP) for atomistic simulations of liquid and amorphous elemental carbon. Based on a machine learning representation of the density-functional theory (DFT) potential-energy surface, such interatomic potentials enable materials simulations with close-to DFT accuracy but at much lower computational cost. We first determine the maximum accuracy that any finite-range potential can achieve in carbon structures; then, using a hierarchical set of two-, three-, and many-body structural descriptors, we construct a GAP model that can indeed reach the target accuracy. The potential yields accurate energetic and structural properties over a wide range of densities; it also correctly captures the structure of the liquid phases, at variance with a state-of-the-art empirical potential. Exemplary applications of the GAP model to surfaces of "diamondlike" tetrahedral amorphous carbon (ta -C) are presented, including an estimate of the amorphous material's surface energy and simulations of high-temperature surface reconstructions ("graphitization"). The presented interatomic potential appears to be promising for realistic and accurate simulations of nanoscale amorphous carbon structures.

  13. Estimation of sand liquefaction based on support vector machines

    Institute of Scientific and Technical Information of China (English)

    苏永华; 马宁; 胡检; 杨小礼

    2008-01-01

    The origin and influence factors of sand liquefaction were analyzed, and the relation between liquefaction and its influence factors was founded. A model based on support vector machines (SVM) was established whose input parameters were selected as following influence factors of sand liquefaction: magnitude (M), the value of SPT, effective pressure of superstratum, the content of clay and the average of grain diameter. Sand was divided into two classes: liquefaction and non-liquefaction, and the class label was treated as output parameter of the model. Then the model was used to estimate sand samples, 20 support vectors and 17 borderline support vectors were gotten, then the parameters were optimized, 14 support vectors and 6 borderline support vectors were gotten, and the prediction precision reaches 100%. In order to verify the generalization of the SVM method, two other practical samples’ data from two cities, Tangshan of Hebei province and Sanshui of Guangdong province, were dealt with by another more intricate model for polytomies, which also considered some influence factors of sand liquefaction as the input parameters and divided sand into four liquefaction grades: serious liquefaction, medium liquefaction, slight liquefaction and non-liquefaction as the output parameters. The simulation results show that the latter model has a very high precision, and using SVM model to estimate sand liquefaction is completely feasible.

  14. Visual Tracking Based on Extreme Learning Machine and Sparse Representation

    Directory of Open Access Journals (Sweden)

    Baoxian Wang

    2015-10-01

    Full Text Available The existing sparse representation-based visual trackers mostly suffer from both being time consuming and having poor robustness problems. To address these issues, a novel tracking method is presented via combining sparse representation and an emerging learning technique, namely extreme learning machine (ELM. Specifically, visual tracking can be divided into two consecutive processes. Firstly, ELM is utilized to find the optimal separate hyperplane between the target observations and background ones. Thus, the trained ELM classification function is able to remove most of the candidate samples related to background contents efficiently, thereby reducing the total computational cost of the following sparse representation. Secondly, to further combine ELM and sparse representation, the resultant confidence values (i.e., probabilities to be a target of samples on the ELM classification function are used to construct a new manifold learning constraint term of the sparse representation framework, which tends to achieve robuster results. Moreover, the accelerated proximal gradient method is used for deriving the optimal solution (in matrix form of the constrained sparse tracking model. Additionally, the matrix form solution allows the candidate samples to be calculated in parallel, thereby leading to a higher efficiency. Experiments demonstrate the effectiveness of the proposed tracker.

  15. A Wavelet Kernel-Based Primal Twin Support Vector Machine for Economic Development Prediction

    Directory of Open Access Journals (Sweden)

    Fang Su

    2013-01-01

    Full Text Available Economic development forecasting allows planners to choose the right strategies for the future. This study is to propose economic development prediction method based on the wavelet kernel-based primal twin support vector machine algorithm. As gross domestic product (GDP is an important indicator to measure economic development, economic development prediction means GDP prediction in this study. The wavelet kernel-based primal twin support vector machine algorithm can solve two smaller sized quadratic programming problems instead of solving a large one as in the traditional support vector machine algorithm. Economic development data of Anhui province from 1992 to 2009 are used to study the prediction performance of the wavelet kernel-based primal twin support vector machine algorithm. The comparison of mean error of economic development prediction between wavelet kernel-based primal twin support vector machine and traditional support vector machine models trained by the training samples with the 3–5 dimensional input vectors, respectively, is given in this paper. The testing results show that the economic development prediction accuracy of the wavelet kernel-based primal twin support vector machine model is better than that of traditional support vector machine.

  16. On the operation of machines powered by quantum non-thermal baths

    Science.gov (United States)

    Niedenzu, Wolfgang; Gelbwaser-Klimovsky, David; Kofman, Abraham G.; Kurizki, Gershon

    2016-08-01

    Diverse models of engines energised by quantum-coherent, hence non-thermal, baths allow the engine efficiency to transgress the standard thermodynamic Carnot bound. These transgressions call for an elucidation of the underlying mechanisms. Here we show that non-thermal baths may impart not only heat, but also mechanical work to a machine. The Carnot bound is inapplicable to such a hybrid machine. Intriguingly, it may exhibit dual action, concurrently as engine and refrigerator, with up to 100% efficiency. We conclude that even though a machine powered by a quantum bath may exhibit an unconventional performance, it still abides by the traditional principles of thermodynamics.

  17. Power distribution of a co-axial dual-mechanical-port flux-switching permanent magnet machine for fuel-based extended range electric vehicles

    Directory of Open Access Journals (Sweden)

    Lingkang Zhou

    2017-05-01

    Full Text Available In this paper, power distribution between the inner and outer machines of a co-axial dual-mechanical-port flux-switching permanent magnet (CADMP-FSPM machine is investigated for fuel-based extended range electric vehicle (ER-EV. Firstly, the topology and operation principle of the CADMP-FSPM machine are introduced, which consist of an inner FSPM machine used for high-speed, an outer FSPM machine for low-speed, and a magnetic isolation ring between them. Then, the magnetic field coupling of the inner and outer FSPM machines is analyzed with more attention paid to the optimization of the isolation ring thickness. Thirdly, the power-dimension (PD equations of the inner and outer FSPM machines are derived, respectively, and thereafter, the PD equation of the whole CADMP-FSPM machine can be given. Finally, the PD equations are validated by finite element analysis, which supplies the guidance on the design of this type of machines.

  18. NC flame pipe cutting machine tool based on open architecture CNC system

    Institute of Scientific and Technical Information of China (English)

    Xiaogen NIE; Yanbing LIU

    2009-01-01

    Based on the analysis of the principle and flame movement of a pipe cutting machine tool, a retrofit NC flame pipe cutting machine tool (NFPCM) that can meet the demands of cutting various pipes is proposed. The paper deals with the design and implementation of an open architecture CNC system for the NFPCM, many of whose aspects are similar to milling machines; however, different from their machining processes and control strategies. The paper emphasizes on the NC system structure and the method for directly creating the NC file according to the cutting type and parameters. Further, the paper develops the program and sets up the open and module NC system.

  19. Design of an Adaptive Human-Machine System Based on Dynamical Pattern Recognition of Cognitive Task-Load

    Science.gov (United States)

    Zhang, Jianhua; Yin, Zhong; Wang, Rubin

    2017-01-01

    This paper developed a cognitive task-load (CTL) classification algorithm and allocation strategy to sustain the optimal operator CTL levels over time in safety-critical human-machine integrated systems. An adaptive human-machine system is designed based on a non-linear dynamic CTL classifier, which maps a set of electroencephalogram (EEG) and electrocardiogram (ECG) related features to a few CTL classes. The least-squares support vector machine (LSSVM) is used as dynamic pattern classifier. A series of electrophysiological and performance data acquisition experiments were performed on seven volunteer participants under a simulated process control task environment. The participant-specific dynamic LSSVM model is constructed to classify the instantaneous CTL into five classes at each time instant. The initial feature set, comprising 56 EEG and ECG related features, is reduced to a set of 12 salient features (including 11 EEG-related features) by using the locality preserving projection (LPP) technique. An overall correct classification rate of about 80% is achieved for the 5-class CTL classification problem. Then the predicted CTL is used to adaptively allocate the number of process control tasks between operator and computer-based controller. Simulation results showed that the overall performance of the human-machine system can be improved by using the adaptive automation strategy proposed. PMID:28367110

  20. Combining discrepancy analysis with sensorless signal resampling for condition monitoring of rotating machines under fluctuating operations

    CSIR Research Space (South Africa)

    Heyns, T

    2012-12-01

    Full Text Available for extensive datasets that are representative of different machine fault conditions. The envelope of the filtered signal is referred to as a discrepancy transform, since the discrepancy signal indicates the presence of fault-induced signal distortions...

  1. Redesigned Surface Based Machining Strategy and Method in Peripheral Milling of Thin-walled Parts

    Institute of Scientific and Technical Information of China (English)

    JIA Zhenyuan; GUO Qiang; SUN Yuwen; GUO Dongming

    2010-01-01

    Currently, simultaneously ensuring the machining accuracy and efficiency of thin-walled structures especially high performance parts still remains a challenge. Existing compensating methods are mainly focusing on 3-aixs machining, which sometimes only take one given point as the compensative point at each given cutter location. This paper presents a redesigned surface based machining strategy for peripheral milling of thin-walled parts. Based on an improved cutting force/heat model and finite element method(FEM) simulation environment, a deflection error prediction model, which takes sequence of cutter contact lines as compensation targets, is established. And an iterative algorithm is presented to determine feasible cutter axis positions. The final redesigned surface is subsequently generated by skinning all discrete cutter axis vectors after compensating by using the proposed algorithm. The proposed machining strategy incorporates the thermo-mechanical coupled effect in deflection prediction, and is also validated with flank milling experiment by using five-axis machine tool. At the same time, the deformation error is detected by using three-coordinate measuring machine. Error prediction values and experimental results indicate that they have a good consistency and the proposed approach is able to significantly reduce the dimension error under the same machining conditions compared with conventional methods. The proposed machining strategy has potential in high-efficiency precision machining of thin-walled parts.

  2. Crack identification for rotating machines based on a nonlinear approach

    Science.gov (United States)

    Cavalini, A. A., Jr.; Sanches, L.; Bachschmid, N.; Steffen, V., Jr.

    2016-10-01

    In a previous contribution, a crack identification methodology based on a nonlinear approach was proposed. The technique uses external applied diagnostic forces at certain frequencies attaining combinational resonances, together with a pseudo-random optimization code, known as Differential Evolution, in order to characterize the signatures of the crack in the spectral responses of the flexible rotor. The conditions under which combinational resonances appear were determined by using the method of multiple scales. In real conditions, the breathing phenomenon arises from the stress and strain distribution on the cross-sectional area of the crack. This mechanism behavior follows the static and dynamic loads acting on the rotor. Therefore, the breathing crack can be simulated according to the Mayes' model, in which the crack transition from fully opened to fully closed is described by a cosine function. However, many contributions try to represent the crack behavior by machining a small notch on the shaft instead of the fatigue process. In this paper, the open and breathing crack models are compared regarding their dynamic behavior and the efficiency of the proposed identification technique. The additional flexibility introduced by the crack is calculated by using the linear fracture mechanics theory (LFM). The open crack model is based on LFM and the breathing crack model corresponds to the Mayes' model, which combines LFM with a given breathing mechanism. For illustration purposes, a rotor composed by a horizontal flexible shaft, two rigid discs, and two self-aligning ball bearings is used to compose a finite element model of the system. Then, numerical simulation is performed to determine the dynamic behavior of the rotor. Finally, the results of the inverse problem conveyed show that the methodology is a reliable tool that is able to estimate satisfactorily the location and depth of the crack.

  3. 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

  4. A Brain-Machine Interface Operating with a Real-Time Spiking Neural Network Control Algorithm.

    Science.gov (United States)

    Dethier, Julie; Nuyujukian, Paul; Eliasmith, Chris; Stewart, Terry; Elassaad, Shauki A; Shenoy, Krishna V; Boahen, Kwabena

    2011-01-01

    Motor prostheses aim to restore function to disabled patients. Despite compelling proof of concept systems, barriers to clinical translation remain. One challenge is to develop a low-power, fully-implantable system that dissipates only minimal power so as not to damage tissue. To this end, we implemented a Kalman-filter based decoder via a spiking neural network (SNN) and tested it in brain-machine interface (BMI) experiments with a rhesus monkey. The Kalman filter was trained to predict the arm's velocity and mapped on to the SNN using the Neural Engineering Framework (NEF). A 2,000-neuron embedded Matlab SNN implementation runs in real-time and its closed-loop performance is quite comparable to that of the standard Kalman filter. The success of this closed-loop decoder holds promise for hardware SNN implementations of statistical signal processing algorithms on neuromorphic chips, which may offer power savings necessary to overcome a major obstacle to the successful clinical translation of neural motor prostheses.

  5. Photosystem II and terminal respiratory oxidases: molecular machines operating in opposite directions.

    Science.gov (United States)

    Siletsky, Sergey A; Borisov, Vitaliy B; Mamedov, Mahir D

    2017-03-01

    In the thylakoid membrane of green plants, cyanobacteria and algae, photosystem II (PSII) uses light energy to split water and generate molecular oxygen. In the opposite process of the biochemical transformation of dioxygen, in heterotrophs, the terminal respiratory oxidases (TRO) are at the end of the respiratory chain in mitochondria and in plasma membrane of many aerobic bacteria reducing dioxygen back to water. Despite the different sources of free energy (light or oxidation of the substrates), energy conversion by these enzymes is based on the spatial organization of enzymatic reactions in which the conversion of water to dioxygen (and vice versa) involves the transfer of protons and electrons in opposite directions across the membrane, which is accompanied by generation of proton-motive force. Similar and distinctive features in structure and function of these important energy-converting molecular machines are described. Information about many fascinating parallels between the mechanisms of TRO and PSII could be used in the artificial light-driven water-splitting process and elucidation of energy conversion mechanism in protein pumps.

  6. The Milling Assistant, Case-Based Reasoning, and machining strategy: A report on the development of automated numerical control programming systems at New Mexico State University

    Energy Technology Data Exchange (ETDEWEB)

    Burd, W. [Sandia National Labs., Albuquerque, NM (United States); Culler, D.; Eskridge, T.; Cox, L.; Slater, T. [New Mexico State Univ., Las Cruces, NM (United States)

    1993-08-01

    The Milling Assistant (MA) programming system demonstrates the automated development of tool paths for Numerical Control (NC) machine tools. By integrating a Case-Based Reasoning decision processor with a commercial CAD/CAM software, intelligent tool path files for milled and point-to-point features can be created. The operational system is capable of reducing the time required to program a variety of parts and improving product quality by collecting and utilizing ``best of practice`` machining strategies.

  7. Operator-based metric for nuclear operations automation assessment

    Energy Technology Data Exchange (ETDEWEB)

    Zacharias, G.L.; Miao, A.X.; Kalkan, A. [Charles River Analytics Inc., Cambridge, MA (United States)] [and others

    1995-04-01

    Continuing advances in real-time computational capabilities will support enhanced levels of smart automation and AI-based decision-aiding systems in the nuclear power plant (NPP) control room of the future. To support development of these aids, we describe in this paper a research tool, and more specifically, a quantitative metric, to assess the impact of proposed automation/aiding concepts in a manner that can account for a number of interlinked factors in the control room environment. In particular, we describe a cognitive operator/plant model that serves as a framework for integrating the operator`s information-processing capabilities with his procedural knowledge, to provide insight as to how situations are assessed by the operator, decisions made, procedures executed, and communications conducted. Our focus is on the situation assessment (SA) behavior of the operator, the development of a quantitative metric reflecting overall operator awareness, and the use of this metric in evaluating automation/aiding options. We describe the results of a model-based simulation of a selected emergency scenario, and metric-based evaluation of a range of contemplated NPP control room automation/aiding options. The results demonstrate the feasibility of model-based analysis of contemplated control room enhancements, and highlight the need for empirical validation.

  8. Global detection of live virtual machine migration based on cellular neural networks.

    Science.gov (United States)

    Xie, Kang; Yang, Yixian; Zhang, Ling; Jing, Maohua; Xin, Yang; Li, Zhongxian

    2014-01-01

    In order to meet the demands of operation monitoring of large scale, autoscaling, and heterogeneous virtual resources in the existing cloud computing, a new method of live virtual machine (VM) migration detection algorithm based on the cellular neural networks (CNNs), is presented. Through analyzing the detection process, the parameter relationship of CNN is mapped as an optimization problem, in which improved particle swarm optimization algorithm based on bubble sort is used to solve the problem. Experimental results demonstrate that the proposed method can display the VM migration processing intuitively. Compared with the best fit heuristic algorithm, this approach reduces the processing time, and emerging evidence has indicated that this new approach is affordable to parallelism and analog very large scale integration (VLSI) implementation allowing the VM migration detection to be performed better.

  9. Global Detection of Live Virtual Machine Migration Based on Cellular Neural Networks

    Directory of Open Access Journals (Sweden)

    Kang Xie

    2014-01-01

    Full Text Available In order to meet the demands of operation monitoring of large scale, autoscaling, and heterogeneous virtual resources in the existing cloud computing, a new method of live virtual machine (VM migration detection algorithm based on the cellular neural networks (CNNs, is presented. Through analyzing the detection process, the parameter relationship of CNN is mapped as an optimization problem, in which improved particle swarm optimization algorithm based on bubble sort is used to solve the problem. Experimental results demonstrate that the proposed method can display the VM migration processing intuitively. Compared with the best fit heuristic algorithm, this approach reduces the processing time, and emerging evidence has indicated that this new approach is affordable to parallelism and analog very large scale integration (VLSI implementation allowing the VM migration detection to be performed better.

  10. Online machining error estimation method of numerical control gear grinding machine tool based on data analysis of internal sensors

    Science.gov (United States)

    Zhao, Fei; Zhang, Chi; Yang, Guilin; Chen, Chinyin

    2016-12-01

    This paper presents an online estimation method of cutting error by analyzing of internal sensor readings. The internal sensors of numerical control (NC) machine tool are selected to avoid installation problem. The estimation mathematic model of cutting error was proposed to compute the relative position of cutting point and tool center point (TCP) from internal sensor readings based on cutting theory of gear. In order to verify the effectiveness of the proposed model, it was simulated and experimented in gear generating grinding process. The cutting error of gear was estimated and the factors which induce cutting error were analyzed. The simulation and experiments verify that the proposed approach is an efficient way to estimate the cutting error of work-piece during machining process.

  11. Mechanism of ultrasonic-pulse electrochemical compound machining based on particles

    Institute of Scientific and Technical Information of China (English)

    张成光; 张勇; 张飞虎

    2014-01-01

    The electric double layer with the transmission of particles was presented based on the principle of electrochemistry. In accordance with this theory, the cavitation catalysis removal mechanism of ultrasonic-pulse electrochemical compound machining (UPECM) based on particles was proposed. The removal mechanism was a particular focus and was thus validated by experiments. The principles and experiments of UPECM were introduced, and the removal model of the UPECM based on the principles of UPECM was established. Furthermore, the effects of the material removal rate for the main processing parameters, including the particles size, the ultrasonic vibration amplitude, the pulse voltage and the minimum machining gap between the tool and the workpiece, were also studied through UPECM. The results show that the particles promote ultrasonic-pulse electrochemical compound machining and thus act as the catalyzer of UPECM. The results also indicate that the processing speed, machining accuracy and surface quality can be improved under UPECM compound machining.

  12. A cost prediction model for machine operation in multi-field production systems

    Directory of Open Access Journals (Sweden)

    Alessandro Sopegno

    Full Text Available ABSTRACT Capacity planning in agricultural field operations needs to give consideration to the operational system design which involves the selection and dimensioning of production components, such as machinery and equipment. Capacity planning models currently onstream are generally based on average norm data and not on specific farm data which may vary from year to year. In this paper a model is presented for predicting the cost of in-field and transport operations for multiple-field and multiple-crop production systems. A case study from a real production system is presented in order to demonstrate the model’s functionalities and its sensitivity to parameters known to be somewhat imprecise. It was shown that the proposed model can provide operation cost predictions for complex cropping systems where labor and machinery are shared between the various operations which can be individually formulated for each individual crop. By so doing, the model can be used as a decision support system at the strategic level of management of agricultural production systems and specifically for the mid-term design process of systems in terms of labor/machinery and crop selection conforming to the criterion of profitability.

  13. GNSS-based operational monitoring devices for forest logging operation chains

    Directory of Open Access Journals (Sweden)

    Raimondo Gallo

    2013-09-01

    Full Text Available The first results of a new approach for implementing operational monitoring tool to control the performance of forest mechanisation chains are proposed and discussed. The solution is based on Global Navigation Satellite System (GNSS tools that are the core of a datalogging system that, in combination with a specific inference-engine, is able to analyse process times, work distances, forward speeds, vehicle tracking and number of working cycles in forest operations. As a consequence the operational monitoring control methods could provide an evaluation of the efficiency of the investigated forest operations. The study has monitored the performance of a tower yarder with crane and processor-head, during logging operations. The field surveys consisted on the installation of the GNSS device directly on the forest equipment for monitoring its movements. Simultaneously the field survey considered the integration of the GNSS information with a time study of work elements based on the continuous time methods supported by a time study board. Additionally, where possible, the onboard computer of the forest machine was also used in order to obtain additional information to be integrated to the GNSS data and the time study. All the recorded GNSS data integrated with the work elements study were thus post-processed through GIS analysis. The preliminary overview about the application of this approach on harvesting operations has permitted to assess a good feasibility of the use of GNSS in the relief of operative times in high mechanised forest chains. Results showed an easy and complete identification of the different operative cycles and elementary operations phases, with a maximum difference between the two methodologies of 10.32%. The use of GNSS installed on forest equipment, integrated with the inferenceengine and also with an interface for data communication or data storage, will permit an automatic or semi-automatic operational monitoring, improving

  14. Distributed Control System Design for Portable PC Based CNC Machine

    Directory of Open Access Journals (Sweden)

    Roni Permana Saputra

    2014-07-01

    Full Text Available The demand on automated machining has been increased and emerges improvement research to achieve many goals such as portability, low cost manufacturability, interoperability, and simplicity in machine usage. These improvements are conducted without ignoring the performance analysis and usability evaluation. This research has designed a distributed control system in purpose to control a portable CNC machine. The design consists of main processing unit, secondary processing unit, motor control, and motor driver. A preliminary simulation has been conducted for performance analysis including linear accuracy and circular accuracy. The results achieved in the simulation provide linear accuracy up to 2 μm with total cost for the whole processing unit is up to 5 million IDR.

  15. SPAM CLASSIFICATION BASED ON SUPERVISED LEARNING USING MACHINE LEARNING TECHNIQUES

    Directory of Open Access Journals (Sweden)

    T. Hamsapriya

    2011-12-01

    Full Text Available E-mail is one of the most popular and frequently used ways of communication due to its worldwide accessibility, relatively fast message transfer, and low sending cost. The flaws in the e-mail protocols and the increasing amount of electronic business and financial transactions directly contribute to the increase in e-mail-based threats. Email spam is one of the major problems of the today’s Internet, bringing financial damage to companies and annoying individual users. Spam emails are invading users without their consent and filling their mail boxes. They consume more network capacity as well as time in checking and deleting spam mails. The vast majority of Internet users are outspoken in their disdain for spam, although enough of them respond to commercial offers that spam remains a viable source of income to spammers. While most of the users want to do right think to avoid and get rid of spam, they need clear and simple guidelines on how to behave. In spite of all the measures taken to eliminate spam, they are not yet eradicated. Also when the counter measures are over sensitive, even legitimate emails will be eliminated. Among the approaches developed to stop spam, filtering is the one of the most important technique. Many researches in spam filtering have been centered on the more sophisticated classifier-related issues. In recent days, Machine learning for spam classification is an important research issue. The effectiveness of the proposed work is explores and identifies the use of different learning algorithms for classifying spam messages from e-mail. A comparative analysis among the algorithms has also been presented.

  16. The Modelling Of Basing Holes Machining Of Automatically Replaceable Cubical Units For Reconfigurable Manufacturing Systems With Low-Waste Production

    Science.gov (United States)

    Bobrovskij, N. M.; Levashkin, D. G.; Bobrovskij, I. N.; Melnikov, P. A.; Lukyanov, A. A.

    2017-01-01

    Article is devoted the decision of basing holes machining accuracy problems of automatically replaceable cubical units (carriers) for reconfigurable manufacturing systems with low-waste production (RMS). Results of automatically replaceable units basing holes machining modeling on the basis of the dimensional chains analysis are presented. Influence of machining parameters processing on accuracy spacings on centers between basing apertures is shown. The mathematical model of carriers basing holes machining accuracy is offered.

  17. Hyperspectral sensing data analysis based on quasiconformal mapping-based multiple kernels learning machine

    Science.gov (United States)

    Li, Jun-Bao; Xie, Xiaodan; Zhai, Jia; Pan, Jeng-Shyang

    2017-06-01

    Hyperspectral remote sensing has a strong ability of object information expression, so it provides better support for object classification. Many methods are proposed for the hyperspectral data classification. The spectrum classification is a classical nonlinear problem, and a kernel-based machine is feasible to classify the spectrum data. In the nonlinear kernel-based space, the spectrum data are more discriminative. The kernel functions determine the data distribution in the feature space. In this paper, we propose the quasiconformal multiple kernels-based machine learning for the hyperspectral data classification. In the framework, the structure of hyperspectral data is adaptively adjusted for classification. The multiple kernels extract the multiple features of hyperspectral data for classification. Multiple features-based machine learning exhibits a great potential on the classification of hyperspectral data. Two public datasets, India Pines dataset and Pavia University dataset, are used to test the proposed algorithm. Experimental results demonstrate that the proposed quasiconformal multiple kernels-based hyperspectral data classification method can show competitive performance.

  18. Steering a Tractor by Means of an EMG-Based Human-Machine Interface

    Science.gov (United States)

    Gomez-Gil, Jaime; San-Jose-Gonzalez, Israel; Nicolas-Alonso, Luis Fernando; Alonso-Garcia, Sergio

    2011-01-01

    An electromiographic (EMG)-based human-machine interface (HMI) is a communication pathway between a human and a machine that operates by means of the acquisition and processing of EMG signals. This article explores the use of EMG-based HMIs in the steering of farm tractors. An EPOC, a low-cost human-computer interface (HCI) from the Emotiv Company, was employed. This device, by means of 14 saline sensors, measures and processes EMG and electroencephalographic (EEG) signals from the scalp of the driver. In our tests, the HMI took into account only the detection of four trained muscular events on the driver’s scalp: eyes looking to the right and jaw opened, eyes looking to the right and jaw closed, eyes looking to the left and jaw opened, and eyes looking to the left and jaw closed. The EMG-based HMI guidance was compared with manual guidance and with autonomous GPS guidance. A driver tested these three guidance systems along three different trajectories: a straight line, a step, and a circumference. The accuracy of the EMG-based HMI guidance was lower than the accuracy obtained by manual guidance, which was lower in turn than the accuracy obtained by the autonomous GPS guidance; the computed standard deviations of error to the desired trajectory in the straight line were 16 cm, 9 cm, and 4 cm, respectively. Since the standard deviation between the manual guidance and the EMG-based HMI guidance differed only 7 cm, and this difference is not relevant in agricultural steering, it can be concluded that it is possible to steer a tractor by an EMG-based HMI with almost the same accuracy as with manual steering. PMID:22164006

  19. Scalable Machine Learning Framework for Behavior-Based Access Control

    Science.gov (United States)

    2013-08-01

    Mahout [10] is an open-source project for scalable machine learning. It provide ready implementations for K-Means clustering following a MapReduce ...paradigm, but does not provide MapReduce implementations for SVMs, which are the most expensive models to train in BBAC. Massive Online Analysis

  20. Open Source Powder based Rapid Prototyping Machine for Ceramics

    NARCIS (Netherlands)

    Budding, A.; Vaneker, T.H.J.; Winnubst, A.J.A.

    2013-01-01

    3DP (Three Dimensional Printing) technology is one of the SFF (Solid Freeform Fabrication) technologies which have recently come into the spotlight due to its adaptability to various applications. However, commercial 3DP machines are limited as to the use of building material, without voiding the wa

  1. Using example-based machine translation to translate DVD subtitles

    DEFF Research Database (Denmark)

    Flanagan, Marian

    Audiovisual Translation (AVT), and in particular subtitling, has been recognised as an area that could potentially benefit from the introduction of machine translation (followed by post-editing). In recent years the demands on subtitlers have increased, while the payment to subtitlers and time al...

  2. POWER OPTIMIZATION OF FINITE STATE MACHINE BASED ON GENETIC ALGORITHM

    Institute of Scientific and Technical Information of China (English)

    Xia Yinshui; A.E.A. Almaini; Wu Xunwei

    2003-01-01

    Using state assignment to minimize power dissipation and area for finite state ma-chines is computationally hard. Most of published results show that the reduction of switchingactivity often trades with area penalty. In this paper, a new approach is proposed. Experimentalresults show a significant reduction of switching activity without area penalty compared withprevious publications.

  3. Thermal Error Modeling of the CNC Machine Tool Based on Data Fusion Method of Kalman Filter

    Directory of Open Access Journals (Sweden)

    Haitong Wang

    2017-01-01

    Full Text Available This paper presents a modeling methodology for the thermal error of machine tool. The temperatures predicted by modified lumped-mass method and the temperatures measured by sensors are fused by the data fusion method of Kalman filter. The fused temperatures, instead of the measured temperatures used in traditional methods, are applied to predict the thermal error. The genetic algorithm is implemented to optimize the parameters in modified lumped-mass method and the covariances in Kalman filter. The simulations indicate that the proposed method performs much better compared with the traditional method of MRA, in terms of prediction accuracy and robustness under a variety of operating conditions. A compensation system is developed based on the controlling system of Siemens 840D. Validated by the compensation experiment, the thermal error after compensation has been reduced dramatically.

  4. Towards a Formal Semantics for UML/MARTE State Machines Based on Hierarchical Timed Automata

    Institute of Scientific and Technical Information of China (English)

    Yu Zhou; Luciano Baresi; Matteo Rossi

    2013-01-01

    UML is a widely-used,general purpose modeling language.But its lack of a rigorous semantics forbids the thorough analysis of designed solution,and thus precludes the discovery of significant problems at design time.To bridge the gap,the paper investigates the underlying semantics of UML state machine diagrams,along with the time-related modeling elements of MARTE,the profile for modeling and analysis of real-time embedded systems,and proposes a formal operational semantics based on extended hierarchical timed automata.The approach is exemplified on a simple example taken from the automotive domain.Verification is accomplished by translating designed models into the input language of the UPPAAL model checker.

  5. A machine vision system for micro-EDM based on linux

    Science.gov (United States)

    Guo, Rui; Zhao, Wansheng; Li, Gang; Li, Zhiyong; Zhang, Yong

    2006-11-01

    Due to the high precision and good surface quality that it can give, Electrical Discharge Machining (EDM) is potentially an important process for the fabrication of micro-tools and micro-components. However, a number of issues remain unsolved before micro-EDM becomes a reliable process with repeatable results. To deal with the difficulties in micro electrodes on-line fabrication and tool wear compensation, a micro-EDM machine vision system is developed with a Charge Coupled Device (CCD) camera, with an optical resolution of 1.61μm and an overall magnification of 113~729. Based on the Linux operating system, an image capturing program is developed with the V4L2 API, and an image processing program is exploited by using OpenCV. The contour of micro electrodes can be extracted by means of the Canny edge detector. Through the system calibration, the micro electrodes diameter can be measured on-line. Experiments have been carried out to prove its performance, and the reasons of measurement error are also analyzed.

  6. Memory-intensive benchmarks: IRAM vs. cache-based machines

    Energy Technology Data Exchange (ETDEWEB)

    Gaeke, Brian G.; Husbands, Parry; Kim, Hyun Jin; Li, Xiaoye S.; Moon, Hyun Jin; Oliker, Leonid; Yelick, Katherine A.; Biswas, Rupak

    2001-09-29

    The increasing gap between processor and memory performance has led to new architectural models for memory-intensive applications. In this paper, we explore the performance of a set of memory-intensive benchmarks and use them to compare the performance of conventional cache-based microprocessors to a mixed logic and DRAM processor called VIRAM. The benchmarks are based on problem statements, rather than specific implementations, and in each case we explore the fundamental hardware requirements of the problem, as well as alternative algorithms and data structures that can help expose fine-grained parallelism or simplify memory access patterns. The benchmarks are characterized by their memory access patterns, their basic structures, and the ratio of computation to memory operation.

  7. Assessment of functional state and adaptation reserves of machine operators in agriculture with different work experience in the profession

    Directory of Open Access Journals (Sweden)

    S.S. Raikin

    2015-09-01

    Full Text Available The results of hemodynamic parameters’ evaluation (blood pressure, heart rate, minute volume of blood, total peripheral vascular resistance and adaptation (adaptive capacity of the circulatory system, the index of physical condition, body mass index to job strains in machine operators of agriculture with a different experience in the profession are presented. It was found that 27 % of the patients – machine operators were in a state of unsatisfactory adaptation and 18.8 % in the state of failure of adaptation options when functional body reserves were sharply reduced, indicating that the work in hazardous conditions resulted in a significant deterioration of the functional state of exhaustion and adaptation reserves. It was found that the professional experience of 10 years or more is a risk factor for the health of machine workers in agriculture, causing the violation of functional state and exhaustion of adaptive reserves of an organism, as evidenced by a statistically significant correlation between the indicators of functional status and work experience in the profession.

  8. CPS Modeling of CNC Machine Tool Work Processes Using an Instruction-Domain Based Approach

    Directory of Open Access Journals (Sweden)

    Jihong Chen

    2015-06-01

    Full Text Available Building cyber-physical system (CPS models of machine tools is a key technology for intelligent manufacturing. The massive electronic data from a computer numerical control (CNC system during the work processes of a CNC machine tool is the main source of the big data on which a CPS model is established. In this work-process model, a method based on instruction domain is applied to analyze the electronic big data, and a quantitative description of the numerical control (NC processes is built according to the G code of the processes. Utilizing the instruction domain, a work-process CPS model is established on the basis of the accurate, real-time mapping of the manufacturing tasks, resources, and status of the CNC machine tool. Using such models, case studies are conducted on intelligent-machining applications, such as the optimization of NC processing parameters and the health assurance of CNC machine tools.

  9. Influence of Voltage Dips on the Operation of Brushless Exciter System of Synchronous Machines

    Science.gov (United States)

    Fedotov, A.; Leonov, A.; Vagapov, G.; Mutule, A.

    2016-06-01

    This paper presents a mathematical model with continuous variables for brushless exciter system of synchronous machines, containing the thyristor elements. Discrete Laplace transform is used for transition from a mathematical model of a system with variable structure in continuous variables to equation finite difference with permanent structure. Then inverse transition is made to a mathematical model in continuous variables with permanent structure.

  10. Machine Shop. Module 4: Power Saw and Drill Press Operation. Instructor's Guide.

    Science.gov (United States)

    Walden, Charles H.; Daniel, Bill

    This document consists of materials for a six-unit course on the following topics: (1) power saw safety and maintenance; (2) cutting stock to length; (3) band machining and contouring; (4) drill press types and safety; (5) drill press work-holding devices; and (6) tools and tool holders. The instructor's guide begins with a list of competencies…

  11. A Machine-Learning Approach to Predict Main Energy Consumption under Realistic Operational Conditions

    DEFF Research Database (Denmark)

    Petersen, Joan P; Winther, Ole; Jacobsen, Daniel J

    2012-01-01

    The paper presents a novel and publicly available set of high-quality sensory data collected from a ferry over a period of two months and overviews exixting machine-learning methods for the prediction of main propulsion efficiency. Neural networks are applied on both real-time and predictive...

  12. A Machine-Learning Approach to Predict Main Energy Consumption under Realistic Operational Conditions

    DEFF Research Database (Denmark)

    Petersen, Joan P; Winther, Ole; Jacobsen, Daniel J

    2012-01-01

    The paper presents a novel and publicly available set of high-quality sensory data collected from a ferry over a period of two months and overviews exixting machine-learning methods for the prediction of main propulsion efficiency. Neural networks are applied on both real-time and predictive sett...

  13. Spectral-Spatial Classification of Hyperspectral Image Based on Kernel Extreme Learning Machine

    National Research Council Canada - National Science Library

    Chen Chen; Wei Li; Hongjun Su; Kui Liu

    2014-01-01

      Extreme learning machine (ELM) is a single-layer feedforward neural network based classifier that has attracted significant attention in computer vision and pattern recognition due to its fast learning speed and strong generalization...

  14. Effects-Based Operations Has Limitations

    Science.gov (United States)

    2005-05-17

    2002. 3 Fayette, Daniel F . "Effects-Based Operations" Air Force Research Laboratory <http://www.afrl.af.mil/techconn/index.htm> [June 2001]. 4...Arlington, VA, 2001. Fayette, Daniel F . "Effects-Based Operations" Air Force Research Laboratory <http://www.afrl.af.mil/techconn/index.htm> [June

  15. A Vectorial modeling for the pentaphase Permanent Magnet Synchronous Machine based on multimachine approach

    Directory of Open Access Journals (Sweden)

    Abdelkrim Sellam,Boubakeur Dehiba,Mohamed B. Benabdallah,Mohamed Abid,Nacéra Bachir Bouiadjra,Boubakeur Bensaid,Mustapha Djouhri

    2012-12-01

    Full Text Available The polyphase [1] machines are developed mainly inthe field of variable speed drives of high powerbecause increasing the number of phases on the onehand allows to reduce the dimensions of thecomponents in power modulators energy and secondlyto improve the operating safety. By a vector approach(vector space, it is possible to find a set of singlephasemachine and / or two-phase fictitious equivalentto polyphase synchronous machine.These fictitiousmachines are coupled electrically and mechanicallybut decoupled magnetically. This approach leads tointroduce the concept of the equivalent machine(multimachine multiconverter system MMS whichaims to analyze systems composed of mul tiplemachines (or multiple converters in electric drives. Afirst classification multimachine multiconvertersystem follows naturally from MMS formalism. Wepresent an example of a synchronous machine pent

  16. Evolving Neural Turing Machines for Reward-based Learning

    DEFF Research Database (Denmark)

    Jacobsen, Emil Juul; Risi, Sebastian; Greve, Rasmus Boll

    2016-01-01

    and integrating new information without losing previously acquired skills. Here we build on recent work by Graves et al. [5] who extended the capabilities of an ANN by combining it with an external memory bank trained through gradient descent. In this paper, we introduce an evolvable version of their Neural...... Turing Machine (NTM) and show that such an approach greatly simplifies the neural model, generalizes better, and does not require accessing the entire memory content at each time-step. The Evolvable Neural Turing Machine (ENTM) is able to solve a simple copy tasks and for the first time, the continuous...... version of the double T-Maze, a complex reinforcement-like learning problem. In the T-Maze learning task the agent uses the memory bank to display adaptive behavior that normally requires a plastic ANN, thereby suggesting a complementary and effective mechanism for adaptive behavior in NE....

  17. A Machine Learning Based Analytical Framework for Semantic Annotation Requirements

    CERN Document Server

    Hassanzadeh, Hamed; 10.5121/ijwest.2011.2203

    2011-01-01

    The Semantic Web is an extension of the current web in which information is given well-defined meaning. The perspective of Semantic Web is to promote the quality and intelligence of the current web by changing its contents into machine understandable form. Therefore, semantic level information is one of the cornerstones of the Semantic Web. The process of adding semantic metadata to web resources is called Semantic Annotation. There are many obstacles against the Semantic Annotation, such as multilinguality, scalability, and issues which are related to diversity and inconsistency in content of different web pages. Due to the wide range of domains and the dynamic environments that the Semantic Annotation systems must be performed on, the problem of automating annotation process is one of the significant challenges in this domain. To overcome this problem, different machine learning approaches such as supervised learning, unsupervised learning and more recent ones like, semi-supervised learning and active learn...

  18. Initial experimental results of a machine learning-based temperature control system for an RF gun

    CERN Document Server

    Edelen, A L; Milton, S V; Chase, B E; Crawford, D J; Eddy, N; Edstrom, D; Harms, E R; Ruan, J; Santucci, J K; Stabile, P

    2015-01-01

    Colorado State University (CSU) and Fermi National Accelerator Laboratory (Fermilab) have been developing a control system to regulate the resonant frequency of an RF electron gun. As part of this effort, we present initial test results for a benchmark temperature controller that combines a machine learning-based model and a predictive control algorithm. This is part of an on-going effort to develop adaptive, machine learning-based tools specifically to address control challenges found in particle accelerator systems.

  19. Optimal Differential Routing based on Finite State Machine Theory

    OpenAIRE

    M. S. Krishnamoorthy; Loy, James R.; McDonald, John F.

    1999-01-01

    Noise margins in high speed digital systems continue to erode. Full differential signal routing provides a mechanism for deferring these effects. This paper proposes a three stage routing process for solving the adjacent placement routing problem of differential signal pairs, and proves that it is optimal. The process views differential pairs as logical nets; routes the logical nets; then bifurcates the result to achieve a physical realization. Finite state machine theory provides the critica...

  20. Chord Recognition Based on Temporal Correlation Support Vector Machine

    OpenAIRE

    Zhongyang Rao; Xin Guan; Jianfu Teng

    2016-01-01

    In this paper, we propose a method called temporal correlation support vector machine (TCSVM) for automatic major-minor chord recognition in audio music. We first use robust principal component analysis to separate the singing voice from the music to reduce the influence of the singing voice and consider the temporal correlations of the chord features. Using robust principal component analysis, we expect the low-rank component of the spectrogram matrix to contain the musical accompaniment and...

  1. ANN Based Tool Condition Monitoring System for CNC Milling Machines

    Directory of Open Access Journals (Sweden)

    Mota-Valtierra G.C.

    2011-10-01

    Full Text Available Most of the companies have as objective to manufacture high-quality products, then by optimizing costs, reducing and controlling the variations in its production processes it is possible. Within manufacturing industries a very important issue is the tool condition monitoring, since the tool state will determine the quality of products. Besides, a good monitoring system will protect the machinery from severe damages. For determining the state of the cutting tools in a milling machine, there is a great variety of models in the industrial market, however these systems are not available to all companies because of their high costs and the requirements of modifying the machining tool in order to attach the system sensors. This paper presents an intelligent classification system which determines the status of cutt ers in a Computer Numerical Control (CNC milling machine. This tool state is mainly detected through the analysis of the cutting forces drawn from the spindle motors currents. This monitoring system does not need sensors so it is no necessary to modify the machine. The correct classification is made by advanced digital signal processing techniques. Just after acquiring a signal, a FIR digital filter is applied to the data to eliminate the undesired noisy components and to extract the embedded force components. A Wavelet Transformation is applied to the filtered signal in order to compress the data amount and to optimize the classifier structure. Then a multilayer perceptron- type neural network is responsible for carrying out the classification of the signal. Achieving a reliability of 95%, the system is capable of detecting breakage and a worn cutter.

  2. Development of Estimating Equation of Machine Operational Skill by Utilizing Eye Movement Measurement and Analysis of Stress and Fatigue

    Directory of Open Access Journals (Sweden)

    Satoshi Suzuki

    2013-01-01

    Full Text Available For an establishment of a skill evaluation method for human support systems, development of an estimating equation of the machine operational skill is presented. Factors of the eye movement such as frequency, velocity, and moving distance of saccade were computed using the developed eye gaze measurement system, and the eye movement features were determined from these factors. The estimating equation was derived through an outlier test (to eliminate nonstandard data and a principal component analysis (to find dominant components. Using a cooperative carrying task (cc-task simulator, the eye movement and operational data of the machine operators were recorded, and effectiveness of the derived estimating equation was investigated. As a result, it was confirmed that the estimating equation was effective strongly against actual simple skill levels (r=0.56–0.84. In addition, effects of internal condition such as fatigue and stress on the estimating equation were analyzed. Using heart rate (HR and coefficient of variation of R-R interval (Cvrri. Correlation analysis between these biosignal indexes and the estimating equation of operational skill found that the equation reflected effects of stress and fatigue, although the equation could estimate the skill level adequately.

  3. Housing Value Forecasting Based on Machine Learning Methods

    Directory of Open Access Journals (Sweden)

    Jingyi Mu

    2014-01-01

    Full Text Available In the era of big data, many urgent issues to tackle in all walks of life all can be solved via big data technique. Compared with the Internet, economy, industry, and aerospace fields, the application of big data in the area of architecture is relatively few. In this paper, on the basis of the actual data, the values of Boston suburb houses are forecast by several machine learning methods. According to the predictions, the government and developers can make decisions about whether developing the real estate on corresponding regions or not. In this paper, support vector machine (SVM, least squares support vector machine (LSSVM, and partial least squares (PLS methods are used to forecast the home values. And these algorithms are compared according to the predicted results. Experiment shows that although the data set exists serious nonlinearity, the experiment result also show SVM and LSSVM methods are superior to PLS on dealing with the problem of nonlinearity. The global optimal solution can be found and best forecasting effect can be achieved by SVM because of solving a quadratic programming problem. In this paper, the different computation efficiencies of the algorithms are compared according to the computing times of relevant algorithms.

  4. Analysis of capacitive effect and life estimation of hydrodynamic journal bearings on repeated starts and stops of a machine operating under the influence of shaft voltages

    Science.gov (United States)

    Prashad, Har; Rao, K. N.

    1994-07-01

    A theoretical analysis has been carried out to study the capacitive effect and life estimation of hydrodynamic journal bearings on repeated starts and stops of a machine operating under the influence of shaft voltages. The analysis gives the time required for the charge accumulation and increase of charge with time on the liner surface of a journal bearing based on bearing capacitance, resistance of film thickness, and the shaft voltage. Also, it investigates the effect of gradual leakage of the accumulated charges with time as the shaft voltage falls when the power supply to the machine is switched off. This paper gives an approach to determine the ratio of the number of shaft revolutions required for charge accumulation and gradual discharge of the accumulated charges on the liner surface of a bearing depending on bearing-to-shaft voltage. Also, the number of repeated starts and stops before initiation of craters on the liner surface of a hydrodynamic journal bearing is established to restrict deterioration and damage of the liner. The diagnosis has the potential to study the transient effect of the shaft voltages on a journal bearing during the start and stop cycle of a machine.

  5. Estimation of pump operational state with model-based methods

    Energy Technology Data Exchange (ETDEWEB)

    Ahonen, Tero; Tamminen, Jussi; Ahola, Jero; Viholainen, Juha; Aranto, Niina [Institute of Energy Technology, Lappeenranta University of Technology, P.O. Box 20, FI-53851 Lappeenranta (Finland); Kestilae, Juha [ABB Drives, P.O. Box 184, FI-00381 Helsinki (Finland)

    2010-06-15

    Pumps are widely used in industry, and they account for 20% of the industrial electricity consumption. Since the speed variation is often the most energy-efficient method to control the head and flow rate of a centrifugal pump, frequency converters are used with induction motor-driven pumps. Although a frequency converter can estimate the operational state of an induction motor without external measurements, the state of a centrifugal pump or other load machine is not typically considered. The pump is, however, usually controlled on the basis of the required flow rate or output pressure. As the pump operational state can be estimated with a general model having adjustable parameters, external flow rate or pressure measurements are not necessary to determine the pump flow rate or output pressure. Hence, external measurements could be replaced with an adjustable model for the pump that uses estimates of the motor operational state. Besides control purposes, modelling the pump operation can provide useful information for energy auditing and optimization purposes. In this paper, two model-based methods for pump operation estimation are presented. Factors affecting the accuracy of the estimation methods are analyzed. The applicability of the methods is verified by laboratory measurements and tests in two pilot installations. Test results indicate that the estimation methods can be applied to the analysis and control of pump operation. The accuracy of the methods is sufficient for auditing purposes, and the methods can inform the user if the pump is driven inefficiently. (author)

  6. Mass detection algorithm based on support vector machine and relevance feedback

    Institute of Scientific and Technical Information of China (English)

    Ying WANG; Xinbo GAO

    2008-01-01

    To improve the detection of mass with appearance that borders on the similarity between mass and density tissues in the breast,an support vector machine classifier based on typical features iS designed to classify the region of interest(ROI).Furthermore,relevance feedback is introduced to improve the performance of support vector machines.A new mass detection scheme based on the support vector machine and the relevance feedback is proposed.Simulation experiments on mammograms illustrate that the novel support vector machine classifier based on typical features can improve the detection performance of the featureless classifier by 5%,while the introduction of relevance feedback can further improve the detection performance to about 90%.

  7. Measurement-induced operation of two-ion quantum heat machines

    Science.gov (United States)

    Chand, Suman; Biswas, Asoka

    2017-03-01

    We show how one can implement a quantum heat machine by using two interacting trapped ions, in presence of a thermal bath. The electronic states of the ions act like a working substance, while the vibrational mode is modelled as the cold bath. The heat exchange with the cold bath is mimicked by the projective measurement of the electronic states. We show how such measurement in a suitable basis can lead to either a quantum heat engine or a refrigerator, which undergoes a quantum Otto cycle. The local magnetic field is adiabatically changed during the heat cycle. The performance of the heat machine depends upon the interaction strength between the ions, the magnetic fields, and the measurement cost. In our model, the coupling to the hot and the cold baths is never switched off in an alternative fashion during the heat cycle, unlike other existing proposals of quantum heat engines. This makes our proposal experimentally realizable using current tapped-ion technology.

  8. Optimal use of human and machine resources for Space Station assembly operations

    Science.gov (United States)

    Parrish, Joseph C.

    1988-01-01

    This paper investigates the issues involved in determining the best mix of human and machine resources for assembly of the Space Station. It presents the current Station assembly sequence, along with descriptions of the available assembly resources. A number of methodologies for optimizing the human/machine tradeoff problem have been developed, but the Space Station assembly offers some unique issues that have not yet been addressed. These include a strong constraint on available EVA time for early flights and a phased deployment of assembly resources over time. A methodology for incorporating the previously developed decision methods to the special case of the Space Station is presented. This methodology emphasizes an application of multiple qualitative and quantitative techniques, including simulation and decision analysis, for producing an objective, robust solution to the tradeoff problem.

  9. Identification and non-integer order modelling of synchronous machines operating as generator

    Directory of Open Access Journals (Sweden)

    Szymon Racewicz

    2012-09-01

    Full Text Available This paper presents an original mathematical model of a synchronous generator using derivatives of fractional order. In contrast to classical models composed of a large number of R-L ladders, it comprises half-order impedances, which enable the accurate description of the electromagnetic induction phenomena in a wide frequency range, while minimizing the order and number of model parameters. The proposed model takes into account the skin eff ect in damper cage bars, the eff ects of eddy currents in rotor solid parts, and the saturation of the machine magnetic circuit. The half-order transfer functions used for modelling these phenomena were verifi ed by simulation of ferromagnetic sheet impedance using the fi nite elements method. The analysed machine’s parameters were identified on the basis of SSFR (StandStill Frequency Response characteristics measured on a gradually magnetised synchronous machine.

  10. The Synthesis of Precise Rotating Machine Mathematical Model, Operating Natural Signals and Virtual Data

    Science.gov (United States)

    Zhilenkov, A. A.; Kapitonov, A. A.

    2017-07-01

    It is known that synchronous machines catalogue data are presented for the case of two-phase machine in rotating coordinate system, e.g. for their description with Park-Gorev’s equation system. Nevertheless, many problems require control of phase currents and voltages, for instance, in modeling of the systems, in which synchronous generators supply powerful rectifiers. Modeling of complex systems with synchronous generators, semiconductor convertors and etc. (with phase currents control necessary for power switch commutation algorithms) becomes achievable with the equation system described in this article. Given model can be used in digital control systems with internal model. It doesn’t require high capacity of computing resources and provides sufficient modeling accuracy.

  11. Influence of Voltage Dips on the Operation of Brushless Exciter System of Synchronous Machines

    Directory of Open Access Journals (Sweden)

    Fedotov A.

    2016-06-01

    Full Text Available This paper presents a mathematical model with continuous variables for brushless exciter system of synchronous machines, containing the thyristor elements. Discrete Laplace transform is used for transition from a mathematical model of a system with variable structure in continuous variables to equation finite difference with permanent structure. Then inverse transition is made to a mathematical model in continuous variables with permanent structure.

  12. Executable Architecture of Net Enabled Operations: State Machine of Federated Nodes

    Science.gov (United States)

    2009-11-01

    améliorations. Il est ressorti d’un des ateliers sur le développement d’une machine à états de nœuds fédérés une question importante et c’est la...processus serait plus facile à comprendre s’il était possible de présenter un ou deux modèles durant l’atelier. Les participants de cet atelier ont

  13. Research on Remote Video Monitoring System Used for Numerical Control Machine Tools Based on Embedded Technology

    Institute of Scientific and Technical Information of China (English)

    LIU Quan; QU Xuehong; ZHOU Henglin; LONG Yihong

    2006-01-01

    This paper designed an embedded video monitoring system using DSP(Digital Signal Processing) and ARM(Advanced RISC Machine). This system is an important part of self-service operation of numerical control machine tools. At first the analog input signals from the CCD(Charge Coupled Device) camera are transformed into digital signals, and then output to the DSP system, where the video sequence is encoded according to the new generation image compressing standard called H.264. The code will be transmitted to the ARM system through xBus, and then be packed in the ARM system and transmitted to the client port through the gateway. Web technology, embedded technology and image compressing as well as coding technology are integrated in the system, which can be widely used in self-service operation of numerical control machine tools and intelligent robot control areas.

  14. Machine-Learning Approach for Design of Nanomagnetic-Based Antennas

    Science.gov (United States)

    Gianfagna, Carmine; Yu, Huan; Swaminathan, Madhavan; Pulugurtha, Raj; Tummala, Rao; Antonini, Giulio

    2017-08-01

    We propose a machine-learning approach for design of planar inverted-F antennas with a magneto-dielectric nanocomposite substrate. It is shown that machine-learning techniques can be efficiently used to characterize nanomagnetic-based antennas by accurately mapping the particle radius and volume fraction of the nanomagnetic material to antenna parameters such as gain, bandwidth, radiation efficiency, and resonant frequency. A modified mixing rule model is also presented. In addition, the inverse problem is addressed through machine learning as well, where given the antenna parameters, the corresponding design space of possible material parameters is identified.

  15. Evaluation of machine learning algorithms for treatment outcome prediction in patients with epilepsy based on structural connectome data.

    Science.gov (United States)

    Munsell, Brent C; Wee, Chong-Yaw; Keller, Simon S; Weber, Bernd; Elger, Christian; da Silva, Laura Angelica Tomaz; Nesland, Travis; Styner, Martin; Shen, Dinggang; Bonilha, Leonardo

    2015-09-01

    The objective of this study is to evaluate machine learning algorithms aimed at predicting surgical treatment outcomes in groups of patients with temporal lobe epilepsy (TLE) using only the structural brain connectome. Specifically, the brain connectome is reconstructed using white matter fiber tracts from presurgical diffusion tensor imaging. To achieve our objective, a two-stage connectome-based prediction framework is developed that gradually selects a small number of abnormal network connections that contribute to the surgical treatment outcome, and in each stage a linear kernel operation is used to further improve the accuracy of the learned classifier. Using a 10-fold cross validation strategy, the first stage in the connectome-based framework is able to separate patients with TLE from normal controls with 80% accuracy, and second stage in the connectome-based framework is able to correctly predict the surgical treatment outcome of patients with TLE with 70% accuracy. Compared to existing state-of-the-art methods that use VBM data, the proposed two-stage connectome-based prediction framework is a suitable alternative with comparable prediction performance. Our results additionally show that machine learning algorithms that exclusively use structural connectome data can predict treatment outcomes in epilepsy with similar accuracy compared with "expert-based" clinical decision. In summary, using the unprecedented information provided in the brain connectome, machine learning algorithms may uncover pathological changes in brain network organization and improve outcome forecasting in the context of epilepsy. Copyright © 2015 Elsevier Inc. All rights reserved.

  16. A Multistage Control Mechanism for Group-Based Machine-Type Communications in an LTE System

    Directory of Open Access Journals (Sweden)

    Wen-Chien Hung

    2013-01-01

    Full Text Available When machine-type communication (MTC devices perform the long-term evolution (LTE attach procedure without bit rate limitations, they may produce congestion in the core network. To prevent this congestion, the LTE standard suggests using group-based policing to regulate the maximum bit rate of all traffic generated by a group of MTC devices. However, previous studies on the access point name-aggregate maximum bit rate based on group-based policing are relatively limited. This study proposes a multistage control (MSC mechanism to process the operations of maximum bit rate allocation based on resource-use information. For performance evaluation, this study uses a Markov chain with to analyze MTC application in a 3GPP network. Traffic flow simulations in an LTE system indicate that the MSC mechanism is an effective bandwidth allocation method in an LTE system with MTC devices. Experimental results show that the MSC mechanism achieves a throughput 22.5% higher than that of the LTE standard model using the group-based policing, and it achieves a lower delay time and greater long-term fairness as well.

  17. Volitional enhancement of firing synchrony and oscillation by neuronal operant conditioning: interaction with neurorehabilitation and brain-machine interface

    Directory of Open Access Journals (Sweden)

    Yoshio eSakurai

    2014-02-01

    Full Text Available In this review, we focus on neuronal operant conditioning in which increments in neuronal activities are directly rewarded without behaviors. We discuss the potential of this approach to elucidate neuronal plasticity for enhancing specific brain functions and its interaction with the progress in neurorehabilitation and brain–machine interfaces. The key to-be-conditioned activities that this paper emphasizes are synchronous and oscillatory firings of multiple neurons that reflect activities of cell assemblies. First, we introduce certain well-known studies on neuronal operant conditioning in which conditioned enhancements of neuronal firing were reported in animals and humans. These studies demonstrated the feasibility of volitional control over neuronal activity. Second, we refer to the recent studies on operant conditioning of synchrony and oscillation of neuronal activities. In particular, we introduce a recent study showing volitional enhancement of oscillatory activity in monkey motor cortex and our study showing selective enhancement of firing synchrony of neighboring neurons in rat hippocampus. Third, we discuss the reasons for emphasizing firing synchrony and oscillation in neuronal operant conditioning, the main reason being that they reflect the activities of cell assemblies, which have been suggested to be basic neuronal codes representing information in the brain. Finally, we discuss the interaction of neuronal operant conditioning with neurorehabilitation and brain–machine interface (BMI. We argue that synchrony and oscillation of neuronal firing are the key activities required for developing both reliable neurorehabilitation and high-performance BMI. Further, we conclude that research of neuronal operant conditioning, neurorehabilitation, BMI, and system neuroscience will produce findings applicable to these interrelated fields, and neuronal synchrony and oscillation can be a common important bridge among all of them.

  18. Logic synthesis for FPGA-based finite state machines

    CERN Document Server

    Barkalov, Alexander; Kolopienczyk, Malgorzata; Mielcarek, Kamil; Bazydlo, Grzegorz

    2016-01-01

    This book discusses control units represented by the model of a finite state machine (FSM). It contains various original methods and takes into account the peculiarities of field-programmable gate arrays (FPGA) chips and a FSM model. It shows that one of the peculiarities of FPGA chips is the existence of embedded memory blocks (EMB). The book is devoted to the solution of problems of logic synthesis and reduction of hardware amount in control units. The book will be interesting and useful for researchers and PhD students in the area of Electrical Engineering and Computer Science, as well as for designers of modern digital systems.

  19. Improved Support Vector Machine Approach Based on Determining Thresholds Automatically

    Institute of Scientific and Technical Information of China (English)

    WANG Xiao-hua; YAN Xue-mei; WANG Xiao-guang

    2007-01-01

    To improve the training speed of support vector machine (SVM), a method called improved center distance ratio method (ICDRM) with determining thresholds automatically is presented here without reduce the identification rate. In this method border vectors are chosen from the given samples by comparing sample vectors with center distance ratio in advance. The number of training samples is reduced greatly and the training speed is improved. This method is used to the identification for license plate characters. Experimental results show that the improved SVM method-ICDRM does well at identification rate and training speed.

  20. An efficient flow-based botnet detection using supervised machine learning

    DEFF Research Database (Denmark)

    Stevanovic, Matija; Pedersen, Jens Myrup

    2014-01-01

    Botnet detection represents one of the most crucial prerequisites of successful botnet neutralization. This paper explores how accurate and timely detection can be achieved by using supervised machine learning as the tool of inferring about malicious botnet traffic. In order to do so, the paper...... introduces a novel flow-based detection system that relies on supervised machine learning for identifying botnet network traffic. For use in the system we consider eight highly regarded machine learning algorithms, indicating the best performing one. Furthermore, the paper evaluates how much traffic needs...... to accurately and timely detect botnet traffic using purely flow-based traffic analysis and supervised machine learning. Additionally, the results show that in order to achieve accurate detection traffic flows need to be monitored for only a limited time period and number of packets per flow. This indicates...

  1. Association Rule-based Predictive Model for Machine Failure in Industrial Internet of Things

    Science.gov (United States)

    Kwon, Jung-Hyok; Lee, Sol-Bee; Park, Jaehoon; Kim, Eui-Jik

    2017-09-01

    This paper proposes an association rule-based predictive model for machine failure in industrial Internet of things (IIoT), which can accurately predict the machine failure in real manufacturing environment by investigating the relationship between the cause and type of machine failure. To develop the predictive model, we consider three major steps: 1) binarization, 2) rule creation, 3) visualization. The binarization step translates item values in a dataset into one or zero, then the rule creation step creates association rules as IF-THEN structures using the Lattice model and Apriori algorithm. Finally, the created rules are visualized in various ways for users’ understanding. An experimental implementation was conducted using R Studio version 3.3.2. The results show that the proposed predictive model realistically predicts machine failure based on association rules.

  2. Effects of Machine Tool Configuration on Its Dynamics Based on Orthogonal Experiment Method

    Institute of Scientific and Technical Information of China (English)

    GAO Xiangsheng; ZHANG Yidu; ZHANG Hongwei; WU Qiong

    2012-01-01

    In order to analyze the influence of configuration parameters on dynamic characteristics of machine tools in the working space,the configuration parameters have been suggested based on the orthogonal experiment method.Dynamic analysis of a milling machine,which is newly designed for producing turbine blades,has been conducted by utilizing the modal synthesis method.The finite element model is verified and updated by experimental modal analysis (EMA) of the machine tool.The result gained by modal synthesis method is compared with whole-model finite element method (FEM) result as well.According to the orthogonal experiment method,four configuration parameters of machine tool are considered as four factors for dynamic characteristics.The influence of configuration parameters on the first three natural frequencies is obtained by range analysis.It is pointed out that configuration parameter is the most important factor affecting the fundamental frequency of machine tools,and configuration parameter has less effect on lower-order modes of the system than others.The combination of configuration parameters which makes the fundamental frequency reach the maximum value is provided.Through demonstration,the conclusion can be drawn that the influence of configuration parameters on the natural frequencies of machine tools can be analyzed explicitly by the orthogonal experiment method,which offers a new method for estimating the dynamic characteristics of machine tools.

  3. Processing outcomes of the AFM probe-based machining approach with different feed directions

    OpenAIRE

    2016-01-01

    We present experimental and theoretical results to describe and explain processing outcomes when producing nanochannels that are a few times wider than the atomic force microscope (AFM) probe using an AFM. This is achieved when AFM tip-based machining is performed with reciprocating motion of the tip of the AFM probe. In this case, different feed directions with respect to the orientation of the AFM probe can be used. The machining outputs of interest are the chip formation process, obtained ...

  4. A Novel Parallel Engraving Machine Based on 6-PUS Mechanism and Related Technologies

    OpenAIRE

    Ling-fu, Kong; Shi-hui, Zhang

    2005-01-01

    A novel parallel engraving machine is proposed and its some key technologies are studied in this paper. Based on the confirming of mechanism type, a group of mechanisms are obtained by changing the sizes of engraving machine. Performance indices are analyzed by considering both the first and the second order influence coefficient matrix of different sample point in every mechanism's workspace, then mechanism's sizes better for both kinematics and dynamics are achieved, so the theory basis for...

  5. A Review on Approaches for Condition Based Maintenance in Applications with Induction Machines located Offshore

    Directory of Open Access Journals (Sweden)

    J. Cibulka

    2012-04-01

    Full Text Available This paper presents a review of different approaches for Condition Based Maintenance (CBM of induction machines and drive trains in offshore applications. The paper contains an overview of common failure modes, monitoring techniques, approaches for diagnostics, and an overview of typical maintenance actions. Although many papers have been written in this area before, this paper puts an emphasis on recent developments and limits the scope to induction machines and drive trains applied in applications located offshore.

  6. Digital Signature Based Fax Machine Using ARM9 and Linux

    Directory of Open Access Journals (Sweden)

    Ch. Komali

    2013-01-01

    Full Text Available In this method we are having the S3C2240A (ARM9 Board which is ported with Linux in it. And this ARM9 board with Linux will be connected to the Touch Screen device. This ARM9 board intern will be connected to the LAN network (Ethernet. To design this fax machine we are using two Arm controller boards. One Arm board will keep at fax Transmission side and another board will keep at fax receiving side. By using the Ethernet we will send and receive the fax, for that we are using TCP/IP server and TCP/IP client. In this fax machine we have too many options on touch screen of arm like retrieve, sign, send, save etc. By selecting the retrieve option we can see the received text data on touch screen. If we want to transmit text data, we can select send option, then the fax will sent to the destination. On the receiving side, the received fax will be displayed on LCD touch screen. If necessary, we can sign directly on the touch panel by selecting the sign option. If we want to retransmit that signed document, we should active server. In this way bidirectional transmission and reception is possible

  7. Chord Recognition Based on Temporal Correlation Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Zhongyang Rao

    2016-05-01

    Full Text Available In this paper, we propose a method called temporal correlation support vector machine (TCSVM for automatic major-minor chord recognition in audio music. We first use robust principal component analysis to separate the singing voice from the music to reduce the influence of the singing voice and consider the temporal correlations of the chord features. Using robust principal component analysis, we expect the low-rank component of the spectrogram matrix to contain the musical accompaniment and the sparse component to contain the vocal signals. Then, we extract a new logarithmic pitch class profile (LPCP feature called enhanced LPCP from the low-rank part. To exploit the temporal correlation among the LPCP features of chords, we propose an improved support vector machine algorithm called TCSVM. We perform this study using the MIREX’09 (Music Information Retrieval Evaluation eXchange Audio Chord Estimation dataset. Furthermore, we conduct comprehensive experiments using different pitch class profile feature vectors to examine the performance of TCSVM. The results of our method are comparable to the state-of-the-art methods that entered the MIREX in 2013 and 2014 for the MIREX’09 Audio Chord Estimation task dataset.

  8. Man-machine Function Allocation Based on Uncertain Linguistic Multiple Attribute Decision Making

    Institute of Scientific and Technical Information of China (English)

    ZHANG An; TANG Zhili; ZHANG Chao

    2011-01-01

    Function allocation is one of the necessary stages in the design course of man-machine systems since appropriate function allocation makes the whole system more effective,reliable and inexpensive.Therefore,our research mainly focuses on the problems of function allocation between man and machine in man-machine systems,analyses each capability advantage of man and machine according to their respective inherent characteristics and makes a comparison between them.In view of highly uncertain characteristics of decision attribute value in the practical process,we introduce the uncertain linguistic multiple attribute decision making (ULMADM) method in the function allocation process.Meanwhile,we also use the uncertain extended weighted arithmetic averaging (UEWAA) method to determine the automation level range of the operator functions.Then,we eventually establish the automation level of man-machine function allocation by using the multi-attribute decision making algorithm,which is combined by UEWAA and uncertain linguistic hybrid aggregation (ULHA) operators.Finally,an example about function allocation is given,that is,fault diagnosis in the cockpit of civil aircraft.The final result of the example demonstrates that the proposed method about function allocation is feasible and effective.

  9. Design synthesis and optimization of permanent magnet synchronous machines based on computationally-efficient finite element analysis

    Science.gov (United States)

    Sizov, Gennadi Y.

    In this dissertation, a model-based multi-objective optimal design of permanent magnet ac machines, supplied by sine-wave current regulated drives, is developed and implemented. The design procedure uses an efficient electromagnetic finite element-based solver to accurately model nonlinear material properties and complex geometric shapes associated with magnetic circuit design. Application of an electromagnetic finite element-based solver allows for accurate computation of intricate performance parameters and characteristics. The first contribution of this dissertation is the development of a rapid computational method that allows accurate and efficient exploration of large multi-dimensional design spaces in search of optimum design(s). The computationally efficient finite element-based approach developed in this work provides a framework of tools that allow rapid analysis of synchronous electric machines operating under steady-state conditions. In the developed modeling approach, major steady-state performance parameters such as, winding flux linkages and voltages, average, cogging and ripple torques, stator core flux densities, core losses, efficiencies and saturated machine winding inductances, are calculated with minimum computational effort. In addition, the method includes means for rapid estimation of distributed stator forces and three-dimensional effects of stator and/or rotor skew on the performance of the machine. The second contribution of this dissertation is the development of the design synthesis and optimization method based on a differential evolution algorithm. The approach relies on the developed finite element-based modeling method for electromagnetic analysis and is able to tackle large-scale multi-objective design problems using modest computational resources. Overall, computational time savings of up to two orders of magnitude are achievable, when compared to current and prevalent state-of-the-art methods. These computational savings allow

  10. A Flywheel Energy Storage System Based on a Doubly Fed Induction Machine and Battery for Microgrid Control

    Directory of Open Access Journals (Sweden)

    Thai-Thanh Nguyen

    2015-06-01

    Full Text Available Microgrids are eco-friendly power systems because they use renewable sources such as solar and wind power as the main power source. However, the stochastic nature of wind and solar power is a considerable challenge for the efficient operation of microgrids. Microgrid operations have to satisfy quality requirements in terms of the frequency and voltage. To overcome these problems, energy storage systems for short- and long-term storage are used with microgrids. Recently, the use of short-term energy storage systems such as flywheels has attracted significant interest as a potential solution to this problem. Conventional flywheel energy storage systems exhibit only one control mode during operation: either smoothing wind power control or frequency control. In this paper, we propose a new flywheel energy storage system based on a doubly fed induction machine and a battery for use with microgrids. The new flywheel energy storage system can be used not only to mitigate wind power fluctuations, but also to control the frequency as well as the voltage of the microgrid during islanded operation. The performance of the proposed flywheel energy storage system is investigated through various simulations using MATLAB/Simulink software. In addition, a conventional flywheel energy storage system based on a doubly fed induction machine is simulated and its performance compared with that of the proposed one.

  11. Heuristic for Critical Machine Based a Lot Streaming for Two-Stage Hybrid Production Environment

    Science.gov (United States)

    Vivek, P.; Saravanan, R.; Chandrasekaran, M.; Pugazhenthi, R.

    2017-03-01

    Lot streaming in Hybrid flowshop [HFS] is encountered in many real world problems. This paper deals with a heuristic approach for Lot streaming based on critical machine consideration for a two stage Hybrid Flowshop. The first stage has two identical parallel machines and the second stage has only one machine. In the second stage machine is considered as a critical by valid reasons these kind of problems is known as NP hard. A mathematical model developed for the selected problem. The simulation modelling and analysis were carried out in Extend V6 software. The heuristic developed for obtaining optimal lot streaming schedule. The eleven cases of lot streaming were considered. The proposed heuristic was verified and validated by real time simulation experiments. All possible lot streaming strategies and possible sequence under each lot streaming strategy were simulated and examined. The heuristic consistently yielded optimal schedule consistently in all eleven cases. The identification procedure for select best lot streaming strategy was suggested.

  12. Neural architecture design based on extreme learning machine.

    Science.gov (United States)

    Bueno-Crespo, Andrés; García-Laencina, Pedro J; Sancho-Gómez, José-Luis

    2013-12-01

    Selection of the optimal neural architecture to solve a pattern classification problem entails to choose the relevant input units, the number of hidden neurons and its corresponding interconnection weights. This problem has been widely studied in many research works but their solutions usually involve excessive computational cost in most of the problems and they do not provide a unique solution. This paper proposes a new technique to efficiently design the MultiLayer Perceptron (MLP) architecture for classification using the Extreme Learning Machine (ELM) algorithm. The proposed method provides a high generalization capability and a unique solution for the architecture design. Moreover, the selected final network only retains those input connections that are relevant for the classification task. Experimental results show these advantages. Copyright © 2013 Elsevier Ltd. All rights reserved.

  13. Wave-Based Turing Machine: Time Reversal and Information Erasing.

    Science.gov (United States)

    Perrard, S; Fort, E; Couder, Y

    2016-08-26

    The investigation of dynamical systems has revealed a deep-rooted difference between waves and objects regarding temporal reversibility and particlelike objects. In nondissipative chaos, the dynamic of waves always remains time reversible, unlike that of particles. Here, we explore the dynamics of a wave-particle entity. It consists in a drop bouncing on a vibrated liquid bath, self-propelled and piloted by the surface waves it generates. This walker, in which there is an information exchange between the particle and the wave, can be analyzed in terms of a Turing machine with waves as the information repository. The experiments reveal that in this system, the drop can read information backwards while erasing it. The drop can thus backtrack on its previous trajectory. A transient temporal reversibility, restricted to the drop motion, is obtained in spite of the system being both dissipative and chaotic.

  14. Wave-Based Turing Machine: Time Reversal and Information Erasing

    Science.gov (United States)

    Perrard, S.; Fort, E.; Couder, Y.

    2016-08-01

    The investigation of dynamical systems has revealed a deep-rooted difference between waves and objects regarding temporal reversibility and particlelike objects. In nondissipative chaos, the dynamic of waves always remains time reversible, unlike that of particles. Here, we explore the dynamics of a wave-particle entity. It consists in a drop bouncing on a vibrated liquid bath, self-propelled and piloted by the surface waves it generates. This walker, in which there is an information exchange between the particle and the wave, can be analyzed in terms of a Turing machine with waves as the information repository. The experiments reveal that in this system, the drop can read information backwards while erasing it. The drop can thus backtrack on its previous trajectory. A transient temporal reversibility, restricted to the drop motion, is obtained in spite of the system being both dissipative and chaotic.

  15. The seam offset identification based on support vector regression machines

    Institute of Scientific and Technical Information of China (English)

    Zeng Songsheng; Shi Yonghua; Wang Guorong; Huang Guoxing

    2009-01-01

    The principle of the support vector regression machine(SVR) is first analysed. Then the new data-dependent kernel function is constructed from information geometry perspective. The current waveforms change regularly in accordance with the different horizontal offset when the rotational frequency of the high speed rotational arc sensor is in the range from 15 Hz to 30 Hz. The welding current data is pretreated by wavelet filtering, mean filtering and normalization treatment. The SVR model is constructed by making use of the evolvement laws, the decision function can be achieved by training the SVR and the seam offset can be identified. The experimental results show that the precision of the offset identification can be greatly improved by modifying the SVR and applying mean filtering from the longitudinal direction.

  16. 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.

  17. The study on the atomic force microscopy base nanoscale electrical discharge machining.

    Science.gov (United States)

    Huang, Jen-Ching; Chen, Chung-Ming

    2012-01-01

    This study proposes an innovative atomic force microscopy (AFM) based nanoscale electrical discharge machining (AFM-based nanoEDM) system which combines an AFM with a self-produced metallic probe and a high-voltage generator to create an atmospheric environment AFM-based nanoEDM system and a deionized water (DI water) environment AFM-based nanoEDM system. This study combines wire-cut processing and electrochemical tip sharpening techniques on a 40-µm thick stainless steel sheet to produce a high conductive AFM probes, the production can withstand high voltage and large current. The tip radius of these probes is approximately 40 nm. A probe test was executed on the AFM using probes to obtain nanoscales morphology of Si wafer surface. The silicon wafer was as a specimen to carry out AFM-base nanoEDM process in atmospheric and DI water environments by AFM-based nanoEDM system. After experiments, the results show that the atmospheric and DI water environment AFM-based nanoEDM systems operate smoothly. From experimental results, it can be found that the electric discharge depth of the silicon wafer at atmospheric environments is a mere 14.54 nm. In a DI water environment, the depth of electric discharge of the silicon wafer can reach 25.4 nm. This indicates that the EDM ability of DI water environment AFM-based nanoEDM system is higher than that of atmospheric environment AFM-based nanoEDM system. After multiple nanoEDM process, the tips become blunt. After applying electrochemical tip sharpening techniques, the tip radius can return to approximately 40 nm. Therefore, AFM probes produced in this study can be reused.

  18. The modelling of dynamic chemical state of paper machine unit operations; Dynaamisen kemiallisen tilan mallintaminen paperikoneen yksikkoeoperaatioissa - MPKT 04

    Energy Technology Data Exchange (ETDEWEB)

    Ylen, J.P.; Jutila, P. [Helsinki Univ. of Technology, Otaniemi (Finland)

    1998-12-31

    The chemical state of paper mass is considered to be a key factor to the smooth operation of the paper machine. There are simulators that have been developed either for dynamic energy and mass balances or for static chemical phenomena, but the combination of these is not a straight forward task. Control Engineering Laboratory of Helsinki University of Technology has studied the paper machine wet end phenomena with the emphasis on pH-modelling. VTT (Technical Research Centre of Finland) Process Physics has used thermodynamical modelling successfully in e.g. Bleaching processes. In this research the different approaches are combined in order to get reliable dynamical models and modelling procedures for various unit operations. A flexible pilot process will be constructed and different materials will be processed starting from simple inorganic substances (e.g. Calcium carbonate and distilled water) working towards more complex masses (thick pulp with process waters and various reagents). The pilot process is well instrumented with ion selective electrodes, total calcium analysator and all basic measurements. (orig.)

  19. Craniux: A LabVIEW-Based Modular Software Framework for Brain-Machine Interface Research

    Directory of Open Access Journals (Sweden)

    Alan D. Degenhart

    2011-01-01

    Full Text Available This paper presents “Craniux,” an open-access, open-source software framework for brain-machine interface (BMI research. Developed in LabVIEW, a high-level graphical programming environment, Craniux offers both out-of-the-box functionality and a modular BMI software framework that is easily extendable. Specifically, it allows researchers to take advantage of multiple features inherent to the LabVIEW environment for on-the-fly data visualization, parallel processing, multithreading, and data saving. This paper introduces the basic features and system architecture of Craniux and describes the validation of the system under real-time BMI operation using simulated and real electrocorticographic (ECoG signals. Our results indicate that Craniux is able to operate consistently in real time, enabling a seamless work flow to achieve brain control of cursor movement. The Craniux software framework is made available to the scientific research community to provide a LabVIEW-based BMI software platform for future BMI research and development.

  20. Craniux: a LabVIEW-based modular software framework for brain-machine interface research.

    Science.gov (United States)

    Degenhart, Alan D; Kelly, John W; Ashmore, Robin C; Collinger, Jennifer L; Tyler-Kabara, Elizabeth C; Weber, Douglas J; Wang, Wei

    2011-01-01

    This paper presents "Craniux," an open-access, open-source software framework for brain-machine interface (BMI) research. Developed in LabVIEW, a high-level graphical programming environment, Craniux offers both out-of-the-box functionality and a modular BMI software framework that is easily extendable. Specifically, it allows researchers to take advantage of multiple features inherent to the LabVIEW environment for on-the-fly data visualization, parallel processing, multithreading, and data saving. This paper introduces the basic features and system architecture of Craniux and describes the validation of the system under real-time BMI operation using simulated and real electrocorticographic (ECoG) signals. Our results indicate that Craniux is able to operate consistently in real time, enabling a seamless work flow to achieve brain control of cursor movement. The Craniux software framework is made available to the scientific research community to provide a LabVIEW-based BMI software platform for future BMI research and development.

  1. Induction machine bearing faults detection based on a multi-dimensional MUSIC algorithm and maximum likelihood estimation.

    Science.gov (United States)

    Elbouchikhi, Elhoussin; Choqueuse, Vincent; Benbouzid, Mohamed

    2016-07-01

    Condition monitoring of electric drives is of paramount importance since it contributes to enhance the system reliability and availability. Moreover, the knowledge about the fault mode behavior is extremely important in order to improve system protection and fault-tolerant control. Fault detection and diagnosis in squirrel cage induction machines based on motor current signature analysis (MCSA) has been widely investigated. Several high resolution spectral estimation techniques have been developed and used to detect induction machine abnormal operating conditions. This paper focuses on the application of MCSA for the detection of abnormal mechanical conditions that may lead to induction machines failure. In fact, this paper is devoted to the detection of single-point defects in bearings based on parametric spectral estimation. A multi-dimensional MUSIC (MD MUSIC) algorithm has been developed for bearing faults detection based on bearing faults characteristic frequencies. This method has been used to estimate the fundamental frequency and the fault related frequency. Then, an amplitude estimator of the fault characteristic frequencies has been proposed and fault indicator has been derived for fault severity measurement. The proposed bearing faults detection approach is assessed using simulated stator currents data, issued from a coupled electromagnetic circuits approach for air-gap eccentricity emulating bearing faults. Then, experimental data are used for validation purposes.

  2. Effects of payment method on work control, work risk and work-related musculoskeletal health among sewing machine operators

    Directory of Open Access Journals (Sweden)

    R. Nawawi

    2015-12-01

    Full Text Available Effects of payment method on work control, work risk and work-related musculoskeletal health among sewing machine operators R. Nawawi1, B.M. Deros1*, D.D.I. Daruis2, A. Ramli3, R.M. Zein4 and L.H. Joseph3 1Dept. of Mechanical and Materials Engineering Faculty of Engineering & Built Environment Universiti Kebangsaan Malaysia, Malaysia *Email: hjbaba@ukm.edu.my 2Faculty of Engineering, Universiti Pertahanan Nasional Malaysia, Malaysia 3Department of Physiotherapy Faculty of Science, Lincoln University College, Malaysia 4Department of Consultation, Research & Development, National Institute of Occupational Safety and Health (NIOSH, Malaysia ABSTRACT This study aimed to identify payment method and its effects on work control, work risk and work-related musculoskeletal health among Malaysian sewing machine operators. The study sample comprised 337 sewing machine operators (male, n=122, female, n=215; aged between 18-54 years old; mean 30.74±8.44 from four different garment-making companies in Malaysia. They were being paid via time rate wages (n=246 and piece rate wages (n=91. Data was collected through Nordic Musculoskeletal Questionnaire and pen-and-paper assessment via Rapid Upper Limb Assessment (RULA. From the study, the piece rate wage group was found to take fewer breaks, had high work production demands, worked at a faster pace and experienced more exhaustion and pressure due to increasing work demands as compared to the time rate group. They were also observed working with higher physical exposure such as repetitive tasks, awkward static postures, awkward grips and hand movements, pulling, lifting and pushing as compared to those in the time rate wage group. The final RULA scores was also higher from the piece rate wage group (72.53% RULA score 7 which indicated higher work risks among them. The study found that the type of wage payment was significantly associated with work risks (p=0.036, df=1 and WRMSD at the shoulder, lower back

  3. Long term reliability and machine operation diagnosis with fiber optic sensors at large turbine generators

    Science.gov (United States)

    Bosselmann, T.; Strack, S.; Villnow, M.; Weidner, J. R.; Willsch, M.

    2013-05-01

    The increasing quantity of renewable energy in electric power generation leads to a higher flexibility in the operation of conventional power plants. The turbo generator has to face the influence of frequent start-stop-operation on thermal movement and vibration of the stator end windings. Large indirect cooled turbo generators have been equipped with FBG strain and temperature sensors to monitor the influence of peak load operation. Fiber optic accelerometers measure the vibration of the end windings at several turbine generators since many years of operation. The long term reliability of fiber optic vibration, temperature and strain sensors has been successfully proved during years of online operation. The analysis of these data in correlation to significant operation parameter lead to important diagnostic information.

  4. A survey of supervised machine learning models for mobile-phone based pathogen identification and classification

    Science.gov (United States)

    Ceylan Koydemir, Hatice; Feng, Steve; Liang, Kyle; Nadkarni, Rohan; Tseng, Derek; Benien, Parul; Ozcan, Aydogan

    2017-03-01

    Giardia lamblia causes a disease known as giardiasis, which results in diarrhea, abdominal cramps, and bloating. Although conventional pathogen detection methods used in water analysis laboratories offer high sensitivity and specificity, they are time consuming, and need experts to operate bulky equipment and analyze the samples. Here we present a field-portable and cost-effective smartphone-based waterborne pathogen detection platform that can automatically classify Giardia cysts using machine learning. Our platform enables the detection and quantification of Giardia cysts in one hour, including sample collection, labeling, filtration, and automated counting steps. We evaluated the performance of three prototypes using Giardia-spiked water samples from different sources (e.g., reagent-grade, tap, non-potable, and pond water samples). We populated a training database with >30,000 cysts and estimated our detection sensitivity and specificity using 20 different classifier models, including decision trees, nearest neighbor classifiers, support vector machines (SVMs), and ensemble classifiers, and compared their speed of training and classification, as well as predicted accuracies. Among them, cubic SVM, medium Gaussian SVM, and bagged-trees were the most promising classifier types with accuracies of 94.1%, 94.2%, and 95%, respectively; we selected the latter as our preferred classifier for the detection and enumeration of Giardia cysts that are imaged using our mobile-phone fluorescence microscope. Without the need for any experts or microbiologists, this field-portable pathogen detection platform can present a useful tool for water quality monitoring in resource-limited-settings.

  5. Adaptive Control of Machine-Tool Vibration Based on an Active Tool Holder Shank with an Embedded Piezo Ceramic Actuator

    OpenAIRE

    Pettersson, Linus; Håkansson, Lars; Claesson, Ingvar; Olsson, Sven

    2001-01-01

    In the turning operation chatter or vibration is a common problem affecting the result of the machining, and, in particular, the surface finish. Tool life is also influenced by vibration. Severe acoustic noise in the working environment frequently occurs as a result of dynamic motion between the cutting tool and the workpiece. These problems can be reduced by active control of machine-tool vibration. However, machine-tool vibration control systems are usually not applicable to a general lathe...

  6. Predictive Models of Work-Related Musculoskeletal Disorders (WMSDs Among Sewing Machine Operators in the Garments Industry

    Directory of Open Access Journals (Sweden)

    Carlos Ignacio P. Lugay

    2015-02-01

    Full Text Available The Philippine garments industry has been a driving force in the country’s economy, with apparel manufacturing firms catering to the local and global markets and providing employment opportunities for skilled Filipinos. Tight competition from neighboring Asian countries however, has made the industry’s situation difficult to flourish, especially in the wake of the Association of Southeast Asian Nations (ASEAN 2015 Integration. To assist the industry, this research examined one of the more common problems among sewing machine operators, termed as Work-related Musculoskeletal Disorders (WMSDs. These disorders are reflective in the frequency and severity of the pain experienced by the sewers while accomplishing their tasks. The causes of these disorders were identified and were correlated with the frequency and severity of pain in various body areas of the operator. To forecast pain from WMSDs among the operators, mathematical models were developed to predict the combined frequency and severity of the pain from WMSDs. Loss time or “unofficial breaktimes” due to pain from WMSDs was likewise forecasted to determine its effects on the firm’s production capacity. Both these predictive models were developed in order to assist garment companies in anticipating better the effects of WMSDs and loss time in their operations. Moreover, ergonomic interventions were suggested to minimize pain from WMSDs, with the expectation of increased productivity of the operators and improved quality of their outputs.

  7. The Designed Operation of the Machine Control System on HL-2A Tokamak

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    The Ethernet and field-bus communications are used in the machine control system (MCS) of HL-2A. The control net, with a programmable logic controller (PLC) as its logic control master, an engineering control management station as its net server, and a timing control PC connected to a number of terminals, flexibly and freely transfers information among the nodes on it with the Ethernet transmission techniques. The PLC masters the field bus, which carries small pieces of information between PLC and the field sites reliably and quickly. The control net is connected into the data net, where Internet access and sharing of more experimental data are enabled. The communication in the MCS guarantees the digitalization, automation and centralization. Also provided are a satisfactory degree of safety, reliability, stability, expandability and flexibility for maintenance.

  8. Lithium-ion battery remaining useful life prediction based on grey support vector machines

    Directory of Open Access Journals (Sweden)

    Xiaogang Li

    2015-12-01

    Full Text Available In this article, an improved grey prediction model is proposed to address low-accuracy prediction issue of grey forecasting model. The first step is using a trigonometric function to transform the original data sequence to smooth the data, which is called smoothness of grey prediction model, and then a grey support vector machine model by integrating the improved grey model with support vector machine is introduced. At the initial stage of the model, trigonometric functions and accumulation generation operation can be used to preprocess the data, which enhances the smoothness of the data and reduces the associated randomness. In addition, support vector machine is implemented to establish a prediction model for the pre-processed data and select the optimal model parameters via genetic algorithms. Finally, the data are restored through the ‘regressive generate’ operation to obtain the forecasting data. To prove that the grey support vector machine model is superior to the other models, the battery life data from the Center for Advanced Life Cycle Engineering are selected, and the presented model is used to predict the remaining useful life of the battery. The predicted result is compared to that of grey model and support vector machines. For a more intuitive comparison of the three models, this article quantifies the root mean square errors for these three different models in the case of different ratio of training samples and prediction samples. The results show that the effect of grey support vector machine model is optimal, and the corresponding root mean square error is only 3.18%.

  9. Network Intrusion Detection System Based On Machine Learning Algorithms

    Directory of Open Access Journals (Sweden)

    Vipin Das

    2010-12-01

    Full Text Available Network and system security is of paramount importance in the present data communication environment. Hackers and intruders can create many successful attempts to cause the crash of the networks and web services by unauthorized intrusion. New threats and associated solutions to prevent these threats are emerging together with the secured system evolution. Intrusion Detection Systems (IDS are one of these solutions. The main function of Intrusion Detection System is to protect the resources from threats. It analyzes and predicts the behaviours of users, and then these behaviours will be considered an attack or a normal behaviour. We use Rough Set Theory (RST and Support Vector Machine (SVM to detect network intrusions. First, packets are captured from the network, RST is used to pre-process the data and reduce the dimensions. The features selected by RST will be sent to SVM model to learn and test respectively. The method is effective to decrease the space density of data. The experiments compare the results with Principal Component Analysis (PCA and show RST and SVM schema could reduce the false positive rate and increase the accuracy.

  10. Small-time scale network traffic prediction based on a local support vector machine regression model

    Institute of Scientific and Technical Information of China (English)

    Meng Qing-Fang; Chen Yue-Hui; Peng Yu-Hua

    2009-01-01

    In this paper we apply the nonlinear time series analysis method to small-time scale traffic measurement data. The prediction-based method is used to determine the embedding dimension of the traffic data. Based on the reconstructed phase space, the local support vector machine prediction method is used to predict the traffic measurement data, and the BIC-based neighbouring point selection method is used to choose the number of the nearest neighbouring points for the local support vector machine regression model. The experimental results show that the local support vector machine prediction method whose neighbouring points are optimized can effectively predict the small-time scale traffic measurement data and can reproduce the statistical features of real traffic measurements.

  11. The deleuzian abstract machines

    DEFF Research Database (Denmark)

    Werner Petersen, Erik

    2005-01-01

    production. In Kafka: Toward a Minor Literature, Deleuze and Guatari gave the most comprehensive explanation to the abstract machine in the work of art. Like the war-machines of Virilio, the Kafka-machine operates in three gears or speeds. Furthermore, the machine is connected to spatial diagrams...

  12. Information theory-based approach for modeling the cognitive behavior of NPP operators

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Jong Hyun; Seong, Poong Hyun [KAIST, Taejon (Korea, Republic of)

    2001-10-01

    An NPP system consists of three important components: the machine system, operators, and MMI. Through the MMI, operators monitor and control the plant system. The cognitive model of NPP operators has become a target of modeling by cognitive engineers due to their work environment: complex, uncertain, and safe critical. We suggested the contextual model for the cognitive behavior of NPP operator and the mathematical fundamentals based on information theory which can quantify the model. The demerit of the methodology using the information theory is that it cannot evaluate the correctness and quality of information. Therefore, the validation through the experiment is needed.

  13. Translating DVD Subtitles English-German, English-Japanese, Using Example-based Machine Translation

    DEFF Research Database (Denmark)

    Armstrong, Stephen; Caffrey, Colm; Flanagan, Marian

    2006-01-01

    Due to limited budgets and an ever-diminishing time-frame for the production of subtitles for movies released in cinema and DVD, there is a compelling case for a technology-based translation solution for subtitles. In this paper we describe how an Example-Based Machine Translation (EBMT) approach...

  14. Support vector machine-based open crop model (SBOCM): Case of rice production in China.

    Science.gov (United States)

    Su, Ying-Xue; Xu, Huan; Yan, Li-Jiao

    2017-03-01

    Existing crop models produce unsatisfactory simulation results and are operationally complicated. The present study, however, demonstrated the unique advantages of statistical crop models for large-scale simulation. Using rice as the research crop, a support vector machine-based open crop model (SBOCM) was developed by integrating developmental stage and yield prediction models. Basic geographical information obtained by surface weather observation stations in China and the 1:1000000 soil database published by the Chinese Academy of Sciences were used. Based on the principle of scale compatibility of modeling data, an open reading frame was designed for the dynamic daily input of meteorological data and output of rice development and yield records. This was used to generate rice developmental stage and yield prediction models, which were integrated into the SBOCM system. The parameters, methods, error resources, and other factors were analyzed. Although not a crop physiology simulation model, the proposed SBOCM can be used for perennial simulation and one-year rice predictions within certain scale ranges. It is convenient for data acquisition, regionally applicable, parametrically simple, and effective for multi-scale factor integration. It has the potential for future integration with extensive social and economic factors to improve the prediction accuracy and practicability.

  15. Support vector machine-based open crop model (SBOCM: Case of rice production in China

    Directory of Open Access Journals (Sweden)

    Ying-xue Su

    2017-03-01

    Full Text Available Existing crop models produce unsatisfactory simulation results and are operationally complicated. The present study, however, demonstrated the unique advantages of statistical crop models for large-scale simulation. Using rice as the research crop, a support vector machine-based open crop model (SBOCM was developed by integrating developmental stage and yield prediction models. Basic geographical information obtained by surface weather observation stations in China and the 1:1000000 soil database published by the Chinese Academy of Sciences were used. Based on the principle of scale compatibility of modeling data, an open reading frame was designed for the dynamic daily input of meteorological data and output of rice development and yield records. This was used to generate rice developmental stage and yield prediction models, which were integrated into the SBOCM system. The parameters, methods, error resources, and other factors were analyzed. Although not a crop physiology simulation model, the proposed SBOCM can be used for perennial simulation and one-year rice predictions within certain scale ranges. It is convenient for data acquisition, regionally applicable, parametrically simple, and effective for multi-scale factor integration. It has the potential for future integration with extensive social and economic factors to improve the prediction accuracy and practicability.

  16. Time series online prediction algorithm based on least squares support vector machine

    Institute of Scientific and Technical Information of China (English)

    WU Qiong; LIU Wen-ying; YANG Yi-han

    2007-01-01

    Deficiencies of applying the traditional least squares support vector machine (LS-SVM) to time series online prediction were specified. According to the kernel function matrix's property and using the recursive calculation of block matrix, a new time series online prediction algorithm based on improved LS-SVM was proposed. The historical training results were fully utilized and the computing speed of LS-SVM was enhanced. Then, the improved algorithm was applied to time series online prediction. Based on the operational data provided by the Northwest Power Grid of China, the method was used in the transient stability prediction of electric power system. The results show that, compared with the calculation time of the traditional LS-SVM(75-1 600 ms), that of the proposed method in different time windows is 40-60 ms, and the prediction accuracy(normalized root mean squared error) of the proposed method is above 0.8. So the improved method is better than the traditional LS-SVM and more suitable for time series online prediction.

  17. A New Automated Design Method Based on Machine Learning for CMOS Analog Circuits

    Science.gov (United States)

    Moradi, Behzad; Mirzaei, Abdolreza

    2016-11-01

    A new simulation based automated CMOS analog circuit design method which applies a multi-objective non-Darwinian-type evolutionary algorithm based on Learnable Evolution Model (LEM) is proposed in this article. The multi-objective property of this automated design of CMOS analog circuits is governed by a modified Strength Pareto Evolutionary Algorithm (SPEA) incorporated in the LEM algorithm presented here. LEM includes a machine learning method such as the decision trees that makes a distinction between high- and low-fitness areas in the design space. The learning process can detect the right directions of the evolution and lead to high steps in the evolution of the individuals. The learning phase shortens the evolution process and makes remarkable reduction in the number of individual evaluations. The expert designer's knowledge on circuit is applied in the design process in order to reduce the design space as well as the design time. The circuit evaluation is made by HSPICE simulator. In order to improve the design accuracy, bsim3v3 CMOS transistor model is adopted in this proposed design method. This proposed design method is tested on three different operational amplifier circuits. The performance of this proposed design method is verified by comparing it with the evolutionary strategy algorithm and other similar methods.

  18. Quantify work load and muscle functional activation patterns in neck-shoulder muscles of female sewing machine operators using surface electromyogram.

    Science.gov (United States)

    Zhang, Fei-Ruo; He, Li-Hua; Wu, Shan-Shan; Li, Jing-Yun; Ye, Kang-Pin; Wang, Sheng

    2011-11-01

    Work-related musculoskeletal disorders (WMSDs) have high prevalence in sewing machine operators employed in the garment industry. Long work duration, sustained low level work and precise hand work are the main risk factors of neck-shoulder disorders for sewing machine operators. Surface electromyogram (sEMG) offers a valuable tool to determine muscle activity (internal exposure) and quantify muscular load (external exposure). During sustained and/or repetitive muscle contractions, typical changes of muscle fatigue in sEMG, as an increase in amplitude or a decrease as a shift in spectrum towards lower frequencies, can be observed. In this paper, we measured and quantified the muscle load and muscular activity patterns of neck-shoulder muscles in female sewing machine operators during sustained sewing machine operating tasks using sEMG. A total of 18 healthy women sewing machine operators volunteered to participate in this study. Before their daily sewing machine operating task, we measured the maximal voluntary contractions (MVC) and 20%MVC of bilateral cervical erector spinae (CES) and upper trapezius (UT) respectively, then the sEMG signals of bilateral UT and CES were monitored and recorded continuously during 200 minutes of sustained sewing machine operating simultaneously which equals to 20 time windows with 10 minutes as one time window. After 200 minutes' work, we retest 20%MVC of four neck-shoulder muscles and recorded the sEMG signals. Linear analysis, including amplitude probability distribution frequency (APDF), amplitude analysis parameters such as roof mean square (RMS) and spectrum analysis parameter as median frequency (MF), were used to calculate and indicate muscle load and muscular activity of bilateral CES and UT. During 200 minutes of sewing machine operating, the median load for the left cervical erector spinae (LCES), right cervical erector spinae (RCES), left upper trapezius (LUT) and right upper trapezius (RUT) were 6.78%MVE, 6.94%MVE, 6

  19. The Machine within the Machine

    CERN Multimedia

    Katarina Anthony

    2014-01-01

    Although Virtual Machines are widespread across CERN, you probably won't have heard of them unless you work for an experiment. Virtual machines - known as VMs - allow you to create a separate machine within your own, allowing you to run Linux on your Mac, or Windows on your Linux - whatever combination you need.   Using a CERN Virtual Machine, a Linux analysis software runs on a Macbook. When it comes to LHC data, one of the primary issues collaborations face is the diversity of computing environments among collaborators spread across the world. What if an institute cannot run the analysis software because they use different operating systems? "That's where the CernVM project comes in," says Gerardo Ganis, PH-SFT staff member and leader of the CernVM project. "We were able to respond to experimentalists' concerns by providing a virtual machine package that could be used to run experiment software. This way, no matter what hardware they have ...

  20. A Web-based machining process monitoring system for E-manufacturing implementation

    Institute of Scientific and Technical Information of China (English)

    SHIN Bong-cheol; KIM Gun-hee; CHOI Jin-hwa; JEON Byung-cheol; LEE Honghee; CHO Myeong-woo; HAN Jin-yong; PARK Dong-sam

    2006-01-01

    Recently, with the rapid growth ofinformation technology, many studies have been performed to implement Web-based manufacturing system. Such technologies are expected to meet the need of many manufacturing industries who want to adopt E-manufacturing system for the construction of globalization, agility, and digitalization to cope with the rapid changing market requirements. In this research, a real-time Web-based machine tool and machining process monitoring system is developed as the first step for implementing E-manufacturing system. In this system, the current variations of the main spindle and feeding motors are measured using hall sensors. And the relationship between the cutting force and the spindle motor RMS (Root Mean Square) current at various spindle rotational speeds is obtained. Thermocouples are used to measure temperature variations of important heat sources of a machine tool. Also, a rule-based expert system is applied in order to decide the machining process and machine tool are in normal conditions. Finally, the effectiveness of the developed system is verified through a series of experiments.

  1. A decomposition heuristics based on multi-bottleneck machines for large-scale job shop scheduling problems

    Directory of Open Access Journals (Sweden)

    Yingni Zhai

    2014-10-01

    Full Text Available Purpose: A decomposition heuristics based on multi-bottleneck machines for large-scale job shop scheduling problems (JSP is proposed.Design/methodology/approach: In the algorithm, a number of sub-problems are constructed by iteratively decomposing the large-scale JSP according to the process route of each job. And then the solution of the large-scale JSP can be obtained by iteratively solving the sub-problems. In order to improve the sub-problems' solving efficiency and the solution quality, a detection method for multi-bottleneck machines based on critical path is proposed. Therewith the unscheduled operations can be decomposed into bottleneck operations and non-bottleneck operations. According to the principle of “Bottleneck leads the performance of the whole manufacturing system” in TOC (Theory Of Constraints, the bottleneck operations are scheduled by genetic algorithm for high solution quality, and the non-bottleneck operations are scheduled by dispatching rules for the improvement of the solving efficiency.Findings: In the process of the sub-problems' construction, partial operations in the previous scheduled sub-problem are divided into the successive sub-problem for re-optimization. This strategy can improve the solution quality of the algorithm. In the process of solving the sub-problems, the strategy that evaluating the chromosome's fitness by predicting the global scheduling objective value can improve the solution quality.Research limitations/implications: In this research, there are some assumptions which reduce the complexity of the large-scale scheduling problem. They are as follows: The processing route of each job is predetermined, and the processing time of each operation is fixed. There is no machine breakdown, and no preemption of the operations is allowed. The assumptions should be considered if the algorithm is used in the actual job shop.Originality/value: The research provides an efficient scheduling method for the

  2. 29 CFR 570.62 - Occupations involved in the operation of bakery machines (Order 11).

    Science.gov (United States)

    2010-07-01

    ... as prohibited by § 570.61(a)(4). (2) This section shall not apply to the operation of pizza-dough... exception does not apply to the setting up, adjusting, repairing, oiling or cleaning of such...

  3. 14 CFR 119.47 - Maintaining a principal base of operations, main operations base, and main maintenance base...

    Science.gov (United States)

    2010-01-01

    ... 14 Aeronautics and Space 3 2010-01-01 2010-01-01 false Maintaining a principal base of operations, main operations base, and main maintenance base; change of address. 119.47 Section 119.47 Aeronautics... operations base, and main maintenance base; change of address. (a) Each certificate holder must maintain...

  4. An Identification Model of Health States of Machine Wear Based on Oil Analysis

    Institute of Scientific and Technical Information of China (English)

    FU Jun-qing; LI Han-xiong; XUAO Xin-hua

    2005-01-01

    This paper presents a modeling procedure for deriving a single value measure based on a regression model, and a method for determining a statistical threshold value as identification criterion of normal or abnormal states of machine wear. A real numerical example is examined by the method and identification criterion presented. The results indicate that the judgments by the presented methods are basically consistent with the real facts, and therefore the method and identification criterion are valuable for judging the normal or abnormal state of machine wear based on oil analysis.

  5. Gear Fault Diagnosis Based on Rough Set and Support Vector Machine

    Institute of Scientific and Technical Information of China (English)

    TIAN Huifang; SUN Shanxia

    2006-01-01

    By introducing Rough Set Theory and the principle of Support vector machine, a gear fault diagnosis method based on them is proposed. Firstly, diagnostic decision-making is reduced based on rough set theory, and the noise and redundancy in the sample are removed, then, according to the chosen reduction, a support vector machine multi-classifier is designed for gear fault diagnosis. Therefore, SVM' training data can be reduced and running speed can quicken. Test shows its accuracy and efficiency of gear fault diagnosis.

  6. Modelling rollover behaviour of exacavator-based forest machines

    Science.gov (United States)

    M.W. Veal; S.E. Taylor; Robert B. Rummer

    2003-01-01

    This poster presentation provides results from analytical and computer simulation models of rollover behaviour of hydraulic excavators. These results are being used as input to the operator protective structure standards development process. Results from rigid body mechanics and computer simulation methods agree well with field rollover test data. These results show...

  7. Passivity-based control of a class of Blondel-Park transformable electric machines

    Energy Technology Data Exchange (ETDEWEB)

    Nicklasson, Per J.; Ortega, Romeo; Espinosa-Perez, Gerardo

    1997-12-31

    The publication presents a study of the viability of extending, to the general rotating electric machine`s model, the passivity-based controller method developed for induction motors. In this approach, the passivity (energy dissipation) properties of the motor are taken advantage of at two different levels. First, there is proved that the motor model can be decomposed as the feedback interconnection of two passive subsystems, which can essentially be identified with the electrical and mechanical dynamics. Then, a torque tracking controller is designed that preserves passivity for the electrical subsystem, and leave the mechanical part as a ``passive disturbance``. In position or speed control applications this procedure naturally leads to the well known cascaded controller structure which is typically analyzed invoking time-scale separation assumptions. A key future of the new cascaded control paradigm is that the latter arguments are obviated in the stability analysis. The objective in this publication is to characterize a class of machines for which such a passivity-based controller solves the output feedback torque tracking problem. Roughly, the class consists of machines whose non-actuated dynamics are well damped and whose electrical and mechanical dynamics can be suitably decoupled via a coordinate transformation. The first condition translates into the requirement of approximate knowledge of the rotor resistances to avoid the need of injecting high gain into the loop. The latter condition is known in the electric machines literature as Blonded-Park transformability, and in practical terms it requires that the air-gap magnetomotive force must be suitably approximated by the first harmonic in its Fourier expansion. These conditions have a clear physical interpretation in terms of the couplings between its electrical, magnetic and mechanical dynamics, and are satisfied by a large number of practical machines. The controller mentioned reduces to the well known

  8. A novel approach to predict surface roughness in machining operations using fuzzy set theory

    Directory of Open Access Journals (Sweden)

    Tzu-Liang (Bill Tseng

    2016-01-01

    Full Text Available The increase of consumer needs for quality metal cutting related products with more precise tolerances and better product surface roughness has driven the metal cutting industry to continuously improve quality control of metal cutting processes. In this paper, two different approaches are discussed. First, design of experiments (DOE is used to determine the significant factors and then fuzzy logic approach is presented for the prediction of surface roughness. The data used for the training and checking the fuzzy logic performance is derived from the experiments conducted on a CNC milling machine. In order to obtain better surface roughness, the proper sets of cutting parameters are determined before the process takes place. The factors considered for DOE in the experiment were the depth of cut, feed rate per tooth, cutting speed, tool nose radius, the use of cutting fluid and the three components of the cutting force. Finally the significant factors were used as input factors for fuzzy logic mechanism and surface roughness is predicted with empirical formula developed. Test results show good agreement between the actual process output and the predicted surface roughness.

  9. Phase-locked loop based on machine surface topography measurement using lensed fibers

    Energy Technology Data Exchange (ETDEWEB)

    Kang, Jin-Ho; Lee, ChaBum; Joo, Jae-Young; Lee, Sun-Kyu

    2011-02-01

    We present the phase-locked loop (PLL)-based metrology concept using lensed fibers for on-machine surface topography measurement. The shape of a single-mode fiber at the endface was designed using an ABCD matrix method, and two designed lensed fibers--the ball type and the tapered type--were fabricated, and the performance was evaluated, respectively. As a result, the interferometric fringe was not found in the case of the ball lensed fiber, but the machined surface could be measured by utilization of autofocusing and intensity methods. On the other hand, a very clear Fizeau interferometric fringe was observed in the case of the tapered lensed fiber. Its performance was compared with the results of the capacitance sensor and a commercially available white-light interferometer. We confirmed that PLL-based surface profile measurement using the tapered and ball lensed fibers can be applied for on-machine surface topography measurement applications.

  10. An information theory based approach for quantitative evaluation of man-machine interface complexity

    Energy Technology Data Exchange (ETDEWEB)

    Kang, Hyun Gook

    1999-02-15

    In complex and high-risk work conditions, especially such as in nuclear power plants, human understanding of the plant is highly cognitive and thus largely dependent on the effectiveness of the man-machine interface system. In order to provide more effective and reliable operating conditions for future nuclear power plants, developing more credible and easy to use evaluation methods will afford great help in designing interface systems in a more efficient manner. In this study, in order to analyze the human-machine interactions, I propose the Human-processor Communication(HPC) model which is based on the information flow concept. It identifies the information flow around a human-processor. Information flow has two aspects: appearance and content. Based on the HPC model, I propose two kinds of measures for evaluating a user interface from the viewpoint of these two aspects of information flow. They measure the communicative complexity of each aspect. In this study, for the evaluation of the aspect of appearance, I propose three complexity measures: Operation Complexity, Transition Complexity, and Screen Complexity. Each one of these measures has its own physical meaning. Two experiments carried out in this work support the utility of these measures. The result of the quiz game experiment shows that as the complexity of task context increases, the usage of the interface system becomes more complex. The experimental results of the three example systems(digital view, LDP style view and hierarchy view) show the utility of the proposed complexity measures. In this study, for the evaluation of the aspect of content, I propose the degree of informational coincidence, R (K, P) as a measure for the usefulness of an alarm-processing system. It is designed to perform user-oriented evaluation based on the informational entropy concept. It will be especially useful inearly design phase because designers can estimate the usefulness of an alarm system by short calculations instead

  11. 退役机床再制造整机性能综合提升方案%Design of machine-based comprehensive upgrading scheme for machine tool remanufacturing

    Institute of Scientific and Technical Information of China (English)

    杜彦斌; 李智明

    2014-01-01

    At present ,there are lots of used machine tools in China which need to be remanufactured to restore and enhance their performance as well as meet the ever-increasing processing requirements at a low cost .Compared with existing maintenance or NC transformation of machine tools ,machine tool remanufacturing can not only restore used ones to normal operation ,but also upgrade machine performance and endow a new life cycle to used machine tools .The machine-based comprehensive upgrading scheme for machine tool remanufacturing is presented from the aspects of energy-saving,environmental friendliness and information function . The technical path and technical solutions are proposed .In addition ,the implementation effects of machine tool upgrading are il-lustrated with the case of lathe and gear hobbing machine remanufacturing .%目前,我国存在大量的退役机床迫切需要实施再制造来恢复并提升其性能水平,以便低成本、绿色化地满足不断提高的零/部件加工要求。机床再制造与已有的维修、数控化改造相比,最重要的区别是其不仅仅恢复退役机床的性能使其正常运转,还要实现机床整机性能的综合提升,重新赋予退役机床新的生命周期。从节能性、环境友好性和信息化等方面,对退役机床再制造整机性能提升方案进行分析,阐述相关的技术路径与技术方案;以车床、滚齿机再制造为例,对相关方案实施效果进行分析。

  12. THE FUZZY LOGIC BASED POWER INJECTION INTO ROTOR CIRCUIT FOR INSTANTANEOUS HIGH TORQUE AND SPEED CONTROL IN INDUCTION MACHINES

    Directory of Open Access Journals (Sweden)

    Selami KESLER

    2009-01-01

    Full Text Available The power flow of the rotor circuit is controlled by different methods in induction machines used for producing high torque in applications involved great power and constant output power with constant frequency in wind turbines. The voltage with slip frequency can be applied on rotor windings to produce controlled high torque and obtain optimal power factor and speed control. In this study, firstly, the dynamic effects of the voltage applying on rotor windings through the rings in slip-ring induction machines are researched and undesirable aspects of the method are exposed with simulations supported by experiments. Afterwards, a fuzzy logic based inverter model on rotor side is proposed with a view to improving the dynamic effects, controlling high torque producing and adjusting machine speed in instantaneous forced conditions. For the simulation model of the system in which the stator side is directly connected to the grid in steady state operation, a C/C++ algorithm is developed and the results obtained for different load conditions are discussed.

  13. 无刷双馈电机电动状态下的能量分析%Power flow in brushless doubly-fed machine under motor operation

    Institute of Scientific and Technical Information of China (English)

    章玮

    2000-01-01

    无刷双馈电机作为一种新颖电机,无论是电机结构还是运行特性都有其特殊性。从电机稳态模型出发,分析了无刷双馈电机作为调速电动机在各种不同转速范围内定、转子间的能量传递关系,为无刷双馈电机的绕组容量设计以及变频器容量的选择方面提供依据。%As a new type motor,Brushless Double-Fed Machine(BDFM) has shown specialties in its structure and operational characteristic.Based on theN steady-state model of the BDFM,this paper discusses the power flow in the two stator windings and the rotor circuit under different speed ranges.The results obtained offer the theoretical basis for machine's de-sign and selecting the capacity of converter.

  14. Quanwei Copper Processing Base Put Into Operation

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    <正>Quanwei (Tongling) Copper Co.,Ltd’s copper processing base in Tongling of Anhui Province has been put into operation at the end of De- cember last year. It is reported that the copper processing project, invested by Zhengwei (Shenzhen) Technology

  15. DROUGHT FORECASTING BASED ON MACHINE LEARNING OF REMOTE SENSING AND LONG-RANGE FORECAST DATA

    Directory of Open Access Journals (Sweden)

    J. Rhee

    2016-06-01

    Full Text Available The reduction of drought impacts may be achieved through sustainable drought management and proactive measures against drought disaster. Accurate and timely provision of drought information is essential. In this study, drought forecasting models to provide high-resolution drought information based on drought indicators for ungauged areas were developed. The developed models predict drought indices of the 6-month Standardized Precipitation Index (SPI6 and the 6-month Standardized Precipitation Evapotranspiration Index (SPEI6. An interpolation method based on multiquadric spline interpolation method as well as three machine learning models were tested. Three machine learning models of Decision Tree, Random Forest, and Extremely Randomized Trees were tested to enhance the provision of drought initial conditions based on remote sensing data, since initial conditions is one of the most important factors for drought forecasting. Machine learning-based methods performed better than interpolation methods for both classification and regression, and the methods using climatology data outperformed the methods using long-range forecast. The model based on climatological data and the machine learning method outperformed overall.

  16. Support vector machine based fault detection approach for RFT-30 cyclotron

    Science.gov (United States)

    Kong, Young Bae; Lee, Eun Je; Hur, Min Goo; Park, Jeong Hoon; Park, Yong Dae; Yang, Seung Dae

    2016-10-01

    An RFT-30 is a 30 MeV cyclotron used for radioisotope applications and radiopharmaceutical researches. The RFT-30 cyclotron is highly complex and includes many signals for control and monitoring of the system. It is quite difficult to detect and monitor the system failure in real time. Moreover, continuous monitoring of the system is hard and time-consuming work for human operators. In this paper, we propose a support vector machine (SVM) based fault detection approach for the RFT-30 cyclotron. The proposed approach performs SVM learning with training samples to construct the classification model. To compensate the system complexity due to the large-scale accelerator, we utilize the principal component analysis (PCA) for transformation of the original data. After training procedure, the proposed approach detects the system faults in real time. We analyzed the performance of the proposed approach utilizing the experimental data of the RFT-30 cyclotron. The performance results show that the proposed SVM approach can provide an efficient way to control the cyclotron system.

  17. Human-Assisted Machine Information Exploitation: a crowdsourced investigation of information-based problem solving

    Science.gov (United States)

    Kase, Sue E.; Vanni, Michelle; Caylor, Justine; Hoye, Jeff

    2017-05-01

    The Human-Assisted Machine Information Exploitation (HAMIE) investigation utilizes large-scale online data collection for developing models of information-based problem solving (IBPS) behavior in a simulated time-critical operational environment. These types of environments are characteristic of intelligence workflow processes conducted during human-geo-political unrest situations when the ability to make the best decision at the right time ensures strategic overmatch. The project takes a systems approach to Human Information Interaction (HII) by harnessing the expertise of crowds to model the interaction of the information consumer and the information required to solve a problem at different levels of system restrictiveness and decisional guidance. The design variables derived from Decision Support Systems (DSS) research represent the experimental conditions in this online single-player against-the-clock game where the player, acting in the role of an intelligence analyst, is tasked with a Commander's Critical Information Requirement (CCIR) in an information overload scenario. The player performs a sequence of three information processing tasks (annotation, relation identification, and link diagram formation) with the assistance of `HAMIE the robot' who offers varying levels of information understanding dependent on question complexity. We provide preliminary results from a pilot study conducted with Amazon Mechanical Turk (AMT) participants on the Volunteer Science scientific research platform.

  18. OPTIMIZATION OF OPERATING PARAMETERS FOR EDM PROCESS BASED ON THE TAGUCHI METHOD AND ARTIFICIAL NEURAL NETWORK

    OpenAIRE

    A.Thillaivanan,; P. Asokan,; K.N.Srinivasan,; Saravanan, R.

    2010-01-01

    In this paper the complexity of electrical discharge machining process which is very difficult to determine optimal cutting parameters for improving cutting performance has been reported. Optimization of operating parameters is an important step in machining, particularly for operating unconventional machiningprocedure like EDM. A suitable selection of machining parameters for the electrical discharge machining process relies heavily on the operators’ technologies and experience because of th...

  19. A Coherent Ising Machine Based On Degenerate Optical Parametric Oscillators

    Science.gov (United States)

    Wang, Zhe; Marandi, Alireza; Wen, Kai; Byer, Robert L.; Yamamoto, Yoshihisa

    2014-03-01

    A degenerate optical parametric oscillator network is proposed to solve the NP-hard problem of finding a ground state of the Ising model. The underlying operating mechanism originates from the bistable output phase of each oscillator and the inherent preference of the network in selecting oscillation modes with the minimum photon decay rate. Computational experiments are performed on all instances reducible to the NP-hard MAX-CUT problems on cubic graphs of order up to 20. The numerical results reasonably suggest the effectiveness of the proposed network. This project is supported by the FIRST program of Japanese Government. Zhe Wang is also grateful for the support from Stanford Graduate Fellowship.

  20. Machine Learning Based Classification of Microsatellite Variation: An Effective Approach for Phylogeographic Characterization of Olive Populations.

    Science.gov (United States)

    Torkzaban, Bahareh; Kayvanjoo, Amir Hossein; Ardalan, Arman; Mousavi, Soraya; Mariotti, Roberto; Baldoni, Luciana; Ebrahimie, Esmaeil; Ebrahimi, Mansour; Hosseini-Mazinani, Mehdi

    2015-01-01

    Finding efficient analytical techniques is overwhelmingly turning into a bottleneck for the effectiveness of large biological data. Machine learning offers a novel and powerful tool to advance classification and modeling solutions in molecular biology. However, these methods have been less frequently used with empirical population genetics data. In this study, we developed a new combined approach of data analysis using microsatellite marker data from our previous studies of olive populations using machine learning algorithms. Herein, 267 olive accessions of various origins including 21 reference cultivars, 132 local ecotypes, and 37 wild olive specimens from the Iranian plateau, together with 77 of the most represented Mediterranean varieties were investigated using a finely selected panel of 11 microsatellite markers. We organized data in two '4-targeted' and '16-targeted' experiments. A strategy of assaying different machine based analyses (i.e. data cleaning, feature selection, and machine learning classification) was devised to identify the most informative loci and the most diagnostic alleles to represent the population and the geography of each olive accession. These analyses revealed microsatellite markers with the highest differentiating capacity and proved efficiency for our method of clustering olive accessions to reflect upon their regions of origin. A distinguished highlight of this study was the discovery of the best combination of markers for better differentiating of populations via machine learning models, which can be exploited to distinguish among other biological populations.

  1. 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.

  2. The machinability of nickel-based alloys in high-pressure jet assisted (HPJA turning

    Directory of Open Access Journals (Sweden)

    D. Kramar

    2013-10-01

    Full Text Available Due to their mechanical, thermal and chemical properties, nickel-based alloys are generally included among materials that are hard to machine. An experimental study has been performed to investigate the capabilities of conventional and high-pressure jet assisted (HPJA turning of hard-to-machine materials, namely Inconel 718. The capabilities of different hard turning procedures are compared by means of chip breakability. The obtained results show that HPJA method offers a significant increase in chip breakability, under the same cutting conditions (cutting speed, feed rate, depth of cut.

  3. A Comparative Performance Analysis of FDM Machines Based on a Calibration Artefact

    DEFF Research Database (Denmark)

    D'Angelo, Greta; Nielsen, Jakob Skov; Rasmussen, Jeppe

    2014-01-01

    During the past ten years Additive Manufacturing (AM) technologies have been constantly developing in terms of materials and processes. This allows the use of the AM not only during the preproduction but also for the manufacturing of final components for commercial use [1], [2]. However one...... and there are no standards to compare them with. To overcome this problem, a method to evaluate the performance of AM machine tools based on the printing of an artefact and the subsequent measuring of its features is proposed and shown. This paper shows a validation of the method by means of a laser interferometer....... Furthermore, different AM machines are tested using the printed artefact....

  4. A Scheduling System Based on Rules of the Machine Tools in FMS

    Institute of Scientific and Technical Information of China (English)

    LI De-xin; ZHAO Hua-qun; JIA Jie; LU Yan-jun

    2003-01-01

    In this paper, a model of the scheduling of machine tools in the flexible manufacturing line is presented by intensive analysis and research of the mathematical method of traditional scheduling. The various factors correlative with machine tools in the flexible manufacturing line are fully considered in this system. Aiming at this model, an intelligent decision system based on rules and simulation technolo-gy integration is constructed by using the OOP ( Object-Orented Programming) method, and the simula-tion experiment analysis is carried out. It is shown from the results that the model is better in practice.

  5. An Investigation into Error Source Identification of Machine Tools Based on Time-Frequency Feature Extraction

    Directory of Open Access Journals (Sweden)

    Dongju Chen

    2016-01-01

    Full Text Available This paper presents a new identification method to identify the main errors of the machine tool in time-frequency domain. The low- and high-frequency signals of the workpiece surface are decomposed based on the Daubechies wavelet transform. With power spectral density analysis, the main features of the high-frequency signal corresponding to the imbalance of the spindle system are extracted from the surface topography of the workpiece in the frequency domain. With the cross-correlation analysis method, the relationship between the guideway error of the machine tool and the low-frequency signal of the surface topography is calculated in the time domain.

  6. Program Suite for Conceptual Designing of Parallel Mechanism-Based Robots and Machine Tools

    Directory of Open Access Journals (Sweden)

    Slobodan Tabaković

    2013-06-01

    This paper describes the categorization of criteria for the conceptual design of parallel mechanism‐based robots or machine tools, resulting from workspace analysis as well as the procedure of their defining. Furthermore, it also presents the designing methodology that was implemented into the program for the creation of a robot or machine tool space model and the optimization of the resulting solution. For verification of the criteria and the programme suite, three common (conceptually different mechanisms with a similar mechanical structure and kinematic characteristics were used.

  7. Fault Diagnosis of a Rotary Machine Based on Information Entropy and Rough Set

    Institute of Scientific and Technical Information of China (English)

    LI Jian-lan; HUANG Shu-hong

    2007-01-01

    There exists some discord or contradiction of information during the process of fault diagnosis for rotary machine. But the traditional methods used in fault diagnosis can not dispose of the information. A model of fault diagnosis for a rotary machine based on information entropy theory and rough set theory is presented in this paper. The model has clear mathematical definition and can dispose both complete unification information and complete inconsistent information of vibration faults. By using the model, decision rules of six typical vibration faults of a steam turbine and electric generating set are deduced from experiment samples. Finally, the decision rules are validated by selected samples and good identification results are acquired.

  8. A rule-based approach to model checking of UML state machines

    Science.gov (United States)

    Grobelna, Iwona; Grobelny, Michał; Stefanowicz, Łukasz

    2016-12-01

    In the paper a new approach to formal verification of control process specification expressed by means of UML state machines in version 2.x is proposed. In contrast to other approaches from the literature, we use the abstract and universal rule-based logical model suitable both for model checking (using the nuXmv model checker), but also for logical synthesis in form of rapid prototyping. Hence, a prototype implementation in hardware description language VHDL can be obtained that fully reflects the primary, already formally verified specification in form of UML state machines. Presented approach allows to increase the assurance that implemented system meets the user-defined requirements.

  9. Differential spatial activity patterns of acupuncture by a machine learning based analysis

    Science.gov (United States)

    You, Youbo; Bai, Lijun; Xue, Ting; Zhong, Chongguang; Liu, Zhenyu; Tian, Jie

    2011-03-01

    Acupoint specificity, lying at the core of the Traditional Chinese Medicine, underlies the theoretical basis of acupuncture application. However, recent studies have reported that acupuncture stimulation at nonacupoint and acupoint can both evoke similar signal intensity decreases in multiple regions. And these regions were spatially overlapped. We used a machine learning based Support Vector Machine (SVM) approach to elucidate the specific neural response pattern induced by acupuncture stimulation. Group analysis demonstrated that stimulation at two different acupoints (belong to the same nerve segment but different meridians) could elicit distinct neural response patterns. Our findings may provide evidence for acupoint specificity.

  10. Modeling and Analysis of Single Machine Scheduling Based on Noncooperative Game Theory

    Institute of Scientific and Technical Information of China (English)

    WANGChang-Jun; XIYu-Geng

    2005-01-01

    Considering the independent optimization requirement for each demander of modern manufacture, we explore the application of noncooperative game in production scheduling research,and model scheduling problem as competition of machine resources among a group of selfish jobs.Each job has its own performance objective. For the single machine, multi-jobs and non-preemptive scheduling problem, a noncooperative game model is established. Based on the model, many problems about Nash equilibrium solution, such as the existence, quantity, properties of solution space,performance of solution and algorithm are discussed. The results are tested by numerical example.

  11. Machine Vision-Based Measurement Systems for Fruit and Vegetable Quality Control in Postharvest.

    Science.gov (United States)

    Blasco, José; Munera, Sandra; Aleixos, Nuria; Cubero, Sergio; Molto, Enrique

    2017-03-14

    Individual items of any agricultural commodity are different from each other in terms of colour, shape or size. Furthermore, as they are living thing, they change their quality attributes over time, thereby making the development of accurate automatic inspection machines a challenging task. Machine vision-based systems and new optical technologies make it feasible to create non-destructive control and monitoring tools for quality assessment to ensure adequate accomplishment of food standards. Such systems are much faster than any manual non-destructive examination of fruit and vegetable quality, thus allowing the whole production to be inspected with objective and repeatable criteria. Moreover, current technology makes it possible to inspect the fruit in spectral ranges beyond the sensibility of the human eye, for instance in the ultraviolet and near-infrared regions. Machine vision-based applications require the use of multiple technologies and knowledge, ranging from those related to image acquisition (illumination, cameras, etc.) to the development of algorithms for spectral image analysis. Machine vision-based systems for inspecting fruit and vegetables are targeted towards different purposes, from in-line sorting into commercial categories to the detection of contaminants or the distribution of specific chemical compounds on the product's surface. This chapter summarises the current state of the art in these techniques, starting with systems based on colour images for the inspection of conventional colour, shape or external defects and then goes on to consider recent developments in spectral image analysis for internal quality assessment or contaminant detection.

  12. The Integration of Project-Based Methodology into Teaching in Machine Translation

    Science.gov (United States)

    Madkour, Magda

    2016-01-01

    This quantitative-qualitative analytical research aimed at investigating the effect of integrating project-based teaching methodology into teaching machine translation on students' performance. Data was collected from the graduate students in the College of Languages and Translation, at Imam Muhammad Ibn Saud Islamic University, Riyadh, Saudi…

  13. Machine vision-based high-resolution weed mapping and patch-sprayer performance simulation

    NARCIS (Netherlands)

    Tang, L.; Tian, L.F.; Steward, B.L.

    1999-01-01

    An experimental machine vision-based patch-sprayer was developed. This sprayer was primarily designed to do real-time weed density estimation and variable herbicide application rate control. However, the sprayer also had the capability to do high-resolution weed mapping if proper mapping techniques

  14. The Relevance Voxel Machine (RVoxM): A Bayesian Method for Image-Based Prediction

    DEFF Research Database (Denmark)

    Sabuncu, Mert R.; Van Leemput, Koen

    2011-01-01

    This paper presents the Relevance VoxelMachine (RVoxM), a Bayesian multivariate pattern analysis (MVPA) algorithm that is specifically designed for making predictions based on image data. In contrast to generic MVPA algorithms that have often been used for this purpose, the method is designed to ...

  15. The Value Simulation-Based Learning Added to Machining Technology in Singapore

    Science.gov (United States)

    Fang, Linda; Tan, Hock Soon; Thwin, Mya Mya; Tan, Kim Cheng; Koh, Caroline

    2011-01-01

    This study seeks to understand the value simulation-based learning (SBL) added to the learning of Machining Technology in a 15-week core subject course offered to university students. The research questions were: (1) How did SBL enhance classroom learning? (2) How did SBL help participants in their test? (3) How did SBL prepare participants for…

  16. The Qualitative Research Method of Dynamics Vibration of a Washing Machine Based on Riccati Equation

    Directory of Open Access Journals (Sweden)

    Sergey P. Petrosov

    2012-09-01

    Full Text Available The accurate method for finding the common solutions of weakly interconnected system of nonhomogeneous differential equations with variable coefficients based on Riccati Equation was developed. This method describes the dynamics of vibration of the suspension drum type of a washing machine in spin mode.

  17. Web-Based Machine Translation as a Tool for Promoting Electronic Literacy and Language Awareness

    Science.gov (United States)

    Williams, Lawrence

    2006-01-01

    This article addresses a pervasive problem of concern to teachers of many foreign languages: the use of Web-Based Machine Translation (WBMT) by students who do not understand the complexities of this relatively new tool. Although networked technologies have greatly increased access to many language and communication tools, WBMT is still…

  18. Effects of Toy Crane Design-Based Learning on Simple Machines

    Science.gov (United States)

    Korur, Fikret; Efe, Gülfem; Erdogan, Fisun; Tunç, Berna

    2017-01-01

    The aim of this 2-group study was to investigate the following question: Are there significant differences between scaffolded design-based learning controlled using 7 forms and teacher-directed instruction methods for the toy crane project on grade 7 students' posttest scores on the simple machines achievement test, attitude toward simple…

  19. Integrating source-language context into phrase-based statistical machine translation

    NARCIS (Netherlands)

    Haque, R.; Kumar Naskar, S.; Bosch, A.P.J. van den; Way, A.

    2011-01-01

    The translation features typically used in Phrase-Based Statistical Machine Translation (PB-SMT) model dependencies between the source and target phrases, but not among the phrases in the source language themselves. A swathe of research has demonstrated that integrating source context modelling dire

  20. Advanced Dynamics and Model-Based Control of Structures and Machines

    CERN Document Server

    Krommer, Michael; Belyaev, Alexander

    2012-01-01

    The book contains 26 scientific contributions by leading experts from Russia, Austria, Italy, Japan and Taiwan. It presents an overview on recent developments in Advanced Dynamics and Model Based Control of Structures and Machines. Main topics are nonlinear control of structures and systems, sensing and actuation, active and passive damping, nano- and micromechanics, vibrations and waves.

  1. VATE: VAlidation of high TEchnology based on large database analysis by learning machine

    NARCIS (Netherlands)

    Meldolesi, E; Van Soest, J; Alitto, A R; Autorino, R; Dinapoli, N; Dekker, A; Gambacorta, M A; Gatta, R; Tagliaferri, L; Damiani, A; Valentini, V

    2014-01-01

    The interaction between implementation of new technologies and different outcomes can allow a broad range of researches to be expanded. The purpose of this paper is to introduce the VAlidation of high TEchnology based on large database analysis by learning machine (VATE) project that aims to combine

  2. Improved method for SNR prediction in machine-learning-based test

    NARCIS (Netherlands)

    Sheng, Xiaoqin; Kerkhoff, Hans G.

    2010-01-01

    This paper applies an improved method for testing the signal-to-noise ratio (SNR) of Analogue-to-Digital Converters (ADC). In previous work, a noisy and nonlinear pulse signal is exploited as the input stimulus to obtain the signature results of ADC. By applying a machine-learning-based approach, th

  3. Improving the quality of automated DVD subtitles via example-based machine translation

    DEFF Research Database (Denmark)

    Armstrong, Stephen; Caffrey, Colm; Flanagan, Marian

    Denoual (2005) discovered that, contrary to popular belief, an Example-Based Machine Translation system trained on heterogeneous data produced significantly better results than a system trained on homogeneous data. Using similar evaluation metrics and a few additional ones, in this paper we show ...

  4. Recycling Texts: Human evaluation of example-based machine translation subtitles for DVD

    DEFF Research Database (Denmark)

    Flanagan, Marian

    2009-01-01

    This project focuses on translation reusability in audiovisual contexts. Specifically, the project seeks to establish (1) whether target language subtitles produced by an Example-Based Machine Translation (EBMT) system are considered intelligible and acceptable by viewers of movies on DVD, and (2...

  5. Improved method for SNR prediction in machine-learning-based test

    NARCIS (Netherlands)

    Sheng, Xiaoqin; Kerkhoff, Hans G.

    2010-01-01

    This paper applies an improved method for testing the signal-to-noise ratio (SNR) of Analogue-to-Digital Converters (ADC). In previous work, a noisy and nonlinear pulse signal is exploited as the input stimulus to obtain the signature results of ADC. By applying a machine-learning-based approach, th

  6. Effects of Toy Crane Design-Based Learning on Simple Machines

    Science.gov (United States)

    Korur, Fikret; Efe, Gülfem; Erdogan, Fisun; Tunç, Berna

    2017-01-01

    The aim of this 2-group study was to investigate the following question: Are there significant differences between scaffolded design-based learning controlled using 7 forms and teacher-directed instruction methods for the toy crane project on grade 7 students' posttest scores on the simple machines achievement test, attitude toward simple…

  7. Static Object Detection Based on a Dual Background Model and a Finite-State Machine

    Directory of Open Access Journals (Sweden)

    Heras Evangelio Rubén

    2011-01-01

    Full Text Available Detecting static objects in video sequences has a high relevance in many surveillance applications, such as the detection of abandoned objects in public areas. In this paper, we present a system for the detection of static objects in crowded scenes. Based on the detection of two background models learning at different rates, pixels are classified with the help of a finite-state machine. The background is modelled by two mixtures of Gaussians with identical parameters except for the learning rate. The state machine provides the meaning for the interpretation of the results obtained from background subtraction; it can be implemented as a look-up table with negligible computational cost and it can be easily extended. Due to the definition of the states in the state machine, the system can be used either full automatically or interactively, making it extremely suitable for real-life surveillance applications. The system was successfully validated with several public datasets.

  8. Ant System Based Optimization Algorithm and Its Applications in Identical Parallel Machine Scheduling

    Institute of Scientific and Technical Information of China (English)

    陈义保; 姚建初; 钟毅芳

    2002-01-01

    Identical parallel machine scheduling problem for minimizing the makespan is a very important productionscheduling problem. When its scale is large, many difficulties will arise in the course of solving identical parallel machinescheduling problem. Ant system based optimization algorithm (ASBOA) has shown great advantages in solving thecombinatorial optimization problem in view of its characteristics of high efficiency and suitability for practical applications.In this paper, an ASBOA for minimizing the makespan in identical machine scheduling problem is presented. Twodifferent scale numerical examples demonstrate that the ASBOA proposed is efficient and fit for large-scale identicalparallel machine scheduling problem for minimizing the makespan, the quality of its solution has advantages over heuristicprocedure and simulated annealing method, as well as genetic algorithm.

  9. A new damage diagnosis approach for NC machine tools based on hybrid Stationary subspace analysis

    Science.gov (United States)

    Gao, Chen; Zhou, Yuqing; Ren, Yan

    2017-05-01

    This paper focused on the damage diagnosis for NC machine tools and put forward a damage diagnosis method based on hybrid Stationary subspace analysis (SSA), for improving the accuracy and visibility of damage identification. First, the observed single sensor signal was reconstructed to multi-dimensional signals by the phase space reconstruction technique, as the inputs of SSA. SSA method was introduced to separate the reconstructed data into stationary components and non-stationary components without the need for independency and prior information of the origin signals. Subsequently, the selected non-stationary components were analysed for training LS-SVM (Least Squares Support Vector Machine) classifier model, in which several statistic parameters in the time and frequency domains were exacted as the sample of LS-SVM. An empirical analysis in NC milling machine tools is developed, and the result shows high accuracy of the proposed approach.

  10. Electrode Wear Prediction in Milling Electrical Discharge Machining Based on Radial Basis Function Neural Network

    Institute of Scientific and Technical Information of China (English)

    HUANG He; BAI Ji-cheng; LU Ze-sheng; GUO Yong-feng

    2009-01-01

    Milling electrical discharge machining (EDM) enables the machining of complex cavities using cylindrical or tubular electrodes. To ensure acceptable machining accuracy the process requires some methods of compensating for electrode wear. Due to the complexity and random nature of the process, existing methods of compensating for such wear usually involve off-line prediction. This paper discusses an innovative model of electrode wear prediction for milling EDM based upon a radial basis function (RBF) network. Data gained from an orthogonal experiment were used to provide training samples for the RBF network. The model established was used to forecast the electrode wear, making it possible to calculate the real-time tool wear in the milling EDM process and, to lay the foundations for dynamic compensation of the electrode wear on-line. This paper demonstrates that by using this model prediction errors can be controlled within 8%.

  11. PSO-based support vector machine with cuckoo search technique for clinical disease diagnoses.

    Science.gov (United States)

    Liu, Xiaoyong; Fu, Hui

    2014-01-01

    Disease diagnosis is conducted with a machine learning method. We have proposed a novel machine learning method that hybridizes support vector machine (SVM), particle swarm optimization (PSO), and cuckoo search (CS). The new method consists of two stages: firstly, a CS based approach for parameter optimization of SVM is developed to find the better initial parameters of kernel function, and then PSO is applied to continue SVM training and find the best parameters of SVM. Experimental results indicate that the proposed CS-PSO-SVM model achieves better classification accuracy and F-measure than PSO-SVM and GA-SVM. Therefore, we can conclude that our proposed method is very efficient compared to the previously reported algorithms.

  12. PSO-Based Support Vector Machine with Cuckoo Search Technique for Clinical Disease Diagnoses

    Directory of Open Access Journals (Sweden)

    Xiaoyong Liu

    2014-01-01

    Full Text Available Disease diagnosis is conducted with a machine learning method. We have proposed a novel machine learning method that hybridizes support vector machine (SVM, particle swarm optimization (PSO, and cuckoo search (CS. The new method consists of two stages: firstly, a CS based approach for parameter optimization of SVM is developed to find the better initial parameters of kernel function, and then PSO is applied to continue SVM training and find the best parameters of SVM. Experimental results indicate that the proposed CS-PSO-SVM model achieves better classification accuracy and F-measure than PSO-SVM and GA-SVM. Therefore, we can conclude that our proposed method is very efficient compared to the previously reported algorithms.

  13. RESEARCH ON ED-MILLING TO COMPLEX CAVITY BASED ON LAMINATION MACHINING

    Institute of Scientific and Technical Information of China (English)

    2003-01-01

    Based on the principle of laminated machining, the method of auto-programming in the electro discharge milling (ED-milling) process is drawn out.With the help of IGES formatted files, the process slicing and the machining locus can be programmed well.The program adopts three-parameter convergence as the basic way to slice the geometry mold and divide the non-uniform rational B-spline curve (NURBS) surface.With the great mount of discrete points, a given arithmetic is drawn out to order them, and then is carried out the interpolation of bi-arc.In the process, according to the character of the EDM process, the zigzag track of machining is accepted to remove the volume of work piece and shape the contour along the contour line of the slicing segments, including multi-connection.As a result, some correlative experiments are accomplished.

  14. Programming and machining of complex parts based on CATIA solid modeling

    Science.gov (United States)

    Zhu, Xiurong

    2017-09-01

    The complex parts of the use of CATIA solid modeling programming and simulation processing design, elaborated in the field of CNC machining, programming and the importance of processing technology. In parts of the design process, first make a deep analysis on the principle, and then the size of the design, the size of each chain, connected to each other. After the use of backstepping and a variety of methods to calculate the final size of the parts. In the selection of parts materials, careful study, repeated testing, the final choice of 6061 aluminum alloy. According to the actual situation of the processing site, it is necessary to make a comprehensive consideration of various factors in the machining process. The simulation process should be based on the actual processing, not only pay attention to shape. It can be used as reference for machining.

  15. Dialogue-Based Research in Man-Machine Communication

    Science.gov (United States)

    1975-11-01

    it is based on case analysis rather than functional system design, the results are in the form of individual computer algorithms (much smaller than systems), and the algorithms are transferable into useful (nonresearch) systems.

  16. How To Teach Common Characteristics of Machine Tools

    Science.gov (United States)

    Kazanas, H. C.

    1970-01-01

    Organizes machine tools and machine operations into commonalities in order to help the student visualize and distinguish the common characteristics which exist between machine tools and operations. (GR)

  17. 互联网机器翻译%Web-based Machine Translation

    Institute of Scientific and Technical Information of China (English)

    王海峰; 吴华; 刘占一

    2011-01-01

    该文在回顾机器翻译发展的基础上,总结了主要的机器翻译方法,并主要阐述互联网机器翻译的特点及面临的挑战.面向互联网机器翻译的应用需求,并针对互联网资源具有海量、高噪声、时效性、稀疏的特点,提出了多策略混合翻译方法、资源挖掘和过滤以及分布式处理技术、领域自适应技术,针对数据稀疏论述枢轴语言技术和新语种快速部署技术;然后结合翻译与搜索技术,阐述翻译个性化特点和方案.最后,论述机器翻译技术和产品的应用.%This paper digs into the characteristics and challenges of web-based machine translation, and proposes possible solutions. First of all, we look back on the history of machine translation and summarize its methods. Next, we analyze the characteristics of internet bilingual corpora and monolingual corpora as: large scale, with lots of noise, real-time and sometimes sparse. Based on the features described above, we propose the hybrid machine translation method, corpus mining and filtering methods, and distributed computing methods. Furthermore, the pivot language approach is adopted to tackle the data sparseness problem, thus enabling the quick development of multilingual machine translation systems. We then discuss the approach to support the personalization of machine translation via the combination of translation technology and search technology. Finally the applications and products of machine translation technology are presented.

  18. Passivity-Based Control of a Class of Blondel-Park Transformable Electric Machines

    Directory of Open Access Journals (Sweden)

    Per J. Nicklasson

    1997-10-01

    Full Text Available In this paper we study the viability of extending, to the general rotating electric machine's model, the passivity-based controller method that we have developed for induction motors. In this approach the passivity (energy dissipation properties of the motor are taken advantage of at two different levels. First, we prove that the motor model can be decomposed as the feedback interconnection of two passive subsystems, which can essentially be identified with the electrical and mechanical dynamics. Then, we design a torque tracking controller that preserves passivity for the electrical subsystem, and leave the mechanical part as a "passive disturbance". In position or speed control applications this procedure naturally leads to the well known cascaded controller structure which is typically analyzed invoking time-scale separation assumptions. A key feature of the new cascaded control paradigm is that the latter arguments are obviated in the stability analysis. Our objective in this paper is to characterize a class of machines for which such a passivity-based controller solves the output feedback torque tracking problem. Roughly speaking, the class consists of machines whose nonactuated dynamics are well damped and whose electrical and mechanical dynamics can be suitably decoupled via a coordinate transformation. The first condition translates into the requirement of approximate knowledge of the rotor resistances to avoid the need of injecting high gain into the loop. The latter condition is known in the electric machines literature as Blondel-Park transformability, and in practical terms it requires that the air-gap magnetomotive force must be suitably approximated by the first harmonic in its Fourier expansion. These conditions, stemming from the construction of the machine, have a clear physical interpretation in terms of the couplings between its electrical, magnetic and mechanical dynamics, and are satisfied by a large number of practical

  19. Hindi to English Transfer Based Machine Translation System

    Directory of Open Access Journals (Sweden)

    Shashi Pal Singh

    2015-06-01

    Full Text Available In large societies like India there is a huge demand to convert one human language into another. Lots of work has been done in this area. Many transfer based MTS have developed for English to other languages, as MANTRA CDAC Pune, MATRA CDAC Pune, SHAKTI IISc Bangalore and IIIT Hyderabad. Still there is a little work done for Hindi to other languages. Currently we are working on it. In this paper we focus on designing a system, that translate the document from Hindi to English by using transfer based approach. This system takes an input text check its structure through parsing. Reordering rules are used to generate the text in target language. It is better than Corpus Based MTS because Corpus Based MTS require large amount of word aligned data for translation that is not available for many languages while Transfer Based MTS requires only knowledge of both the languages (source language and target language to make transfer rules. We get correct translation for simple assertive sentences and almost correct for complex and compound sentences.

  20. Attaching Chuck Keys to Machine Tools

    Science.gov (United States)

    Richardson, V.

    1984-01-01

    Chuck keys attached to portable machine tools by retracting lanyards. Lanyard held taut by recoil caddy attached to tool base. Chuck key available for use when needed and safely secured during operation of tool.