Preliminary Development of Real Time Usage-Phase Monitoring System for CNC Machine Tools with a Case Study on CNC Machine VMC 250

Science.gov (United States)

Budi Harja, Herman; Prakosa, Tri; Raharno, Sri; Yuwana Martawirya, Yatna; Nurhadi, Indra; Setyo Nogroho, Alamsyah

2018-03-01

The production characteristic of job-shop industry at which products have wide variety but small amounts causes every machine tool will be shared to conduct production process with dynamic load. Its dynamic condition operation directly affects machine tools component reliability. Hence, determination of maintenance schedule for every component should be calculated based on actual usage of machine tools component. This paper describes study on development of monitoring system to obtaining information about each CNC machine tool component usage in real time approached by component grouping based on its operation phase. A special device has been developed for monitoring machine tool component usage by utilizing usage phase activity data taken from certain electronics components within CNC machine. The components are adaptor, servo driver and spindle driver, as well as some additional components such as microcontroller and relays. The obtained data are utilized for detecting machine utilization phases such as power on state, machine ready state or spindle running state. Experimental result have shown that the developed CNC machine tool monitoring system is capable of obtaining phase information of machine tool usage as well as its duration and displays the information at the user interface application.

Monitoring machining conditions by analyzing cutting force vibration

Energy Technology Data Exchange (ETDEWEB)

Piao, Chun Guang; Kim, Ju Wan; Kim, Jin Oh; Shin, Yoan [Soongsl University, Seoul (Korea, Republic of)

2015-09-15

This paper deals with an experimental technique for monitoring machining conditions by analyzing cutting-force vibration measured at a milling machine. This technique is based on the relationship of the cutting-force vibrations with the feed rate and cutting depth as reported earlier. The measurement system consists of dynamic force transducers and a signal amplifier. The analysis system includes an oscilloscope and a computer with a LabVIEW program. Experiments were carried out at various feed rates and cutting depths, while the rotating speed was kept constant. The magnitude of the cutting force vibration component corresponding to the number of cutting edges multiplied by the frequency of rotation was linearly correlated with the machining conditions. When one condition of machining is known, another condition can be identified by analyzing the cutting-force vibration.

Monitoring machining conditions by analyzing cutting force vibration

International Nuclear Information System (INIS)

Piao, Chun Guang; Kim, Ju Wan; Kim, Jin Oh; Shin, Yoan

2015-01-01

This paper deals with an experimental technique for monitoring machining conditions by analyzing cutting-force vibration measured at a milling machine. This technique is based on the relationship of the cutting-force vibrations with the feed rate and cutting depth as reported earlier. The measurement system consists of dynamic force transducers and a signal amplifier. The analysis system includes an oscilloscope and a computer with a LabVIEW program. Experiments were carried out at various feed rates and cutting depths, while the rotating speed was kept constant. The magnitude of the cutting force vibration component corresponding to the number of cutting edges multiplied by the frequency of rotation was linearly correlated with the machining conditions. When one condition of machining is known, another condition can be identified by analyzing the cutting-force vibration

Learning to Monitor Machine Health with Convolutional Bi-Directional LSTM Networks

OpenAIRE

Rui Zhao; Ruqiang Yan; Jinjiang Wang; Kezhi Mao

2017-01-01

In modern manufacturing systems and industries, more and more research efforts have been made in developing effective machine health monitoring systems. Among various machine health monitoring approaches, data-driven methods are gaining in popularity due to the development of advanced sensing and data analytic techniques. However, considering the noise, varying length and irregular sampling behind sensory data, this kind of sequential data cannot be fed into classification and regression mode...

Improved thermal monitoring of rotating machine insulation

International Nuclear Information System (INIS)

Stone, G.C.; Sedding, H.G.; Bernstein, B.S.

1991-01-01

Aging of motor and generator insulation is most often induced as a result of operation at high temperatures. In spite of this knowledge, stator and rotor temperatures are only crudely monitored in existing machines. In EPRI project RP2577-1, three new means of detecting machine temperatures were successfully developed. Two of the techniques, the Electronic Rotor Temperature Sensor and the Passive Rotor Temperature Sensor, were specifically developed to give point temperature readings on turbine generator rotor windings. The Insulation Sniffer allows operators to determine when any electrical insulation in a motor is overheating. Another electronic device, called the Thermal Life Indicator, helps operators and maintenance personnel determine how accumulated operation has affected the remaining life of the insulation in rotating machines. These new devices permit nuclear station operators to avoid hazardous operating conditions and will help to determine priorities for maintenance and plant life extension programs

Monitoring of large rotating machines at EDF

International Nuclear Information System (INIS)

Chevalier, R.; Oswald, G.P.; Morel, J.

1993-09-01

The purpose of equipment surveillance is the prevention of major risks, the early detection of abnormal conditions and post-incident analysis to correct faults observed. At EDF, overall vibration monitoring in the control room was supplemented by a special vibration monitoring system. However, in order to satisfy more elaborate, real time detection requirements and benefit from the new possibilities offered by computer-based systems, EDF has developed the PSAD concept (Surveillance and Diagnosis-aid Station) which groups surveillance processing, organized on surveillance functions including turbogenerator and reactor coolant pump surveillance. The purpose of the present paper is to describe the turbogenerator and reactor coolant pump surveillance functions and present the first examples of reactor coolant pump behaviour feedback using a PSAD mockup (Automated Surveillance of Rotating Machines). In the first place, surveillance implies determining exactly what has to be monitored. This entails considering incidents liable to affect machine behaviour and, of course, specifying both the vibration quantities and those defining the operating condition of the machine considered which are necessary to be able to interpret the vibrations. Data processing requirements concern detection of faults and diagnosis aids. Faults detection must be automatic, but not the diagnosis function. Data can be processed to evidence one or several faults, using the most appropriate data display system. Interpretation is then entrusted to experts. To satisfy the above requirements, the PSAD system integrates two new concepts: distributed surveillance, involving depth distribution (different layers of software organized for increasingly sophisticated and gradually narrowing data processing) and space distribution (the work is performed in the most appropriate place, whether this be the plant, with automatic real time processing, or elsewhere if the complexity of the diagnosis so requires

Quality of referral of short children to the paediatric endocrinologist and impact of a fax communication system.

Science.gov (United States)

Chiniara, Lyne; Perry, Rebecca J; Van Vliet, Guy; Huot, Céline; Deal, Cheri

2013-12-01

In 2001, a chart review of children referred to the authors' endocrine clinic because of short stature revealed that many were referred with insufficient baseline data, had normal height velocity and were within genetic target height. Therefore, a two-way fax communication system was implemented between referring physicians and the authors' service before the first visit. Aspects that were assessed included whether this system increased the information accompanying the patient at referral, resulted in children with nonpathological shortness not being seen in the clinic, and was used differently by paediatricians and general practitioners. Between January and December 2006, 138 referrals for short stature, diagnosed with familial short stature, constitutional delay or idiopathic short stature, were audited (69 with and 69 without previous fax communication). Data collected included source of referral, clinical information provided, available growth measurements, and results from laboratory and imaging studies. Fax communication resulted in growth curves being provided more often (95.6% of cases versus 40.5% of cases without fax communication [Pshort stature being given to 31 children based on the growth curve, laboratory and imaging results, without the children being seen in the endocrine clinic. Fax communication was also used more frequently by paediatricians (84%) than by general practitioners (15%). The fax communication system resulted in a more complete evaluation of referred patients by their physicians and reduced the number of unnecessary visits to the authors' specialty clinic while promoting medical education.

Using virtual machine monitors to overcome the challenges of monitoring and managing virtualized cloud infrastructures

Science.gov (United States)

Bamiah, Mervat Adib; Brohi, Sarfraz Nawaz; Chuprat, Suriayati

2012-01-01

Virtualization is one of the hottest research topics nowadays. Several academic researchers and developers from IT industry are designing approaches for solving security and manageability issues of Virtual Machines (VMs) residing on virtualized cloud infrastructures. Moving the application from a physical to a virtual platform increases the efficiency, flexibility and reduces management cost as well as effort. Cloud computing is adopting the paradigm of virtualization, using this technique, memory, CPU and computational power is provided to clients' VMs by utilizing the underlying physical hardware. Beside these advantages there are few challenges faced by adopting virtualization such as management of VMs and network traffic, unexpected additional cost and resource allocation. Virtual Machine Monitor (VMM) or hypervisor is the tool used by cloud providers to manage the VMs on cloud. There are several heterogeneous hypervisors provided by various vendors that include VMware, Hyper-V, Xen and Kernel Virtual Machine (KVM). Considering the challenge of VM management, this paper describes several techniques to monitor and manage virtualized cloud infrastructures.

Detecting System of Nested Hardware Virtual Machine Monitor

Directory of Open Access Journals (Sweden)

Artem Vladimirovich Iuzbashev

2015-03-01

Full Text Available Method of nested hardware virtual machine monitor detection was proposed in this work. The method is based on HVM timing attack. In case of HVM presence in system, the number of different instruction sequences execution time values will increase. We used this property as indicator in our detection.

Application of Machine Learning to Rotorcraft Health Monitoring

Science.gov (United States)

Cody, Tyler; Dempsey, Paula J.

2017-01-01

Machine learning is a powerful tool for data exploration and model building with large data sets. This project aimed to use machine learning techniques to explore the inherent structure of data from rotorcraft gear tests, relationships between features and damage states, and to build a system for predicting gear health for future rotorcraft transmission applications. Classical machine learning techniques are difficult, if not irresponsible to apply to time series data because many make the assumption of independence between samples. To overcome this, Hidden Markov Models were used to create a binary classifier for identifying scuffing transitions and Recurrent Neural Networks were used to leverage long distance relationships in predicting discrete damage states. When combined in a workflow, where the binary classifier acted as a filter for the fatigue monitor, the system was able to demonstrate accuracy in damage state prediction and scuffing identification. The time dependent nature of the data restricted data exploration to collecting and analyzing data from the model selection process. The limited amount of available data was unable to give useful information, and the division of training and testing sets tended to heavily influence the scores of the models across combinations of features and hyper-parameters. This work built a framework for tracking scuffing and fatigue on streaming data and demonstrates that machine learning has much to offer rotorcraft health monitoring by using Bayesian learning and deep learning methods to capture the time dependent nature of the data. Suggested future work is to implement the framework developed in this project using a larger variety of data sets to test the generalization capabilities of the models and allow for data exploration.

Electric machines modeling, condition monitoring, and fault diagnosis

CERN Document Server

Toliyat, Hamid A; Choi, Seungdeog; Meshgin-Kelk, Homayoun

2012-01-01

With countless electric motors being used in daily life, in everything from transportation and medical treatment to military operation and communication, unexpected failures can lead to the loss of valuable human life or a costly standstill in industry. To prevent this, it is important to precisely detect or continuously monitor the working condition of a motor. Electric Machines: Modeling, Condition Monitoring, and Fault Diagnosis reviews diagnosis technologies and provides an application guide for readers who want to research, develop, and implement a more effective fault diagnosis and condi

Seed-specific overexpression of AtFAX1 increases seed oil content in Arabidopsis.

Science.gov (United States)

Tian, Yinshuai; Lv, Xueyan; Xie, Guilan; Zhang, Jing; Xu, Ying; Chen, Fang

2018-06-02

Biosynthesis of plant seed oil is accomplished through the coordinate action of multiple enzymes in multiple subcellular compartments. Fatty acid (FA) has to be transported from plastid to endoplasmic reticulum (ER) for TAG synthesis. However, the role of plastid FA transportation during seed oil accumulation has not been evaluated. AtFAX1 (Arabidopsis fatty acid export1) mediated the FA export from plastid. In this study, we overexpressed AtFAX1 under the control of a seed specific promoter in Arabidopsis. The resultant overexpression lines (OEs) produced seeds which contained 21-33% more oil and 24-30% more protein per seed than those of the wild type (WT). The increased oil content was probably because of the enhanced FA and TAG synthetic activity. The seed size and weight were both increased accordingly. In addition, the seed number per silique and silique number per plant had no changes in transgenic plants. Taken together, our results demonstrated that seed specific overexpression of AtFAX1 could promote oil accumulation in Arabidopsis seeds and manipulating FA transportation is a feasible strategy for increasing the seed oil content. Copyright © 2018 Elsevier Inc. All rights reserved.

[Extension of cardiac monitoring function by used of ordinary ECG machine].

Science.gov (United States)

Chen, Zhencheng; Jiang, Yong; Ni, Lili; Wang, Hongyan

2002-06-01

This paper deals with a portable monitor system on liquid crystal display (LCD) based on this available ordinary ECG machine, which is low power and suitable for China's specific condition. Apart from developing the overall scheme of the system, this paper also has completed the design of the hardware and the software. The 80c196 single chip microcomputer is taken as the central microprocessor and real time electrocardiac single is data treated and analyzed in the system. With the performance of ordinary monitor, this machine also possesses the following functions: five types of arrhythmia analysis, alarm, freeze, and record of automatic pappering, convenient in carrying, with alternate-current (AC) or direct-current (DC) powered. The hardware circuit is simplified and the software structure is optimized in this paper. Multiple low power designs and LCD unit design are adopted and completed in it. Popular in usage, low in cost price, the portable monitor system will have a valuable influence on China's monitor system field.

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.

Beam Loss Monitoring for LHC Machine Protection

Science.gov (United States)

Holzer, Eva Barbara; Dehning, Bernd; Effnger, Ewald; Emery, Jonathan; Grishin, Viatcheslav; Hajdu, Csaba; Jackson, Stephen; Kurfuerst, Christoph; Marsili, Aurelien; Misiowiec, Marek; Nagel, Markus; Busto, Eduardo Nebot Del; Nordt, Annika; Roderick, Chris; Sapinski, Mariusz; Zamantzas, Christos

The energy stored in the nominal LHC beams is two times 362 MJ, 100 times the energy of the Tevatron. As little as 1 mJ/cm3 deposited energy quenches a magnet at 7 TeV and 1 J/cm3 causes magnet damage. The beam dumps are the only places to safely dispose of this beam. One of the key systems for machine protection is the beam loss monitoring (BLM) system. About 3600 ionization chambers are installed at likely or critical loss locations around the LHC ring. The losses are integrated in 12 time intervals ranging from 40 μs to 84 s and compared to threshold values defined in 32 energy ranges. A beam abort is requested when potentially dangerous losses are detected or when any of the numerous internal system validation tests fails. In addition, loss data are used for machine set-up and operational verifications. The collimation system for example uses the loss data for set-up and regular performance verification. Commissioning and operational experience of the BLM are presented: The machine protection functionality of the BLM system has been fully reliable; the LHC availability has not been compromised by false beam aborts.

Machine and lubricant condition monitoring for extended equipment lifetimes and predictive maintenance

Energy Technology Data Exchange (ETDEWEB)

Lukas, M; Anderson, D P [Spectro Incorporated, Littleton, Massachusetts (United States)

1998-12-31

Predictive maintenance has gained wide acceptance as a cost cutting strategy in modern industry. Condition monitoring by lubricant analysis is one of the basic tools of a predictive maintenance program along with vibration monitoring, performance monitoring and thermography. In today`s modern power generation, manufacturing, refinery, transportation, mining, and military operations, the cost of equipment maintenance, service, and lubricants are ever increasing. Parts, labor, equipment downtime and lubricant prices and disposal costs are a primary concern in a well run maintenance management program. Machine condition monitoring based on oil analysis has become a prerequisite in most maintenance programs. Few operations can afford not to implement a program if they wish to remain competitive, and in some cases, profitable. This presentation describes a comprehensive Machine Condition Monitoring Program based on oil analysis. Actual operational condition monitoring programs will be used to review basic components and analytical requirements. Case histories will be cited as examples of cost savings, reduced equipment downtime and increased efficiencies of maintenance programs through a well managed oil analysis program. (orig.)

Machine and lubricant condition monitoring for extended equipment lifetimes and predictive maintenance

Energy Technology Data Exchange (ETDEWEB)

Lukas, M.; Anderson, D.P. [Spectro Incorporated, Littleton, Massachusetts (United States)

1997-12-31

Predictive maintenance has gained wide acceptance as a cost cutting strategy in modern industry. Condition monitoring by lubricant analysis is one of the basic tools of a predictive maintenance program along with vibration monitoring, performance monitoring and thermography. In today`s modern power generation, manufacturing, refinery, transportation, mining, and military operations, the cost of equipment maintenance, service, and lubricants are ever increasing. Parts, labor, equipment downtime and lubricant prices and disposal costs are a primary concern in a well run maintenance management program. Machine condition monitoring based on oil analysis has become a prerequisite in most maintenance programs. Few operations can afford not to implement a program if they wish to remain competitive, and in some cases, profitable. This presentation describes a comprehensive Machine Condition Monitoring Program based on oil analysis. Actual operational condition monitoring programs will be used to review basic components and analytical requirements. Case histories will be cited as examples of cost savings, reduced equipment downtime and increased efficiencies of maintenance programs through a well managed oil analysis program. (orig.)

Reading presence and absence in Fax from Sarajevo’s rape narrative

NARCIS (Netherlands)

in ‘t Veld, L. (Laurike)

2018-01-01

textabstractIn Joe Kubert’s Fax from Sarajevo, the chapter ‘The Rape Camp’ deals with the mass rape of women by Serb troops during the Bosnian War. Kubert’s rape narrative displays a tension between presence and absence that is analysed on different (extra)textual levels. Formally, the two

RAW MILK IN AUTOMATIC SALE MACHINES: MONITORING PLAN IN PIEDEMONT REGION

Directory of Open Access Journals (Sweden)

S. Gallina

2010-06-01

Full Text Available Raw milk at vending machine is surging in popularity amongst consumers of Northern Italy; indeed in Piedmont Region there are more than 100 vending machines. In June 2008 Piedmont Region set out a specific monitoring plan to check the milk quality. From June to December 2008, 113 raw milk samples were collected at vending machines. Samples were analysed for Listeria monocytogenes, Salmonella spp., coagulase positive staphylococci, Staphylococcus aureus and Campylobacter. Moreover, 100 samples were analysed for the quantification of aflatoxin M1. 26 samples have been resulted Not Conform for the hygienic criteria and 1 exceeded the aflatoxin M1 limit.

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.

Vibration Sensor Monitoring of Nickel-Titanium Alloy Turning for Machinability Evaluation

Directory of Open Access Journals (Sweden)

Tiziana Segreto

2017-12-01

Full Text Available Nickel-Titanium (Ni-Ti alloys are very difficult-to-machine materials causing notable manufacturing problems due to their unique mechanical properties, including superelasticity, high ductility, and severe strain-hardening. In this framework, the aim of this paper is to assess the machinability of Ni-Ti alloys with reference to turning processes in order to realize a reliable and robust in-process identification of machinability conditions. An on-line sensor monitoring procedure based on the acquisition of vibration signals was implemented during the experimental turning tests. The detected vibration sensorial data were processed through an advanced signal processing method in time-frequency domain based on wavelet packet transform (WPT. The extracted sensorial features were used to construct WPT pattern feature vectors to send as input to suitably configured neural networks (NNs for cognitive pattern recognition in order to evaluate the correlation between input sensorial information and output machinability conditions.

Vibration Sensor Monitoring of Nickel-Titanium Alloy Turning for Machinability Evaluation.

Science.gov (United States)

Segreto, Tiziana; Caggiano, Alessandra; Karam, Sara; Teti, Roberto

2017-12-12

Nickel-Titanium (Ni-Ti) alloys are very difficult-to-machine materials causing notable manufacturing problems due to their unique mechanical properties, including superelasticity, high ductility, and severe strain-hardening. In this framework, the aim of this paper is to assess the machinability of Ni-Ti alloys with reference to turning processes in order to realize a reliable and robust in-process identification of machinability conditions. An on-line sensor monitoring procedure based on the acquisition of vibration signals was implemented during the experimental turning tests. The detected vibration sensorial data were processed through an advanced signal processing method in time-frequency domain based on wavelet packet transform (WPT). The extracted sensorial features were used to construct WPT pattern feature vectors to send as input to suitably configured neural networks (NNs) for cognitive pattern recognition in order to evaluate the correlation between input sensorial information and output machinability conditions.

Development of Dual-Axis MEMS Accelerometers for Machine Tools Vibration Monitoring

Directory of Open Access Journals (Sweden)

Chih-Yung Huang

2016-07-01

Full Text Available With the development of intelligent machine tools, monitoring the vibration by the accelerometer is an important issue. Accelerometers used for measuring vibration signals during milling processes require the characteristics of high sensitivity, high resolution, and high bandwidth. A commonly used accelerometer is the lead zirconate titanate (PZT type; however, integrating it into intelligent modules is excessively expensive and difficult. Therefore, the micro electro mechanical systems (MEMS accelerometer is an alternative with the advantages of lower price and superior integration. In the present study, we integrated two MEMS accelerometer chips into a low-pass filter and housing to develop a low-cost dual-axis accelerometer with a bandwidth of 5 kHz and a full scale range of ±50 g for measuring machine tool vibration. In addition, a platform for measuring the linearity, cross-axis sensitivity and frequency response of the MEMS accelerometer by using the back-to-back calibration method was also developed. Finally, cutting experiments with steady and chatter cutting were performed to verify the results of comparing the MEMS accelerometer with the PZT accelerometer in the time and frequency domains. The results demonstrated that the dual-axis MEMS accelerometer is suitable for monitoring the vibration of machine tools at low cost.

Monitoring wear and corrosion in industrial machines and systems: A radiation tool

International Nuclear Information System (INIS)

Konstantinov, I.O.; Zatolokin, B.V.

1994-01-01

Industrial equipment and machines, transport systems, nuclear and conventional power plants, pipelines, and other materials is substantially influenced by degradation processes such as wear and corrosion. For safety and economic reasons, appropriately monitoring the damage could prevent dangerous accidents. When the surfaces of machine parts under investigation are not easy to reach or are concealed by overlying structures, nuclear methods have become powerful tools for examination. They include X-ray radiography, neutron radiography, and a technique known as thin layer activation (TLA)

Implementing a fax referral program for quitline smoking cessation services in urban health centers: a qualitative study

Directory of Open Access Journals (Sweden)

Cantrell Jennifer

2009-12-01

Full Text Available Abstract Background Fax referral services that connect smokers to state quitlines have been implemented in 49 U.S. states and territories and promoted as a simple solution to improving smoker assistance in medical practice. This study is an in-depth examination of the systems-level changes needed to implement and sustain a fax referral program in primary care. Methods The study involved implementation of a fax referral system paired with a chart stamp prompting providers to identify smoking patients, provide advice to quit and refer interested smokers to a state-based fax quitline. Three focus groups (n = 26 and eight key informant interviews were conducted with staff and physicians at two clinics after the intervention. We used the Chronic Care Model as a framework to analyze the data, examining how well the systems changes were implemented and the impact of these changes on care processes, and to develop recommendations for improvement. Results Physicians and staff described numerous benefits of the fax referral program for providers and patients but pointed out significant barriers to full implementation, including the time-consuming process of referring patients to the Quitline, substantial patient resistance, and limitations in information and care delivery systems for referring and tracking smokers. Respondents identified several strategies for improving integration, including simplification of the referral form, enhanced teamwork, formal assignment of responsibility for referrals, ongoing staff training and patient education. Improvements in Quitline feedback were needed to compensate for clinics' limited internal information systems for tracking smokers. Conclusions Establishing sustainable linkages to quitline services in clinical sites requires knowledge of existing patterns of care and tailored organizational changes to ensure new systems are prioritized, easily integrated into current office routines, formally assigned to specific

Monitoring machining conditions by infrared images

Science.gov (United States)

Borelli, Joao E.; Gonzaga Trabasso, Luis; Gonzaga, Adilson; Coelho, Reginaldo T.

2001-03-01

During machining process the knowledge of the temperature is the most important factor in tool analysis. It allows to control main factors that influence tool use, life time and waste. The temperature in the contact area between the piece and the tool is resulting from the material removal in cutting operation and it is too difficult to be obtained because the tool and the work piece are in motion. One way to measure the temperature in this situation is detecting the infrared radiation. This work presents a new methodology for diagnosis and monitoring of machining processes with the use of infrared images. The infrared image provides a map in gray tones of the elements in the process: tool, work piece and chips. Each gray tone in the image corresponds to a certain temperature for each one of those materials and the relationship between the gray tones and the temperature is gotten by the previous of infrared camera calibration. The system developed in this work uses an infrared camera, a frame grabber board and a software composed of three modules. The first module makes the image acquisition and processing. The second module makes the feature image extraction and performs the feature vector. Finally, the third module uses fuzzy logic to evaluate the feature vector and supplies the tool state diagnostic as output.

A Sensor-less Method for Online Thermal Monitoring of Switched Reluctance Machine

DEFF Research Database (Denmark)

Wang, Chao; Liu, Hui; Liu, Xiao

2015-01-01

Stator winding is one of the most vulnerable parts in Switched Reluctance Machine (SRM), especially under thermal stresses during frequently changing operation circumstances and susceptible heat dissipation conditions. Thus real-time online thermal monitoring of the stator winding is of great sig...

Monitoring of laser material processing using machine integrated low-coherence interferometry

Science.gov (United States)

Kunze, Rouwen; König, Niels; Schmitt, Robert

2017-06-01

Laser material processing has become an indispensable tool in modern production. With the availability of high power pico- and femtosecond laser sources, laser material processing is advancing into applications, which demand for highest accuracies such as laser micro milling or laser drilling. In order to enable narrow tolerance windows, a closedloop monitoring of the geometrical properties of the processed work piece is essential for achieving a robust manufacturing process. Low coherence interferometry (LCI) is a high-precision measuring principle well-known from surface metrology. In recent years, we demonstrated successful integrations of LCI into several different laser material processing methods. Within this paper, we give an overview about the different machine integration strategies, that always aim at a complete and ideally telecentric integration of the measurement device into the existing beam path of the processing laser. Thus, highly accurate depth measurements within machine coordinates and a subsequent process control and quality assurance are possible. First products using this principle have already found its way to the market, which underlines the potential of this technology for the monitoring of laser material processing.

A machine learning approach to the accurate prediction of monitor units for a compact proton machine.

Science.gov (United States)

Sun, Baozhou; Lam, Dao; Yang, Deshan; Grantham, Kevin; Zhang, Tiezhi; Mutic, Sasa; Zhao, Tianyu

2018-05-01

Clinical treatment planning systems for proton therapy currently do not calculate monitor units (MUs) in passive scatter proton therapy due to the complexity of the beam delivery systems. Physical phantom measurements are commonly employed to determine the field-specific output factors (OFs) but are often subject to limited machine time, measurement uncertainties and intensive labor. In this study, a machine learning-based approach was developed to predict output (cGy/MU) and derive MUs, incorporating the dependencies on gantry angle and field size for a single-room proton therapy system. The goal of this study was to develop a secondary check tool for OF measurements and eventually eliminate patient-specific OF measurements. The OFs of 1754 fields previously measured in a water phantom with calibrated ionization chambers and electrometers for patient-specific fields with various range and modulation width combinations for 23 options were included in this study. The training data sets for machine learning models in three different methods (Random Forest, XGBoost and Cubist) included 1431 (~81%) OFs. Ten-fold cross-validation was used to prevent "overfitting" and to validate each model. The remaining 323 (~19%) OFs were used to test the trained models. The difference between the measured and predicted values from machine learning models was analyzed. Model prediction accuracy was also compared with that of the semi-empirical model developed by Kooy (Phys. Med. Biol. 50, 2005). Additionally, gantry angle dependence of OFs was measured for three groups of options categorized on the selection of the second scatters. Field size dependence of OFs was investigated for the measurements with and without patient-specific apertures. All three machine learning methods showed higher accuracy than the semi-empirical model which shows considerably large discrepancy of up to 7.7% for the treatment fields with full range and full modulation width. The Cubist-based solution

Development of hardware system using temperature and vibration maintenance models integration concepts for conventional machines monitoring: A case study

OpenAIRE

Adeyeri, Michael Kanisuru; Mpofu, Khumbulani; Kareem, Buliaminu

2016-01-01

This article describes the integration of temperature and vibration models for maintenance monitoring of conventional machinery parts in which their optimal andbest functionalities are affected by abnormal changes in temperature and vibration values thereby resulting in machine failures, machines breakdown, poor quality of products, inability to meeting customers' demand, poor inventory control and just to mention a few. The work entails the use of temperature and vibration sensors as monitor...

Development of hardware system using temperature and vibration maintenance models integration concepts for conventional machines monitoring: a case study

Science.gov (United States)

Adeyeri, Michael Kanisuru; Mpofu, Khumbulani; Kareem, Buliaminu

2016-03-01

This article describes the integration of temperature and vibration models for maintenance monitoring of conventional machinery parts in which their optimal and best functionalities are affected by abnormal changes in temperature and vibration values thereby resulting in machine failures, machines breakdown, poor quality of products, inability to meeting customers' demand, poor inventory control and just to mention a few. The work entails the use of temperature and vibration sensors as monitoring probes programmed in microcontroller using C language. The developed hardware consists of vibration sensor of ADXL345, temperature sensor of AD594/595 of type K thermocouple, microcontroller, graphic liquid crystal display, real time clock, etc. The hardware is divided into two: one is based at the workstation (majorly meant to monitor machines behaviour) and the other at the base station (meant to receive transmission of machines information sent from the workstation), working cooperatively for effective functionalities. The resulting hardware built was calibrated, tested using model verification and validated through principles pivoted on least square and regression analysis approach using data read from the gear boxes of extruding and cutting machines used for polyethylene bag production. The results got therein confirmed related correlation existing between time, vibration and temperature, which are reflections of effective formulation of the developed concept.

Monitoring coordinate measuring machines by calibrated parts

International Nuclear Information System (INIS)

Weckenmann, A; Lorz, J

2005-01-01

Coordinate measuring machines (CMM) are essential for quality assurance and production control in modern manufacturing. Due to the necessity of assuring traceability during the use of CMM, interim checks with calibrated objects carried out periodically. For this purpose usually special artefacts like standardized ball plates, hole plates, ball bars or step gages are measured. Measuring calibrated series parts would be more advantageous. Applying the substitution method of ISO 15530-3: 2000 such parts can be used. It is less cost intensive and less time consuming than measuring expensive special standardized objects in special programmed measurement routines. Moreover, the measurement results can directly compare with the calibration values; thus, direct information on systematic measurement deviations and uncertainty of the measured features are available. The paper describes a procedure for monitoring horizontal-arm CMMs with calibrated sheet metal series parts

Human monitoring and decision-making in man/machine systems

International Nuclear Information System (INIS)

Johannsen, G.

1979-01-01

Monitoring and decision-making together are very well characterizing the role of the human operator in highly automated systems. In this report, the analysis of human monitoring and decision-making behavior as well as its modeling are described. The goal is to present a survey. 'Classic' and optimal control theoretic monitoring models are dealt with. The relationship between attention allocation and eye movements is discussed. As an example for applications, the evaluation of predictor displays by means of the optimal control model is explained. Fault detection in continuous signals and decision-making behavior of the human operator in fault diagnosis during different operation and maintenance situations are illustrated. The computer-aided decision-making is considered as a queueing problem. It is shown to what extent computer-aiding may be based on the state of human activity as measured by psychophysiological quantities. Finally, management information systems for different application areas are mentioned. As an appendix, the report includes an English-written paper in which the possibilities of mathematical modeling of human behavior in complex man-machine systems are critically assessed. (orig.) 891 GL/orig. 892 MKO [de

Unsupervised process monitoring and fault diagnosis with machine learning methods

CERN Document Server

Aldrich, Chris

2013-01-01

This unique text/reference describes in detail the latest advances in unsupervised process monitoring and fault diagnosis with machine learning methods. Abundant case studies throughout the text demonstrate the efficacy of each method in real-world settings. The broad coverage examines such cutting-edge topics as the use of information theory to enhance unsupervised learning in tree-based methods, the extension of kernel methods to multiple kernel learning for feature extraction from data, and the incremental training of multilayer perceptrons to construct deep architectures for enhanced data

Air quality monitoring using mobile microscopy and machine learning

KAUST Repository

Wu, Yi-Chen; Shiledar, Ashutosh; Li, Yi-Cheng; Wong, Jeffrey; Feng, Steve; Chen, Xuan; Chen, Christine; Jin, Kevin; Janamian, Saba; Yang, Zhe; Ballard, Zachary Scott; Gö rö cs, Zoltá n; Feizi, Alborz; Ozcan, Aydogan

2017-01-01

Rapid, accurate and high-throughput sizing and quantification of particulate matter (PM) in air is crucial for monitoring and improving air quality. In fact, particles in air with a diameter of ≤2.5 μm have been classified as carcinogenic by the World Health Organization. Here we present a field-portable cost-effective platform for high-throughput quantification of particulate matter using computational lens-free microscopy and machine-learning. This platform, termed c-Air, is also integrated with a smartphone application for device control and display of results. This mobile device rapidly screens 6.5 L of air in 30 s and generates microscopic images of the aerosols in air. It provides statistics of the particle size and density distribution with a sizing accuracy of ~93%. We tested this mobile platform by measuring the air quality at different indoor and outdoor environments and measurement times, and compared our results to those of an Environmental Protection Agency–approved device based on beta-attenuation monitoring, which showed strong correlation to c-Air measurements. Furthermore, we used c-Air to map the air quality around Los Angeles International Airport (LAX) over 24 h to confirm that the impact of LAX on increased PM concentration was present even at >7 km away from the airport, especially along the direction of landing flights. With its machine-learning-based computational microscopy interface, c-Air can be adaptively tailored to detect specific particles in air, for example, various types of pollen and mold and provide a cost-effective mobile solution for highly accurate and distributed sensing of air quality.

Air quality monitoring using mobile microscopy and machine learning

KAUST Repository

Wu, Yi-Chen

2017-09-08

Rapid, accurate and high-throughput sizing and quantification of particulate matter (PM) in air is crucial for monitoring and improving air quality. In fact, particles in air with a diameter of ≤2.5 μm have been classified as carcinogenic by the World Health Organization. Here we present a field-portable cost-effective platform for high-throughput quantification of particulate matter using computational lens-free microscopy and machine-learning. This platform, termed c-Air, is also integrated with a smartphone application for device control and display of results. This mobile device rapidly screens 6.5 L of air in 30 s and generates microscopic images of the aerosols in air. It provides statistics of the particle size and density distribution with a sizing accuracy of ~93%. We tested this mobile platform by measuring the air quality at different indoor and outdoor environments and measurement times, and compared our results to those of an Environmental Protection Agency–approved device based on beta-attenuation monitoring, which showed strong correlation to c-Air measurements. Furthermore, we used c-Air to map the air quality around Los Angeles International Airport (LAX) over 24 h to confirm that the impact of LAX on increased PM concentration was present even at >7 km away from the airport, especially along the direction of landing flights. With its machine-learning-based computational microscopy interface, c-Air can be adaptively tailored to detect specific particles in air, for example, various types of pollen and mold and provide a cost-effective mobile solution for highly accurate and distributed sensing of air quality.

Bite traces in a turtle carapace fragment from the middle Danian (Lower Paleocene) bryozoan limestone, Faxe, Denmark

DEFF Research Database (Denmark)

Milan, Jesper; Lindow, Bent Erik Kramer; Lauridsen, Bodil Wesenberg

2011-01-01

A fragment of a turtle carapace from the Middle Danian bryozoan limestone at the Faxe quarry, eastern Denmark, is identified as a partial costal plate from the carapace of a chelonioid turtle. The fragment bears traces of three separate acts of predation or scavenging. Two circular bite traces Ni...... either alone or in a row of three, are either from sharks or fish. This is the first record of turtles from the Danian bryozoan limestone exposed in Faxe....... Nihilichnus nihilicus Mikuláš et al. 2006, 4 mm in diameter, situated 2.5 cm apart, are interpreted as crocodylian. Groups of parallel scrapes, Machichnus bohemicus Mikuláš et al. 2006, 4–5 mm long and 0.5 mm wide, are interpreted as bite traces from sharks. Small circular traces, ~1 mm in diameter, found...

An on-line monitoring system for a micro electrical discharge machining (micro-EDM) process

International Nuclear Information System (INIS)

Liao, Y S; Chang, T Y; Chuang, T J

2008-01-01

A pulse-type discriminating system to monitor the process of micro electrical discharge machining (micro-EDM) is developed and implemented. The specific features are extracted and the pulses from a RC-type power source are classified into normal, effective arc, transient short circuit and complex types. An approach to discriminate the pulse type according to three durations measured at three pre-determined voltage levels of a pulse is proposed. The developed system is verified by using simulated signals. Discrimination of the pulse trains in actual machining processes shows that the pulses are mainly the normal type for micro wire-EDM and micro-EDM milling. The pulse-type distribution varies during the micro-EDM drilling process. The percentage of complex-type pulse increases monotonically with the drilling depth. It starts to drop when the gap condition is seriously deteriorated. Accordingly, an on-line monitoring strategy for the micro-EDM drilling process is proposed

The development of condition monitoring for the safety of rotating machine in PWR using motor current signature analysis

International Nuclear Information System (INIS)

Syaiful Bakhri

2013-01-01

Condition monitoring of rotating machine is essential to guarantee the safety operation as well as to improve the efficiency of nuclear power plants operations. One of the promising condition monitoring techniques which has been preferred currently since it is simple, non-invasive and inexpensive is Motor Stator Signature Analysis (MCSA). However, the investigation of the MCSA technique using a compact, low cost, and having industrial class hardware which is capable for nuclear power plant applications has been limited. The research is aimed to develop condition monitoring method based on MCSA utilizing a compact industrial class for nuclear power plant. The investigation includes development of condition monitoring based on real-time FPGA-CompatRIO hardware, development of a custom built display module for early warning system, testing of the monitoring hardware, fault frequency analysis of electric motors including the performances of fault detections. The condition monitoring system is able to execute a fault detection task around 164 ms, to recognize accurately fault frequencies of stator shorted turn for about 75%, broken rotor bar around 95%, eccentricity 65%, mechanical misalignment 85%, including supply voltage unbalances 100%. The condition monitoring system based on its performance assessments could become a suitable alternative not only for rotating machines but also condition monitoring for other nuclear reactor components. (author)

Design of a New Collimation System to Prevent Interference between X-ray Machines and Radiation Portal Monitors

International Nuclear Information System (INIS)

Guzzardo, Tyler; Livesay, Jake

2012-01-01

Researchers at Oak Ridge National Laboratory (ORNL) developed a new collimation system that allows radiation portal monitors (RPMs) installed near x-ray machines to operate with a negligible false-positive alarm rate. RPMs are usually installed as far as possible from x-ray machines because false alarms are triggered by escaping x-rays; however, constraints at the installation site sometimes make it necessary that RPMs be installed near x-ray machines. Such RPMs are often plagued by high alarm rates resulting from the simultaneous operation of the RPMs and x-ray machines. Limitations on pedestrian flow, x-ray machine orientation, and RPM location often preclude a simple solution for lowering the alarm rate. Adding additional collimation to the x-ray machines to stop the x-rays at the source can reduce the alarm rate without interfering with site operations or adversely affecting the minimum detectable quantity of material (MDQ). A collimation design has been verified by measurements conducted at a RPM installation site and is applicable to all new and existing RPM installations near x-ray machines.

Wireless Monitoring of Induction Machine Rotor Physical Variables

Directory of Open Access Journals (Sweden)

Jefferson Doolan Fernandes

2017-11-01

Full Text Available With the widespread use of electric machines, there is a growing need to extract information from the machines to improve their control systems and maintenance management. The present work shows the development of an embedded system to perform the monitoring of the rotor physical variables of a squirrel cage induction motor. The system is comprised of: a circuit to acquire desirable rotor variable(s and value(s that send it to the computer; a rectifier and power storage circuit that converts an alternating current in a continuous current but also stores energy for a certain amount of time to wait for the motor’s shutdown; and a magnetic generator that harvests energy from the rotating field to power the circuits mentioned above. The embedded system is set on the rotor of a 5 HP squirrel cage induction motor, making it difficult to power the system because it is rotating. This problem can be solved with the construction of a magnetic generator device to avoid the need of using batteries or collector rings and will send data to the computer using a wireless NRF24L01 module. For the proposed system, initial validation tests were made using a temperature sensor (DS18b20, as this variable is known as the most important when identifying the need for maintenance and control systems. Few tests have shown promising results that, with further improvements, can prove the feasibility of using sensors in the rotor.

Wireless Monitoring of Induction Machine Rotor Physical Variables.

Science.gov (United States)

Doolan Fernandes, Jefferson; Carvalho Souza, Francisco Elvis; Cipriano Maniçoba, Glauco George; Salazar, Andrés Ortiz; de Paiva, José Alvaro

2017-11-18

With the widespread use of electric machines, there is a growing need to extract information from the machines to improve their control systems and maintenance management. The present work shows the development of an embedded system to perform the monitoring of the rotor physical variables of a squirrel cage induction motor. The system is comprised of: a circuit to acquire desirable rotor variable(s) and value(s) that send it to the computer; a rectifier and power storage circuit that converts an alternating current in a continuous current but also stores energy for a certain amount of time to wait for the motor's shutdown; and a magnetic generator that harvests energy from the rotating field to power the circuits mentioned above. The embedded system is set on the rotor of a 5 HP squirrel cage induction motor, making it difficult to power the system because it is rotating. This problem can be solved with the construction of a magnetic generator device to avoid the need of using batteries or collector rings and will send data to the computer using a wireless NRF24L01 module. For the proposed system, initial validation tests were made using a temperature sensor (DS18b20), as this variable is known as the most important when identifying the need for maintenance and control systems. Few tests have shown promising results that, with further improvements, can prove the feasibility of using sensors in the rotor.

Feasibility study and technical proposal for seismic monitoring of tunnel boring machine in Olkiluoto

Energy Technology Data Exchange (ETDEWEB)

Saari, J.; Lakio, A. (AF-Consult Ltd, Vantaa (Finland))

2009-01-15

In Olkiluoto, Posiva Oy has operated a local seismic network since February 2002. The purpose of the microearthquake measurements at Olkiluoto is to improve understanding of the structure, behaviour and long term stability of the bedrock. The studies include both tectonic and excavation-induced microearthquakes. An additional task of monitoring is related to safeguarding of the ONKALO. The possibility to excavate an illegal access to the ONKALO, have been concerned when the safeguards are discussed. Therefore all recorded explosions in the Olkiluoto area and in the ONKALO are located. If a concentration of explosions is observed, the origin of that is found out. Also a concept of hidden illegal explosions, detonated at the same time as the real excavation blasts, has been examined. According to the experience gained in Olkiluoto, it can be concluded that, as long the seismic network is in operation and the results are analysed by a skilled person, it is practically impossible to do illegal excavation by blasts. In this report a possibility of seismic monitoring of illegal excavation done by tunnel boring machine (TBM) has been investigated. Characteristics of the seismic signal generated by the raise boring machine are described. According to this study, it can be concluded that the generated seismic signal can be detected and the source of the signal can be located. However, this task calls for different kind of monitoring system than that, which is currently used for monitoring microearthquakes and explosions. The presented technical proposal for seismic monitoring of TBM in Olkiluoto is capable to detect and locate TBM coming outside the ONKALO area about two months before it would reach the ONKALO. (orig.)

Feasibility study and technical proposal for seismic monitoring of tunnel boring machine in Olkiluoto

International Nuclear Information System (INIS)

Saari, J.; Lakio, A.

2009-01-01

In Olkiluoto, Posiva Oy has operated a local seismic network since February 2002. The purpose of the microearthquake measurements at Olkiluoto is to improve understanding of the structure, behaviour and long term stability of the bedrock. The studies include both tectonic and excavation-induced microearthquakes. An additional task of monitoring is related to safeguarding of the ONKALO. The possibility to excavate an illegal access to the ONKALO, have been concerned when the safeguards are discussed. Therefore all recorded explosions in the Olkiluoto area and in the ONKALO are located. If a concentration of explosions is observed, the origin of that is found out. Also a concept of hidden illegal explosions, detonated at the same time as the real excavation blasts, has been examined. According to the experience gained in Olkiluoto, it can be concluded that, as long the seismic network is in operation and the results are analysed by a skilled person, it is practically impossible to do illegal excavation by blasts. In this report a possibility of seismic monitoring of illegal excavation done by tunnel boring machine (TBM) has been investigated. Characteristics of the seismic signal generated by the raise boring machine are described. According to this study, it can be concluded that the generated seismic signal can be detected and the source of the signal can be located. However, this task calls for different kind of monitoring system than that, which is currently used for monitoring microearthquakes and explosions. The presented technical proposal for seismic monitoring of TBM in Olkiluoto is capable to detect and locate TBM coming outside the ONKALO area about two months before it would reach the ONKALO. (orig.)

Development of Client-Server Application by Using UDP Socket Programming for Remotely Monitoring CNC Machine Environment in Fixture Process

Directory of Open Access Journals (Sweden)

Darmawan Darmawan

2016-08-01

Full Text Available The use of computer technology in manufacturing industries can improve manufacturing flexibility significantly, especially in manufacturing processes; many software applications have been utilized to improve machining performance. However, none of them has discussed the abilities to perform direct machining. In this paper, an integrated system for remote operation and monitoring of Computer Numerical Control (CNC machines is put into consideration. The integrated system includes computerization, network technology, and improved holding mechanism. The work proposed by this research is mainly on the software development for such integrated system. It uses Java three-dimensional (3D programming and Virtual Reality Modeling Language (VRML at the client side for visualization of machining environment. This research is aimed at developing a control system to remotely operate and monitor a self-reconfiguration fixture mechanism of a CNC milling machine through internet connection and integration of Personal Computer (PC-based CNC controller, a server side, a client side and CNC milling. The performance of the developed system was evaluated by testing with one type of common protocols particularly User Datagram Protocol (UDP.  Using UDP, the developed system requires 3.9 seconds to complete the close clamping, less than 1 second to release the clamping and it can deliver 463 KiloByte.

Explosion Monitoring with Machine Learning: A LSTM Approach to Seismic Event Discrimination

Science.gov (United States)

Magana-Zook, S. A.; Ruppert, S. D.

2017-12-01

The streams of seismic data that analysts look at to discriminate natural from man- made events will soon grow from gigabytes of data per day to exponentially larger rates. This is an interesting problem as the requirement for real-time answers to questions of non-proliferation will remain the same, and the analyst pool cannot grow as fast as the data volume and velocity will. Machine learning is a tool that can solve the problem of seismic explosion monitoring at scale. Using machine learning, and Long Short-term Memory (LSTM) models in particular, analysts can become more efficient by focusing their attention on signals of interest. From a global dataset of earthquake and explosion events, a model was trained to recognize the different classes of events, given their spectrograms. Optimal recurrent node count and training iterations were found, and cross validation was performed to evaluate model performance. A 10-fold mean accuracy of 96.92% was achieved on a balanced dataset of 30,002 instances. Given that the model is 446.52 MB it can be used to simultaneously characterize all incoming signals by researchers looking at events in isolation on desktop machines, as well as at scale on all of the nodes of a real-time streaming platform. LLNL-ABS-735911

Learning to Monitor Machine Health with Convolutional Bi-Directional LSTM Networks.

Science.gov (United States)

Zhao, Rui; Yan, Ruqiang; Wang, Jinjiang; Mao, Kezhi

2017-01-30

In modern manufacturing systems and industries, more and more research efforts have been made in developing effective machine health monitoring systems. Among various machine health monitoring approaches, data-driven methods are gaining in popularity due to the development of advanced sensing and data analytic techniques. However, considering the noise, varying length and irregular sampling behind sensory data, this kind of sequential data cannot be fed into classification and regression models directly. Therefore, previous work focuses on feature extraction/fusion methods requiring expensive human labor and high quality expert knowledge. With the development of deep learning methods in the last few years, which redefine representation learning from raw data, a deep neural network structure named Convolutional Bi-directional Long Short-Term Memory networks (CBLSTM) has been designed here to address raw sensory data. CBLSTM firstly uses CNN to extract local features that are robust and informative from the sequential input. Then, bi-directional LSTM is introduced to encode temporal information. Long Short-Term Memory networks(LSTMs) are able to capture long-term dependencies and model sequential data, and the bi-directional structure enables the capture of past and future contexts. Stacked, fully-connected layers and the linear regression layer are built on top of bi-directional LSTMs to predict the target value. Here, a real-life tool wear test is introduced, and our proposed CBLSTM is able to predict the actual tool wear based on raw sensory data. The experimental results have shown that our model is able to outperform several state-of-the-art baseline methods.

Learning to Monitor Machine Health with Convolutional Bi-Directional LSTM Networks

Directory of Open Access Journals (Sweden)

Rui Zhao

2017-01-01

Full Text Available In modern manufacturing systems and industries, more and more research efforts have been made in developing effective machine health monitoring systems. Among various machine health monitoring approaches, data-driven methods are gaining in popularity due to the development of advanced sensing and data analytic techniques. However, considering the noise, varying length and irregular sampling behind sensory data, this kind of sequential data cannot be fed into classification and regression models directly. Therefore, previous work focuses on feature extraction/fusion methods requiring expensive human labor and high quality expert knowledge. With the development of deep learning methods in the last few years, which redefine representation learning from raw data, a deep neural network structure named Convolutional Bi-directional Long Short-Term Memory networks (CBLSTM has been designed here to address raw sensory data. CBLSTM firstly uses CNN to extract local features that are robust and informative from the sequential input. Then, bi-directional LSTM is introduced to encode temporal information. Long Short-Term Memory networks(LSTMs are able to capture long-term dependencies and model sequential data, and the bi-directional structure enables the capture of past and future contexts. Stacked, fully-connected layers and the linear regression layer are built on top of bi-directional LSTMs to predict the target value. Here, a real-life tool wear test is introduced, and our proposed CBLSTM is able to predict the actual tool wear based on raw sensory data. The experimental results have shown that our model is able to outperform several state-of-the-art baseline methods.

Machine learning techniques for optical communication system optimization

DEFF Research Database (Denmark)

Zibar, Darko; Wass, Jesper; Thrane, Jakob

In this paper, machine learning techniques relevant to optical communication are presented and discussed. The focus is on applying machine learning tools to optical performance monitoring and performance prediction.......In this paper, machine learning techniques relevant to optical communication are presented and discussed. The focus is on applying machine learning tools to optical performance monitoring and performance prediction....

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 This paper proposes a novel framework for monitoring the condition of a rotating machine (for example a gearbox or a bearing) that may be subject to load and speed fluctuations. The methodology is especially relevant in situations where no (or only...

Analysis on machine tool systems using spindle vibration monitoring for automatic tool changer

OpenAIRE

Shang-Liang Chen; Yin-Ting Cheng; Chin-Fa Su

2015-01-01

Recently, the intelligent systems of technology have become one of the major items in the development of machine tools. One crucial technology is the machinery status monitoring function, which is required for abnormal warnings and the improvement of cutting efficiency. During processing, the mobility act of the spindle unit determines the most frequent and important part such as automatic tool changer. The vibration detection system includes the development of hardware and software, such as ...

Analysis on machine tool systems using spindle vibration monitoring for automatic tool changer

Directory of Open Access Journals (Sweden)

Shang-Liang Chen

2015-12-01

Full Text Available Recently, the intelligent systems of technology have become one of the major items in the development of machine tools. One crucial technology is the machinery status monitoring function, which is required for abnormal warnings and the improvement of cutting efficiency. During processing, the mobility act of the spindle unit determines the most frequent and important part such as automatic tool changer. The vibration detection system includes the development of hardware and software, such as vibration meter, signal acquisition card, data processing platform, and machine control program. Meanwhile, based on the difference between the mechanical configuration and the desired characteristics, it is difficult for a vibration detection system to directly choose the commercially available kits. For this reason, it was also selected as an item for self-development research, along with the exploration of a significant parametric study that is sufficient to represent the machine characteristics and states. However, we also launched the development of functional parts of the system simultaneously. Finally, we entered the conditions and the parameters generated from both the states and the characteristics into the developed system to verify its feasibility.

Advances in industrial biopharmaceutical batch process monitoring: Machine-learning methods for small data problems.

Science.gov (United States)

Tulsyan, Aditya; Garvin, Christopher; Ündey, Cenk

2018-04-06

Biopharmaceutical manufacturing comprises of multiple distinct processing steps that require effective and efficient monitoring of many variables simultaneously in real-time. The state-of-the-art real-time multivariate statistical batch process monitoring (BPM) platforms have been in use in recent years to ensure comprehensive monitoring is in place as a complementary tool for continued process verification to detect weak signals. This article addresses a longstanding, industry-wide problem in BPM, referred to as the "Low-N" problem, wherein a product has a limited production history. The current best industrial practice to address the Low-N problem is to switch from a multivariate to a univariate BPM, until sufficient product history is available to build and deploy a multivariate BPM platform. Every batch run without a robust multivariate BPM platform poses risk of not detecting potential weak signals developing in the process that might have an impact on process and product performance. In this article, we propose an approach to solve the Low-N problem by generating an arbitrarily large number of in silico batches through a combination of hardware exploitation and machine-learning methods. To the best of authors' knowledge, this is the first article to provide a solution to the Low-N problem in biopharmaceutical manufacturing using machine-learning methods. Several industrial case studies from bulk drug substance manufacturing are presented to demonstrate the efficacy of the proposed approach for BPM under various Low-N scenarios. © 2018 Wiley Periodicals, Inc.

Prediction of Machine Tool Condition Using Support Vector Machine

International Nuclear Information System (INIS)

Wang Peigong; Meng Qingfeng; Zhao Jian; Li Junjie; Wang Xiufeng

2011-01-01

Condition monitoring and predicting of CNC machine tools are investigated in this paper. Considering the CNC machine tools are often small numbers of samples, a condition predicting method for CNC machine tools based on support vector machines (SVMs) is proposed, then one-step and multi-step condition prediction models are constructed. The support vector machines prediction models are used to predict the trends of working condition of a certain type of CNC worm wheel and gear grinding machine by applying sequence data of vibration signal, which is collected during machine processing. And the relationship between different eigenvalue in CNC vibration signal and machining quality is discussed. The test result shows that the trend of vibration signal Peak-to-peak value in surface normal direction is most relevant to the trend of surface roughness value. In trends prediction of working condition, support vector machine has higher prediction accuracy both in the short term ('One-step') and long term (multi-step) prediction compared to autoregressive (AR) model and the RBF neural network. Experimental results show that it is feasible to apply support vector machine to CNC machine tool condition prediction.

Faxing Structures to the Moon: Freeform Additive Construction System (FACS)

Science.gov (United States)

Howe, A. Scott; Wilcox, Brian; McQuin, Christopher; Townsend, Julie; Rieber, Richard; Barmatz, Martin; Leichty, John

2013-01-01

Using the highly articulated All-Terrain Hex-Limbed Extra-Terrestrial Explorer (ATHLETE) robotic mobility system as a precision positioning tool, a variety of print head technologies can be used to 3D print large-scale in-situ structures on planetary surfaces such as the moon or Mars. In effect, in the same way CAD models can be printed in a 3D printer, large-scale structures such as walls, vaults, domes, berms, paving, trench walls, and other insitu derived elements can be FAXed to the planetary surface and built in advance of the arrival of crews, supplementing equipment and materials brought from earth. This paper discusses the ATHLETE system as a mobility / positioning platform, and presents several options for large-scale additive print head technologies, including tunable microwave "sinterator" approaches and in-situ concrete deposition. The paper also discusses potential applications, such as sintered-in-place habitat shells, radiation shielding, road paving, modular bricks, and prefabricated construction components.

Electrical machines diagnosis

CERN Document Server

Trigeassou, Jean-Claude

2013-01-01

Monitoring and diagnosis of electrical machine faults is a scientific and economic issue which is motivated by objectives for reliability and serviceability in electrical drives.This book provides a survey of the techniques used to detect the faults occurring in electrical drives: electrical, thermal and mechanical faults of the electrical machine, faults of the static converter and faults of the energy storage unit.Diagnosis of faults occurring in electrical drives is an essential part of a global monitoring system used to improve reliability and serviceability. This diagnosis is perf

Computer-based diagnostic monitoring to enhance the human-machine interface of complex processes

International Nuclear Information System (INIS)

Kim, I.S.

1992-02-01

There is a growing interest in introducing an automated, on-line, diagnostic monitoring function into the human-machine interfaces (HMIs) or control rooms of complex process plants. The design of such a system should be properly integrated with other HMI systems in the control room, such as the alarms system or the Safety Parameter Display System (SPDS). This paper provides a conceptual foundation for the development of a Plant-wide Diagnostic Monitoring System (PDMS), along with functional requirements for the system and other advanced HMI systems. Insights are presented into the design of an efficient and robust PDMS, which were gained from a critical review of various methodologies developed in the nuclear power industry, the chemical process industry, and the space technological community

A Field Programmable Gate Array-Based Reconfigurable Smart-Sensor Network for Wireless Monitoring of New Generation Computer Numerically Controlled Machines

Directory of Open Access Journals (Sweden)

Ion Stiharu

2010-08-01

Full Text Available Computer numerically controlled (CNC machines have evolved to adapt to increasing technological and industrial requirements. To cover these needs, new generation machines have to perform monitoring strategies by incorporating multiple sensors. Since in most of applications the online Processing of the variables is essential, the use of smart sensors is necessary. The contribution of this work is the development of a wireless network platform of reconfigurable smart sensors for CNC machine applications complying with the measurement requirements of new generation CNC machines. Four different smart sensors are put under test in the network and their corresponding signal processing techniques are implemented in a Field Programmable Gate Array (FPGA-based sensor node.

A Field Programmable Gate Array-Based Reconfigurable Smart-Sensor Network for Wireless Monitoring of New Generation Computer Numerically Controlled Machines

Science.gov (United States)

Moreno-Tapia, Sandra Veronica; Vera-Salas, Luis Alberto; Osornio-Rios, Roque Alfredo; Dominguez-Gonzalez, Aurelio; Stiharu, Ion; de Jesus Romero-Troncoso, Rene

2010-01-01

Computer numerically controlled (CNC) machines have evolved to adapt to increasing technological and industrial requirements. To cover these needs, new generation machines have to perform monitoring strategies by incorporating multiple sensors. Since in most of applications the online Processing of the variables is essential, the use of smart sensors is necessary. The contribution of this work is the development of a wireless network platform of reconfigurable smart sensors for CNC machine applications complying with the measurement requirements of new generation CNC machines. Four different smart sensors are put under test in the network and their corresponding signal processing techniques are implemented in a Field Programmable Gate Array (FPGA)-based sensor node. PMID:22163602

78 FR 37723 - Laser Products; Proposed Amendment to Performance Standard

Science.gov (United States)

2013-06-24

... of products that incorporate lasers are compact disc and DVD players, fax machines, fiber optic and... incorporate lasers are compact disc and DVD players, fax machines, fiber optic and free-air communication... additional training costs associated with learning the new standard, but believe estimated costs would be so...

Indirect Tire Monitoring System - Machine Learning Approach

Science.gov (United States)

Svensson, O.; Thelin, S.; Byttner, S.; Fan, Y.

2017-10-01

The heavy vehicle industry has today no requirement to provide a tire pressure monitoring system by law. This has created issues surrounding unknown tire pressure and thread depth during active service. There is also no standardization for these kind of systems which means that different manufacturers and third party solutions work after their own principles and it can be hard to know what works for a given vehicle type. The objective is to create an indirect tire monitoring system that can generalize a method that detect both incorrect tire pressure and thread depth for different type of vehicles within a fleet without the need for additional physical sensors or vehicle specific parameters. The existing sensors that are connected communicate through CAN and are interpreted by the Drivec Bridge hardware that exist in the fleet. By using supervised machine learning a classifier was created for each axle where the main focus was the front axle which had the most issues. The classifier will classify the vehicles tires condition and will be implemented in Drivecs cloud service where it will receive its data. The resulting classifier is a random forest implemented in Python. The result from the front axle with a data set consisting of 9767 samples of buses with correct tire condition and 1909 samples of buses with incorrect tire condition it has an accuracy of 90.54% (0.96%). The data sets are created from 34 unique measurements from buses between January and May 2017. This classifier has been exported and is used inside a Node.js module created for Drivecs cloud service which is the result of the whole implementation. The developed solution is called Indirect Tire Monitoring System (ITMS) and is seen as a process. This process will predict bad classes in the cloud which will lead to warnings. The warnings are defined as incidents. They contain only the information needed and the bandwidth of the incidents are also controlled so incidents are created within an

The heater system monitoring and control of the fuelling machines test rig fluid

International Nuclear Information System (INIS)

Iorga, C.; Iorga, H.

2016-01-01

The thermo-mechanical hot loop (HL) of the testing rig for the fuelling machines (F/Ms) represents a set of facilities and equipment that perform the pressure, temperature and flow thermo-hydraulic parameters similar to those from the fuel channel for CANDU 600 reactor types. The 2.1 MW electric heater (EH), part of the HL, working under the conditions of a pressure vessel (110 bars) and provides an average temperature of 300°C of the working agent. The monitoring equipment implemented aims to simultaneously control the temperature for each of the 12 modules that compose the EH, without influencing the work logic of the display/recording and protecting existing equipment. This paper presents the structure of the monitoring equipment and its performance obtained after performing the functional tests. (authors)

Real-time depth monitoring and control of laser machining through scanning beam delivery system

International Nuclear Information System (INIS)

Ji, Yang; Grindal, Alexander W; Fraser, James M; Webster, Paul J L

2015-01-01

Scanning optics enable many laser applications in manufacturing because their low inertia allows rapid movement of the process beam across the sample. We describe our method of inline coherent imaging for real-time (up to 230 kHz) micron-scale (7–8 µm axial resolution) tracking and control of laser machining depth through a scanning galvo-telecentric beam delivery system. For 1 cm trench etching in stainless steel, we collect high speed intrapulse and interpulse morphology which is useful for further understanding underlying mechanisms or comparison with numerical models. We also collect overall sweep-to-sweep depth penetration which can be used for feedback depth control. For trench etching in silicon, we show the relationship of etch rate with average power and scan speed by computer processing of depth information without destructive sample post-processing. We also achieve three-dimensional infrared continuous wave (modulated) laser machining of a 3.96 × 3.96 × 0.5 mm 3 (length × width × maximum depth) pattern on steel with depth feedback. To the best of our knowledge, this is the first successful demonstration of direct real-time depth monitoring and control of laser machining with scanning optics. (paper)

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.

A Machine-Learning and Filtering Based Data Assimilation Framework for Geologic Carbon Sequestration Monitoring Optimization

Science.gov (United States)

Chen, B.; Harp, D. R.; Lin, Y.; Keating, E. H.; Pawar, R.

2017-12-01

Monitoring is a crucial aspect of geologic carbon sequestration (GCS) risk management. It has gained importance as a means to ensure CO2 is safely and permanently stored underground throughout the lifecycle of a GCS project. Three issues are often involved in a monitoring project: (i) where is the optimal location to place the monitoring well(s), (ii) what type of data (pressure, rate and/or CO2 concentration) should be measured, and (iii) What is the optimal frequency to collect the data. In order to address these important issues, a filtering-based data assimilation procedure is developed to perform the monitoring optimization. The optimal monitoring strategy is selected based on the uncertainty reduction of the objective of interest (e.g., cumulative CO2 leak) for all potential monitoring strategies. To reduce the computational cost of the filtering-based data assimilation process, two machine-learning algorithms: Support Vector Regression (SVR) and Multivariate Adaptive Regression Splines (MARS) are used to develop the computationally efficient reduced-order-models (ROMs) from full numerical simulations of CO2 and brine flow. The proposed framework for GCS monitoring optimization is demonstrated with two examples: a simple 3D synthetic case and a real field case named Rock Spring Uplift carbon storage site in Southwestern Wyoming.

Machine Learning

CERN Multimedia

CERN. Geneva

2017-01-01

Machine learning, which builds on ideas in computer science, statistics, and optimization, focuses on developing algorithms to identify patterns and regularities in data, and using these learned patterns to make predictions on new observations. Boosted by its industrial and commercial applications, the field of machine learning is quickly evolving and expanding. Recent advances have seen great success in the realms of computer vision, natural language processing, and broadly in data science. Many of these techniques have already been applied in particle physics, for instance for particle identification, detector monitoring, and the optimization of computer resources. Modern machine learning approaches, such as deep learning, are only just beginning to be applied to the analysis of High Energy Physics data to approach more and more complex problems. These classes will review the framework behind machine learning and discuss recent developments in the field.

Specificity of DNA-binding by the FAX-1 and NHR-67 nuclear receptors of Caenorhabditis elegans is partially mediated via a subclass-specific P-box residue

Directory of Open Access Journals (Sweden)

Smith Eric L

2008-01-01

Full Text Available Abstract Background The nuclear receptors of the NR2E class play important roles in pattern formation and nervous system development. Based on a phylogenetic analysis of DNA-binding domains, we define two conserved groups of orthologous NR2E genes: the NR2E1 subclass, which includes C. elegans nhr-67, Drosophila tailless and dissatisfaction, and vertebrate Tlx (NR2E2, NR2E4, NR2E1, and the NR2E3 subclass, which includes C. elegans fax-1 and vertebrate PNR (NR2E5, NR2E3. PNR and Tll nuclear receptors have been shown to bind the hexamer half-site AAGTCA, instead of the hexamer AGGTCA recognized by most other nuclear receptors, suggesting unique DNA-binding properties for NR2E class members. Results We show that NR2E3 subclass member FAX-1, unlike NHR-67 and other NR2E1 subclass members, binds to hexamer half-sites with relaxed specificity: it will bind hexamers with the sequence ANGTCA, although it prefers a purine to a pyrimidine at the second position. We use site-directed mutagenesis to demonstrate that the difference between FAX-1 and NHR-67 binding preference is partially mediated by a conserved subclass-specific asparagine or aspartate residue at position 19 of the DNA-binding domain. This amino acid position is part of the "P box" that plays a critical role in defining binding site specificity and has been shown to make hydrogen-bond contacts to the second position of the hexamer in co-crystal structures for other nuclear receptors. The relaxed specificity allows FAX-1 to bind a much larger repertoire of half-sites than NHR-67. While NR2E1 class proteins bind both monomeric and dimeric sites, the NR2E3 class proteins bind only dimeric sites. The presence of a single strong site adjacent to a very weak site allows dimeric FAX-1 binding, further increasing the number of dimeric binding sites to which FAX-1 may bind in vivo. Conclusion These findings identify subclass-specific DNA-binding specificities and dimerization properties for the NR2E1

An illustration of new methods in machine condition monitoring, Part I: stochastic resonance

International Nuclear Information System (INIS)

Worden, K.; Antoniadou, I.; Marchesiello, S.; Mba, C.; Garibaldi, L.

2017-01-01

There have been many recent developments in the application of data-based methods to machine condition monitoring. A powerful methodology based on machine learning has emerged, where diagnostics are based on a two-step procedure: extraction of damage-sensitive features, followed by unsupervised learning (novelty detection) or supervised learning (classification). The objective of the current pair of papers is simply to illustrate one state-of-the-art procedure for each step, using synthetic data representative of reality in terms of size and complexity. The first paper in the pair will deal with feature extraction. Although some papers have appeared in the recent past considering stochastic resonance as a means of amplifying damage information in signals, they have largely relied on ad hoc specifications of the resonator used. In contrast, the current paper will adopt a principled optimisation-based approach to the resonator design. The paper will also show that a discrete dynamical system can provide all the benefits of a continuous system, but also provide a considerable speed-up in terms of simulation time in order to facilitate the optimisation approach. (paper)

A DSP-Based Beam Current Monitoring System for Machine Protection Using Adaptive Filtering

International Nuclear Information System (INIS)

J. Musson; H. Dong; R. Flood; C. Hovater; J. Hereford

2001-01-01

The CEBAF accelerator at Jefferson Lab is currently using an analog beam current monitoring (BCM) system for its machine protection system (MPS), which has a loss accuracy of 2 micro-amps. Recent burn-through simulations predict catastrophic beam line component failures below 1 micro-amp of loss, resulting in a blind spot for the MPS. Revised MPS requirements target an ultimate beam loss accuracy of 250 nA. A new beam current monitoring system has been developed which utilizes modern digital receiver technology and digital signal processing concepts. The receiver employs a direct-digital down converter integrated circuit, mated with a Jefferson Lab digital signal processor VME card. Adaptive filtering is used to take advantage of current-dependent burn-through rates. Benefits of such a system include elimination of DC offsets, generic algorithm development, extensive filter options, and interfaces to UNIX-based control systems

Machine Learning Techniques in Clinical Vision Sciences.

Science.gov (United States)

Caixinha, Miguel; Nunes, Sandrina

2017-01-01

This review presents and discusses the contribution of machine learning techniques for diagnosis and disease monitoring in the context of clinical vision science. Many ocular diseases leading to blindness can be halted or delayed when detected and treated at its earliest stages. With the recent developments in diagnostic devices, imaging and genomics, new sources of data for early disease detection and patients' management are now available. Machine learning techniques emerged in the biomedical sciences as clinical decision-support techniques to improve sensitivity and specificity of disease detection and monitoring, increasing objectively the clinical decision-making process. This manuscript presents a review in multimodal ocular disease diagnosis and monitoring based on machine learning approaches. In the first section, the technical issues related to the different machine learning approaches will be present. Machine learning techniques are used to automatically recognize complex patterns in a given dataset. These techniques allows creating homogeneous groups (unsupervised learning), or creating a classifier predicting group membership of new cases (supervised learning), when a group label is available for each case. To ensure a good performance of the machine learning techniques in a given dataset, all possible sources of bias should be removed or minimized. For that, the representativeness of the input dataset for the true population should be confirmed, the noise should be removed, the missing data should be treated and the data dimensionally (i.e., the number of parameters/features and the number of cases in the dataset) should be adjusted. The application of machine learning techniques in ocular disease diagnosis and monitoring will be presented and discussed in the second section of this manuscript. To show the clinical benefits of machine learning in clinical vision sciences, several examples will be presented in glaucoma, age-related macular degeneration

Design and setting up of a system for remote monitoring and control on auxiliary machines in electric vehicles

Directory of Open Access Journals (Sweden)

Dimitrov Vasil

2017-01-01

Full Text Available Systems for remote monitoring and control of the proper operation, energy consumption, and efficiency of the controlled objects are very often used in different spheres of industry, in the electricity distribution network, etc. Various types of intelligent energy meters, PLCs and other control devices are involved in such systems. Proper operation of the auxiliary machines in electric vehicles is of great importance and implementation of a system for their remote monitoring and control is useful and ensures reliability and increased efficiency. A system has been designed and built using contemporary devices. An asynchronous motor is controlled by a soft starter and opportunities for remote monitoring (by an intelligent energy meter and control (by a PLC and Touch panel have been provided. Soft starters are widely used in industry for control on asynchronous drives when speed regulation is not a mandatory requirement. They are cheaper than inverters and frequency converters and allow for temporal reduction of the torque and current surge during start-up, as well as smooth deceleration. Therefore they can also be used in electric vehicles to control auxiliary machines (pumps, fans, air coolers, compressors, etc.. The present paper presents a methodology for their design and setting up.

On the Impossibility of Detecting Virtual Machine Monitors

Science.gov (United States)

Gueron, Shay; Seifert, Jean-Pierre

Virtualization based upon Virtual Machines is a central building block of Trusted Computing, and it is believed to offer isolation and confinement of privileged instructions among other security benefits. However, it is not necessarily bullet-proof — some recent publications have shown that Virtual Machine technology could potentially allow the installation of undetectable malware root kits. As a result, it was suggested that such virtualization attacks could be mitigated by checking if a threatened system runs in a virtualized or in a native environment. This naturally raises the following problem: Can a program determine whether it is running in a virtualized environment, or in a native machine environment? We prove here that, under a classical VM model, this problem is not decidable. Further, although our result seems to be quite theoretic, we also show that it has practical implications on related virtualization problems.

Investigation into the effect of fixturing systems on the design of condition monitoring for machining operations

OpenAIRE

Abbas, JK

2013-01-01

The global market competition has drawn the manufacturer’s attention on automated manufacturing processes using condition monitoring systems. These systems have been used for improving product quality, eliminating inspection, and enhancing manufacturing productivity. Fixtures are essential devices in machining processes to hold the tool or workpiece, hence they are influenced directly by the stability of the cutting tool. Therefore, tool and fixturing faults play an important part in the inac...

Integrating Statistical Machine Learning in a Semantic Sensor Web for Proactive Monitoring and Control

Directory of Open Access Journals (Sweden)

Jude Adekunle Adeleke

2017-04-01

Full Text Available Proactive monitoring and control of our natural and built environments is important in various application scenarios. Semantic Sensor Web technologies have been well researched and used for environmental monitoring applications to expose sensor data for analysis in order to provide responsive actions in situations of interest. While these applications provide quick response to situations, to minimize their unwanted effects, research efforts are still necessary to provide techniques that can anticipate the future to support proactive control, such that unwanted situations can be averted altogether. This study integrates a statistical machine learning based predictive model in a Semantic Sensor Web using stream reasoning. The approach is evaluated in an indoor air quality monitoring case study. A sliding window approach that employs the Multilayer Perceptron model to predict short term PM 2 . 5 pollution situations is integrated into the proactive monitoring and control framework. Results show that the proposed approach can effectively predict short term PM 2 . 5 pollution situations: precision of up to 0.86 and sensitivity of up to 0.85 is achieved over half hour prediction horizons, making it possible for the system to warn occupants or even to autonomously avert the predicted pollution situations within the context of Semantic Sensor Web.

Integrating Statistical Machine Learning in a Semantic Sensor Web for Proactive Monitoring and Control.

Science.gov (United States)

Adeleke, Jude Adekunle; Moodley, Deshendran; Rens, Gavin; Adewumi, Aderemi Oluyinka

2017-04-09

Proactive monitoring and control of our natural and built environments is important in various application scenarios. Semantic Sensor Web technologies have been well researched and used for environmental monitoring applications to expose sensor data for analysis in order to provide responsive actions in situations of interest. While these applications provide quick response to situations, to minimize their unwanted effects, research efforts are still necessary to provide techniques that can anticipate the future to support proactive control, such that unwanted situations can be averted altogether. This study integrates a statistical machine learning based predictive model in a Semantic Sensor Web using stream reasoning. The approach is evaluated in an indoor air quality monitoring case study. A sliding window approach that employs the Multilayer Perceptron model to predict short term PM 2 . 5 pollution situations is integrated into the proactive monitoring and control framework. Results show that the proposed approach can effectively predict short term PM 2 . 5 pollution situations: precision of up to 0.86 and sensitivity of up to 0.85 is achieved over half hour prediction horizons, making it possible for the system to warn occupants or even to autonomously avert the predicted pollution situations within the context of Semantic Sensor Web.

vSphere virtual machine management

CERN Document Server

Fitzhugh, Rebecca

2014-01-01

This book follows a step-by-step tutorial approach with some real-world scenarios that vSphere businesses will be required to overcome every day. This book also discusses creating and configuring virtual machines and also covers monitoring virtual machine performance and resource allocation options. This book is for VMware administrators who want to build their knowledge of virtual machine administration and configuration. It's assumed that you have some experience with virtualization administration and vSphere.

Fully automatic CNC machining production system

Directory of Open Access Journals (Sweden)

Lee Jeng-Dao

2017-01-01

Full Text Available Customized manufacturing is increasing years by years. The consumption habits change has been cause the shorter of product life cycle. Therefore, many countries view industry 4.0 as a target to achieve more efficient and more flexible automated production. To develop an automatic loading and unloading CNC machining system via vision inspection is the first step in industrial upgrading. CNC controller is adopted as the main controller to command to the robot, conveyor, and other equipment in this study. Moreover, machine vision systems are used to detect position of material on the conveyor and the edge of the machining material. In addition, Open CNC and SCADA software will be utilized to make real-time monitor, remote system of control, alarm email notification, and parameters collection. Furthermore, RFID has been added to employee classification and management. The machine handshaking has been successfully proposed to achieve automatic vision detect, edge tracing measurement, machining and system parameters collection for data analysis to accomplish industrial automation system integration with real-time monitor.

Methodology for testing a system for remote monitoring and control on auxiliary machines in electric vehicles

Directory of Open Access Journals (Sweden)

Dimitrov Vasil

2017-01-01

Full Text Available A laboratory system for remote monitoring and control of an asynchronous motor controlled by a soft starter and contemporary measuring and control devices has been developed and built. This laboratory system is used for research and in teaching. A study of the principles of operation, setting up and examination of intelligent energy meters, soft starters and PLC has been made as knowledge of the relevant software products is necessary. This is of great importance because systems for remote monitoring and control of energy consumption, efficiency and proper operation of the controlled objects are very often used in different spheres of industry, in building automation, transport, electricity distribution network, etc. Their implementation in electric vehicles for remote monitoring and control on auxiliary machines is also possible and very useful. In this paper, a methodology of tests is developed and some experiments are presented. Thus, an experimental verification of the developed methodology is made.

Sixth international conference on electrical machines and drives

International Nuclear Information System (INIS)

1993-01-01

This volume contains 111 papers presented at the Sixth International Conference on Electrical Machines and Drives. The topics covered include: miniature and micro motors; induction motors; DC machines; reluctance motors; condition monitoring; synchronous machines and drives; induction machines; induction generators; simulation; design; and operating experience; linear machines; noise and vibration; special machines. Separate abstracts have been prepared for a paper on linear step motors for control rod drives and for a paper on a motor drive for gas filtration in gas-cooled reactors. (UK)

Automated system of monitoring and positioning of functional units of mining technological machines for coal-mining enterprises

Directory of Open Access Journals (Sweden)

Meshcheryakov Yaroslav

2018-01-01

Full Text Available This article is show to the development of an automated monitoring and positioning system for functional nodes of mining technological machines. It describes the structure, element base, algorithms for identifying the operating states of a walking excavator; various types of errors in the functioning of microelectromechanical gyroscopes and accelerometers, as well as methods for their correction based on the Madgwick fusion filter. The results of industrial tests of an automated monitoring and positioning system for functional units on one of the opencast coal mines of Kuzbass are presented. This work is addressed to specialists working in the fields of the development of embedded systems and control systems, radio electronics, mechatronics, and robotics.

The fate of a middle Danian (Lower Paleocene) turtle from the bryozoan limestone of Faxe Quarry, Denmark

DEFF Research Database (Denmark)

Milàn, Jesper; Lindow, Bent Erik Kramer; Lauridsen, Bodil Wesenberg

A piece of turtle carapace from the Middle Danian bryozoan limestone at the Faxe quarry, eastern Denmark, is identified as a partial coastal plate from the carapace of a chelonioid turtle. In addition to being the first record of turtles from the Middle Danian of Denmark, the fragment bears evide....... Smaller groups of parallel scrapes, 4-5mm long and 0.5mm, wide are interpreted as bite traces from sharks, and small circular traces, only 1mm in diameter, found either solitary or in a row of three, are interpreted as scavenging traces from fish....

Ultrasensitive and Highly Stable Resistive Pressure Sensors with Biomaterial-Incorporated Interfacial Layers for Wearable Health-Monitoring and Human-Machine Interfaces.

Science.gov (United States)

Chang, Hochan; Kim, Sungwoong; Jin, Sumin; Lee, Seung-Woo; Yang, Gil-Tae; Lee, Ki-Young; Yi, Hyunjung

2018-01-10

Flexible piezoresistive sensors have huge potential for health monitoring, human-machine interfaces, prosthetic limbs, and intelligent robotics. A variety of nanomaterials and structural schemes have been proposed for realizing ultrasensitive flexible piezoresistive sensors. However, despite the success of recent efforts, high sensitivity within narrower pressure ranges and/or the challenging adhesion and stability issues still potentially limit their broad applications. Herein, we introduce a biomaterial-based scheme for the development of flexible pressure sensors that are ultrasensitive (resistance change by 5 orders) over a broad pressure range of 0.1-100 kPa, promptly responsive (20 ms), and yet highly stable. We show that employing biomaterial-incorporated conductive networks of single-walled carbon nanotubes as interfacial layers of contact-based resistive pressure sensors significantly enhances piezoresistive response via effective modulation of the interlayer resistance and provides stable interfaces for the pressure sensors. The developed flexible sensor is capable of real-time monitoring of wrist pulse waves under external medium pressure levels and providing pressure profiles applied by a thumb and a forefinger during object manipulation at a low voltage (1 V) and power consumption (<12 μW). This work provides a new insight into the material candidates and approaches for the development of wearable health-monitoring and human-machine interfaces.

Remediating radium contaminated legacy sites: Advances made through machine learning in routine monitoring of “hot” particles

Energy Technology Data Exchange (ETDEWEB)

Varley, Adam, E-mail: a.l.varley@stir.ac.uk [Department of Biological and Environmental Sciences, University of Stirling, Stirling FK9 4LA (United Kingdom); Tyler, Andrew, E-mail: a.n.tyler@stir.ac.uk [Department of Biological and Environmental Sciences, University of Stirling, Stirling FK9 4LA (United Kingdom); Smith, Leslie, E-mail: l.s.smith@cs.stir.ac.uk [Department of Computing Science and Mathematics, University of Stirling, Stirling FK9 4LA (United Kingdom); Dale, Paul, E-mail: paul.dale@sepa.org.uk [Scottish Environmental Protection Agency, Radioactive Substances, Strathallan House, Castle Business Park, Stirling FK9 4TZ (United Kingdom); Davies, Mike, E-mail: Mike.Davies@nuvia.co.uk [Nuvia Limited, The Library, Eight Street, Harwell Oxford, Didcot, Oxfordshire OX11 0RL (United Kingdom)

2015-07-15

The extensive use of radium during the 20th century for industrial, military and pharmaceutical purposes has led to a large number of contaminated legacy sites across Europe and North America. Sites that pose a high risk to the general public can present expensive and long-term remediation projects. Often the most pragmatic remediation approach is through routine monitoring operating gamma-ray detectors to identify, in real-time, the signal from the most hazardous heterogeneous contamination (hot particles); thus facilitating their removal and safe disposal. However, current detection systems do not fully utilise all spectral information resulting in low detection rates and ultimately an increased risk to the human health. The aim of this study was to establish an optimised detector-algorithm combination. To achieve this, field data was collected using two handheld detectors (sodium iodide and lanthanum bromide) and a number of Monte Carlo simulated hot particles were randomly injected into the field data. This allowed for the detection rate of conventional deterministic (gross counts) and machine learning (neural networks and support vector machines) algorithms to be assessed. The results demonstrated that a Neural Network operated on a sodium iodide detector provided the best detection capability. Compared to deterministic approaches, this optimised detection system could detect a hot particle on average 10 cm deeper into the soil column or with half of the activity at the same depth. It was also found that noise presented by internal contamination restricted lanthanum bromide for this application. - Highlights: • Land contaminated with radium is hazardous to human health. • Routine monitoring permits identification and removal of radioactive hot particles. • Current alarm algorithms do not provide reliable hot particle detection. • Spectral processing using Machine Learning significantly improves detection.

Remediating radium contaminated legacy sites: Advances made through machine learning in routine monitoring of “hot” particles

International Nuclear Information System (INIS)

Varley, Adam; Tyler, Andrew; Smith, Leslie; Dale, Paul; Davies, Mike

2015-01-01

The extensive use of radium during the 20th century for industrial, military and pharmaceutical purposes has led to a large number of contaminated legacy sites across Europe and North America. Sites that pose a high risk to the general public can present expensive and long-term remediation projects. Often the most pragmatic remediation approach is through routine monitoring operating gamma-ray detectors to identify, in real-time, the signal from the most hazardous heterogeneous contamination (hot particles); thus facilitating their removal and safe disposal. However, current detection systems do not fully utilise all spectral information resulting in low detection rates and ultimately an increased risk to the human health. The aim of this study was to establish an optimised detector-algorithm combination. To achieve this, field data was collected using two handheld detectors (sodium iodide and lanthanum bromide) and a number of Monte Carlo simulated hot particles were randomly injected into the field data. This allowed for the detection rate of conventional deterministic (gross counts) and machine learning (neural networks and support vector machines) algorithms to be assessed. The results demonstrated that a Neural Network operated on a sodium iodide detector provided the best detection capability. Compared to deterministic approaches, this optimised detection system could detect a hot particle on average 10 cm deeper into the soil column or with half of the activity at the same depth. It was also found that noise presented by internal contamination restricted lanthanum bromide for this application. - Highlights: • Land contaminated with radium is hazardous to human health. • Routine monitoring permits identification and removal of radioactive hot particles. • Current alarm algorithms do not provide reliable hot particle detection. • Spectral processing using Machine Learning significantly improves detection

Machinery condition monitoring principles and practices

CERN Document Server

Mohanty, Amiya Ranjan

2015-01-01

Find the Fault in the MachinesDrawing on the author's more than two decades of experience with machinery condition monitoring and consulting for industries in India and abroad, Machinery Condition Monitoring: Principles and Practices introduces the practicing engineer to the techniques used to effectively detect and diagnose faults in machines. Providing the working principle behind the instruments, the important elements of machines as well as the technique to understand their conditions, this text presents every available method of machine fault detection occurring in machines in general, an

TORQUE MEASUREMENT IN WORM AGLOMERATION MACHINE

Directory of Open Access Journals (Sweden)

Marian DUDZIAK

2014-03-01

Full Text Available The paper presents the operating characteristics of the worm agglomeration machine. The paper indicates the need for continuous monitoring of the value of the torque due to the efficiency of the machine. An original structure of torque meter which is built in the standard drive system of briquetting machine was presented. A number of benefits arising from the application of the proposed solution were presented. Exemplary measurement results obtained by means of this torque meter were presented.

Cloud Monitoring for Solar Plants with Support Vector Machine Based Fault Detection System

Directory of Open Access Journals (Sweden)

Hong-Chan Chang

2014-01-01

Full Text Available This study endeavors to develop a cloud monitoring system for solar plants. This system incorporates numerous subsystems, such as a geographic information system, an instantaneous power-consumption information system, a reporting system, and a failure diagnosis system. Visual C# was integrated with ASP.NET and SQL technologies for the proposed monitoring system. A user interface for database management system was developed to enable users to access solar power information and management systems. In addition, by using peer-to-peer (P2P streaming technology and audio/video encoding/decoding technology, real-time video data can be transmitted to the client end, providing instantaneous and direct information. Regarding smart failure diagnosis, the proposed system employs the support vector machine (SVM theory to train failure mathematical models. The solar power data are provided to the SVM for analysis in order to determine the failure types and subsequently eliminate failures at an early stage. The cloud energy-management platform developed in this study not only enhances the management and maintenance efficiency of solar power plants but also increases the market competitiveness of solar power generation and renewable energy.

Analysis Of Electrical – Thermal Coupling Of Induction Machine ...

African Journals Online (AJOL)

The interaction of the Electrical and mechanical parts of Electrical machines gives rise to the heating of the machine's constituent parts. This consequently leads to an increase in temperature which if not properly monitored may lead to the breakdown of the machine. This paper therefore presents the Electrical and thermal ...

Online Vibration Monitoring of a Water Pump Machine to Detect Its Malfunction Components Based on Artificial Neural Network

Science.gov (United States)

Rahmawati, P.; Prajitno, P.

2018-04-01

Vibration monitoring is a measurement instrument used to identify, predict, and prevent failures in machine instruments[6]. This is very needed in the industrial applications, cause any problem with the equipment or plant translates into economical loss and they are mostly monitored component off-line[2]. In this research, a system has been developed to detect the malfunction of the components of Shimizu PS-128BT water pump machine, such as capacitor, bearing and impeller by online measurements. The malfunction components are detected by taking vibration data using a Micro-Electro-Mechanical System(MEMS)-based accelerometer that are acquired by using Raspberry Pi microcomputer and then the data are converted into the form of Relative Power Ratio(RPR). In this form the signal acquired from different components conditions have different patterns. The collected RPR used as the base of classification process for recognizing the damage components of the water pump that are conducted by Artificial Neural Network(ANN). Finally, the damage test result will be sent via text message using GSM module that are connected to Raspberry Pi microcomputer. The results, with several measurement readings, with each reading in 10 minutes duration for each different component conditions, all cases yield 100% of accuracies while in the case of defective capacitor yields 90% of accuracy.

Utilization of MAX and FAX human phantoms for space radiation exposure calculations using HZETRN

Science.gov (United States)

Qualls, Garry; Slaba, Tony; Clowdsley, Martha; Blattnig, Steve; Walker, Steven; Simonsen, Lisa

To estimate astronaut health risk due to space radiation, one must have the ability to calculate, for known radiation environments external to the body, particle spectra, LET spectra, dose, dose equivalent, or gray equivalent that are averaged over specific organs or tissue types. This may be accomplished using radiation transport software and computational human body tissue models. Historically, NASA scientists have used the HZETRN software to calculate radiation transport through both vehicle shielding materials and body tissue. The Computerized Anatomical Man (CAM) and the Computerized Anatomical Female (CAF) body models, combined with the CAMERA software, have been used for body tissue self-shielding calculations. The CAM and CAF, which were developed in 1973 and 1992, respectively, model the 50th percentile U.S. Air Force male and female and are constructed using individual quadric surfaces that combine to form thousands of solid regions that represent specific tissues and structures within the body. In order to transport an external radiation environment to a point within one of the body models using HZETRN, a directional distribution of the tissues surrounding that point is needed. The CAMERA software is used to "ray trace" the CAM and CAF models, providing the thickness of each tissue type traversed along each of a large number of rays originating at a dose point. More recently, R. Kramer of the Departmento de Energia Nuclear, Universidade Federal de Pernambuco in Brazil and his co-workers developed the Male Adult voXel (MAX) model and the Female Adult voXel (FAX). These voxel-based body models were developed using segmented Computed Tomography (CT) scans of adult cadavers, and the quantities and distributions of various body tissues have been adjusted to match those specified in the International Commission on Radiological Protection (ICRP) reference adult male and female. A new set of tools has been developed to facilitate space radiation exposure

Development of a Data Acquisition Program for the Purpose of Monitoring Processing Statistics Throughout the BaBar Online Computing Infrastructure's Farm Machines

Energy Technology Data Exchange (ETDEWEB)

Stonaha, P.

2004-09-03

A current shortcoming of the BaBar monitoring system is the lack of systematic gathering, archiving, and access to the running statistics of the BaBar Online Computing Infrastructure's farm machines. Using C, a program has been written to gather the raw data of each machine's running statistics and compute various rates and percentages that can be used for system monitoring. These rates and percentages then can be stored in an EPICS database for graphing, archiving, and future access. Graphical outputs show the reception of the data into the EPICS database. The C program can read if the data are 32- or 64-bit and correct for overflows. This program is not exclusive to BaBar and can be easily modified for any system.

Sitting Posture Monitoring System Based on a Low-Cost Load Cell Using Machine Learning

Directory of Open Access Journals (Sweden)

Jongryun Roh

2018-01-01

Full Text Available Sitting posture monitoring systems (SPMSs help assess the posture of a seated person in real-time and improve sitting posture. To date, SPMS studies reported have required many sensors mounted on the backrest plate and seat plate of a chair. The present study, therefore, developed a system that measures a total of six sitting postures including the posture that applied a load to the backrest plate, with four load cells mounted only on the seat plate. Various machine learning algorithms were applied to the body weight ratio measured by the developed SPMS to identify the method that most accurately classified the actual sitting posture of the seated person. After classifying the sitting postures using several classifiers, average and maximum classification rates of 97.20% and 97.94%, respectively, were obtained from nine subjects with a support vector machine using the radial basis function kernel; the results obtained by this classifier showed a statistically significant difference from the results of multiple classifications using other classifiers. The proposed SPMS was able to classify six sitting postures including the posture with loading on the backrest and showed the possibility of classifying the sitting posture even though the number of sensors is reduced.

Advances in Machine Technology.

Science.gov (United States)

Clark, William R; Villa, Gianluca; Neri, Mauro; Ronco, Claudio

2018-01-01

Continuous renal replacement therapy (CRRT) machines have evolved into devices specifically designed for critically ill over the past 40 years. In this chapter, a brief history of this evolution is first provided, with emphasis on the manner in which changes have been made to address the specific needs of the critically ill patient with acute kidney injury. Subsequently, specific examples of technology developments for CRRT machines are discussed, including the user interface, pumps, pressure monitoring, safety features, and anticoagulation capabilities. © 2018 S. Karger AG, Basel.

Photonometers for coating and sputtering machines

Science.gov (United States)

Oupický, P.; Jareš, D.; Václavík, J.; Vápenka, D.

2013-04-01

The concept of photonometers (alternative name of optical monitor of a vacuum deposition process) for coating and sputtering machines is based on photonometers produced by companies like SATIS or HV Dresden. Photometers were developed in the TOPTEC centre and its predecessor VOD (Optical Development Workshop of Institut of Plasma Physics AS CR) for more than 10 years. The article describes current status of the technology and ideas which will be incorporated in next development steps. Hardware and software used on coating machines B63D, VNA600 and sputtering machine UPM810 is presented.

Machine learning-based patient specific prompt-gamma dose monitoring in proton therapy

Science.gov (United States)

Gueth, P.; Dauvergne, D.; Freud, N.; Létang, J. M.; Ray, C.; Testa, E.; Sarrut, D.

2013-07-01

Online dose monitoring in proton therapy is currently being investigated with prompt-gamma (PG) devices. PG emission was shown to be correlated with dose deposition. This relationship is mostly unknown under real conditions. We propose a machine learning approach based on simulations to create optimized treatment-specific classifiers that detect discrepancies between planned and delivered dose. Simulations were performed with the Monte-Carlo platform Gate/Geant4 for a spot-scanning proton therapy treatment and a PG camera prototype currently under investigation. The method first builds a learning set of perturbed situations corresponding to a range of patient translation. This set is then used to train a combined classifier using distal falloff and registered correlation measures. Classifier performances were evaluated using receiver operating characteristic curves and maximum associated specificity and sensitivity. A leave-one-out study showed that it is possible to detect discrepancies of 5 mm with specificity and sensitivity of 85% whereas using only distal falloff decreases the sensitivity down to 77% on the same data set. The proposed method could help to evaluate performance and to optimize the design of PG monitoring devices. It is generic: other learning sets of deviations, other measures and other types of classifiers could be studied to potentially reach better performance. At the moment, the main limitation lies in the computation time needed to perform the simulations.

Machine learning-based patient specific prompt-gamma dose monitoring in proton therapy

International Nuclear Information System (INIS)

Gueth, P; Freud, N; Létang, J M; Sarrut, D; Dauvergne, D; Ray, C; Testa, E

2013-01-01

Online dose monitoring in proton therapy is currently being investigated with prompt-gamma (PG) devices. PG emission was shown to be correlated with dose deposition. This relationship is mostly unknown under real conditions. We propose a machine learning approach based on simulations to create optimized treatment-specific classifiers that detect discrepancies between planned and delivered dose. Simulations were performed with the Monte-Carlo platform Gate/Geant4 for a spot-scanning proton therapy treatment and a PG camera prototype currently under investigation. The method first builds a learning set of perturbed situations corresponding to a range of patient translation. This set is then used to train a combined classifier using distal falloff and registered correlation measures. Classifier performances were evaluated using receiver operating characteristic curves and maximum associated specificity and sensitivity. A leave-one-out study showed that it is possible to detect discrepancies of 5 mm with specificity and sensitivity of 85% whereas using only distal falloff decreases the sensitivity down to 77% on the same data set. The proposed method could help to evaluate performance and to optimize the design of PG monitoring devices. It is generic: other learning sets of deviations, other measures and other types of classifiers could be studied to potentially reach better performance. At the moment, the main limitation lies in the computation time needed to perform the simulations. (paper)

Real Time Monitoring System of Pollution Waste on Musi River Using Support Vector Machine (SVM) Method

Science.gov (United States)

Fachrurrozi, Muhammad; Saparudin; Erwin

2017-04-01

Real-time Monitoring and early detection system which measures the quality standard of waste in Musi River, Palembang, Indonesia is a system for determining air and water pollution level. This system was designed in order to create an integrated monitoring system and provide real time information that can be read. It is designed to measure acidity and water turbidity polluted by industrial waste, as well as to show and provide conditional data integrated in one system. This system consists of inputting and processing the data, and giving output based on processed data. Turbidity, substances, and pH sensor is used as a detector that produce analog electrical direct current voltage (DC). Early detection system works by determining the value of the ammonia threshold, acidity, and turbidity level of water in Musi River. The results is then presented based on the level group pollution by the Support Vector Machine classification method.

Positional reference system for ultraprecision machining

International Nuclear Information System (INIS)

Arnold, J.B.; Burleson, R.R.; Pardue, R.M.

1982-01-01

A stable positional reference system for use in improving the cutting tool-to-part contour position in numerical controlledmultiaxis metal turning machines is provided. The reference system employs a plurality of interferometers referenced to orthogonally disposed metering bars which are substantially isolated from machine strain induced position errors for monitoring the part and tool positions relative to the metering bars. A microprocessor-based control system is employed in conjunction with the plurality of position interferometers and part contour description data inputs to calculate error components for each axis of movement and output them to corresponding axis drives with appropriate scaling and error compensation. Real-time position control, operating in combination with the reference system, makes possible the positioning of the cutting points of a tool along a part locus with a substantially greater degree of accuracy than has been attained previously in the art by referencing and then monitoring only the tool motion relative to a reference position located on the machine base

Positional reference system for ultraprecision machining

Science.gov (United States)

Arnold, J.B.; Burleson, R.R.; Pardue, R.M.

1980-09-12

A stable positional reference system for use in improving the cutting tool-to-part contour position in numerical controlled-multiaxis metal turning machines is provided. The reference system employs a plurality of interferometers referenced to orthogonally disposed metering bars which are substantially isolated from machine strain induced position errors for monitoring the part and tool positions relative to the metering bars. A microprocessor-based control system is employed in conjunction with the plurality of positions interferometers and part contour description data input to calculate error components for each axis of movement and output them to corresponding axis driven with appropriate scaling and error compensation. Real-time position control, operating in combination with the reference system, makes possible the positioning of the cutting points of a tool along a part locus with a substantially greater degree of accuracy than has been attained previously in the art by referencing and then monitoring only the tool motion relative to a reference position located on the machine base.

Using GPS to evaluate productivity and performance of forest machine systems

Science.gov (United States)

Steven E. Taylor; Timothy P. McDonald; Matthew W. Veal; Ton E. Grift

2001-01-01

This paper reviews recent research and operational applications of using GPS as a tool to help monitor the locations, travel patterns, performance, and productivity of forest machines. The accuracy of dynamic GPS data collected on forest machines under different levels of forest canopy is reviewed first. Then, the paper focuses on the use of GPS for monitoring forest...

Development of new plant monitoring and control system with advanced man-machine interfaces NUCAMM-80

International Nuclear Information System (INIS)

Sato, Hideyuki; Joge, Toshio; Miyake, Masao; Kishi, Shoichi

1981-01-01

BWR type nuclear power stations are the typical plants adopting central monitoring system in view of the size of the scale of system and the prevention of radiation exposure. Central control boards became large as much informations and many operating tools are concentrated on them. Recently, the unit capacity has increased, and the safety has been strengthened, therefore more improvement of the man-machine interface is required concerning the monitoring of plant operation. Hitachi Ltd. developed the central monitoring and control system for nuclear power stations ''NUCAMM-80'', concentrating related fundamental techniques such as the collection of plant informations, the expansion of automatic operation, the ergonomic re-evaluation of the arrangement of panels and subsystems, and the effective use of functional hardwares such as controlling computers and cathode ray tubes, for the purposes of improving the reliability of plant operation and the rate of operation, the reduction of the burden of operators and drastic labor saving. The fundamental policy of the development, the construction of the system, panel layout and the collection of informations, the development of the system for plant automation, the development of plant diagnosis and prevention systems, computer system and the merits of this system are described. (Kako, I.)

Control processes and machine protection on ASDEX Upgrade

International Nuclear Information System (INIS)

Raupp, G.; Treutterer, W.; Mertens, V.; Neu, G.; Sips, A.; Zasche, D.; Zehetbauer, Th.

2007-01-01

Safe operation of ASDEX Upgrade is guaranteed by a conventional hierarchy of simple and robust hard-wired systems for personnel and machine protection featuring standardized switch-off procedures. Machine protection and handling of off-normal events is further enhanced and peak and lifetime stress minimized through the plasma control system. Based on a real-time process model supporting safety critical applications with data quality tagging, process self-monitoring, watchdog monitoring and alarm propagation, processes detect complex and critical failures and reliably perform case-sensitive counter measures. Intelligent real-time failure handling is done with hardware or software redundancy and performance degradation, or modification of reference values to continue or terminate discharges with reduced machine stress. Examples implemented so far on ASDEX Upgrade are given, such as recovery from measurement failures, switch-over of redundant actuators, handling of actuator limitations, detection of plasma instabilities, plasma state dependent soft landing, or handling of failed switch-off procedures through breakers disconnecting the machine from grid

Photonometers for coating and sputtering machines

Directory of Open Access Journals (Sweden)

Václavík J.

2013-05-01

Full Text Available The concept of photonometers (alternative name of optical monitor of a vacuum deposition process for coating and sputtering machines is based on photonometers produced by companies like SATIS or HV Dresden. Photometers were developed in the TOPTEC centre and its predecessor VOD (Optical Development Workshop of Institut of Plasma Physics AS CR for more than 10 years. The article describes current status of the technology and ideas which will be incorporated in next development steps. Hardware and software used on coating machines B63D, VNA600 and sputtering machine UPM810 is presented.

Climate-relevant monitorings in Germany

International Nuclear Information System (INIS)

Metternich, P.

1993-01-01

This catalogue contains so-called meta-data; i.e. information on data. For each measuring programme or set of data, users find the address (postal address, telephone, fax-number) of the respective contact person at the beginning of the entry. The catalogue has three parts: Part A is a compilation of monitoring programmes using conventional methods adopted on the ground. Part B contains research programmes or sets of data from the field of remote sensing. In part C, data sets from time series of climate-relevant parameters are described. Section A was additionally structured according so the compartments of the climate system: Atmosphere, hydrosphere, cryosphere, biosphere. (orig./KW) [de

State machine operation of the MICE cooling channel

International Nuclear Information System (INIS)

Hanlet, Pierrick

2014-01-01

The Muon Ionization Cooling Experiment (MICE) is a demonstration experiment to prove the feasibility of cooling a beam of muons for use in a Neutrino Factory and/or Muon Collider. The MICE cooling channel is a section of a modified Study II cooling channel which will provide a 10% reduction in beam emittance. In order to ensure a reliable measurement, MICE will measure the beam emittance before and after the cooling channel at the level of 1%, a relative measurement of 0.001. This renders MICE a precision experiment which requires strict controls and monitoring of all experimental parameters in order to control systematic errors. The MICE Controls and Monitoring system is based on EPICS and integrates with the DAQ, Data monitoring systems, and a configuration database. The cooling channel for MICE has between 12 and 18 superconductnig solenoid coils in 3 to 7 magnets, depending on the staged development of the experiment. The magnets are coaxial and in close proximity which requires coordinated operation of the magnets when ramping, responding to quench conditions, and quench recovery. To reliably manage the operation of the magnets, MICE is implementing state machines for each magnet and an over-arching state machine for the magnets integrated in the cooling channel. The state machine transitions and operating parameters are stored/restored to/from the configuration database and coupled with MICE Run Control. Proper implementation of the state machines will not only ensure safe operation of the magnets, but will help ensure reliable data quality. A description of MICE, details of the state machines, and lessons learned from use of the state machines in recent magnet training tests will be discussed.

A dose monitoring system for dental radiography

Energy Technology Data Exchange (ETDEWEB)

Lee, Chena; Lee, Sam Sun; Kim, Jo Eun; Huh, Kyung Hoe; Yi, Woo Jin; Heo, Min Suk; Choi, Soon Chul [Dept. of Oral and Maxillofacial Radiology and Dental Research Institute, School of Dentistry, Seoul National University, Seoul (Korea, Republic of); Symkhampha, Khanthaly [Dept. of Oral and Maxillofacial Radiology, Department of Basic Science, Faculty of Dentistry, University of Health Sciences, Vientiane (Lao People' s Democratic Republic); Lee, Woo Jin [Dept. of Interdisciplinary Program in Radiation, Applied Life Sciences Major, College of Medicine, BK21, and Dental Research Institute, Seoul National University, Seoul (Korea, Republic of); Yeom, Heon Young [School of Computer Science Engineering, Seoul National University, Seoul (Korea, Republic of)

2016-06-15

The current study investigates the feasibility of a platform for a nationwide dose monitoring system for dental radiography. The essential elements for an unerring system are also assessed. An intraoral radiographic machine with 14 X-ray generators and five sensors, 45 panoramic radiographic machines, and 23 cone-beam computed tomography (CBCT) models used in Korean dental clinics were surveyed to investigate the type of dose report. A main server for storing the dose data from each radiographic machine was prepared. The dose report transfer pathways from the radiographic machine to the main sever were constructed. An effective dose calculation method was created based on the machine specifications and the exposure parameters of three intraoral radiographic machines, five panoramic radiographic machines, and four CBCTs. A viewing system was developed for both dentists and patients to view the calculated effective dose. Each procedure and the main server were integrated into one system. The dose data from each type of radiographic machine was successfully transferred to the main server and converted into an effective dose. The effective dose stored in the main server is automatically connected to a viewing program for dentist and patient access. A patient radiation dose monitoring system is feasible for dental clinics. Future research in cooperation with clinicians, industry, and radiologists is needed to ensure format convertibility for an efficient dose monitoring system to monitor unexpected radiation dose.

A dose monitoring system for dental radiography

International Nuclear Information System (INIS)

Lee, Chena; Lee, Sam Sun; Kim, Jo Eun; Huh, Kyung Hoe; Yi, Woo Jin; Heo, Min Suk; Choi, Soon Chul; Symkhampha, Khanthaly; Lee, Woo Jin; Yeom, Heon Young

2016-01-01

The current study investigates the feasibility of a platform for a nationwide dose monitoring system for dental radiography. The essential elements for an unerring system are also assessed. An intraoral radiographic machine with 14 X-ray generators and five sensors, 45 panoramic radiographic machines, and 23 cone-beam computed tomography (CBCT) models used in Korean dental clinics were surveyed to investigate the type of dose report. A main server for storing the dose data from each radiographic machine was prepared. The dose report transfer pathways from the radiographic machine to the main sever were constructed. An effective dose calculation method was created based on the machine specifications and the exposure parameters of three intraoral radiographic machines, five panoramic radiographic machines, and four CBCTs. A viewing system was developed for both dentists and patients to view the calculated effective dose. Each procedure and the main server were integrated into one system. The dose data from each type of radiographic machine was successfully transferred to the main server and converted into an effective dose. The effective dose stored in the main server is automatically connected to a viewing program for dentist and patient access. A patient radiation dose monitoring system is feasible for dental clinics. Future research in cooperation with clinicians, industry, and radiologists is needed to ensure format convertibility for an efficient dose monitoring system to monitor unexpected radiation dose

[Fax Survey to Elucidate the Information Needs of General Practitioners in Lower Saxony Regarding the Topic of Medical Implants].

Science.gov (United States)

Schaper, M; Berndt, M; Schrimpf, C; Wilhelmi, M; Elff, M; Haverich, A; Wilhelmi, M

2016-12-01

Background: Medial implants help a multitude of patients to gain more health, mobility and thus, quality of life. In collaboration with a still growing expectation of life especially, i.e., within Western industrial countries, this has led to an increasing use of implants over the last years. However, although biomechanical characteristics of modern implant materials have improved considerably, one big challenge still exists - the implant-associated infection. Early diagnostic and therapeutic interventions could clearly mitigate this issue, but are general practitioners sufficiently informed regarding this topic? Material and Methods: In March 2013 and in close cooperation with the Lower Saxony association of general practitioners, we initiated a survey to elucidate the information demands of general practitioners regarding the topic of medical implants. A total of 939 members of the association were contacted via fax and 101 (10.8 %) responded. Based on the obtained data, we then evaluated which topics are most interesting for this group of medical professionals. Results: The survey clearly indicates that general practitioners request more general implant-related data, e.g., type and specification of an implant as well as its location within the individual patient and contact addresses of the implanting hospital, but also want more specific information regarding diagnostic and therapeutic strategies in the case of implant-associated complications. Conclusion: The present article reports in detail on the conducted fax survey and shows some initial strategies as to how the identified challenges might be faced. Georg Thieme Verlag KG Stuttgart · New York.

Machine Learning Techniques for Optical Performance Monitoring from Directly Detected PDM-QAM Signals

DEFF Research Database (Denmark)

Thrane, Jakob; Wass, Jesper; Piels, Molly

2017-01-01

Linear signal processing algorithms are effective in dealing with linear transmission channel and linear signal detection, while the nonlinear signal processing algorithms, from the machine learning community, are effective in dealing with nonlinear transmission channel and nonlinear signal...... detection. In this paper, a brief overview of the various machine learning methods and their application in optical communication is presented and discussed. Moreover, supervised machine learning methods, such as neural networks and support vector machine, are experimentally demonstrated for in-band optical...

Structural health monitoring for bolt loosening via a non-invasive vibro-haptics human-machine cooperative interface

Science.gov (United States)

Pekedis, Mahmut; Mascerañas, David; Turan, Gursoy; Ercan, Emre; Farrar, Charles R.; Yildiz, Hasan

2015-08-01

For the last two decades, developments in damage detection algorithms have greatly increased the potential for autonomous decisions about structural health. However, we are still struggling to build autonomous tools that can match the ability of a human to detect and localize the quantity of damage in structures. Therefore, there is a growing interest in merging the computational and cognitive concepts to improve the solution of structural health monitoring (SHM). The main object of this research is to apply the human-machine cooperative approach on a tower structure to detect damage. The cooperation approach includes haptic tools to create an appropriate collaboration between SHM sensor networks, statistical compression techniques and humans. Damage simulation in the structure is conducted by releasing some of the bolt loads. Accelerometers are bonded to various locations of the tower members to acquire the dynamic response of the structure. The obtained accelerometer results are encoded in three different ways to represent them as a haptic stimulus for the human subjects. Then, the participants are subjected to each of these stimuli to detect the bolt loosened damage in the tower. Results obtained from the human-machine cooperation demonstrate that the human subjects were able to recognize the damage with an accuracy of 88 ± 20.21% and response time of 5.87 ± 2.33 s. As a result, it is concluded that the currently developed human-machine cooperation SHM may provide a useful framework to interact with abstract entities such as data from a sensor network.

Graphic man-machine interface applied to nuclear reactor designs

International Nuclear Information System (INIS)

Pereira, Claudio M.N.A; Mol, Antonio Carlos A.

1999-01-01

The Man-Machine Interfaces have been of interest of many researchers in the area of nuclear human factors engineering, principally applied to monitoring systems. The clarity of information provides best adaptation of the men to the machine. This work proposes the development of a Graphic Man-Machine Interface applied to nuclear reactor designs as a tool to optimize them. Here is present a prototype of a graphic man-machine interface for the Hammer code developed for PC under the Windows environment. The results of its application are commented. (author)

Four-year monitoring of foodborne pathogens in raw milk sold by vending machines in Italy.

Science.gov (United States)

Giacometti, Federica; Bonilauri, Paolo; Serraino, Andrea; Peli, Angelo; Amatiste, Simonetta; Arrigoni, Norma; Bianchi, Manila; Bilei, Stefano; Cascone, Giuseppe; Comin, Damiano; Daminelli, Paolo; Decastelli, Lucia; Fustini, Mattia; Mion, Renzo; Petruzzelli, Annalisa; Rosmini, Roberto; Rugna, Gianluca; Tamba, Marco; Tonucci, Franco; Bolzoni, Giuseppe

2013-11-01

Prevalence data were collected from official microbiological records monitoring four selected foodborne pathogens (Salmonella, Listeria monocytogenes, Escherichia coli O157:H7, and Campylobacter jejuni) in raw milk sold by self-service vending machines in seven Italian regions (60,907 samples from 1,239 vending machines) from 2008 to 2011. Data from samples analyzed by both culture-based and real-time PCR methods were collected in one region. One hundred raw milk consumers in four regions were interviewed while purchasing raw milk from vending machines. One hundred seventy-eight of 60,907 samples were positive for one of the four foodborne pathogens investigated: 18 samples were positive for Salmonella, 83 for L. monocytogenes, 24 for E. coli O157:H7, and 53 for C. jejuni in the seven regions investigated. No significant differences in prevalence were found among regions, but a significant increase in C. jejuni prevalence was observed over the years of the study. A comparison of the two analysis methods revealed that real-time PCR was 2.71 to 9.40 times more sensitive than the culture-based method. Data on consumer habits revealed that some behaviors may enhance the risk of infection linked to raw milk consumption: 37% of consumers did not boil milk before consumption, 93% never used an insulated bag to transport raw milk home, and raw milk was consumed by children younger than 5 years of age. These results emphasize that end-product controls alone are not sufficient to guarantee an adequate level of consumer protection. The beta distribution of positive samples in this study and the data on raw milk consumer habits will be useful for the development of a national quantitative risk assessment of Salmonella, L. monocytogenes, E. coli O157, and C. jejuni infection associated with raw milk consumption.

Java online monitoring framework

International Nuclear Information System (INIS)

Ronan, M.; Kirkby, D.; Johnson, A.S.; Groot, D. de

1997-10-01

An online monitoring framework has been written in the Java Language Environment to develop applications for monitoring special purpose detectors during commissioning of the PEP-II Interaction Region. PEP-II machine parameters and signals from several of the commissioning detectors are logged through VxWorks/EPICS and displayed by Java display applications. Remote clients are able to monitor the machine and detector performance using graphical displays and analysis histogram packages. In this paper, the design and implementation of the object-oriented Java framework is described. Illustrations of data acquisition, display and histograming applications are also given

Tool Wear Prediction in Ti-6Al-4V Machining through Multiple Sensor Monitoring and PCA Features Pattern Recognition

Directory of Open Access Journals (Sweden)

Alessandra Caggiano

2018-03-01

Full Text Available Machining of titanium alloys is characterised by extremely rapid tool wear due to the high cutting temperature and the strong adhesion at the tool-chip and tool-workpiece interface, caused by the low thermal conductivity and high chemical reactivity of Ti alloys. With the aim to monitor the tool conditions during dry turning of Ti-6Al-4V alloy, a machine learning procedure based on the acquisition and processing of cutting force, acoustic emission and vibration sensor signals during turning is implemented. A number of sensorial features are extracted from the acquired sensor signals in order to feed machine learning paradigms based on artificial neural networks. To reduce the large dimensionality of the sensorial features, an advanced feature extraction methodology based on Principal Component Analysis (PCA is proposed. PCA allowed to identify a smaller number of features (k = 2 features, the principal component scores, obtained through linear projection of the original d features into a new space with reduced dimensionality k = 2, sufficient to describe the variance of the data. By feeding artificial neural networks with the PCA features, an accurate diagnosis of tool flank wear (VBmax was achieved, with predicted values very close to the measured tool wear values.

Tool Wear Prediction in Ti-6Al-4V Machining through Multiple Sensor Monitoring and PCA Features Pattern Recognition

Science.gov (United States)

2018-01-01

Machining of titanium alloys is characterised by extremely rapid tool wear due to the high cutting temperature and the strong adhesion at the tool-chip and tool-workpiece interface, caused by the low thermal conductivity and high chemical reactivity of Ti alloys. With the aim to monitor the tool conditions during dry turning of Ti-6Al-4V alloy, a machine learning procedure based on the acquisition and processing of cutting force, acoustic emission and vibration sensor signals during turning is implemented. A number of sensorial features are extracted from the acquired sensor signals in order to feed machine learning paradigms based on artificial neural networks. To reduce the large dimensionality of the sensorial features, an advanced feature extraction methodology based on Principal Component Analysis (PCA) is proposed. PCA allowed to identify a smaller number of features (k = 2 features), the principal component scores, obtained through linear projection of the original d features into a new space with reduced dimensionality k = 2, sufficient to describe the variance of the data. By feeding artificial neural networks with the PCA features, an accurate diagnosis of tool flank wear (VBmax) was achieved, with predicted values very close to the measured tool wear values. PMID:29522443

Tool Wear Prediction in Ti-6Al-4V Machining through Multiple Sensor Monitoring and PCA Features Pattern Recognition.

Science.gov (United States)

Caggiano, Alessandra

2018-03-09

Machining of titanium alloys is characterised by extremely rapid tool wear due to the high cutting temperature and the strong adhesion at the tool-chip and tool-workpiece interface, caused by the low thermal conductivity and high chemical reactivity of Ti alloys. With the aim to monitor the tool conditions during dry turning of Ti-6Al-4V alloy, a machine learning procedure based on the acquisition and processing of cutting force, acoustic emission and vibration sensor signals during turning is implemented. A number of sensorial features are extracted from the acquired sensor signals in order to feed machine learning paradigms based on artificial neural networks. To reduce the large dimensionality of the sensorial features, an advanced feature extraction methodology based on Principal Component Analysis (PCA) is proposed. PCA allowed to identify a smaller number of features ( k = 2 features), the principal component scores, obtained through linear projection of the original d features into a new space with reduced dimensionality k = 2, sufficient to describe the variance of the data. By feeding artificial neural networks with the PCA features, an accurate diagnosis of tool flank wear ( VB max ) was achieved, with predicted values very close to the measured tool wear values.

Assessments of conversion coefficients between equivalent dose and accumulated activity using pre-dose scanning images of patients subjected to radioiodine treatment and the Fax/Egs4 computational model

International Nuclear Information System (INIS)

Lopes Filho, Ferdinand de J.; Vieira, Jose W.; Andrade Lima, Fernando R. de

2008-01-01

The radioiodine is a technique for treatment of thyroid cancer. In this technique, the patients are submitted to the incorporation of the radioactive substance sodium iodide (Na 131 I), which reacts with physiologically metastasis, thyroid tissue remains of and other organs and tissues of the human body. The locations of these reactions are known as areas of highest concentration, hipercaptured areas, hiperconcentrator areas, 'hot areas' or organ-sources and are viewed through images of nuclear medicine scan known as pre-dose (front and rear). To obtain these images, the patient receives, orally, a quantity of 131 I with low activity (± 74 MBq) and is positioned in the chamber of flicker. According to the attendance of hot areas shown in the images, the doctor determines the nuclear activity to be administered in treatment. This analysis is purely qualitative. In this study, the scanning images of pre-dose were adjusted to the dimensions of FAX voxel phantom, and the hot areas correspond to internal sources of the proposed model. Algorithms were developed to generate particles (photons and electrons) in these regions of the FAX. To estimate the coefficients of conversions between equivalent dose and accumulated activity in major radiosensitive organs, FAX and algorithms source were coupled to the Monte Carlo EGS4 code (Electron Gamma Shower, version 4). With these factors is possible to estimate the equivalent doses in the radiosensitive organs and tissues of patients as long as is know the activity administered and the half-life of organic sources. (author)

Machine and plasma diagnostic instrumentation systems for the Tandem Mirror Experiment Upgrade

International Nuclear Information System (INIS)

Coutts, G.W.; Coffield, F.E.; Lang, D.D.; Hornady, R.S.

1981-01-01

To evaluate performance of a second generation Tandem Mirror Machine, an extensive instrumentation system is being designed and installed as part of the major device fabrication. The systems listed will be operational during the start-up phase of the TMX Upgrade machine and provide bench marks for future performance data. In addition to plasma diagnostic instrumentation, machine parameter monitoring systems will be installed prior to machine operation. Simultaneous recording of machine parameters will permit evaluation of plasma parameters sensitive to machine conditions

The dynamic state monitoring of bearings system

Directory of Open Access Journals (Sweden)

Marek Krynke

2015-03-01

Full Text Available The article discusses the methods of dynamic state monitoring of bearings system. A vibration signal contains important technical information about the machine condition and is currently the most frequently used in diagnostic bearings systems. One of the main ad-vantages of machine condition monitoring is identifying the cause of failure of the bearings and taking preventative measures, otherwise the operation of such a machine will lead to frequent replacement of the bearings. Monitoring changes in the course of the operation of machin-ery repair strategies allows keeping the conditioned state of dynamic failure conditioned preventive repairs and repairs after-failure time. In addition, the paper also presents the fundamental causes of bearing failure and identifies mechanisms related to the creation of any type of damage.

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

KAUST Repository

Harrou, Fouzi; Ramahaleomiarantsoa, Jacques F.; Nounou, Mohamed N.; Nounou, Hazem N.

2016-01-01

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

Machine Learning applications in CMS

CERN Multimedia

CERN. Geneva

2017-01-01

Machine Learning is used in many aspects of CMS data taking, monitoring, processing and analysis. We review a few of these use cases and the most recent developments, with an outlook to future applications in the LHC Run III and for the High-Luminosity phase.

Detection of correct and incorrect measurements in real-time continuous glucose monitoring systems by applying a postprocessing support vector machine.

Science.gov (United States)

Leal, Yenny; Gonzalez-Abril, Luis; Lorencio, Carol; Bondia, Jorge; Vehi, Josep

2013-07-01

Support vector machines (SVMs) are an attractive option for detecting correct and incorrect measurements in real-time continuous glucose monitoring systems (RTCGMSs), because their learning mechanism can introduce a postprocessing strategy for imbalanced datasets. The proposed SVM considers the geometric mean to obtain a more balanced performance between sensitivity and specificity. To test this approach, 23 critically ill patients receiving insulin therapy were monitored over 72 h using an RTCGMS, and a dataset of 537 samples, classified according to International Standards Organization (ISO) criteria (372 correct and 165 incorrect measurements), was obtained. The results obtained were promising for patients with septic shock or with sepsis, for which the proposed system can be considered as reliable. However, this approach cannot be considered suitable for patients without sepsis.

Implementing Machine Learning in Radiology Practice and Research.

Science.gov (United States)

Kohli, Marc; Prevedello, Luciano M; Filice, Ross W; Geis, J Raymond

2017-04-01

The purposes of this article are to describe concepts that radiologists should understand to evaluate machine learning projects, including common algorithms, supervised as opposed to unsupervised techniques, statistical pitfalls, and data considerations for training and evaluation, and to briefly describe ethical dilemmas and legal risk. Machine learning includes a broad class of computer programs that improve with experience. The complexity of creating, training, and monitoring machine learning indicates that the success of the algorithms will require radiologist involvement for years to come, leading to engagement rather than replacement.

Mechanical properties of JT-60 tokamak machine in power tests

International Nuclear Information System (INIS)

Takatsu, Hideyuki; Ohkubo, Minoru; Yamamoto, Masahiro; Ohta, Mitsuru

1986-01-01

JT-60 power tests were carried out from Dec. 10, 1984 to Feb. 20, 1985 to demonstrate, in advance of actual plasma operation, satisfactory performance of tokamak machine, power suppliers and control system in combination. The tests began with low power test of individual coil systems and progressed to full power tests. The coil current was raised step by step, monitoring the mechanical, thermal, electrical and vacuum data. Power tests were concluded with successful results. All of the coil systems were raised up to full power operation in combination and system performance was verified including the structural integrity of tokamak machine. Measured strain and deflection showed good agreements with those predicted in the design, which was an evidence that electromagnetic forces were supported as expected in the design. A few limitations to machine operation was made clear quantitatively. And it was found that existing detectors were insufficient to monitor machine integrity and two kinds of detector were proposed to be installed. (author)

A New Application of Support Vector Machine Method: Condition Monitoring and Analysis of Reactor Coolant Pump

International Nuclear Information System (INIS)

Meng Qinghu; Meng Qingfeng; Feng Wuwei

2012-01-01

Fukushima nuclear power plant accident caused huge losses and pollution and it showed that the reactor coolant pump is very important in a nuclear power plant. Therefore, to keep the safety and reliability, the condition of the coolant pump needs to be online condition monitored and fault analyzed. In this paper, condition monitoring and analysis based on support vector machine (SVM) is proposed. This method is just to aim at the small sample studies such as reactor coolant pump. Both experiment data and field data are analyzed. In order to eliminate the noise and useless frequency, these data are disposed through a multi-band FIR filter. After that, a fault feature selection method based on principal component analysis is proposed. The related variable quantity is changed into unrelated variable quantity, and the dimension is descended. Then the SVM method is used to separate different fault characteristics. Firstly, this method is used as a two-kind classifier to separate each two different running conditions. Then the SVM is used as a multiple classifier to separate all of the different condition types. The SVM could separate these conditions successfully. After that, software based on SVM was designed for reactor coolant pump condition analysis. This software is installed on the reactor plant control system of Qinshan nuclear power plant in China. It could monitor the online data and find the pump mechanical fault automatically.

Provisional English Translation by the IAEA of Notification Faxes Sent by the Fukushima Daiichi NPP Site Superintendent to Off-Site Officials on 11 March 2011. Annex I of Technical Volume 3

International Nuclear Information System (INIS)

2015-01-01

This annex contains a provisional English translation of the faxes sent by the Fukushima Daiichi NPP Site Superintendent to METI, the Governor of Fukushima Prefecture and the Mayors of Okuma and Futaba on 11 March 2011

Machine Protection

CERN Document Server

Schmidt, R

2014-01-01

The protection of accelerator equipment is as old as accelerator technology and was for many years related to high-power equipment. Examples are the protection of powering equipment from overheating (magnets, power converters, high-current cables), of superconducting magnets from damage after a quench and of klystrons. The protection of equipment from beam accidents is more recent. It is related to the increasing beam power of high-power proton accelerators such as ISIS, SNS, ESS and the PSI cyclotron, to the emission of synchrotron light by electron–positron accelerators and FELs, and to the increase of energy stored in the beam (in particular for hadron colliders such as LHC). Designing a machine protection system requires an excellent understanding of accelerator physics and operation to anticipate possible failures that could lead to damage. Machine protection includes beam and equipment monitoring, a system to safely stop beam operation (e.g. dumping the beam or stopping the beam at low energy) and an ...

Methods and Research for Multi-Component Cutting Force Sensing Devices and Approaches in Machining

Directory of Open Access Journals (Sweden)

Qiaokang Liang

2016-11-01

Full Text Available Multi-component cutting force sensing systems in manufacturing processes applied to cutting tools are gradually becoming the most significant monitoring indicator. Their signals have been extensively applied to evaluate the machinability of workpiece materials, predict cutter breakage, estimate cutting tool wear, control machine tool chatter, determine stable machining parameters, and improve surface finish. Robust and effective sensing systems with capability of monitoring the cutting force in machine operations in real time are crucial for realizing the full potential of cutting capabilities of computer numerically controlled (CNC tools. The main objective of this paper is to present a brief review of the existing achievements in the field of multi-component cutting force sensing systems in modern manufacturing.

Methods and Research for Multi-Component Cutting Force Sensing Devices and Approaches in Machining.

Science.gov (United States)

Liang, Qiaokang; Zhang, Dan; Wu, Wanneng; Zou, Kunlin

2016-11-16

Multi-component cutting force sensing systems in manufacturing processes applied to cutting tools are gradually becoming the most significant monitoring indicator. Their signals have been extensively applied to evaluate the machinability of workpiece materials, predict cutter breakage, estimate cutting tool wear, control machine tool chatter, determine stable machining parameters, and improve surface finish. Robust and effective sensing systems with capability of monitoring the cutting force in machine operations in real time are crucial for realizing the full potential of cutting capabilities of computer numerically controlled (CNC) tools. The main objective of this paper is to present a brief review of the existing achievements in the field of multi-component cutting force sensing systems in modern manufacturing.

Man-machine design integration

Energy Technology Data Exchange (ETDEWEB)

Carrera, J.P. [Westinghouse Electric Corp., Monroeville, PA (United States). Nuclear Technology Div.; Haentjens, J. [Westinghouse Electric Corp., Brussels (Belgium). Nuclear Technology Div.

1995-12-31

The presentation overviews the bases for Man-Machine Interface (MMI) designs that are part of three other presentations during the same conference: Advanced Alarm Management System, Functional Displays and System for Emergency Procedure Execution Monitoring. The MMD group history, team and goals are summarized to give some context to the core of the MMD philosophy and integration. (10 refs., 5 figs.).

XII International Conference on the Theory of Machines and Mechanisms

CERN Document Server

Bílek, Martin; Žabka, Petr

2017-01-01

This book presents the most recent advances in the research of machines and mechanisms. It collects 54 reviewed papers presented at the XII International Conference on the Theory of Machines and mechanisms (TMM 2016) held in Liberec, Czech Republic, September 6-8, 2016. This volume offers an international selection of the most important new results and developments, grouped in six different parts, representing a well-balanced overview, and spanning the general theory of machines and mechanisms, through analysis and synthesis of planar and spatial mechanisms, linkages and cams, robots and manipulators, dynamics of machines and mechanisms, rotor dynamics, computational mechanics, vibration and noise in machines, optimization of mechanisms and machines, mechanisms of textile machines, mechatronics to the control and monitoring systems of machines. This conference is traditionally organised every four year under the auspices of the international organisation IFToMM and the Czech Society for Mechanics.

MAINTENANCE PLANNING OF THE SEWING NEEDLES OF SIMPLE SEWING MACHINES

Directory of Open Access Journals (Sweden)

ŞUTEU Marius Darius

2017-05-01

Full Text Available The effectiveness of simple sewing machines can be increased through the planning of predictive maintenance activities. The monitoring of the technical condition of the sewing needles of simple sewing machines was based on the measurement of their noise level. For this purpose a Center 322 sonometer was used, while the data obtained during the monitoring process was analyzed through the E322 software. The working speed of the simple sewing machine that was used for obtaining the experimental results varied from 200 stitches/minute to 4000 stitches/minute. The noise levels of a new needle at the working speed of 200 stitches/minute and 4000 stitches/minute were measured. The noise levels for a fault needle at the same working speed of 200 stitches/minute, respectively 4000 stitches/minute were also measured. Using Fuzzy Logic Toolbox ™ module of Matlab®, a decision-making system for determining when replacement of the sewing needles of simple sewing machines should be performed was developed. A case study illustrates the employment of the decision-making system based on fuzzy logic for a simple sewing machine. By replacing the sewing needles of simple sewing machines at the time specified through the decision-making system based on fuzzy logic, the occurrence of the failure can be prevented and the quality of textile products can be improved.

DESIGN OF CAMERA MOUNT AND ITS APPLICATION FOR MONITORING MACHINING PROCESS

Directory of Open Access Journals (Sweden)

Nadežda Čuboňová

2015-05-01

Full Text Available The article deals with the solution to the problem of holding a scanning device – GoPro camera in the vicinity of milling machine EMCO Concept MILL 105, practical part solves the design and production of the fixture. The proposal of the fixture includes the best placing of the fixture within the milling area. On this basis individual variants of this solution are elaborated. The best variant for holding of the camera was selected and fixture production was experimentally performed on a 3D printer – Easy 3D Maker. Fixture functionality was verified on the milling machine.

41 CFR 301-12.1 - What miscellaneous expenses are reimbursable?

Science.gov (United States)

2010-07-01

..., printers, faxing machines, and scanners. Fees for certified checks Costs of photographs for passports and visas. Services of typists, data processors, or stenographers. Transaction fees for use of automated teller machines (ATMs)-Government contractor-issued charge card Foreign country exit fees. Services of an...

Machine monitoring via current signature analysis techniques

International Nuclear Information System (INIS)

Smith, S.F.; Castleberry, K.N.; Nowlin, C.H.

1992-01-01

A significant need in the effort to provide increased production quality is to provide improved plant equipment monitoring capabilities. Unfortunately, in today's tight economy, even such monitoring instrumentation must be implemented in a recognizably cost effective manner. By analyzing the electric current drawn by motors, actuator, and other line-powered industrial equipment, significant insights into the operations of the movers, driven equipment, and even the power source can be obtained. The generic term 'current signature analysis' (CSA) has been coined to describe several techniques for extracting useful equipment or process monitoring information from the electrical power feed system. A patented method developed at Oak Ridge National Laboratory is described which recognizes the presence of line-current modulation produced by motors and actuators driving varying loads. The in-situ application of applicable linear demodulation techniques to the analysis of numerous motor-driven systems is also discussed. The use of high-quality amplitude and angle-demodulation circuitry has permitted remote status monitoring of several types of medium and high-power gas compressors in (US DOE facilities) driven by 3-phase induction motors rated from 100 to 3,500 hp, both with and without intervening speed increasers. Flow characteristics of the compressors, including various forms of abnormal behavior such as surging and rotating stall, produce at the output of the specialized detectors specific time and frequency signatures which can be easily identified for monitoring, control, and fault-prevention purposes. The resultant data are similar in form to information obtained via standard vibration-sensing techniques and can be analyzed using essentially identical methods. In addition, other machinery such as refrigeration compressors, brine pumps, vacuum pumps, fans, and electric motors have been characterized

Tool set for distributed real-time machine control

Science.gov (United States)

Carrott, Andrew J.; Wright, Christopher D.; West, Andrew A.; Harrison, Robert; Weston, Richard H.

1997-01-01

Demands for increased control capabilities require next generation manufacturing machines to comprise intelligent building elements, physically located at the point where the control functionality is required. Networks of modular intelligent controllers are increasingly designed into manufacturing machines and usable standards are slowly emerging. To implement a control system using off-the-shelf intelligent devices from multi-vendor sources requires a number of well defined activities, including (a) the specification and selection of interoperable control system components, (b) device independent application programming and (c) device configuration, management, monitoring and control. This paper briefly discusses the support for the above machine lifecycle activities through the development of an integrated computing environment populated with an extendable software toolset. The toolset supports machine builder activities such as initial control logic specification, logic analysis, machine modeling, mechanical verification, application programming, automatic code generation, simulation/test, version control, distributed run-time support and documentation. The environment itself consists of system management tools and a distributed object-oriented database which provides storage for the outputs from machine lifecycle activities and specific target control solutions.

Trust versus confidence: Microprocessors and personnel monitoring

International Nuclear Information System (INIS)

Chiaro, P.J. Jr.

1993-01-01

Due to recent technological advances, substantial improvements have been made in personnel contamination monitoring. In all likelihood, these advances will close out the days of manually frisking personnel for radioactive contamination. Unfortunately, as microprocessor-based monitors become more widely used, not only at commercial power reactors but also at government facilities, questions concerning their trustworthiness arise. Algorithms make decisions that were previously made by technicians. Trust is placed not in technicians but in machines. In doing this it is assumed that the machine never misses. Inevitably, this trust drops, due largely to ''false alarms''. This is especially true when monitoring for alpha contamination. What is a ''false alarm''? Do these machines and their algorithms that we put our trust in make mistakes? An analysis was performed on half-body and hand-and-foot monitors at Oak Ridge National Laboratory (ORNL) in order to justify the suggested confidence level used for alarm point determination. Sources used in this analysis had activities approximating ORNL's contamination limits

Trust versus confidence: Microprocessors and personnel monitoring

International Nuclear Information System (INIS)

Chiaro, P.J. Jr.

1994-01-01

Due to recent technological advances, substantial improvements have been made in personnel contamination monitoring. In all likelihood, these advances will close out the days of manually frisking personnel for radioactive contamination. Unfortunately, as microprocessor-based monitors become more widely used, not only at commercial power reactors but also at government facilities, questions concerning their trustworthiness arise. Algorithms make decisions that were previously made by technicians. Trust is placed not in technicians but in machines. In doing this it is assumed that the machine never misses. Inevitably, this trust drops, due largely to ''false alarms''. This is especially true when monitoring for alpha contamination. What is a ''false alarm''? Do these machines and their algorithms that they put their trust in make mistakes? An analysis was performed on half-body and hand-and-foot monitors at Oak Ridge National Laboratory (ORNL) in order to justify the suggested confidence level used for alarm point determination. Sources used in this analysis had activities approximating ORNL's contamination limits

Beam loss monitor system for machine protection

CERN Document Server

Dehning, B

2005-01-01

Most beam loss monitoring systems are based on the detection of secondary shower particles which depose their energy in the accelerator equipment and finally also in the monitoring detector. To allow an efficient protection of the equipment, the likely loss locations have to be identified by tracking simulations or by using low intensity beams. If superconducting magnets are used for the beam guiding system, not only a damage protection is required but also quench preventions. The quench levels for high field magnets are several orders of magnitude below the damage levels. To keep the operational efficiency high under such circumstances, the calibration factor between the energy deposition in the coils and the energy deposition in the detectors has to be accurately known. To allow a reliable damage protection and quench prevention, the mean time between failures should be high. If in such failsafe system the number of monitors is numerous, the false dump probability has to be kept low to keep a high operation...

Electrical-thermal coupling of induction machine for improved ...

African Journals Online (AJOL)

Electrical-thermal coupling of induction machine for improved thermal performance. ... Nigerian Journal of Technology ... The interaction of its electrical and mechanical parts leads to an increase in temperature which if not properly monitored ...

Monitoring of the state of the paper machine circulation water with a wide-band impedance measurement; Paperikoneen kiertoveden tilan seuranta laajakaistaisella impedanssimittauksella - MPKT 02

Energy Technology Data Exchange (ETDEWEB)

Varpula, T. [VTT Automation, Espoo (Finland). Measurement Technology

1998-12-31

A new measurement method for monitoring the chemical state of the circulation water in the paper machine is proposed and studied. In the method, the electrical properties - conductivity and permittivity - of the water are measured in a wide frequency band: 20 Hz - 10 mhz. Large-molecule organic compounds in the water are expected cause characteristic changes in the dielectric properties of the water. Continuous monitoring of the permittivity in the wide frequency band thus reveals their presence. Various electronic measurement setups for the measurement are constructed and studied by using test samples. If the method turns out to be promising, a prototype device will be made. (orig.)

Monitoring of the state of the paper machine circulation water with a wide-band impedance measurement; Paperikoneen kiertoveden tilan seuranta laajakaistaisella impedanssimittauksella - MPKT 02

Energy Technology Data Exchange (ETDEWEB)

Varpula, T [VTT Automation, Espoo (Finland). Measurement Technology

1999-12-31

A new measurement method for monitoring the chemical state of the circulation water in the paper machine is proposed and studied. In the method, the electrical properties - conductivity and permittivity - of the water are measured in a wide frequency band: 20 Hz - 10 mhz. Large-molecule organic compounds in the water are expected cause characteristic changes in the dielectric properties of the water. Continuous monitoring of the permittivity in the wide frequency band thus reveals their presence. Various electronic measurement setups for the measurement are constructed and studied by using test samples. If the method turns out to be promising, a prototype device will be made. (orig.)

A deviation based assessment methodology for multiple machine health patterns classification and fault detection

Science.gov (United States)

Jia, Xiaodong; Jin, Chao; Buzza, Matt; Di, Yuan; Siegel, David; Lee, Jay

2018-01-01

Successful applications of Diffusion Map (DM) in machine failure detection and diagnosis have been reported in several recent studies. DM provides an efficient way to visualize the high-dimensional, complex and nonlinear machine data, and thus suggests more knowledge about the machine under monitoring. In this paper, a DM based methodology named as DM-EVD is proposed for machine degradation assessment, abnormality detection and diagnosis in an online fashion. Several limitations and challenges of using DM for machine health monitoring have been analyzed and addressed. Based on the proposed DM-EVD, a deviation based methodology is then proposed to include more dimension reduction methods. In this work, the incorporation of Laplacian Eigen-map and Principal Component Analysis (PCA) are explored, and the latter algorithm is named as PCA-Dev and is validated in the case study. To show the successful application of the proposed methodology, case studies from diverse fields are presented and investigated in this work. Improved results are reported by benchmarking with other machine learning algorithms.

RISMA: A Rule-based Interval State Machine Algorithm for Alerts Generation, Performance Analysis and Monitoring Real-Time Data Processing

Science.gov (United States)

Laban, Shaban; El-Desouky, Aly

2013-04-01

The monitoring of real-time systems is a challenging and complicated process. So, there is a continuous need to improve the monitoring process through the use of new intelligent techniques and algorithms for detecting exceptions, anomalous behaviours and generating the necessary alerts during the workflow monitoring of such systems. The interval-based or period-based theorems have been discussed, analysed, and used by many researches in Artificial Intelligence (AI), philosophy, and linguistics. As explained by Allen, there are 13 relations between any two intervals. Also, there have also been many studies of interval-based temporal reasoning and logics over the past decades. Interval-based theorems can be used for monitoring real-time interval-based data processing. However, increasing the number of processed intervals makes the implementation of such theorems a complex and time consuming process as the relationships between such intervals are increasing exponentially. To overcome the previous problem, this paper presents a Rule-based Interval State Machine Algorithm (RISMA) for processing, monitoring, and analysing the behaviour of interval-based data, received from real-time sensors. The proposed intelligent algorithm uses the Interval State Machine (ISM) approach to model any number of interval-based data into well-defined states as well as inferring them. An interval-based state transition model and methodology are presented to identify the relationships between the different states of the proposed algorithm. By using such model, the unlimited number of relationships between similar large numbers of intervals can be reduced to only 18 direct relationships using the proposed well-defined states. For testing the proposed algorithm, necessary inference rules and code have been designed and applied to the continuous data received in near real-time from the stations of International Monitoring System (IMS) by the International Data Centre (IDC) of the Preparatory

A computer-controlled conformal radiotherapy system. III: graphical simulation and monitoring of treatment delivery

International Nuclear Information System (INIS)

Kessler, Marc L.; McShan, Daniel L.; Fraass, Benedick A.

1995-01-01

Purpose: Safe and efficient delivery of radiotherapy using computer-controlled machines requires new procedures to design and verify the actual delivery of these treatments. Graphical simulation and monitoring techniques for treatment delivery have been developed for this purpose. Methods and Materials: A graphics-based simulator of the treatment machine and a set of procedures for creating and manipulating treatment delivery scripts are used to simulate machine motions, detect collisions, and monitor machine positions during treatment. The treatment delivery simulator is composed of four components: a three-dimensional dynamic model of the treatment machine; a motion simulation and collision detection algorithm, user-interface widgets that mimic the treatment machine's control and readout devices; and an icon-based interface for creating and manipulating treatment delivery scripts. These components are used in a stand-alone fashion for interactive treatment delivery planning and integrated with a machine control system for treatment implementation and monitoring. Results: A graphics-based treatment delivery simulator and a set of procedures for planning and monitoring computer-controlled treatment delivery have been developed and implemented as part of a comprehensive computer-controlled conformal radiotherapy system. To date, these techniques have been used to design and help monitor computer-controlled treatments on a radiotherapy machine for more than 200 patients. Examples using these techniques for treatment delivery planning and on-line monitoring of machine motions during therapy are described. Conclusion: A system that provides interactive graphics-based tools for defining the sequence of machine motions, simulating treatment delivery including collision detection, and presenting the therapists with continual visual feedback from the treatment machine has been successfully implemented for routine clinical use as part of an overall system for computer

The APS machine protection system (MPS)

Energy Technology Data Exchange (ETDEWEB)

Fuja, R.; Berg, B.; Arnold, N. [and others

1996-08-01

The machine protection system (MPS) that protects the APS storage ring vacuum chamber from x-ray beams, is active. There are over 650 sensors monitored and networked through the MPS system. About the same number of other process variables are monitored by the much slower EPICS control system, which also has an input to the rf abort chain. The MPS network is still growing with the beam position limits detection system coming on-line. The network configuration, along with a limited description of individual subsystems, is presented.

The APS machine protection system (MPS)

International Nuclear Information System (INIS)

Fuja, R.; Berg, B.; Arnold, N.

1996-01-01

The machine protection system (MPS) that protects the APS storage ring vacuum chamber from x-ray beams, is active. There are over 650 sensors monitored and networked through the MPS system. About the same number of other process variables are monitored by the much slower EPICS control system, which also has an input to the rf abort chain. The MPS network is still growing with the beam position limits detection system coming on-line. The network configuration, along with a limited description of individual subsystems, is presented

Analysis of machining and machine tools

CERN Document Server

Liang, Steven Y

2016-01-01

This book delivers the fundamental science and mechanics of machining and machine tools by presenting systematic and quantitative knowledge in the form of process mechanics and physics. It gives readers a solid command of machining science and engineering, and familiarizes them with the geometry and functionality requirements of creating parts and components in today’s markets. The authors address traditional machining topics, such as: single and multiple point cutting processes grinding components accuracy and metrology shear stress in cutting cutting temperature and analysis chatter They also address non-traditional machining, such as: electrical discharge machining electrochemical machining laser and electron beam machining A chapter on biomedical machining is also included. This book is appropriate for advanced undergraduate and graduate mechani cal engineering students, manufacturing engineers, and researchers. Each chapter contains examples, exercises and their solutions, and homework problems that re...

TFTR grounding scheme and ground-monitor system

International Nuclear Information System (INIS)

Viola, M.

1983-01-01

The Tokamak Fusion Test Reactor (TFTR) grounding system utilizes a single-point ground. It is located directly under the machine, at the basement floor level, and is tied to the building perimeter ground. Wired to this single-point ground, via individual 500 MCM insulated cables, are: the vacuum vessel; four toroidal field coil cases/inner support structure quadrants; umbrella structure halves; the substructure ring girder; radial beams and columns; and the diagnostic systems. Prior to the first machine operation, a ground-loop removal program was initiated. It required insulation of all hangers and supports (within a 35-foot radius of the center of the machine) of the various piping, conduits, cable trays, and ventilation systems. A special ground-monitor system was designed and installed. It actively monitors each of the individual machine grounds to insure that there are no inadvertent ground loops within the machine structure or its ground and that the machine grounds are intact prior to each pulse. The TFTR grounding system has proven to be a very manageable system and one that is easy to maintain

Stereoscopic display in a slot machine

Science.gov (United States)

Laakso, M.

2012-03-01

This paper reports the results of a user trial with a slot machine equipped with a stereoscopic display. The main research question was to find out what kind of added value does stereoscopic 3D (S-3D) bring to slot games? After a thorough literature survey, a novel gaming platform was designed and implemented. Existing multi-game slot machine "Nova" was converted to "3DNova" by replacing the monitor with an S-3D display and converting six original games to S-3D format. To evaluate the system, several 3DNova machines were put available for players for four months. Both qualitative and quantitative analysis was carried out from statistical values, questionnaires and observations. According to the results, people find the S-3D concept interesting but the technology is not optimal yet. Young adults and adults were fascinated by the system, older people were more cautious. Especially the need to wear stereoscopic glasses provide a challenge; ultimate system would probably use autostereoscopic technology. Also the games should be designed to utilize its full power. The main contributions of this paper are lessons learned from creating an S-3D slot machine platform and novel information about human factors related to stereoscopic slot machine gaming.

Support Vector Machine Based Monitoring of Cardio-Cerebrovascular Reserve during Simulated Hemorrhage.

Science.gov (United States)

van der Ster, Björn J P; Bennis, Frank C; Delhaas, Tammo; Westerhof, Berend E; Stok, Wim J; van Lieshout, Johannes J

2017-01-01

Introduction: In the initial phase of hypovolemic shock, mean blood pressure (BP) is maintained by sympathetically mediated vasoconstriction rendering BP monitoring insensitive to detect blood loss early. Late detection can result in reduced tissue oxygenation and eventually cellular death. We hypothesized that a machine learning algorithm that interprets currently used and new hemodynamic parameters could facilitate in the detection of impending hypovolemic shock. Method: In 42 (27 female) young [mean (sd): 24 (4) years], healthy subjects central blood volume (CBV) was progressively reduced by application of -50 mmHg lower body negative pressure until the onset of pre-syncope. A support vector machine was trained to classify samples into normovolemia (class 0), initial phase of CBV reduction (class 1) or advanced CBV reduction (class 2). Nine models making use of different features were computed to compare sensitivity and specificity of different non-invasive hemodynamic derived signals. Model features included : volumetric hemodynamic parameters (stroke volume and cardiac output), BP curve dynamics, near-infrared spectroscopy determined cortical brain oxygenation, end-tidal carbon dioxide pressure, thoracic bio-impedance, and middle cerebral artery transcranial Doppler (TCD) blood flow velocity. Model performance was tested by quantifying the predictions with three methods : sensitivity and specificity, absolute error, and quantification of the log odds ratio of class 2 vs. class 0 probability estimates. Results: The combination with maximal sensitivity and specificity for classes 1 and 2 was found for the model comprising volumetric features (class 1: 0.73-0.98 and class 2: 0.56-0.96). Overall lowest model error was found for the models comprising TCD curve hemodynamics. Using probability estimates the best combination of sensitivity for class 1 (0.67) and specificity (0.87) was found for the model that contained the TCD cerebral blood flow velocity derived

Support Vector Machine Based Monitoring of Cardio-Cerebrovascular Reserve during Simulated Hemorrhage

Directory of Open Access Journals (Sweden)

Björn J. P. van der Ster

2018-01-01

Full Text Available Introduction: In the initial phase of hypovolemic shock, mean blood pressure (BP is maintained by sympathetically mediated vasoconstriction rendering BP monitoring insensitive to detect blood loss early. Late detection can result in reduced tissue oxygenation and eventually cellular death. We hypothesized that a machine learning algorithm that interprets currently used and new hemodynamic parameters could facilitate in the detection of impending hypovolemic shock.Method: In 42 (27 female young [mean (sd: 24 (4 years], healthy subjects central blood volume (CBV was progressively reduced by application of −50 mmHg lower body negative pressure until the onset of pre-syncope. A support vector machine was trained to classify samples into normovolemia (class 0, initial phase of CBV reduction (class 1 or advanced CBV reduction (class 2. Nine models making use of different features were computed to compare sensitivity and specificity of different non-invasive hemodynamic derived signals. Model features included: volumetric hemodynamic parameters (stroke volume and cardiac output, BP curve dynamics, near-infrared spectroscopy determined cortical brain oxygenation, end-tidal carbon dioxide pressure, thoracic bio-impedance, and middle cerebral artery transcranial Doppler (TCD blood flow velocity. Model performance was tested by quantifying the predictions with three methods: sensitivity and specificity, absolute error, and quantification of the log odds ratio of class 2 vs. class 0 probability estimates.Results: The combination with maximal sensitivity and specificity for classes 1 and 2 was found for the model comprising volumetric features (class 1: 0.73–0.98 and class 2: 0.56–0.96. Overall lowest model error was found for the models comprising TCD curve hemodynamics. Using probability estimates the best combination of sensitivity for class 1 (0.67 and specificity (0.87 was found for the model that contained the TCD cerebral blood flow velocity

Machine Protection and Interlock Systems for Circular Machines - Example for LHC

CERN Document Server

Schmidt, R.

2016-01-01

This paper introduces the protection of circular particle accelerators from accidental beam losses. Already the energy stored in the beams for accelerators such as the TEVATRON at Fermilab and Super Proton Synchrotron (SPS) at CERN could cause serious damage in case of uncontrolled beam loss. With the CERN Large Hadron Collider (LHC), the energy stored in particle beams has reached a value two orders of magnitude above previous accelerators and poses new threats with respect to hazards from the energy stored in the particle beams. A single accident damaging vital parts of the accelerator could interrupt operation for years. Protection of equipment from beam accidents is mandatory. Designing a machine protection system requires an excellent understanding of accelerator physics and operation to anticipate possible failures that could lead to damage. Machine protection includes beam and equipment monitoring, a system to safely stop beam operation (e.g. extraction of the beam towards a dedicated beam dump block o...

Smart machine protection system

International Nuclear Information System (INIS)

Clark, S.; Nelson, D.; Grillo, A.

1992-01-01

A Machine Protection System implemented on the SLC automatically controls the beam repetition rates in the accelerator so that radiation or temperature faults slow the repetition rate to bring the fault within tolerance without shutting down the machine. This process allows the accelerators to aid in the fault diagnostic process, and the protection system automatically restores the beams back to normal rates when the fault is diagnosed and corrected. The user interface includes facilities to monitor the performance of the system, and track rate limits, faults, and recoveries. There is an edit facility to define the devices to be included in the protection system, along with their set points, limits, and trip points. This set point and limit data is downloaded into the CAMAC modules, and the configuration data is complied into a logical decision tree for the 68030 processor. (author)

Smart Machine Protection System

International Nuclear Information System (INIS)

Clark, S.; Nelson, D.; Grillo, A.; Spencer, N.; Hutchinson, D.; Olsen, J.; Millsom, D.; White, G.; Gromme, T.; Allison, S.; Underwood, K.; Zelazny, M.; Kang, H.

1991-11-01

A Machine Protection System implemented on the SLC automatically controls the beam repetition rates in the accelerator so that radiation or temperature faults slow the repetition rate to bring the fault within tolerance without shutting down the machine. This process allows the accelerator to aid in the fault diagnostic process, and the protection system automatically restores the beams back to normal rates when the fault is diagnosed and corrected. The user interface includes facilities to monitor the performance of the system, and track rate limits, faults, and recoveries. There is an edit facility to define the devices to be included in the protection system, along with their set points, limits, and trip points. This set point and limit data is downloaded into the CAMAC modules, and the configuration data is compiled into a logical decision tree for the 68030 processor. 3 figs

LHCb experience with running jobs in virtual machines

Science.gov (United States)

McNab, A.; Stagni, F.; Luzzi, C.

2015-12-01

The LHCb experiment has been running production jobs in virtual machines since 2013 as part of its DIRAC-based infrastructure. We describe the architecture of these virtual machines and the steps taken to replicate the WLCG worker node environment expected by user and production jobs. This relies on the uCernVM system for providing root images for virtual machines. We use the CernVM-FS distributed filesystem to supply the root partition files, the LHCb software stack, and the bootstrapping scripts necessary to configure the virtual machines for us. Using this approach, we have been able to minimise the amount of contextualisation which must be provided by the virtual machine managers. We explain the process by which the virtual machine is able to receive payload jobs submitted to DIRAC by users and production managers, and how this differs from payloads executed within conventional DIRAC pilot jobs on batch queue based sites. We describe our operational experiences in running production on VM based sites managed using Vcycle/OpenStack, Vac, and HTCondor Vacuum. Finally we show how our use of these resources is monitored using Ganglia and DIRAC.

Machine learning-based Landsat-MODIS data fusion approach for 8-day 30m evapotranspiration monitoring

Science.gov (United States)

Im, J.; Ke, Y.; Park, S.

2016-12-01

Continuous monitoring of evapotranspiration (ET) is important for understanding of hydrological cycles and energy flux dynamics. At regional and local scales, routine ET estimation is a critical for efficient water management, drought impact assessment and ecosystem health monitoring, etc. Remote sensing has long been recognized to be able to provide ET monitoring over large areas. However, no single satellite could provide temporally continuous ET at relatively high spatial resolution due to the trade-off between the spatial and temporal resolution of current satellite sensors. Landsat-series satellites provide optical and thermal imagery at 30-100m resolution, whereas the 16-day revisit cycle hinders the observation of ET dynamics; MODIS provides sources of ET estimation at daily basis, but the 500-1000m ground sampling distance is too coarse for field level applications. In this study, we present a machine learning and STARFM based method for Landsat/MODIS ET fusion. The approach first downscales MODIS 8-day 1km ET (MOD16A2) to 30m based on eleven Landsat-derived indicators such as NDVI, EVI, NDWI etc on the cloud-free Landsat-available days using Random Forest approach. For the days when Landsat data are not available, downscaled ET is synthesized by MODIS and Landsat data fusion with STARFM and STI-FM approaches. The models are evaluated using in situ flux tower measurements at US-ARM and US-Twt AmeriFlux sites the United States. Results show that the downscaled 30m ET have good agreement with MODIS ET (RMSE=0.42-3.4mm/8days, rRMSE=3.2%-26%) and the downscaled ET have higher accuracy than MODIS ET when compared to in-situ measurements.

Amplifying human ability through autonomics and machine learning in IMPACT

Science.gov (United States)

Dzieciuch, Iryna; Reeder, John; Gutzwiller, Robert; Gustafson, Eric; Coronado, Braulio; Martinez, Luis; Croft, Bryan; Lange, Douglas S.

2017-05-01

Amplifying human ability for controlling complex environments featuring autonomous units can be aided by learned models of human and system performance. In developing a command and control system that allows a small number of people to control a large number of autonomous teams, we employ an autonomics framework to manage the networks that represent mission plans and the networks that are composed of human controllers and their autonomous assistants. Machine learning allows us to build models of human and system performance useful for monitoring plans and managing human attention and task loads. Machine learning also aids in the development of tactics that human supervisors can successfully monitor through the command and control system.

Man-machine supervision; Supervision homme-machine

Energy Technology Data Exchange (ETDEWEB)

Montmain, J. [CEA Valrho, Dir. de l' Energie Nucleaire (DEN), 30 - Marcoule (France)

2005-05-01

Today's complexity of systems where man is involved has led to the development of more and more sophisticated information processing systems where decision making has become more and more difficult. The operator task has moved from operation to supervision and the production tool has become indissociable from its numerical instrumentation and control system. The integration of more and more numerous and sophisticated control indicators in the control room does not necessary fulfill the expectations of the operation team. It is preferable to develop cooperative information systems which are real situation understanding aids. The stake is not the automation of operators' cognitive tasks but the supply of a reasoning help. One of the challenges of interactive information systems is the selection, organisation and dynamical display of information. The efficiency of the whole man-machine system depends on the communication interface efficiency. This article presents the principles and specificities of man-machine supervision systems: 1 - principle: operator's role in control room, operator and automation, monitoring and diagnosis, characteristics of useful models for supervision; 2 - qualitative reasoning: origin, trends, evolutions; 3 - causal reasoning: causality, causal graph representation, causal and diagnostic graph; 4 - multi-points of view reasoning: multi flow modeling method, Sagace method; 5 - approximate reasoning: the symbolic numerical interface, the multi-criteria decision; 6 - example of application: supervision in a spent-fuel reprocessing facility. (J.S.)

Trust versus confidence: Microprocessors and personnel monitoring

International Nuclear Information System (INIS)

Chiaro, P.J. Jr.

1993-01-01

Due to recent technological advances, substantial improvements have been made in personnel contamination monitoring. In all likelihood, these advances will close out the days of manually frisking personnel for radioactive contamination. Unfortunately, as microprocessor-based monitors become more widely used, not only at commercial power reactors but also at government facilities, questions concerning their trustworthiness arise. Algorithms make decisions that were previously made by technicians. Trust is placed not in technicians but in machines. In doing this it is assumed that the machine never misses. Inevitably, this trust drops, due largely to open-quotes false alarms.close quotes This is especially true when monitoring for alpha contamination. What is a open-quotes false alarm?close quotes Do these machines and their algorithms that we put our trust in make mistakes? An analysis was performed on half-body and hand-and-foot monitors at Oak Ridge National Laboratory (ORNL) in order to justify the suggested confidence level used for alarm point determination. Sources used in this analysis had activities approximating ORNL's contamination limits

Development of large size NC trepanning and horning machine

International Nuclear Information System (INIS)

Wada, Yoshiei; Aono, Fumiaki; Siga, Toshihiko; Sudo, Eiichi; Takasa, Seiju; Fukuyama, Masaaki; Sibukawa, Koichi; Nakagawa, Hirokatu

2010-01-01

Due to the recent increase in world energy demand, construction of considerable number of nuclear and fossil power plant has been proceeded and is further planned. High generating capacity plant requires large forged components such as monoblock turbine rotor shafts and the dimensions of them tend to increase. Some of these components have center bore for material test, NDE and other use. In order to cope with the increase in production of these large forgings with center bores, a new trepanning machine, which exclusively bore a deep hole, was developed in JSW taking account of many accumulated experiences and know-how of experts. The machine is the world largest 400t trepanning and horning machine with numerical control and has many advantage in safety, the machining precision, machining efficiency, operability, labor-saving, and energy saving. Furthermore, transfer of the technical skill became easy through concentrated monitoring system based on numerically analysed experts' know-how. (author)

Establishing Interaction between Machine and Medaka using Deep Q-Network

Directory of Open Access Journals (Sweden)

Ryo Nishimura

2016-05-01

Full Text Available Social interaction is the basic ability for animals to survive. It is difficult for a machine to interact with human or other animals because it is not clear how the machine should interact. This paper examines whether an artificial dot controlled by a machine can interact with a medaka and induce a desired behavior. The dot is displayed on a monitor. We use deep Q network (DQN to learn how to move the dot. As a result, the DQN could learn some basic elements to interact with the medaka and the desired behavior could be induced.

Machine learning for radioxenon event classification for the Comprehensive Nuclear-Test-Ban Treaty

Energy Technology Data Exchange (ETDEWEB)

Stocki, Trevor J., E-mail: trevor_stocki@hc-sc.gc.c [Radiation Protection Bureau, 775 Brookfield Road, A.L. 6302D1, Ottawa, ON, K1A 1C1 (Canada); Li, Guichong; Japkowicz, Nathalie [School of Information Technology and Engineering, University of Ottawa, 800 King Edward Avenue, Ottawa, ON, K1N 6N5 (Canada); Ungar, R. Kurt [Radiation Protection Bureau, 775 Brookfield Road, A.L. 6302D1, Ottawa, ON, K1A 1C1 (Canada)

2010-01-15

A method of weapon detection for the Comprehensive nuclear-Test-Ban-Treaty (CTBT) consists of monitoring the amount of radioxenon in the atmosphere by measuring and sampling the activity concentration of {sup 131m}Xe, {sup 133}Xe, {sup 133m}Xe, and {sup 135}Xe by radionuclide monitoring. Several explosion samples were simulated based on real data since the measured data of this type is quite rare. These data sets consisted of different circumstances of a nuclear explosion, and are used as training data sets to establish an effective classification model employing state-of-the-art technologies in machine learning. A study was conducted involving classic induction algorithms in machine learning including Naive Bayes, Neural Networks, Decision Trees, k-Nearest Neighbors, and Support Vector Machines, that revealed that they can successfully be used in this practical application. In particular, our studies show that many induction algorithms in machine learning outperform a simple linear discriminator when a signal is found in a high radioxenon background environment.

Machine learning for radioxenon event classification for the Comprehensive Nuclear-Test-Ban Treaty

International Nuclear Information System (INIS)

Stocki, Trevor J.; Li, Guichong; Japkowicz, Nathalie; Ungar, R. Kurt

2010-01-01

A method of weapon detection for the Comprehensive nuclear-Test-Ban-Treaty (CTBT) consists of monitoring the amount of radioxenon in the atmosphere by measuring and sampling the activity concentration of 131m Xe, 133 Xe, 133m Xe, and 135 Xe by radionuclide monitoring. Several explosion samples were simulated based on real data since the measured data of this type is quite rare. These data sets consisted of different circumstances of a nuclear explosion, and are used as training data sets to establish an effective classification model employing state-of-the-art technologies in machine learning. A study was conducted involving classic induction algorithms in machine learning including Naive Bayes, Neural Networks, Decision Trees, k-Nearest Neighbors, and Support Vector Machines, that revealed that they can successfully be used in this practical application. In particular, our studies show that many induction algorithms in machine learning outperform a simple linear discriminator when a signal is found in a high radioxenon background environment.

TMI-2 core boring machine

International Nuclear Information System (INIS)

Croft, K.M.; Helbert, H.J.; Laney, W.M.

1986-01-01

An important and essential aspect of the TMI-2 defueling effort is to determine what occurred in the core region during the accident. Remote cameras and probes only portray a portion of the overall picture. What lies beneath the rubble bed and solidified sublayer is, as yet, unknown. This paper discusses the TMI-2 Core Boring Machine, which has been developed to drill into the damaged core of the TMI-2 reactor and extract stratified samples of the core. This machine, its unique support structure, positioning and leveling systems, and specially designed drill bits, combine to provide a unique mechanical system. In addition, the machine is controlled by a microprocessor; which actually controls the drilling operation, allowing relatively inexperienced operators to drill the core samples. A data acquisition system is data integral with the controlling system and collects data relative to system conditions and monitored parameters during drilling. Data obtained during the actual drilling operations are collected in a data base which will be used for actual mapping of the core region, identifying materials and stratification levels that are present

Principles of control automation of soil compacting machine operating mechanism

Science.gov (United States)

Anatoly Fedorovich, Tikhonov; Drozdov, Anatoly

2018-03-01

The relevance of the qualitative compaction of soil bases in the erection of embankment and foundations in building and structure construction is given.The quality of the compactible gravel and sandy soils provides the bearing capability and, accordingly, the strength and durability of constructed buildings.It has been established that the compaction quality depends on many external actions, such as surface roughness and soil moisture; granulometry, chemical composition and degree of elasticity of originalfilled soil for compaction.The analysis of technological processes of soil bases compaction of foreign and domestic information sources showed that the solution of such important problem as a continuous monitoring of soil compaction actual degree in the process of machine operation carry out only with the use of modern means of automation. An effective vibrodynamic method of gravel and sand material sealing for the building structure foundations for various applications was justified and suggested.The method of continuous monitoring the soil compaction by measurement of the amplitudes and frequencies of harmonic oscillations on the compactible surface was determined, which allowed to determine the basic elements of facilities of soil compacting machine monitoring system of operating, etc. mechanisms: an accelerometer, a bandpass filter, a vibro-harmonics, an on-board microcontroller. Adjustable parameters have been established to improve the soil compaction degree and the soil compacting machine performance, and the adjustable parameter dependences on the overall indexhave been experimentally determined, which is the soil compaction degree.A structural scheme of automatic control of the soil compacting machine control mechanism and theoperation algorithm has been developed.

Oil analysis in machine diagnostics

Energy Technology Data Exchange (ETDEWEB)

Vaehaeoja, P.

2006-07-01

This study concentrates on developing and tuning various oil analysis methods to meet the requirements of modern industry and environmental analytics. Oil analysis methods form a vital part of techniques used to monitor the condition of machines and may help to improve the overall equipment effectiveness value of a factory in a significant manner. Worm gears are used in various production machines, and their breakdowns may cause significant production losses. Wearing of these gears is relatively difficult to monitor with vibration analysis. Analysis of two indicator metals, copper and iron, may reveal wearing phenomena of worm gears effectively, and savings can be significant. Effective wear metal analysis requires good tools. ICP-OES with kerosene dilution is widely used in wear metal analysis, but purchasing and using of ICP-OES is expensive. A cheaper FAAS technique with similar pre-treatment of oil samples was tested and it proved to be useful especially in analyzing small amounts of samples. The accuracy of FAAS was sufficient for quantitative work in machine diagnostics and waste oil characterization. Solid debris analyses are useful in oil contamination control as well as in detection of wearing mechanisms. Membrane filtration, optical microscopy, SEM and automatic particle counting were applied in analysis of rolling and gear oils. Particle counting is an effective way to detect oil contamination, but in the studied cases even larger particles than those detected in normal ISO classes would be informative. However, membrane filtration and optical microscopy may reveal the wearing machine element exactly. Additives provide oils with desired properties thus they should be monitored intensively. A FTIR method for quantitative analysis of fatty alcohols and fatty acid esters in machinery oils was developed during this work. It has already been used successfully in quantitative and qualitative analysis of machinery oil samples. Various kinds of oils may be

Machine learning for identifying botnet network traffic

DEFF Research Database (Denmark)

Stevanovic, Matija; Pedersen, Jens Myrup

2013-01-01

. Due to promise of non-invasive and resilient detection, botnet detection based on network traffic analysis has drawn a special attention of the research community. Furthermore, many authors have turned their attention to the use of machine learning algorithms as the mean of inferring botnet......-related knowledge from the monitored traffic. This paper presents a review of contemporary botnet detection methods that use machine learning as a tool of identifying botnet-related traffic. The main goal of the paper is to provide a comprehensive overview on the field by summarizing current scientific efforts....... The contribution of the paper is three-fold. First, the paper provides a detailed insight on the existing detection methods by investigating which bot-related heuristic were assumed by the detection systems and how different machine learning techniques were adapted in order to capture botnet-related knowledge...

Machine rates for selected forest harvesting machines

Science.gov (United States)

R.W. Brinker; J. Kinard; Robert Rummer; B. Lanford

2002-01-01

Very little new literature has been published on the subject of machine rates and machine cost analysis since 1989 when the Alabama Agricultural Experiment Station Circular 296, Machine Rates for Selected Forest Harvesting Machines, was originally published. Many machines discussed in the original publication have undergone substantial changes in various aspects, not...

Safety Aspects of EPS-3000 Electron Beam Machine

International Nuclear Information System (INIS)

Siti Aiasah Hashim; Shari Jahar; Ayub Muhamad; Sarada Idris

2011-01-01

The EPS-3000 electron beam machine was installed and commission in 1991 at the Alurtron Electron Beam Irradiation Centre. It is utilized as a tool to enhance finished products through electron beam irradiation. The machine and its auxiliary systems were built with highest safety in mind due to the possible dangers that it can cause during the irradiation activities. Automatic stops may be activated via various interlocks to protect the integrity of the machine. This type of interlocks are controlled by the set upper and lower limits, mostly related to the machine high voltage (and beam) generation and cooling systems. Radiation safety is also taken care of by provision of shielding and area monitoring. Other potential hazards include ozone poisoning and electromagnetic field (EMF) could be generated by the high voltage. This paper describes the safety and security systems installed within the facility as measures to protect the workers and general public from radiation and other physical threats. (author)

Mechatronic sensor system for robots and automated machines

CSIR Research Space (South Africa)

Shaik, AA

2007-01-01

Full Text Available machine makes a calculated estimate of where the tool-head should be. This is often achieved by monitoring sensors on axes that track linear translation and rotations of shafts or gears. For low precision applications this system is appropriate. However...

A Comparative Experimental Study on the Use of Machine Learning Approaches for Automated Valve Monitoring Based on Acoustic Emission Parameters

Science.gov (United States)

Ali, Salah M.; Hui, K. H.; Hee, L. M.; Salman Leong, M.; Al-Obaidi, M. A.; Ali, Y. H.; Abdelrhman, Ahmed M.

2018-03-01

Acoustic emission (AE) analysis has become a vital tool for initiating the maintenance tasks in many industries. However, the analysis process and interpretation has been found to be highly dependent on the experts. Therefore, an automated monitoring method would be required to reduce the cost and time consumed in the interpretation of AE signal. This paper investigates the application of two of the most common machine learning approaches namely artificial neural network (ANN) and support vector machine (SVM) to automate the diagnosis of valve faults in reciprocating compressor based on AE signal parameters. Since the accuracy is an essential factor in any automated diagnostic system, this paper also provides a comparative study based on predictive performance of ANN and SVM. AE parameters data was acquired from single stage reciprocating air compressor with different operational and valve conditions. ANN and SVM diagnosis models were subsequently devised by combining AE parameters of different conditions. Results demonstrate that ANN and SVM models have the same results in term of prediction accuracy. However, SVM model is recommended to automate diagnose the valve condition in due to the ability of handling a high number of input features with low sampling data sets.

Time-Frequency Analysis of Signals Generated by Rotating Machines

Directory of Open Access Journals (Sweden)

R. Zetik

1999-06-01

Full Text Available This contribution is devoted to the higher order time-frequency analyses of signals. Firstly, time-frequency representations of higher order (TFRHO are defined. Then L-Wigner distribution (LWD is given as a special case of TFRHO. Basic properties of LWD are illustrated based on the analysis of mono-component and multi-component synthetic signals and acoustical signals generated by rotating machine. The obtained results confirm usefulness of LWD application for the purpose of rotating machine condition monitoring.

A methodology for online visualization of the energy flow in a machine tool

DEFF Research Database (Denmark)

Mohammadi, Ali; Züst, Simon; Mayr, Josef

2017-01-01

the machining process and by this increasing its energy efficiency. This study intents to propose a method which has the capability of real-time monitoring of the entire energetic flows in a CNC machine tool including motors, pumps and cooling fluid. The structure of this approach is based on categorizing...

CODAS object monitoring service

International Nuclear Information System (INIS)

Wheatley, M.R.; Rainford, M.

2001-01-01

The primary Control and Data Acquisition System (CODAS) of JET is based on a TCP/IP network of more than 150 computers. The CODAS computers provide the JET machine control and data acquisition for over 70,000 digital and analog signals. The Object Monitoring Service (OMS) is used by applications for monitoring objects for presentation to the JET machine operators and for the operation of individual software components (such as valve state, access control, mimic definition changes and internal data distribution). Each server typically handles connections from around 60 clients monitoring upwards of 2000 objects. Some servers have over 150 clients and 5000 objects. Acquisition libraries are dynamically linked into a running server as required either to acquire data values for objects or to forward requests to other OMS servers. A mechanism involving dynamic linking allows new libraries to be integrated without stopping or changing running software. OMS provides a very reliable and highly successful 'data-type independent' means of monitoring many different objects. It allows applications to take advantage of new data sources, without the need to change existing code

Tool Wear Monitoring Using Time Series Analysis

Science.gov (United States)

Song, Dong Yeul; Ohara, Yasuhiro; Tamaki, Haruo; Suga, Masanobu

A tool wear monitoring approach considering the nonlinear behavior of cutting mechanism caused by tool wear and/or localized chipping is proposed, and its effectiveness is verified through the cutting experiment and actual turning machining. Moreover, the variation in the surface roughness of the machined workpiece is also discussed using this approach. In this approach, the residual error between the actually measured vibration signal and the estimated signal obtained from the time series model corresponding to dynamic model of cutting is introduced as the feature of diagnosis. Consequently, it is found that the early tool wear state (i.e. flank wear under 40µm) can be monitored, and also the optimal tool exchange time and the tool wear state for actual turning machining can be judged by this change in the residual error. Moreover, the variation of surface roughness Pz in the range of 3 to 8µm can be estimated by the monitoring of the residual error.

Prehospital ECG transmission: comparison of advanced mobile phone and facsimile devices in an urban Emergency Medical Service System.

Science.gov (United States)

Väisänen, Olli; Mäkijärvi, Markku; Silfvast, Tom

2003-05-01

To compare the speed and reliability of electrocardiogram (ECG) transmissions from the prehospital setting to a conventional table facsimile device and to an advanced mobile phone in a Helicopter Emergency Medical Service System (HEMS). Eighteen authentic ECGs stored in the memory module of a monitor defibrillator were used. The ECGs were (1) sent directly from the monitor defibrillator to a table fax and an advanced mobile phone at the HEMS base; (2) printed out and sent from a mobile fax connected to an ordinary mobile phone to the table fax and the advanced mobile phone at the HEMS base; (3) printed out and sent from an ordinary table fax as well as from a table fax connected to a satellite phone system to the receiving devices at the HEMS base. When the ECGs were sent from the table fax via satellite, the transmission times were longer to the advanced mobile phone than to the table fax at the HEMS base (1 min 54 s+/-0 min 21 s vs. 1 min 37 s+/-0 min 20 s, (mean+/-SD), (Ptransmission from the other fax devices, there were no differences in transmission times between the two receiving devices. The fastest way to transmit ECGs to the advanced mobile phone was to send it from conventional table fax (1 min 22 s+/-0 min 18 s) and the longest transmission times were with mobile fax connected to mobile phone (5 min 23 s+/-3 min 5 s). In all ECGs transmitted except one the cardiac rhythm and ST-changes could be recognised. An advanced mobile phone is as fast and reliable as a conventional table fax in receiving ECGs. A mobile phone with advanced features is a practical tool for HEMS physicians who need to evaluate ECGs in the prehospital setting.

Vibration-based condition monitoring industrial, aerospace and automotive applications

CERN Document Server

Randall, Robert Bond

2010-01-01

""Without doubt the best modern and up-to-date text on the topic, wirtten by one of the world leading experts in the field. Should be on the desk of any practitioner or researcher involved in the field of Machine Condition Monitoring"" Simon Braun, Israel Institute of Technology Explaining complex ideas in an easy to understand way, Vibration-based Condition Monitoring provides a comprehensive survey of the application of vibration analysis to the condition monitoring of machines. Reflecting the natural progression of these systems by presenting the fundamental material

Fault Diagnosis and Condition Monitoring of an All Geared Lathe Machine Using Piezoelectric Sensor

Directory of Open Access Journals (Sweden)

Amiya BHAUMIK

2008-12-01

Full Text Available Undesired vibrations are serious problems that affect and deteriorate the quality of the product. This paper investigates dynamic and vibrational characteristics of a newly installed All Geared Lathe Machine with piezoelectric sensor. A comparison is drawn with the data measured and acceptable data as per ISO 10816 and thus concluded that the machine is in working condition.

Beam position monitors for the high brightness lattice

International Nuclear Information System (INIS)

Ring, T.

1985-06-01

Engineering developments associated with the high brightness lattice and the projected change in machine operating parameters will inherently affect the diagnostics systems and devices installed at present in the storage ring. This is particularly true of the beam position monitoring (BPI) system. The new sixteen unit cell lattice with its higher betatron tune values and the limited space available in the redesigned machine straights for fitting standard BPI vessels forces a fundamental re-evaluation of the beam position monitor system. The design aims for the new system are based on accepting the space limitations imposed while still providing the monitor points required to give good radial and vertical closed orbit plots. The locations of BPI's in the redesigned machine straights is illustrated. A description of the new BPI assemblies and their calibration is given. The BPI's use capacitance button type pick-ups; their response is described. (U.K.)

Practical implementation of machine tool metrology and maintenance management systems

International Nuclear Information System (INIS)

Perkins, C; Longstaff, A P; Fletcher, S; Willoughby, P

2012-01-01

Maximising asset utilisation and minimising downtime and waste are becoming increasingly important to all manufacturing facilities as competition increases and profits decrease. The tools to assist with monitoring these machining processes are becoming more and more in demand. A system designed to fulfil the needs of machine tool operators and supervisors has been developed and its impact on the precision manufacturing industry is being considered. The benefits of implementing this system, compared to traditional methods, will be discussed here.

[A new machinability test machine and the machinability of composite resins for core built-up].

Science.gov (United States)

Iwasaki, N

2001-06-01

A new machinability test machine especially for dental materials was contrived. The purpose of this study was to evaluate the effects of grinding conditions on machinability of core built-up resins using this machine, and to confirm the relationship between machinability and other properties of composite resins. The experimental machinability test machine consisted of a dental air-turbine handpiece, a control weight unit, a driving unit of the stage fixing the test specimen, and so on. The machinability was evaluated as the change in volume after grinding using a diamond point. Five kinds of core built-up resins and human teeth were used in this study. The machinabilities of these composite resins increased with an increasing load during grinding, and decreased with repeated grinding. There was no obvious correlation between the machinability and Vickers' hardness; however, a negative correlation was observed between machinability and scratch width.

The Human/Machine Humanities: A Proposal

Directory of Open Access Journals (Sweden)

Ollivier Dyens

2016-03-01

Full Text Available What does it mean to be human in the 21st century? The pull of engineering on every aspect of our lives, the impact of machines on how we represent ourselves, the influence of computers on our understanding of free-will, individuality and species, and the effect of microorganisms on our behaviour are so great that one cannot discourse on humanity and humanities without considering their entanglement with technology and with the multiple new dimensions of reality that it opens up. The future of humanities should take into account AI, bacteria, software, viruses (both organic and inorganic, hardware, machine language, parasites, big data, monitors, pixels, swarms systems and the Internet. One cannot think of humanity and humanities as distinct from technology anymore.

Introduction to Machine Protection

CERN Document Server

Schmidt, R

2016-01-01

Protection of accelerator equipment is as old as accelerator technology and was for many years related to high-power equipment. Examples are the protection of powering equipment from overheating (magnets, power converters, high-current cables), of superconducting magnets from damage after a quench and of klystrons. The protection of equipment from beam accidents is more recent, although there was one paper that discussed beam-induced damage for the SLAC linac (Stanford Linear Accelerator Center) as early as in 1967. It is related to the increasing beam power of high-power proton accelerators, to the emission of synchrotron light by electron-positron accelerators and to the increase of energy stored in the beam. Designing a machine protection system requires an excellent understanding of accelerator physics and operation to anticipate possible failures that could lead to damage. Machine protection includes beam and equipment monitoring, a system to safely stop beam operation (e.g. dumping the beam or stopping ...

FY 2000 Immediate-effect type project for research and development for international standards supporting information technology industries. Standardization of the machine monitoring technologies of the next generation for protecting safety of personnel; 2000 nendo joho sangyo shien sokkogata kokusai hyojun kaihatsu jigyo seika hokokusho. Hito no anzen wo mamoru jisedai kikai kanshi gijutsu no hyojunka

Energy Technology Data Exchange (ETDEWEB)

NONE

2001-03-01

This project is aimed at establishing the international standards for the mechanical safety area. Described herein are the FY 2000 results of the developmental research on the machine monitoring devices of the next generation in which the image processing technologies are applied. The developed image sensors are the video camera and optical radar type sensor capable of scanning the three-dimensional space. The video camera functions self-confirmation that it is functioning without failure by the aid of the background reference pattern, and detects a person and machine when the pattern is hidden by them. The optical radar type sensor works to continuously confirm its performance by monitoring light reflected from the standard reflection body. The machine monitoring algorithms with the aid of the two-value images are also studied for e.g., judgment of stopping a machine by predicting that it will enter a closed space. The prototype monitor developed is subjected to various tests, including the tests of the individual device and assemblies in which it is incorporated, and the field tests in which it is incorporated in a machine in a commercial production line, to confirm that it can exhibit all of its required functions. (NEDO)

Application of Support Vector Machine to Forex Monitoring

Science.gov (United States)

Kamruzzaman, Joarder; Sarker, Ruhul A.

Previous studies have demonstrated superior performance of artificial neural network (ANN) based forex forecasting models over traditional regression models. This paper applies support vector machines to build a forecasting model from the historical data using six simple technical indicators and presents a comparison with an ANN based model trained by scaled conjugate gradient (SCG) learning algorithm. The models are evaluated and compared on the basis of five commonly used performance metrics that measure closeness of prediction as well as correctness in directional change. Forecasting results of six different currencies against Australian dollar reveal superior performance of SVM model using simple linear kernel over ANN-SCG model in terms of all the evaluation metrics. The effect of SVM parameter selection on prediction performance is also investigated and analyzed.

Modelling Machine Tools using Structure Integrated Sensors for Fast Calibration

Directory of Open Access Journals (Sweden)

Benjamin Montavon

2018-02-01

Full Text Available Monitoring of the relative deviation between commanded and actual tool tip position, which limits the volumetric performance of the machine tool, enables the use of contemporary methods of compensation to reduce tolerance mismatch and the uncertainties of on-machine measurements. The development of a primarily optical sensor setup capable of being integrated into the machine structure without limiting its operating range is presented. The use of a frequency-modulating interferometer and photosensitive arrays in combination with a Gaussian laser beam allows for fast and automated online measurements of the axes’ motion errors and thermal conditions with comparable accuracy, lower cost, and smaller dimensions as compared to state-of-the-art optical measuring instruments for offline machine tool calibration. The development is tested through simulation of the sensor setup based on raytracing and Monte-Carlo techniques.

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...

Light-driven molecular machine at ITIES

International Nuclear Information System (INIS)

Kornyshev, Alexei A; Kuimova, Marina; Kuznetsov, Alexander M; Ulstrup, Jens; Urbakh, Michael

2007-01-01

We suggest a principle of operation of a new molecular device that transforms the energy of light into repetitive mechanical motions. Such a device can also serve as a model system for the study of the effect of electric field on intramolecular electron transfer. We discuss the design of suitable molecular systems and the methods that may monitor the 'performance' of such a machine

Simulation-driven machine learning: Bearing fault classification

Science.gov (United States)

Sobie, Cameron; Freitas, Carina; Nicolai, Mike

2018-01-01

Increasing the accuracy of mechanical fault detection has the potential to improve system safety and economic performance by minimizing scheduled maintenance and the probability of unexpected system failure. Advances in computational performance have enabled the application of machine learning algorithms across numerous applications including condition monitoring and failure detection. Past applications of machine learning to physical failure have relied explicitly on historical data, which limits the feasibility of this approach to in-service components with extended service histories. Furthermore, recorded failure data is often only valid for the specific circumstances and components for which it was collected. This work directly addresses these challenges for roller bearings with race faults by generating training data using information gained from high resolution simulations of roller bearing dynamics, which is used to train machine learning algorithms that are then validated against four experimental datasets. Several different machine learning methodologies are compared starting from well-established statistical feature-based methods to convolutional neural networks, and a novel application of dynamic time warping (DTW) to bearing fault classification is proposed as a robust, parameter free method for race fault detection.

Characteristics of the Arcing Plasma Formation Effect in Spark-Assisted Chemical Engraving of Glass, Based on Machine Vision

OpenAIRE

Chao-Ching Ho; Dung-Sheng Wu

2018-01-01

Spark-assisted chemical engraving (SACE) is a non-traditional machining technology that is used to machine electrically non-conducting materials including glass, ceramics, and quartz. The processing accuracy, machining efficiency, and reproducibility are the key factors in the SACE process. In the present study, a machine vision method is applied to monitor and estimate the status of a SACE-drilled hole in quartz glass. During the machining of quartz glass, the spring-fed tool electrode was p...

Hydraulic stud-tensioning machines in reactor technology

International Nuclear Information System (INIS)

Lachner, H.

1978-01-01

Hydraulic multiple stud tensioner (MST) for the simultaneous prestressing of all the stud bolts is make it possible to achieve highly accurate prestress levels in the highly stressed bolts holding down the top head of reactor pressure vessels. These machines can remove and replace the nuts and studs, and can rotate these components upwards and downwards, during the operation of opening and closing the reactor pressure vessel. In order to reduce the radiation exposure of the service personnel, and also to reduce the time required for this work which may lie in the critical path of the refuelling time schedule, it is desirable to achieve complete mechanisation of these machines, including remote control and remote monitoring. The devices and components required for this purpose are without precedent in machine construction with respect to their functions and to the load range involved. The reported operating experience therefore also covers some points of general interest while the data on maintenance reflect the known status of the technology. (orig.) [de

Overall design concepts for the APS storage ring machine protection system

International Nuclear Information System (INIS)

Lumpkin, A.; Fuja, R.; Votaw, A.; Wang, X.; Shu, D.; Stepp, J.; Arnold, N.; Nawrocki, G.; Decker, G.; Chung, Y.

1995-01-01

The basic design and status of the machine protection system for the Advanced Photon Source (APS) storage ring are discussed. The machine is passively safe to the bending magnet sources, but the high power of the insertion devices requires missteering conditions to be identified and the beam aborted in less than one millisecond. The basic aspects of waterflow, temperature, beam position, etc. monitoring are addressed. Initial commissioning of subsystems and sensors is statused

Vibration Monitoring of Gas Turbine Engines: Machine-Learning Approaches and Their Challenges

Directory of Open Access Journals (Sweden)

Ioannis Matthaiou

2017-09-01

Full Text Available In this study, condition monitoring strategies are examined for gas turbine engines using vibration data. The focus is on data-driven approaches, for this reason a novelty detection framework is considered for the development of reliable data-driven models that can describe the underlying relationships of the processes taking place during an engine’s operation. From a data analysis perspective, the high dimensionality of features extracted and the data complexity are two problems that need to be dealt with throughout analyses of this type. The latter refers to the fact that the healthy engine state data can be non-stationary. To address this, the implementation of the wavelet transform is examined to get a set of features from vibration signals that describe the non-stationary parts. The problem of high dimensionality of the features is addressed by “compressing” them using the kernel principal component analysis so that more meaningful, lower-dimensional features can be used to train the pattern recognition algorithms. For feature discrimination, a novelty detection scheme that is based on the one-class support vector machine (OCSVM algorithm is chosen for investigation. The main advantage, when compared to other pattern recognition algorithms, is that the learning problem is being cast as a quadratic program. The developed condition monitoring strategy can be applied for detecting excessive vibration levels that can lead to engine component failure. Here, we demonstrate its performance on vibration data from an experimental gas turbine engine operating on different conditions. Engine vibration data that are designated as belonging to the engine’s “normal” condition correspond to fuels and air-to-fuel ratio combinations, in which the engine experienced low levels of vibration. Results demonstrate that such novelty detection schemes can achieve a satisfactory validation accuracy through appropriate selection of two parameters of the

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 ...

Quaternion Based Thermal Condition Monitoring System

Science.gov (United States)

Wong, Wai Kit; Loo, Chu Kiong; Lim, Way Soong; Tan, Poi Ngee

In this paper, we will propose a new and effective machine condition monitoring system using log-polar mapper, quaternion based thermal image correlator and max-product fuzzy neural network classifier. Two classification characteristics namely: peak to sidelobe ratio (PSR) and real to complex ratio of the discrete quaternion correlation output (p-value) are applied in the proposed machine condition monitoring system. Large PSR and p-value observe in a good match among correlation of the input thermal image with a particular reference image, while small PSR and p-value observe in a bad/not match among correlation of the input thermal image with a particular reference image. In simulation, we also discover that log-polar mapping actually help solving rotation and scaling invariant problems in quaternion based thermal image correlation. Beside that, log-polar mapping can have a two fold of data compression capability. Log-polar mapping can help smoother up the output correlation plane too, hence makes a better measurement way for PSR and p-values. Simulation results also show that the proposed system is an efficient machine condition monitoring system with accuracy more than 98%.

Ergonomic principles for the design of combined drilling and loading machines

Energy Technology Data Exchange (ETDEWEB)

Mason, S.; Simpson, G.C.

1990-08-08

Underground investigations of development machines have revealed a number of limitations in ergonomics aspects of their design which could influence both the safety and efficiency of the operation. This handbook is intended to provide designers of Combined Drilling and Loading machines with the ergonomic information which can be used to eliminate or reduce such problems. The following criteria were examined: workspace position; operator clearances; operator protection; operator visual communications; operator visual machine monitoring; operator visual safety information; operator seating; operature posture; operator access to workspace; control types; control operating forces; control-response stereotypes; safety controls; control dynamics; control layout; control clearances; control protection; visual displays.

Ratios between the effective doses for tomographic phantoms MAX and FAX

International Nuclear Information System (INIS)

Kramer, R.; Khoury, H.J.

2005-01-01

In the last two decades, the coefficients for the equivalent dose in organs and tissues, as well as to the effective dose, recommended by the International Commission on Radiological Protection (ICRP) were determined using exposure models based on stylized phantoms type MIRD, representing the human body with its radiosensitive organs and tissues according to the ICRP 23 Reference Man, Monte Carlo codes that simulate in a simplified way radiation physics, fabric compositions from different sources, and sometimes applied in a no realistic way, and by the list of organs and tissues at risk with their corresponding weight factors, published in ICRP 60. In the meantime, the International Commission on radiation units and Measurements (ICRU) published reference data to human tissue compositions in ICRU 44 and ICRP launched new anatomical and physiological data of reference in the report number 89. In addition a draft report with recommendations to be released in 2005 (http://icrp.org/) advances significant changes in the list of radiosensitive organs and tissues as well as their corresponding weight factors. As a practical consequence, all components of the traditional stylized models of exposure should be replaced: Monte Carlo codes, human phantoms, the compositions of the fabric and the selection of the organs and tissues at risk with their respective weight factors to determine the effective dose. This article presents the results of comprehensive research into the dosimetric consequences of replacing the stylized models of exposure. The calculations were done using the EGS4 Monte Carlo and MCNP4C codes for external and internal exposure to photons and electrons with phantoms ADAM and EVA, as well as with tomographic phantoms MAX and FAX, for different compositions and tissue distributions. The ratios between effective doses for models of exposure based on phantoms of voxels and effective doses for the stylized models for external and internal exposure to photons and

Machine assisted histogram classification

Science.gov (United States)

Benyó, B.; Gaspar, C.; Somogyi, P.

2010-04-01

LHCb is one of the four major experiments under completion at the Large Hadron Collider (LHC). Monitoring the quality of the acquired data is important, because it allows the verification of the detector performance. Anomalies, such as missing values or unexpected distributions can be indicators of a malfunctioning detector, resulting in poor data quality. Spotting faulty or ageing components can be either done visually using instruments, such as the LHCb Histogram Presenter, or with the help of automated tools. In order to assist detector experts in handling the vast monitoring information resulting from the sheer size of the detector, we propose a graph based clustering tool combined with machine learning algorithm and demonstrate its use by processing histograms representing 2D hitmaps events. We prove the concept by detecting ion feedback events in the LHCb experiment's RICH subdetector.

Machine assisted histogram classification

Energy Technology Data Exchange (ETDEWEB)

Benyo, B; Somogyi, P [BME-IIT, H-1117 Budapest, Magyar tudosok koerutja 2. (Hungary); Gaspar, C, E-mail: Peter.Somogyi@cern.c [CERN-PH, CH-1211 Geneve 23 (Switzerland)

2010-04-01

LHCb is one of the four major experiments under completion at the Large Hadron Collider (LHC). Monitoring the quality of the acquired data is important, because it allows the verification of the detector performance. Anomalies, such as missing values or unexpected distributions can be indicators of a malfunctioning detector, resulting in poor data quality. Spotting faulty or ageing components can be either done visually using instruments, such as the LHCb Histogram Presenter, or with the help of automated tools. In order to assist detector experts in handling the vast monitoring information resulting from the sheer size of the detector, we propose a graph based clustering tool combined with machine learning algorithm and demonstrate its use by processing histograms representing 2D hitmaps events. We prove the concept by detecting ion feedback events in the LHCb experiment's RICH subdetector.

Thutmose - Investigation of Machine Learning-Based Intrusion Detection Systems

Science.gov (United States)

2016-06-01

monitoring. This analyzed payload is within the application layer of the OSI model . The analysis tries to establish whether or not the payload is...24 3.2.5 Model Drift Experiments...ADVERSARIAL ENVIRONMENTS (SPIE DSS 2014) .................................................. 58 APPENDIX C - EVALUATING MODEL DRIFT IN MACHINE LEARNING

Machine Learning for Optical Performance Monitoring from Directly Detected PDM-QAM Signals

DEFF Research Database (Denmark)

Wass, J.; Thrane, Jakob; Piels, Molly

2016-01-01

Supervised machine learning methods are applied and demonstrated experimentally for inband OSNR estimation and modulation format classification in optical communication systems. The proposed methods accurately evaluate coherent signals up to 64QAM using only intensity information....

Effect of Machining Velocity in Nanoscale Machining Operations

International Nuclear Information System (INIS)

Islam, Sumaiya; Khondoker, Noman; Ibrahim, Raafat

2015-01-01

The aim of this study is to investigate the generated forces and deformations of single crystal Cu with (100), (110) and (111) crystallographic orientations at nanoscale machining operation. A nanoindenter equipped with nanoscratching attachment was used for machining operations and in-situ observation of a nano scale groove. As a machining parameter, the machining velocity was varied to measure the normal and cutting forces. At a fixed machining velocity, different levels of normal and cutting forces were generated due to different crystallographic orientations of the specimens. Moreover, after machining operation percentage of elastic recovery was measured and it was found that both the elastic and plastic deformations were responsible for producing a nano scale groove within the range of machining velocities from 250-1000 nm/s. (paper)

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

Science.gov (United States)

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

2017-09-21

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

Brain Machine Interfaces for Robotic Control in Space Applications, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — This SBIR will study the application of a brain machine interface (BMI) to enable crew to remotely operate and monitor robots from inside a flight vehicle, habitat...

AE Monitoring of Diamond Turned Rapidly Soldified Aluminium 443

International Nuclear Information System (INIS)

Onwuka, G; Abou-El-Hossein, K; Mkoko, Z

2017-01-01

The fast replacement of conventional aluminium with rapidly solidified aluminium alloys has become a noticeable trend in the current manufacturing industries involved in the production of optics and optical molding inserts. This is as a result of the improved performance and durability of rapidly solidified aluminium alloys when compared to conventional aluminium. Melt spinning process is vital for manufacturing rapidly solidified aluminium alloys like RSA 905, RSA 6061 and RSA 443 which are common in the industries today. RSA 443 is a newly developed alloy with few research findings and huge research potential. There is no available literature focused on monitoring the machining of RSA 443 alloys. In this research, Acoustic Emission sensing technique was applied to monitor the single point diamond turning of RSA 443 on an ultrahigh precision lathe machine. The machining process was carried out after careful selection of feed, speed and depths of cut. The monitoring process was achieved with a high sampling data acquisition system using different tools while concurrent measurement of the surface roughness and tool wear were initiated after covering a total feed distance of 13km. An increasing trend of raw AE spikes and peak to peak signal were observed with an increase in the surface roughness and tool wear values. Hence, acoustic emission sensing technique proves to be an effective monitoring method for the machining of RSA 443 alloy. (paper)

Man machine interface and its implementation

International Nuclear Information System (INIS)

Hills, B.G.; Boettcher, D.B.; Reed, R.

1992-01-01

Sizewell B is the latest nuclear power station to be constructed in the United Kingdom: its Man-Machine Interfaces are therefore, by definition, the state-of-the-art. This paper discusses the principal Man-Machine Interfaces used in the operation of the station, and the systems that implement them. The Man-Machine Interface facilities discussed are: in the Main Control Room, which is used for normal operation and shutdown of the plant: in the Auxiliary Shutdown Room, which allows shutdown of the reactor if evacuation of the main Control Room is necessary: and in the Technical Support Centre, which is used for remote monitoring of the plant. The Man-Machine Interfaces that are described are parts of a station-wide group of interlinked computer systems called the Data Processing and Control System. This system collects data from the plant and displays it to the operators via discrete devices and on graphical computer displays. It also acquires control inputs from the operators via switches, which are then used to provide remote manual control, modulating control and sequence control. The computer system that handles the plant process data and alarm information displays uses a windowing interface with keyboard and trackerball navigation to allow easy retrieval and viewing of information. It is this system that is the main topic of this paper. (author)

Structural health monitoring an advanced signal processing perspective

CERN Document Server

Chen, Xuefeng; Mukhopadhyay, Subhas

2017-01-01

This book highlights the latest advances and trends in advanced signal processing (such as wavelet theory, time-frequency analysis, empirical mode decomposition, compressive sensing and sparse representation, and stochastic resonance) for structural health monitoring (SHM). Its primary focus is on the utilization of advanced signal processing techniques to help monitor the health status of critical structures and machines encountered in our daily lives: wind turbines, gas turbines, machine tools, etc. As such, it offers a key reference guide for researchers, graduate students, and industry professionals who work in the field of SHM.

Machine vision theory, algorithms, practicalities

CERN Document Server

Davies, E R

2005-01-01

In the last 40 years, machine vision has evolved into a mature field embracing a wide range of applications including surveillance, automated inspection, robot assembly, vehicle guidance, traffic monitoring and control, signature verification, biometric measurement, and analysis of remotely sensed images. While researchers and industry specialists continue to document their work in this area, it has become increasingly difficult for professionals and graduate students to understand the essential theory and practicalities well enough to design their own algorithms and systems. This book directl

Design of an automatic production monitoring system on job shop manufacturing

Science.gov (United States)

Prasetyo, Hoedi; Sugiarto, Yohanes; Rosyidi, Cucuk Nur

2018-02-01

Every production process requires monitoring system, so the desired efficiency and productivity can be monitored at any time. This system is also needed in the job shop type of manufacturing which is mainly influenced by the manufacturing lead time. Processing time is one of the factors that affect the manufacturing lead time. In a conventional company, the recording of processing time is done manually by the operator on a sheet of paper. This method is prone to errors. This paper aims to overcome this problem by creating a system which is able to record and monitor the processing time automatically. The solution is realized by utilizing electric current sensor, barcode, RFID, wireless network and windows-based application. An automatic monitoring device is attached to the production machine. It is equipped with a touch screen-LCD so that the operator can use it easily. Operator identity is recorded through RFID which is embedded in his ID card. The workpiece data are collected from the database by scanning the barcode listed on its monitoring sheet. A sensor is mounted on the machine to measure the actual machining time. The system's outputs are actual processing time and machine's capacity information. This system is connected wirelessly to a workshop planning application belongs to the firm. Test results indicated that all functions of the system can run properly. This system successfully enables supervisors, PPIC or higher level management staffs to monitor the processing time quickly with a better accuracy.

Design of instrumentation and software for precise laser machining

Science.gov (United States)

Wyszyński, D.; Grabowski, Marcin; Lipiec, Piotr

2017-10-01

The paper concerns the design of instrumentation and software for precise laser machining. Application of advanced laser beam manipulation instrumentation enables noticeable improvement of cut quality and material loss. This factors have significant impact on process efficiency and cutting edge quality by means of machined part size and shape accuracy, wall taper, material loss reduction (e.g. diamond) and time effectiveness. The goal can be reached by integration of laser drive, observation and optical measurement system, beam manipulation system and five axis mechanical instrumentation with use of advanced tailored software enabling full laser cutting process control and monitoring.

A machine learning calibration model using random forests to improve sensor performance for lower-cost air quality monitoring

Science.gov (United States)

Zimmerman, Naomi; Presto, Albert A.; Kumar, Sriniwasa P. N.; Gu, Jason; Hauryliuk, Aliaksei; Robinson, Ellis S.; Robinson, Allen L.; Subramanian, R.

2018-01-01

Low-cost sensing strategies hold the promise of denser air quality monitoring networks, which could significantly improve our understanding of personal air pollution exposure. Additionally, low-cost air quality sensors could be deployed to areas where limited monitoring exists. However, low-cost sensors are frequently sensitive to environmental conditions and pollutant cross-sensitivities, which have historically been poorly addressed by laboratory calibrations, limiting their utility for monitoring. In this study, we investigated different calibration models for the Real-time Affordable Multi-Pollutant (RAMP) sensor package, which measures CO, NO2, O3, and CO2. We explored three methods: (1) laboratory univariate linear regression, (2) empirical multiple linear regression, and (3) machine-learning-based calibration models using random forests (RF). Calibration models were developed for 16-19 RAMP monitors (varied by pollutant) using training and testing windows spanning August 2016 through February 2017 in Pittsburgh, PA, US. The random forest models matched (CO) or significantly outperformed (NO2, CO2, O3) the other calibration models, and their accuracy and precision were robust over time for testing windows of up to 16 weeks. Following calibration, average mean absolute error on the testing data set from the random forest models was 38 ppb for CO (14 % relative error), 10 ppm for CO2 (2 % relative error), 3.5 ppb for NO2 (29 % relative error), and 3.4 ppb for O3 (15 % relative error), and Pearson r versus the reference monitors exceeded 0.8 for most units. Model performance is explored in detail, including a quantification of model variable importance, accuracy across different concentration ranges, and performance in a range of monitoring contexts including the National Ambient Air Quality Standards (NAAQS) and the US EPA Air Sensors Guidebook recommendations of minimum data quality for personal exposure measurement. A key strength of the RF approach is that

A machine protection beam position monitor system

International Nuclear Information System (INIS)

Medvedko, E.; Smith, S.; Fisher, A.

1998-01-01

Loss of the stored beam in an uncontrolled manner can cause damage to the PEP-II B Factory. We describe here a device which detects large beam position excursions or unexpected beam loss and triggers the beam abort system to extract the stored beam safely. The bad-orbit abort trigger beam position monitor (BOAT BPM) generates a trigger when the beam orbit is far off the center (>20 mm), or rapid beam current loss (dI/dT) is detected. The BOAT BPM averages the input signal over one turn (136 kHz). AM demodulation is used to convert input signals at 476 MHz to baseband voltages. The detected signal goes to a filter section for suppression of the revolution frequency, then on to amplifiers, dividers, and comparators for position and current measurements and triggering. The derived current signal goes to a special filter, designed to perform dI/dT monitoring at fast, medium, and slow current loss rates. The BOAT BPM prototype test results confirm the design concepts. copyright 1998 American Institute of Physics

Cluster processing business level monitor

International Nuclear Information System (INIS)

Muniz, Francisco J.

2017-01-01

This article describes a Cluster Processing Monitor. Several applications with this functionality can be freely found doing a search in the Google machine. However, those applications may offer more features that are needed on the Processing Monitor being proposed. Therefore, making the monitor output evaluation difficult to be understood by the user, at-a-glance. In addition, such monitors may add unnecessary processing cost to the Cluster. For these reasons, a completely new Cluster Processing Monitor module was designed and implemented. In the CDTN, Clusters are broadly used, mainly, in deterministic methods (CFD) and non-deterministic methods (Monte Carlo). (author)

Cluster processing business level monitor

Energy Technology Data Exchange (ETDEWEB)

Muniz, Francisco J., E-mail: muniz@cdtn.br [Centro de Desenvolvimento da Tecnologia Nuclear (CDTN/CNEN-MG), Belo Horizonte, MG (Brazil)

2017-07-01

This article describes a Cluster Processing Monitor. Several applications with this functionality can be freely found doing a search in the Google machine. However, those applications may offer more features that are needed on the Processing Monitor being proposed. Therefore, making the monitor output evaluation difficult to be understood by the user, at-a-glance. In addition, such monitors may add unnecessary processing cost to the Cluster. For these reasons, a completely new Cluster Processing Monitor module was designed and implemented. In the CDTN, Clusters are broadly used, mainly, in deterministic methods (CFD) and non-deterministic methods (Monte Carlo). (author)

CloudMonitor: Profiling Power Usage

OpenAIRE

Smith, James William; Khajeh-Hosseini, Ali; Ward, Jonathan Stuart; Sommerville, Ian

2012-01-01

In Cloud Computing platforms the addition of hardware monitoring devices to gather power usage data can be impractical or uneconomical due to the large number of machines to be metered. CloudMonitor, a monitoring tool that can generate power models for software-based power estimation, can provide insights to the energy costs of deployments without additional hardware. Accurate power usage data leads to the possibility of Cloud providers creating a separate tariff for power and therefore incen...

Environmentally Friendly Machining

CERN Document Server

Dixit, U S; Davim, J Paulo

2012-01-01

Environment-Friendly Machining provides an in-depth overview of environmentally-friendly machining processes, covering numerous different types of machining in order to identify which practice is the most environmentally sustainable. The book discusses three systems at length: machining with minimal cutting fluid, air-cooled machining and dry machining. Also covered is a way to conserve energy during machining processes, along with useful data and detailed descriptions for developing and utilizing the most efficient modern machining tools. Researchers and engineers looking for sustainable machining solutions will find Environment-Friendly Machining to be a useful volume.

Micro-machined resonator oscillator

Science.gov (United States)

Koehler, Dale R.; Sniegowski, Jeffry J.; Bivens, Hugh M.; Wessendorf, Kurt O.

1994-01-01

A micro-miniature resonator-oscillator is disclosed. Due to the miniaturization of the resonator-oscillator, oscillation frequencies of one MHz and higher are utilized. A thickness-mode quartz resonator housed in a micro-machined silicon package and operated as a "telemetered sensor beacon" that is, a digital, self-powered, remote, parameter measuring-transmitter in the FM-band. The resonator design uses trapped energy principles and temperature dependence methodology through crystal orientation control, with operation in the 20-100 MHz range. High volume batch-processing manufacturing is utilized, with package and resonator assembly at the wafer level. Unique design features include squeeze-film damping for robust vibration and shock performance, capacitive coupling through micro-machined diaphragms allowing resonator excitation at the package exterior, circuit integration and extremely small (0.1 in. square) dimensioning. A family of micro-miniature sensor beacons is also disclosed with widespread applications as bio-medical sensors, vehicle status monitors and high-volume animal identification and health sensors. The sensor family allows measurement of temperatures, chemicals, acceleration and pressure. A microphone and clock realization is also available.

LHCb: Machine assisted histogram classification

CERN Multimedia

Somogyi, P; Gaspar, C

2009-01-01

LHCb is one of the four major experiments under completion at the Large Hadron Collider (LHC). Monitoring the quality of the acquired data is important, because it allows the verification of the detector performance. Anomalies, such as missing values or unexpected distributions can be indicators of a malfunctioning detector, resulting in poor data quality. Spotting faulty components can be either done visually using instruments such as the LHCb Histogram Presenter, or by automated tools. In order to assist detector experts in handling the vast monitoring information resulting from the sheer size of the detector, a graph-theoretic based clustering tool, combined with machine learning algorithms is proposed and demonstrated by processing histograms representing 2D event hitmaps. The concept is proven by detecting ion feedback events in the LHCb RICH subdetector.

Single-molecule imaging and manipulation of biomolecular machines and systems.

Science.gov (United States)

Iino, Ryota; Iida, Tatsuya; Nakamura, Akihiko; Saita, Ei-Ichiro; You, Huijuan; Sako, Yasushi

2018-02-01

Biological molecular machines support various activities and behaviors of cells, such as energy production, signal transduction, growth, differentiation, and migration. We provide an overview of single-molecule imaging methods involving both small and large probes used to monitor the dynamic motions of molecular machines in vitro (purified proteins) and in living cells, and single-molecule manipulation methods used to measure the forces, mechanical properties and responses of biomolecules. We also introduce several examples of single-molecule analysis, focusing primarily on motor proteins and signal transduction systems. Single-molecule analysis is a powerful approach to unveil the operational mechanisms both of individual molecular machines and of systems consisting of many molecular machines. Quantitative, high-resolution single-molecule analyses of biomolecular systems at the various hierarchies of life will help to answer our fundamental question: "What is life?" This article is part of a Special Issue entitled "Biophysical Exploration of Dynamical Ordering of Biomolecular Systems" edited by Dr. Koichi Kato. Copyright © 2017 Elsevier B.V. All rights reserved.

Ergonomics in drivers' cabs on open-cast mining machines; Ergonomie bei Fuehrerstaenden auf Tagebaugeraeten

Energy Technology Data Exchange (ETDEWEB)

Vater, L. [Ergonomie/Gefahrstoffe, Vattenfall Europe Mining AG, Senftenberg (Germany)

2004-08-12

Ergonomically designed driver's cabs also contribute directly to the increase in safety at work. In the course of the electrical re-design of the open-cast mining machines new drivers' cabs, which eliminate ergonomic deficits, were used. Other important aspects in addition to the improvements in the environmental factors noise, vibration and dust, are in particular the visibility conditions, visualisation of process data and monitoring as well as operating concepts. Taking into account the different types of machine drivers' cabs with a modified basic design and bearing design are used. Optimisation of the installation of the monitors and the basic structuring of the control panels was carried out. In addition to the increase in the effectiveness of control another aim is to minimise faulty operation by the driver when changing machines frequently. (orig.)

Tolkku - a toolbox for decision support from condition monitoring data

International Nuclear Information System (INIS)

Saarela, Olli; Lehtonen, Mikko; Halme, Jari; Aikala, Antti; Raivio, Kimmo

2012-01-01

This paper describes a software toolbox (a software library) designed for condition monitoring and diagnosis of machines. This toolbox implements both new methods and prior art and is aimed for practical down-to-earth data analysis work. The target is to improve knowledge of the operation and behaviour of machines and processes throughout their entire life-cycles. The toolbox supports different phases of condition based maintenance with tools that extract essential information and automate data processing. The paper discusses principles that have guided toolbox design and the implemented toolbox structure. Case examples are used to illustrate how condition monitoring applications can be built using the toolbox. In the first case study the toolbox is applied to fault detection of industrial centrifuges based on measured electrical current. The second case study outlines an application for centralized monitoring of a fleet of machines that supports organizational learning.

Automated valve fault detection based on acoustic emission parameters and support vector machine

Directory of Open Access Journals (Sweden)

Salah M. Ali

2018-03-01

Full Text Available Reciprocating compressors are one of the most used types of compressors with wide applications in industry. The most common failure in reciprocating compressors is always related to the valves. Therefore, a reliable condition monitoring method is required to avoid the unplanned shutdown in this category of machines. Acoustic emission (AE technique is one of the effective recent methods in the field of valve condition monitoring. However, a major challenge is related to the analysis of AE signal which perhaps only depends on the experience and knowledge of technicians. This paper proposes automated fault detection method using support vector machine (SVM and AE parameters in an attempt to reduce human intervention in the process. Experiments were conducted on a single stage reciprocating air compressor by combining healthy and faulty valve conditions to acquire the AE signals. Valve functioning was identified through AE waveform analysis. SVM faults detection model was subsequently devised and validated based on training and testing samples respectively. The results demonstrated automatic valve fault detection model with accuracy exceeding 98%. It is believed that valve faults can be detected efficiently without human intervention by employing the proposed model for a single stage reciprocating compressor. Keywords: Condition monitoring, Faults detection, Signal analysis, Acoustic emission, Support vector machine

Micro-machined calorimetric biosensors

Science.gov (United States)

Doktycz, Mitchel J.; Britton, Jr., Charles L.; Smith, Stephen F.; Oden, Patrick I.; Bryan, William L.; Moore, James A.; Thundat, Thomas G.; Warmack, Robert J.

2002-01-01

A method and apparatus are provided for detecting and monitoring micro-volumetric enthalpic changes caused by molecular reactions. Micro-machining techniques are used to create very small thermally isolated masses incorporating temperature-sensitive circuitry. The thermally isolated masses are provided with a molecular layer or coating, and the temperature-sensitive circuitry provides an indication when the molecules of the coating are involved in an enthalpic reaction. The thermally isolated masses may be provided singly or in arrays and, in the latter case, the molecular coatings may differ to provide qualitative and/or quantitative assays of a substance.

Survey of Machine Learning Methods for Database Security

Science.gov (United States)

Kamra, Ashish; Ber, Elisa

Application of machine learning techniques to database security is an emerging area of research. In this chapter, we present a survey of various approaches that use machine learning/data mining techniques to enhance the traditional security mechanisms of databases. There are two key database security areas in which these techniques have found applications, namely, detection of SQL Injection attacks and anomaly detection for defending against insider threats. Apart from the research prototypes and tools, various third-party commercial products are also available that provide database activity monitoring solutions by profiling database users and applications. We present a survey of such products. We end the chapter with a primer on mechanisms for responding to database anomalies.

Limerick Nuclear Generating Station vibration monitoring system

International Nuclear Information System (INIS)

Mikulski, R.

1988-01-01

Philadelphia Electric Company utilizes a vibration monitoring computer system at its Limerick Nuclear Generating Station to evaluate machine performance. Performance can be evaluated through instantaneous sampling, online static and transient data. The system functions as an alarm monitor, displaying timely alarm data to the control area. The passage of time since the system's inception has been a learning period. Evaluation through continuous use has led to many enhancements in alarm handling and in the acquisition and display of machine data. Due to the system's sophistication, a routine maintenance program is a necessity. This paper describes the system's diagnostic tools and current utilization. System development and maintenance techniques will also be discussed

Hybrid machining processes perspectives on machining and finishing

CERN Document Server

Gupta, Kapil; Laubscher, R F

2016-01-01

This book describes various hybrid machining and finishing processes. It gives a critical review of the past work based on them as well as the current trends and research directions. For each hybrid machining process presented, the authors list the method of material removal, machining system, process variables and applications. This book provides a deep understanding of the need, application and mechanism of hybrid machining processes.

Human Reliability and the Current Dilemma in Human-Machine Interface Design Strategies

International Nuclear Information System (INIS)

Passalacqua, Roberto; Yamada, Fumiaki

2002-01-01

Since human error dominates the probability of failures of still-existing human-requiring systems (as the Monju reactor), the human-machine interface needs to be improved. Several rationales may lead to the conclusion that 'humans' should limit themselves to monitor the 'machine'. For example, this is the trend in the aviation industry: newest aircrafts are designed to be able to return to a safe state by the use of control systems, which do not need human intervention. Thus, the dilemma whether we really need operators (for example in the nuclear industry) might arise. However, social-technical approaches in recent human error analyses are pointing out the so-called 'organizational errors' and the importance of a human-machine interface harmonization. Typically plant's operators are a 'redundant' safety system with a much lower reliability (than the machine): organizational factors and harmonization requirements suggest designing the human-machine interface in a way that allows improvement of operator's reliability. In addition, taxonomy studies of accident databases have also proved that operators' training should promote processes of decision-making. This is accomplished in the latest trends of PSA technology by introducing the concept of a 'Safety Monitor' that is a computer-based tool that uses a level 1 PSA model of the plant. Operators and maintenance schedulers of the Monju FBR will be able to perform real-time estimations of the plant risk level. The main benefits are risk awareness and improvements in decision-making by operators. Also scheduled maintenance can be approached in a more rational (safe and economic) way. (authors)

A REVIEW OF VIBRATION MACHINE DIAGNOSTICS BY USING ARTIFICIAL INTELLIGENCE METHODS

Directory of Open Access Journals (Sweden)

Grover Zurita

2016-09-01

Full Text Available In the industry, gears and rolling bearings failures are one of the foremost causes of breakdown in rotating machines, reducing availability time of the production and resulting in costly systems downtime. Therefore, there are growing demands for vibration condition based monitoring of gears and bearings, and any method in order to improve the effectiveness, reliability, and accuracy of the bearing faults diagnosis ought to be evaluated. In order to perform machine diagnosis efficiently, researchers have extensively investigated different advanced digital signal processing techniques and artificial intelligence methods to accurately extract fault characteristics from vibration signals. The main goal of this article is to present the state-of-the-art development in vibration analysis for machine diagnosis based on artificial intelligence methods.

Integrated Monitoring System of Production Processes

Directory of Open Access Journals (Sweden)

Oborski Przemysław

2016-12-01

Full Text Available Integrated monitoring system for discrete manufacturing processes is presented in the paper. The multilayer hardware and software reference model was developed. Original research are an answer for industry needs of the integration of information flow in production process. Reference model corresponds with proposed data model based on multilayer data tree allowing to describe orders, products, processes and save monitoring data. Elaborated models were implemented in the integrated monitoring system demonstrator developed in the project. It was built on the base of multiagent technology to assure high flexibility and openness on applying intelligent algorithms for data processing. Currently on the base of achieved experience an application integrated monitoring system for real production system is developed. In the article the main problems of monitoring integration are presented, including specificity of discrete production, data processing and future application of Cyber-Physical-Systems. Development of manufacturing systems is based more and more on taking an advantage of applying intelligent solutions into machine and production process control and monitoring. Connection of technical systems, machine tools and manufacturing processes monitoring with advanced information processing seems to be one of the most important areas of near future development. It will play important role in efficient operation and competitiveness of the whole production system. It is also important area of applying in the future Cyber-Physical-Systems that can radically improve functionally of monitoring systems and reduce the cost of its implementation.

Verifax: Biometric instruments measuring neuromuscular disorders/performance impairments

Science.gov (United States)

Morgenthaler, George W.; Shrairman, Ruth; Landau, Alexander

1998-01-01

VeriFax, founded in 1990 by Dr. Ruth Shrairman and Mr. Alex Landau, began operations with the aim of developing a biometric tool for the verification of signatures from a distance. In the course of developing this VeriFax Autograph technology, two other related applications for the technologies under development at VeriFax became apparent. The first application was in the use of biometric measurements as clinical monitoring tools for physicians investigating neuromuscular diseases (embodied in VeriFax's Neuroskill technology). The second application was to evaluate persons with critical skills (e.g., airline pilots, bus drivers) for physical and mental performance impairments caused by stress, physiological disorders, alcohol, drug abuse, etc. (represented by VeriFax's Impairoscope prototype instrument). This last application raised the possibility of using a space-qualified Impairoscope variant to evaluate astronaut performance with respect to the impacts of stress, fatigue, excessive workload, build-up of toxic chemicals within the space habitat, etc. The three applications of VeriFax's patented technology are accomplished by application-specific modifications of the customized VeriFax software. Strong commercial market potentials exist for all three VeriFax technology applications, and market progress will be presented in more detail below.

Telecommunications for the Deaf: Echoes of the Past--A Glimpse of the Future.

Science.gov (United States)

Jensema, Carl J.

1994-01-01

This article traces developments in telephone and telecommunications technology from Alexander Graham Bell to the present, explaining technical and practical aspects of teletypewriters, fax machines, online information services, electronic mail, video telephones, relay systems, teleconferencing, video telephones, and speech recognition.…

Portable water quality monitoring system

Science.gov (United States)

Nizar, N. B.; Ong, N. R.; Aziz, M. H. A.; Alcain, J. B.; Haimi, W. M. W. N.; Sauli, Z.

2017-09-01

Portable water quality monitoring system was a developed system that tested varied samples of water by using different sensors and provided the specific readings to the user via short message service (SMS) based on the conditions of the water itself. In this water quality monitoring system, the processing part was based on a microcontroller instead of Lead and Copper Rule (LCR) machines to receive the results. By using four main sensors, this system obtained the readings based on the detection of the sensors, respectively. Therefore, users can receive the readings through SMS because there was a connection between Arduino Uno and GSM Module. This system was designed to be portable so that it would be convenient for users to carry it anywhere and everywhere they wanted to since the processor used is smaller in size compared to the LCR machines. It was also developed to ease the user to monitor and control the water quality. However, the ranges of the sensors' detection still a limitation in this study.

Elevating Virtual Machine Introspection for Fine-Grained Process Monitoring: Techniques and Applications

Science.gov (United States)

Srinivasan, Deepa

2013-01-01

Recent rapid malware growth has exposed the limitations of traditional in-host malware-defense systems and motivated the development of secure virtualization-based solutions. By running vulnerable systems as virtual machines (VMs) and moving security software from inside VMs to the outside, the out-of-VM solutions securely isolate the anti-malware…

Real time monitoring of electron processors

International Nuclear Information System (INIS)

Nablo, S.V.; Kneeland, D.R.; McLaughlin, W.L.

1995-01-01

A real time radiation monitor (RTRM) has been developed for monitoring the dose rate (current density) of electron beam processors. The system provides continuous monitoring of processor output, electron beam uniformity, and an independent measure of operating voltage or electron energy. In view of the device's ability to replace labor-intensive dosimetry in verification of machine performance on a real-time basis, its application to providing archival performance data for in-line processing is discussed. (author)

Machine terms dictionary

Energy Technology Data Exchange (ETDEWEB)

NONE

1979-04-15

This book gives descriptions of machine terms which includes machine design, drawing, the method of machine, machine tools, machine materials, automobile, measuring and controlling, electricity, basic of electron, information technology, quality assurance, Auto CAD and FA terms and important formula of mechanical engineering.

1st International Conference on Machine Learning for Cyber Physical Systems and Industry 4.0

CERN Document Server

Beyerer, Jürgen

2016-01-01

The work presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains some selected papers from the international Conference ML4CPS – Machine Learning for Cyber Physical Systems, which was held in Lemgo, October 1-2, 2015. Cyber Physical Systems are characterized by their ability to adapt and to learn: They analyze their environment and, based on observations, they learn patterns, correlations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnosis. Machine Learning is the key technology for these developments.

Development of system decision support tools for behavioral trends monitoring of machinery maintenance in a competitive environment

Science.gov (United States)

Adeyeri, Michael Kanisuru; Mpofu, Khumbulani

2017-06-01

The article is centred on software system development for manufacturing company that produces polyethylene bags using mostly conventional machines in a competitive world where each business enterprise desires to stand tall. This is meant to assist in gaining market shares, taking maintenance and production decisions by the dynamism and flexibilities embedded in the package as customers' demand varies under the duress of meeting the set goals. The production and machine condition monitoring software (PMCMS) is programmed in C# and designed in such a way to support hardware integration, real-time machine conditions monitoring, which is based on condition maintenance approach, maintenance decision suggestions and suitable production strategies as the demand for products keeps changing in a highly competitive environment. PMCMS works with an embedded device which feeds it with data from the various machines being monitored at the workstation, and the data are read at the base station through transmission via a wireless transceiver and stored in a database. A case study was used in the implementation of the developed system, and the results show that it can monitor the machine's health condition effectively by displaying machines' health status, gives repair suggestions to probable faults, decides strategy for both production methods and maintenance, and, thus, can enhance maintenance performance obviously.

Technical diagnostics functioning machines and mechanisms

Science.gov (United States)

Kiselev, M. I.; Pronyakin, V. I.; Tulekbaeva, A. K.

2018-02-01

Article discusses the machines and mechanisms technical state monitoring problem. Approaches for estimating mechanical systems current technical state, defects detection and evaluation of mechanical elements degradation levels are considered. The paper analyzes the traditional methods offered in international and national standards, especially vibrodiagnostics. An advanced phase method is presented which is based on registration the kinematic parameters of the mechanism running cycle. The result of coupling the phase method and mathematical modeling is shown, and simulation comparison with the experimental data is presented.

Some relations between quantum Turing machines and Turing machines

OpenAIRE

Sicard, Andrés; Vélez, Mario

1999-01-01

For quantum Turing machines we present three elements: Its components, its time evolution operator and its local transition function. The components are related with the components of deterministic Turing machines, the time evolution operator is related with the evolution of reversible Turing machines and the local transition function is related with the transition function of probabilistic and reversible Turing machines.

Predictive modeling for corrective maintenance of imaging devices from machine logs.

Science.gov (United States)

Patil, Ravindra B; Patil, Meru A; Ravi, Vidya; Naik, Sarif

2017-07-01

In the cost sensitive healthcare industry, an unplanned downtime of diagnostic and therapy imaging devices can be a burden on the financials of both the hospitals as well as the original equipment manufacturers (OEMs). In the current era of connectivity, it is easier to get these devices connected to a standard monitoring station. Once the system is connected, OEMs can monitor the health of these devices remotely and take corrective actions by providing preventive maintenance thereby avoiding major unplanned downtime. In this article, we present an overall methodology of predicting failure of these devices well before customer experiences it. We use data-driven approach based on machine learning to predict failures in turn resulting in reduced machine downtime, improved customer satisfaction and cost savings for the OEMs. One of the use-case of predicting component failure of PHILIPS iXR system is explained in this article.

Decision Fusion System for Bolted Joint Monitoring

Directory of Open Access Journals (Sweden)

Dong Liang

2015-01-01

Full Text Available Bolted joint is widely used in mechanical and architectural structures, such as machine tools, industrial robots, transport machines, power plants, aviation stiffened plate, bridges, and steel towers. The bolt loosening induced by flight load and environment factor can cause joint failure leading to a disastrous accident. Hence, structural health monitoring is critical for the bolted joint detection. In order to realize a real-time and convenient monitoring and satisfy the requirement of advanced maintenance of the structure, this paper proposes an intelligent bolted joint failure monitoring approach using a developed decision fusion system integrated with Lamb wave propagation based actuator-sensor monitoring method. Firstly, the basic knowledge of decision fusion and classifier selection techniques is briefly introduced. Then, a developed decision fusion system is presented. Finally, three fusion algorithms, which consist of majority voting, Bayesian belief, and multiagent method, are adopted for comparison in a real-world monitoring experiment for the large aviation aluminum plate. Based on the results shown in the experiment, a big potential in real-time application is presented that the method can accurately and rapidly identify the bolt loosening by analyzing the acquired strain signal using proposed decision fusion system.

Design of Online Monitoring and Fault Diagnosis System for Belt Conveyors Based on Wavelet Packet Decomposition and Support Vector Machine

Directory of Open Access Journals (Sweden)

Wei Li

2013-01-01

Full Text Available Belt conveyors are the equipment widely used in coal mines and other manufacturing factories, whose main components are a number of idlers. The faults of belt conveyors can directly influence the daily production. In this paper, a fault diagnosis method combining wavelet packet decomposition (WPD and support vector machine (SVM is proposed for monitoring belt conveyors with the focus on the detection of idler faults. Since the number of the idlers could be large, one acceleration sensor is applied to gather the vibration signals of several idlers in order to reduce the number of sensors. The vibration signals are decomposed with WPD, and the energy of each frequency band is extracted as the feature. Then, the features are employed to train an SVM to realize the detection of idler faults. The proposed fault diagnosis method is firstly tested on a testbed, and then an online monitoring and fault diagnosis system is designed for belt conveyors. An experiment is also carried out on a belt conveyor in service, and it is verified that the proposed system can locate the position of the faulty idlers with a limited number of sensors, which is important for operating belt conveyors in practices.

Constant Cutting Force Control for CNC Machining Using Dynamic Characteristic-Based Fuzzy Controller

Directory of Open Access Journals (Sweden)

Hengli Liu

2015-01-01

Full Text Available This paper presents a dynamic characteristic-based fuzzy adaptive control algorithm (DCbFACA to avoid the influence of cutting force changing rapidly on the machining stability and precision. The cutting force is indirectly obtained in real time by monitoring and extraction of the motorized spindle current, the feed speed is fuzzy adjusted online, and the current was used as a feedback to control cutting force and maintain the machining process stable. Different from the traditional fuzzy control methods using the experience-based control rules, and according to the complex nonlinear characteristics of CNC machining, the power bond graph method is implemented to describe the dynamic characteristics of process, and then the appropriate variation relations are achieved between current and feed speed, and the control rules are optimized and established based on it. The numerical results indicated that DCbFACA can make the CNC machining process more stable and improve the machining precision.

A comparison study of support vector machines and hidden Markov models in machinery condition monitoring

International Nuclear Information System (INIS)

Miao, Qiang; Huang, Hong Zhong; Fan, Xianfeng

2007-01-01

Condition classification is an important step in machinery fault detection, which is a problem of pattern recognition. Currently, there are a lot of techniques in this area and the purpose of this paper is to investigate two popular recognition techniques, namely hidden Markov model and support vector machine. At the beginning, we briefly introduced the procedure of feature extraction and the theoretical background of this paper. The comparison experiment was conducted for gearbox fault detection and the analysis results from this work showed that support vector machine has better classification performance in this area

INFORMATION AND COMMUNICATION

African Journals Online (AJOL)

USER

and constantly used communication models of mobile telephony 100%, electronic-mail, 65% than other forms ... services offered, and providing marketing ... questions. FINDINGS. NO. OF ICT LITERATES. Name of Institutions. No. of. Librarians. On-line. Network. Internet E-mail. Mobile. Telephoning. Fax. Machine. DELSU ...

An Effective Mechanism for Virtual Machine Placement using Aco in IAAS Cloud

Science.gov (United States)

Shenbaga Moorthy, Rajalakshmi; Fareentaj, U.; Divya, T. K.

2017-08-01

Cloud computing provides an effective way to dynamically provide numerous resources to meet customer demands. A major challenging problem for cloud providers is designing efficient mechanisms for optimal virtual machine Placement (OVMP). Such mechanisms enable the cloud providers to effectively utilize their available resources and obtain higher profits. In order to provide appropriate resources to the clients an optimal virtual machine placement algorithm is proposed. Virtual machine placement is NP-Hard problem. Such NP-Hard problem can be solved using heuristic algorithm. In this paper, Ant Colony Optimization based virtual machine placement is proposed. Our proposed system focuses on minimizing the cost spending in each plan for hosting virtual machines in a multiple cloud provider environment and the response time of each cloud provider is monitored periodically, in such a way to minimize delay in providing the resources to the users. The performance of the proposed algorithm is compared with greedy mechanism. The proposed algorithm is simulated in Eclipse IDE. The results clearly show that the proposed algorithm minimizes the cost, response time and also number of migrations.

Simulations of Quantum Turing Machines by Quantum Multi-Stack Machines

OpenAIRE

Qiu, Daowen

2005-01-01

As was well known, in classical computation, Turing machines, circuits, multi-stack machines, and multi-counter machines are equivalent, that is, they can simulate each other in polynomial time. In quantum computation, Yao [11] first proved that for any quantum Turing machines $M$, there exists quantum Boolean circuit $(n,t)$-simulating $M$, where $n$ denotes the length of input strings, and $t$ is the number of move steps before machine stopping. However, the simulations of quantum Turing ma...

The reflection of evolving bearing faults in the stator current's extended park vector approach for induction machines

Science.gov (United States)

Corne, Bram; Vervisch, Bram; Derammelaere, Stijn; Knockaert, Jos; Desmet, Jan

2018-07-01

Stator current analysis has the potential of becoming the most cost-effective condition monitoring technology regarding electric rotating machinery. Since both electrical and mechanical faults are detected by inexpensive and robust current-sensors, measuring current is advantageous on other techniques such as vibration, acoustic or temperature analysis. However, this technology is struggling to breach into the market of condition monitoring as the electrical interpretation of mechanical machine-problems is highly complicated. Recently, the authors built a test-rig which facilitates the emulation of several representative mechanical faults on an 11 kW induction machine with high accuracy and reproducibility. Operating this test-rig, the stator current of the induction machine under test can be analyzed while mechanical faults are emulated. Furthermore, while emulating, the fault-severity can be manipulated adaptively under controllable environmental conditions. This creates the opportunity of examining the relation between the magnitude of the well-known current fault components and the corresponding fault-severity. This paper presents the emulation of evolving bearing faults and their reflection in the Extended Park Vector Approach for the 11 kW induction machine under test. The results confirm the strong relation between the bearing faults and the stator current fault components in both identification and fault-severity. Conclusively, stator current analysis increases reliability in the application as a complete, robust, on-line condition monitoring technology.

Methodics of computing the results of monitoring the exploratory gallery

Directory of Open Access Journals (Sweden)

Krúpa Víazoslav

2000-09-01

Full Text Available At building site of motorway tunnel Višòové-Dubná skala , the priority is given to driving of exploration galley that secures in detail: geologic, engineering geology, hydrogeology and geotechnics research. This research is based on gathering information for a supposed use of the full profile driving machine that would drive the motorway tunnel. From a part of the exploration gallery which is driven by the TBM method, a fulfilling information is gathered about the parameters of the driving process , those are gathered by a computer monitoring system. The system is mounted on a driving machine. This monitoring system is based on the industrial computer PC 104. It records 4 basic values of the driving process: the electromotor performance of the driving machine Voest-Alpine ATB 35HA, the speed of driving advance, the rotation speed of the disintegrating head TBM and the total head pressure. The pressure force is evaluated from the pressure in the hydraulic cylinders of the machine. Out of these values, the strength of rock mass, the angle of inner friction, etc. are mathematically calculated. These values characterize rock mass properties as their changes. To define the effectivity of the driving process, the value of specific energy and the working ability of driving head is used. The article defines the methodics of computing the gathered monitoring information, that is prepared for the driving machine Voest – Alpine ATB 35H at the Institute of Geotechnics SAS. It describes the input forms (protocols of the developed method created by an EXCEL program and shows selected samples of the graphical elaboration of the first monitoring results obtained from exploratory gallery driving process in the Višòové – Dubná skala motorway tunnel.

On-line condition monitoring of nuclear systems via symbolic time series analysis

International Nuclear Information System (INIS)

Rajagopalan, V.; Ray, A.; Garcia, H. E.

2006-01-01

This paper provides a symbolic time series analysis approach to fault diagnostics and condition monitoring. The proposed technique is built upon concepts from wavelet theory, symbolic dynamics and pattern recognition. Various aspects of the methodology such as wavelet selection, choice of alphabet and determination of depth of D-Markov Machine are explained in the paper. The technique is validated with experiments performed in a Machine Condition Monitoring (MCM) test bed at the Idaho National Laboratory. (authors)

Process capability improvement through DMAIC for aluminum alloy wheel machining

Science.gov (United States)

Sharma, G. V. S. S.; Rao, P. Srinivasa; Babu, B. Surendra

2017-07-01

This paper first enlists the generic problems of alloy wheel machining and subsequently details on the process improvement of the identified critical-to-quality machining characteristic of A356 aluminum alloy wheel machining process. The causal factors are traced using the Ishikawa diagram and prioritization of corrective actions is done through process failure modes and effects analysis. Process monitoring charts are employed for improving the process capability index of the process, at the industrial benchmark of four sigma level, which is equal to the value of 1.33. The procedure adopted for improving the process capability levels is the define-measure-analyze-improve-control (DMAIC) approach. By following the DMAIC approach, the C p, C pk and C pm showed signs of improvement from an initial value of 0.66, -0.24 and 0.27, to a final value of 4.19, 3.24 and 1.41, respectively.

Monitoring and control of fine abrasive finishing processes

DEFF Research Database (Denmark)

Lazarev, Ruslan

In engineering, surfaces with specified functional properties are of high demand in various applications. Desired surface finish can be obtained using several methods. Abrasive finishing is one of the most important processes in the manufacturing of mould and dies tools. It is a principal method ...... was segmented using discretization methods. The applied methodology was proposed for implementation as an on-line system and is considered to be a part of the next generation of STRECON NanoRAP machine....... to remove unwanted material, obtain desired geometry, surface quality and surface functional properties. The automation and computerization of finishing processes involves utilisation of robots, specialized machines with several degrees of freedom, sensors and data acquisition systems. The focus...... of this work was to investigate foundations for process monitoring and control methods in application to semi-automated polishing machine based on the industrial robot. The monitoring system was built on NI data acquisition system with two sensors, acoustic emission sensor and accelerometer. Acquired sensory...

Machine tool structures

CERN Document Server

Koenigsberger, F

1970-01-01

Machine Tool Structures, Volume 1 deals with fundamental theories and calculation methods for machine tool structures. Experimental investigations into stiffness are discussed, along with the application of the results to the design of machine tool structures. Topics covered range from static and dynamic stiffness to chatter in metal cutting, stability in machine tools, and deformations of machine tool structures. This volume is divided into three sections and opens with a discussion on stiffness specifications and the effect of stiffness on the behavior of the machine under forced vibration c

Environmental noise forecasting based on support vector machine

Science.gov (United States)

Fu, Yumei; Zan, Xinwu; Chen, Tianyi; Xiang, Shihan

2018-01-01

As an important pollution source, the noise pollution is always the researcher's focus. Especially in recent years, the noise pollution is seriously harmful to the human beings' environment, so the research about the noise pollution is a very hot spot. Some noise monitoring technologies and monitoring systems are applied in the environmental noise test, measurement and evaluation. But, the research about the environmental noise forecasting is weak. In this paper, a real-time environmental noise monitoring system is introduced briefly. This monitoring system is working in Mianyang City, Sichuan Province. It is monitoring and collecting the environmental noise about more than 20 enterprises in this district. Based on the large amount of noise data, the noise forecasting by the Support Vector Machine (SVM) is studied in detail. Compared with the time series forecasting model and the artificial neural network forecasting model, the SVM forecasting model has some advantages such as the smaller data size, the higher precision and stability. The noise forecasting results based on the SVM can provide the important and accuracy reference to the prevention and control of the environmental noise.

Man-machine supervision

International Nuclear Information System (INIS)

Montmain, J.

2005-01-01

Today's complexity of systems where man is involved has led to the development of more and more sophisticated information processing systems where decision making has become more and more difficult. The operator task has moved from operation to supervision and the production tool has become indissociable from its numerical instrumentation and control system. The integration of more and more numerous and sophisticated control indicators in the control room does not necessary fulfill the expectations of the operation team. It is preferable to develop cooperative information systems which are real situation understanding aids. The stake is not the automation of operators' cognitive tasks but the supply of a reasoning help. One of the challenges of interactive information systems is the selection, organisation and dynamical display of information. The efficiency of the whole man-machine system depends on the communication interface efficiency. This article presents the principles and specificities of man-machine supervision systems: 1 - principle: operator's role in control room, operator and automation, monitoring and diagnosis, characteristics of useful models for supervision; 2 - qualitative reasoning: origin, trends, evolutions; 3 - causal reasoning: causality, causal graph representation, causal and diagnostic graph; 4 - multi-points of view reasoning: multi flow modeling method, Sagace method; 5 - approximate reasoning: the symbolic numerical interface, the multi-criteria decision; 6 - example of application: supervision in a spent-fuel reprocessing facility. (J.S.)

Hα Monitors for TJII

International Nuclear Information System (INIS)

Tafalla, D.; Tabares, F.L.; Ortiz, P.; Lopez-Sanchez, A.; Martin Fresno, L.M.; Sanchez Sarabia, E.; Encabo, J.

1998-06-01

A set of monitors for the measurement of Hα radiation (656.3 nm) have been installed in TJ-II stellarator. The detectors are placed directly on the windows of the chamber and they are built using Si photodiodes and interference filters with a compact design that make easy their handling and maintenance. Here we describe the mechanical and electrical design of the monitors, their position in TJ-II and some examples of their working during the first discharges of the machine. (Author) 3 refs

Electricity of machine tool

International Nuclear Information System (INIS)

Gijeon media editorial department

1977-10-01

This book is divided into three parts. The first part deals with electricity machine, which can taints from generator to motor, motor a power source of machine tool, electricity machine for machine tool such as switch in main circuit, automatic machine, a knife switch and pushing button, snap switch, protection device, timer, solenoid, and rectifier. The second part handles wiring diagram. This concludes basic electricity circuit of machine tool, electricity wiring diagram in your machine like milling machine, planer and grinding machine. The third part introduces fault diagnosis of machine, which gives the practical solution according to fault diagnosis and the diagnostic method with voltage and resistance measurement by tester.

Machine medical ethics

CERN Document Server

Pontier, Matthijs

2015-01-01

The essays in this book, written by researchers from both humanities and sciences, describe various theoretical and experimental approaches to adding medical ethics to a machine in medical settings. Medical machines are in close proximity with human beings, and getting closer: with patients who are in vulnerable states of health, who have disabilities of various kinds, with the very young or very old, and with medical professionals. In such contexts, machines are undertaking important medical tasks that require emotional sensitivity, knowledge of medical codes, human dignity, and privacy. As machine technology advances, ethical concerns become more urgent: should medical machines be programmed to follow a code of medical ethics? What theory or theories should constrain medical machine conduct? What design features are required? Should machines share responsibility with humans for the ethical consequences of medical actions? How ought clinical relationships involving machines to be modeled? Is a capacity for e...

Humanizing machines: Anthropomorphization of slot machines increases gambling.

Science.gov (United States)

Riva, Paolo; Sacchi, Simona; Brambilla, Marco

2015-12-01

Do people gamble more on slot machines if they think that they are playing against humanlike minds rather than mathematical algorithms? Research has shown that people have a strong cognitive tendency to imbue humanlike mental states to nonhuman entities (i.e., anthropomorphism). The present research tested whether anthropomorphizing slot machines would increase gambling. Four studies manipulated slot machine anthropomorphization and found that exposing people to an anthropomorphized description of a slot machine increased gambling behavior and reduced gambling outcomes. Such findings emerged using tasks that focused on gambling behavior (Studies 1 to 3) as well as in experimental paradigms that included gambling outcomes (Studies 2 to 4). We found that gambling outcomes decrease because participants primed with the anthropomorphic slot machine gambled more (Study 4). Furthermore, we found that high-arousal positive emotions (e.g., feeling excited) played a role in the effect of anthropomorphism on gambling behavior (Studies 3 and 4). Our research indicates that the psychological process of gambling-machine anthropomorphism can be advantageous for the gaming industry; however, this may come at great expense for gamblers' (and their families') economic resources and psychological well-being. (c) 2015 APA, all rights reserved).

78 FR 21387 - Notice of Issuance of Final Determination Concerning Printer and Fax Machine

Science.gov (United States)

2013-04-10

... network switching and routing functionality among other operations. Accordingly, the country of origin of... Malaysia. The firmware that allows access to the hardware (such as trays, and paper size) and software (ex.... software, at significant cost to the company and over many years plus the programming of an imported local...

LINEAR KERNEL SUPPORT VECTOR MACHINES FOR MODELING PORE-WATER PRESSURE RESPONSES

Directory of Open Access Journals (Sweden)

KHAMARUZAMAN W. YUSOF

2017-08-01

Full Text Available Pore-water pressure responses are vital in many aspects of slope management, design and monitoring. Its measurement however, is difficult, expensive and time consuming. Studies on its predictions are lacking. Support vector machines with linear kernel was used here to predict the responses of pore-water pressure to rainfall. Pore-water pressure response data was collected from slope instrumentation program. Support vector machine meta-parameter calibration and model development was carried out using grid search and k-fold cross validation. The mean square error for the model on scaled test data is 0.0015 and the coefficient of determination is 0.9321. Although pore-water pressure response to rainfall is a complex nonlinear process, the use of linear kernel support vector machine can be employed where high accuracy can be sacrificed for computational ease and time.

Equipment monitoring and diagnosis of their mechanical condition

International Nuclear Information System (INIS)

Morel, J.; Monnier, B.

1994-01-01

The main objectives of reactor monitoring are reviewed and the three monitoring types are described: reception controls and alarms, periodical controls, and specific monitoring. The monitoring process is then presented: information acquisition, dysfunction detection and diagnosis, risk analysis and maintenance action determination. Diagnosis assistance is now automated with expert systems such as DIVA (shaft vibration diagnosis) and DIAPO (primary pump diagnosis). Several application examples at EDF are described: SEXTEN reactor containment tightness monitoring, large and small-size turbo-machine monitoring, reactor inner structure monitoring, loose part detection in the primary circuit. All these informations will be centralized in a general monitoring and diagnosis assistance station. 3 fig

Machine Protection

International Nuclear Information System (INIS)

Schmidt, R

2014-01-01

The protection of accelerator equipment is as old as accelerator technology and was for many years related to high-power equipment. Examples are the protection of powering equipment from overheating (magnets, power converters, high-current cables), of superconducting magnets from damage after a quench and of klystrons. The protection of equipment from beam accidents is more recent. It is related to the increasing beam power of high-power proton accelerators such as ISIS, SNS, ESS and the PSI cyclotron, to the emission of synchrotron light by electron–positron accelerators and FELs, and to the increase of energy stored in the beam (in particular for hadron colliders such as LHC). Designing a machine protection system requires an excellent understanding of accelerator physics and operation to anticipate possible failures that could lead to damage. Machine protection includes beam and equipment monitoring, a system to safely stop beam operation (e.g. dumping the beam or stopping the beam at low energy) and an interlock system providing the glue between these systems. The most recent accelerator, the LHC, will operate with about 3 × 10 14 protons per beam, corresponding to an energy stored in each beam of 360 MJ. This energy can cause massive damage to accelerator equipment in case of uncontrolled beam loss, and a single accident damaging vital parts of the accelerator could interrupt operation for years. This article provides an overview of the requirements for protection of accelerator equipment and introduces the various protection systems. Examples are mainly from LHC, SNS and ESS

An Automatic Decision-Making Mechanism for Virtual Machine Live Migration in Private Clouds

Directory of Open Access Journals (Sweden)

Ming-Tsung Kao

2014-01-01

Full Text Available Due to the increasing number of computer hosts deployed in an enterprise, automatic management of electronic applications is inevitable. To provide diverse services, there will be increases in procurement, maintenance, and electricity costs. Virtualization technology is getting popular in cloud computing environment, which enables the efficient use of computing resources and reduces the operating cost. In this paper, we present an automatic mechanism to consolidate virtual servers and shut down the idle physical machines during the off-peak hours, while activating more machines at peak times. Through the monitoring of system resources, heavy system loads can be evenly distributed over physical machines to achieve load balancing. By integrating the feature of load balancing with virtual machine live migration, we successfully develop an automatic private cloud management system. Experimental results demonstrate that, during the off-peak hours, we can save power consumption of about 69 W by consolidating the idle virtual servers. And the load balancing implementation has shown that two machines with 80% and 40% CPU loads can be uniformly balanced to 60% each. And, through the use of preallocated virtual machine images, the proposed mechanism can be easily applied to a large amount of physical machines.

A Novel Vaping Machine Dedicated to Fully Controlling the Generation of E-Cigarette Emissions

OpenAIRE

Soulet, Sébastien; Pairaud, Charly; Lalo, Hélène

2017-01-01

The accurate study of aerosol composition and nicotine release by electronic cigarettes is a major issue. In order to fully and correctly characterize aerosol, emission generation has to be completely mastered. This study describes an original vaping machine named Universal System for Analysis of Vaping (U-SAV), dedicated to vaping product study, enabling the control and real-time monitoring of applied flow rate and power. Repeatability and stability of the machine are demonstrated on flow ra...

Code-expanded radio access protocol for machine-to-machine communications

DEFF Research Database (Denmark)

Thomsen, Henning; Kiilerich Pratas, Nuno; Stefanovic, Cedomir

2013-01-01

The random access methods used for support of machine-to-machine, also referred to as Machine-Type Communications, in current cellular standards are derivatives of traditional framed slotted ALOHA and therefore do not support high user loads efficiently. We propose an approach that is motivated b...... subframes and orthogonal preambles, the amount of available contention resources is drastically increased, enabling the massive support of Machine-Type Communication users that is beyond the reach of current systems.......The random access methods used for support of machine-to-machine, also referred to as Machine-Type Communications, in current cellular standards are derivatives of traditional framed slotted ALOHA and therefore do not support high user loads efficiently. We propose an approach that is motivated...... by the random access method employed in LTE, which significantly increases the amount of contention resources without increasing the system resources, such as contention subframes and preambles. This is accomplished by a logical, rather than physical, extension of the access method in which the available system...

Multi-category micro-milling tool wear monitoring with continuous hidden Markov models

Science.gov (United States)

Zhu, Kunpeng; Wong, Yoke San; Hong, Geok Soon

2009-02-01

In-process monitoring of tool conditions is important in micro-machining due to the high precision requirement and high tool wear rate. Tool condition monitoring in micro-machining poses new challenges compared to conventional machining. In this paper, a multi-category classification approach is proposed for tool flank wear state identification in micro-milling. Continuous Hidden Markov models (HMMs) are adapted for modeling of the tool wear process in micro-milling, and estimation of the tool wear state given the cutting force features. For a noise-robust approach, the HMM outputs are connected via a medium filter to minimize the tool state before entry into the next state due to high noise level. A detailed study on the selection of HMM structures for tool condition monitoring (TCM) is presented. Case studies on the tool state estimation in the micro-milling of pure copper and steel demonstrate the effectiveness and potential of these methods.

Machine Control System of Steady State Superconducting Tokamak-1

Energy Technology Data Exchange (ETDEWEB)

Masand, Harish, E-mail: harish@ipr.res.in; Kumar, Aveg; Bhandarkar, M.; Mahajan, K.; Gulati, H.; Dhongde, J.; Patel, K.; Chudasma, H.; Pradhan, S.

2016-11-15

Highlights: • Central Control System. • SST-1. • Machine Control System. - Abstract: Central Control System (CCS) of the Steady State Superconducting Tokamak-1 (SST-1) controls and monitors around 25 plant and experiment subsystems of SST-1 located remotely from the Central-Control room. Machine Control System (MCS) is a supervisory system that sits on the top of the CCS hierarchy and implements the CCS state diagram. MCS ensures the software interlock between the SST-1 subsystems with the CCS, any subsystem communication failure or its local error does not prohibit the execution of the MCS and in-turn the CCS operation. MCS also periodically monitors the subsystem’s status and their vital process parameters throughout the campaign. It also provides the platform for the Central Control operator to visualize and exchange remotely the operational and experimental configuration parameters with the sub-systems. MCS remains operational 24 × 7 from the commencement to the termination of the SST-1 campaign. The developed MCS has performed robustly and flawlessly during all the last campaigns of SST-1 carried out so far. This paper will describe various aspects of the development of MCS.

Condition Assessment and End-of-Life Prediction System for Electric Machines and Their Loads

Science.gov (United States)

Parlos, Alexander G.; Toliyat, Hamid A.

2005-01-01

An end-of-life prediction system developed for electric machines and their loads could be used in integrated vehicle health monitoring at NASA and in other government agencies. This system will provide on-line, real-time condition assessment and end-of-life prediction of electric machines (e.g., motors, generators) and/or their loads of mechanically coupled machinery (e.g., pumps, fans, compressors, turbines, conveyor belts, magnetic levitation trains, and others). In long-duration space flight, the ability to predict the lifetime of machinery could spell the difference between mission success or failure. Therefore, the system described here may be of inestimable value to the U.S. space program. The system will provide continuous monitoring for on-line condition assessment and end-of-life prediction as opposed to the current off-line diagnoses.

Development of a wearable measurement and control unit for personal customizing machine-supported exercise.

Science.gov (United States)

Wang, Zhihui; Tamura, Naoki; Kiryu, Tohru

2005-01-01

Wearable technology has been used in various health-related fields to develop advanced monitoring solutions. However, the monitoring function alone cannot meet all the requirements of personal customizing machine-supported exercise that have biosignal-based controls. In this paper, we propose a new wearable unit design equipped with measurement and control functions to support the personal customization process. The wearable unit can measure the heart rate and electromyogram signals during exercise and output workload control commands to the exercise machines. We then applied a prototype of the wearable unit to an Internet-based cycle ergometer system. The wearable unit was examined using twelve young people to check its feasibility. The results verified that the unit could successfully adapt to the control of the workload and was effective for continuously supporting gradual changes in physical activities.

Simple machines

CERN Document Server

Graybill, George

2007-01-01

Just how simple are simple machines? With our ready-to-use resource, they are simple to teach and easy to learn! Chocked full of information and activities, we begin with a look at force, motion and work, and examples of simple machines in daily life are given. With this background, we move on to different kinds of simple machines including: Levers, Inclined Planes, Wedges, Screws, Pulleys, and Wheels and Axles. An exploration of some compound machines follows, such as the can opener. Our resource is a real time-saver as all the reading passages, student activities are provided. Presented in s

High-pressure microscopy for tracking dynamic properties of molecular machines.

Science.gov (United States)

Nishiyama, Masayoshi

2017-12-01

High-pressure microscopy is one of the powerful techniques to visualize the effects of hydrostatic pressures on research targets. It could be used for monitoring the pressure-induced changes in the structure and function of molecular machines in vitro and in vivo. This review focuses on the dynamic properties of the assemblies and machines, analyzed by means of high-pressure microscopy measurement. We developed a high-pressure microscope that is optimized both for the best image formation and for the stability to hydrostatic pressure up to 150 MPa. Application of pressure could change polymerization and depolymerization processes of the microtubule cytoskeleton, suggesting a modulation of the intermolecular interaction between tubulin molecules. A novel motility assay demonstrated that high hydrostatic pressure induces counterclockwise (CCW) to clockwise (CW) reversals of the Escherichia coli flagellar motor. The present techniques could be extended to study how molecular machines in complicated systems respond to mechanical stimuli. Copyright © 2017 Elsevier B.V. All rights reserved.

Machine performance assessment and enhancement for a hexapod machine

Energy Technology Data Exchange (ETDEWEB)

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

1998-03-19

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

Estimation of past sea-level variations based on ground-penetrating radar mapping of beach-ridges - preliminary results from Feddet, Faxe Bay, eastern Denmark

DEFF Research Database (Denmark)

Hede, Mikkel Ulfeldt; Nielsen, Lars; Clemmensen, Lars B

2011-01-01

Estimates of past sea-level variations based on different methods and techniques have been presented in a range of studies, including interpretation of beach ridge characteristics. In Denmark, Holocene beach ridge plains have been formed during the last c. 7700 years, a period characterised by both...... isostatic uplift and changes in eustatic sea-level, and therefore represent an archive of past relative sea-level variations. Here, we present preliminary results from investigation of beach ridges from Feddet, a small peninsula located in Faxe Bay (Baltic Sea) in the eastern part of Denmark. Feddet has...... been chosen as a key-locality in this project, as it is located relatively close to the current 0-isobase of isostatic rebound. GPR reflection data have been acquired with shielded 250 MHz Sensors & software antennae along a number of profile lines across beach ridge and swale structures of the Feddet...

Superconducting rotating machines

International Nuclear Information System (INIS)

Smith, J.L. Jr.; Kirtley, J.L. Jr.; Thullen, P.

1975-01-01

The opportunities and limitations of the applications of superconductors in rotating electric machines are given. The relevant properties of superconductors and the fundamental requirements for rotating electric machines are discussed. The current state-of-the-art of superconducting machines is reviewed. Key problems, future developments and the long range potential of superconducting machines are assessed

In-situ acoustic signature monitoring in additive manufacturing processes

Science.gov (United States)

Koester, Lucas W.; Taheri, Hossein; Bigelow, Timothy A.; Bond, Leonard J.; Faierson, Eric J.

2018-04-01

Additive manufacturing is a rapidly maturing process for the production of complex metallic, ceramic, polymeric, and composite components. The processes used are numerous, and with the complex geometries involved this can make quality control and standardization of the process and inspection difficult. Acoustic emission measurements have been used previously to monitor a number of processes including machining and welding. The authors have identified acoustic signature measurement as a potential means of monitoring metal additive manufacturing processes using process noise characteristics and those discrete acoustic emission events characteristic of defect growth, including cracks and delamination. Results of acoustic monitoring for a metal additive manufacturing process (directed energy deposition) are reported. The work investigated correlations between acoustic emissions and process noise with variations in machine state and deposition parameters, and provided proof of concept data that such correlations do exist.

Sustainable machining

CERN Document Server

2017-01-01

This book provides an overview on current sustainable machining. Its chapters cover the concept in economic, social and environmental dimensions. It provides the reader with proper ways to handle several pollutants produced during the machining process. The book is useful on both undergraduate and postgraduate levels and it is of interest to all those working with manufacturing and machining technology.

Machine learning application in online lending risk prediction

OpenAIRE

Yu, Xiaojiao

2017-01-01

Online leading has disrupted the traditional consumer banking sector with more effective loan processing. Risk prediction and monitoring is critical for the success of the business model. Traditional credit score models fall short in applying big data technology in building risk model. In this manuscript, data with various format and size were collected from public website, third-parties and assembled with client's loan application information data. Ensemble machine learning models, random fo...

Balancing Machine Work, Comfort Work, and Sentimental Work

DEFF Research Database (Denmark)

Pedersen, Maria Ie; Hansen, Magnus; Hertzum, Morten

2011-01-01

and attention. We investigate ambulance care in three of Denmark’s five healthcare regions, which staff ambulances with emergency medical technicians, paramedics, and physicians. Using the concept of illness trajectory we analyse how the ambulance crews balance machine work, which involves continuously...... monitoring the equipment, comfort work, which is actions taken to relieve the pain or discomfort of the patient, and sentimental work, which is care for the patient’s physical and mental well-being, often verbal in nature. The analysis shows that comfort and sentimental work often takes priority over machine...... work, but also that this has negative consequences. Equipment for use in ambulances should aim at supporting the ambulance crews in competently and dynamically balancing the different types of work and should, consequently, avoid binding the crew’s attention for unbroken periods of time....

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.

Asynchronized synchronous machines

CERN Document Server

Botvinnik, M M

1964-01-01

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

On the Interaction between a Tunnel Boring Machine and the Surrounding Soil

NARCIS (Netherlands)

Festa, D.

2015-01-01

The thesis investigates the mechanical equilibrium of a Tunnel Boring Machine (TBM) driving in soft soil. The interaction between the TBM-shield and the soil is also investigated. The analysis is based on monitoring data gathered during the construction of the Hubertus tunnel in The Hague,

Machine Shop Lathes.

Science.gov (United States)

Dunn, James

This guide, the second in a series of five machine shop curriculum manuals, was designed for use in machine shop courses in Oklahoma. The purpose of the manual is to equip students with basic knowledge and skills that will enable them to enter the machine trade at the machine-operator level. The curriculum is designed so that it can be used in…

Condition monitoring of rotormachinery in nuclear power plants

International Nuclear Information System (INIS)

Suedmersen, U.; Runkel, J.; Vortriede, A.; Reimche, W.; Stegemann, D.

1996-01-01

Due to safety and economical reasons diagnostic and monitoring systems are of growing interest in nuclear power plants and other complex industrial productions. Key components of NPP's are rotating machineries of the primary and secondary loops like PWR main coolant pumps, BWR recirculation pumps, turbines, fresh water pumps and feed water pumps. Diagnostic systems are requested which detect, diagnose and localize faulty operation conditions at an early stage in order to prevent severe failures and to enable predictive and condition oriented maintenance. The knowledge of characteristical machine signatures and their time dependent behaviour are the basis of efficient condition monitoring of rotating machines. The performance of reference measurements are of importance for fault detection during operation by trend settings. The comparison with thresholds given by norms and standards is only a small section of available possibilities. Therefore, for each machinery own thresholds should be determined using statistical time values, spectra comparison, cepstrum analysis and correlation analysis for source localization corresponding to certain machine operation conditions. (author). 14 refs, 15 figs

Condition monitoring of rotormachinery in nuclear power plants

Energy Technology Data Exchange (ETDEWEB)

Suedmersen, U; Runkel, J; Vortriede, A; Reimche, W; Stegemann, D [University of Hannover, Hannover (Germany). Inst. of Nuclear Engineering and Nondestructive Testing

1997-12-31

Due to safety and economical reasons diagnostic and monitoring systems are of growing interest in nuclear power plants and other complex industrial productions. Key components of NPP`s are rotating machineries of the primary and secondary loops like PWR main coolant pumps, BWR recirculation pumps, turbines, fresh water pumps and feed water pumps. Diagnostic systems are requested which detect, diagnose and localize faulty operation conditions at an early stage in order to prevent severe failures and to enable predictive and condition oriented maintenance. The knowledge of characteristical machine signatures and their time dependent behaviour are the basis of efficient condition monitoring of rotating machines. The performance of reference measurements are of importance for fault detection during operation by trend settings. The comparison with thresholds given by norms and standards is only a small section of available possibilities. Therefore, for each machinery own thresholds should be determined using statistical time values, spectra comparison, cepstrum analysis and correlation analysis for source localization corresponding to certain machine operation conditions. (author). 14 refs, 15 figs.

An integrated condition-monitoring method for a milling process using reduced decomposition features

International Nuclear Information System (INIS)

Liu, Jie; Wu, Bo; Hu, Youmin; Wang, Yan

2017-01-01

Complex and non-stationary cutting chatter affects productivity and quality in the milling process. Developing an effective condition-monitoring approach is critical to accurately identify cutting chatter. In this paper, an integrated condition-monitoring method is proposed, where reduced features are used to efficiently recognize and classify machine states in the milling process. In the proposed method, vibration signals are decomposed into multiple modes with variational mode decomposition, and Shannon power spectral entropy is calculated to extract features from the decomposed signals. Principal component analysis is adopted to reduce feature size and computational cost. With the extracted feature information, the probabilistic neural network model is used to recognize and classify the machine states, including stable, transition, and chatter states. Experimental studies are conducted, and results show that the proposed method can effectively detect cutting chatter during different milling operation conditions. This monitoring method is also efficient enough to satisfy fast machine state recognition and classification. (paper)

Machining of Machine Elements Made of Polymer Composite Materials

Science.gov (United States)

Baurova, N. I.; Makarov, K. A.

2017-12-01

The machining of the machine elements that are made of polymer composite materials (PCMs) or are repaired using them is considered. Turning, milling, and drilling are shown to be most widely used among all methods of cutting PCMs. Cutting conditions for the machining of PCMs are presented. The factors that most strongly affect the roughness parameters and the accuracy of cutting PCMs are considered.

Fluorescence excitation-emission matrix spectroscopy for degradation monitoring of machinery lubricants

Science.gov (United States)

Sosnovski, Oleg; Suresh, Pooja; Dudelzak, Alexander E.; Green, Benjamin

2018-02-01

Lubrication oil is a vital component of heavy rotating machinery defining the machine's health, operational safety and effectiveness. Recently, the focus has been on developing sensors that provide real-time/online monitoring of oil condition/lubricity. Industrial practices and standards for assessing oil condition involve various analytical methods. Most these techniques are unsuitable for online applications. The paper presents the results of studying degradation of antioxidant additives in machinery lubricants using Fluorescence Excitation-Emission Matrix (EEM) Spectroscopy and Machine Learning techniques. EEM Spectroscopy is capable of rapid and even standoff sensing; it is potentially applicable to real-time online monitoring.

Integrating multisensor satellite data merging and image reconstruction in support of machine learning for better water quality management.

Science.gov (United States)

Chang, Ni-Bin; Bai, Kaixu; Chen, Chi-Farn

2017-10-01

Monitoring water quality changes in lakes, reservoirs, estuaries, and coastal waters is critical in response to the needs for sustainable development. This study develops a remote sensing-based multiscale modeling system by integrating multi-sensor satellite data merging and image reconstruction algorithms in support of feature extraction with machine learning leading to automate continuous water quality monitoring in environmentally sensitive regions. This new Earth observation platform, termed "cross-mission data merging and image reconstruction with machine learning" (CDMIM), is capable of merging multiple satellite imageries to provide daily water quality monitoring through a series of image processing, enhancement, reconstruction, and data mining/machine learning techniques. Two existing key algorithms, including Spectral Information Adaptation and Synthesis Scheme (SIASS) and SMart Information Reconstruction (SMIR), are highlighted to support feature extraction and content-based mapping. Whereas SIASS can support various data merging efforts to merge images collected from cross-mission satellite sensors, SMIR can overcome data gaps by reconstructing the information of value-missing pixels due to impacts such as cloud obstruction. Practical implementation of CDMIM was assessed by predicting the water quality over seasons in terms of the concentrations of nutrients and chlorophyll-a, as well as water clarity in Lake Nicaragua, providing synergistic efforts to better monitor the aquatic environment and offer insightful lake watershed management strategies. Copyright © 2017 Elsevier Ltd. All rights reserved.

Development of Wireless Smart Sensor for Structure and Machine Monitoring

Directory of Open Access Journals (Sweden)

Ismoyo Haryanto

2013-07-01

Full Text Available Vibration based condition monitoring is a method used for determining the condition of a system. The condition of mechanical or a structural system can be determined from the vibration. The vibration that is produced by the system indicates the condition of a system and possibly used to calculate the lifetime of a system or even used to take early action before fatal failure occurred. This paper explains how the wireless smart sensor can be used to identify the health condition of a system by monitoring the vibration parameters. The wireless smart sensor would continously  senses the vibration parameters of the system in a real-time systems and then data will be transmitted wirelessly  to a base station which is a host PC used for digital signal processing, from there the vibration will be plotted as a graph which used to analyzed the condition of the system. Finally, several tested performed to the real system to verify the accuracy of a smart sensor and the method of condition based monitoring.

Dynamic Modeling and Analysis of the Large-Scale Rotary Machine with Multi-Supporting

Directory of Open Access Journals (Sweden)

Xuejun Li

2011-01-01

Full Text Available The large-scale rotary machine with multi-supporting, such as rotary kiln and rope laying machine, is the key equipment in the architectural, chemistry, and agriculture industries. The body, rollers, wheels, and bearings constitute a chain multibody system. Axis line deflection is a vital parameter to determine mechanics state of rotary machine, thus body axial vibration needs to be studied for dynamic monitoring and adjusting of rotary machine. By using the Riccati transfer matrix method, the body system of rotary machine is divided into many subsystems composed of three elements, namely, rigid disk, elastic shaft, and linear spring. Multiple wheel-bearing structures are simplified as springs. The transfer matrices of the body system and overall transfer equation are developed, as well as the response overall motion equation. Taken a rotary kiln as an instance, natural frequencies, modal shape, and response vibration with certain exciting axis line deflection are obtained by numerical computing. The body vibration modal curves illustrate the cause of dynamical errors in the common axis line measurement methods. The displacement response can be used for further measurement dynamical error analysis and compensation. The response overall motion equation could be applied to predict the body motion under abnormal mechanics condition, and provide theory guidance for machine failure diagnosis.

Centralized operation and monitoring system for nuclear power plants

International Nuclear Information System (INIS)

Kudo, Mitsuru; Sato, Hideyuki; Murata, Fumio

1988-01-01

According to the prospect of long term energy demand, in 2000, the nuclear power generation facilities in Japan are expected to take 15.9% of the total energy demand. From this fact, it is an important subject to supply nuclear power more stably, and in the field of instrumentation and control, many researches and developments and the incessant effort of improvement have been continued. In the central operation and monitoring system which is the center of the stable operation of nuclear power plants, the man-machine technology aiding operators by electronic and computer application technologies has been positively developed and applied. It is considered that hereafter, for the purpose of rationally heightening the operation reliability of the plants, the high quality man-machine system freely using the most advanced technologies such as high reliability digital technology, optical information transmission, knowledge engineering and so on is developed and applied. The technical trend of operation and monitoring system, the concept of heightening operation and monitoring capability, the upgrading of operation and monitoring system, and the latest operation, monitoring and control systems for nuclear power plants and waste treatment facilities are described. (K.I.)

Improving Machining Accuracy of CNC Machines with Innovative Design Methods

Science.gov (United States)

Yemelyanov, N. V.; Yemelyanova, I. V.; Zubenko, V. L.

2018-03-01

The article considers achieving the machining accuracy of CNC machines by applying innovative methods in modelling and design of machining systems, drives and machine processes. The topological method of analysis involves visualizing the system as matrices of block graphs with a varying degree of detail between the upper and lower hierarchy levels. This approach combines the advantages of graph theory and the efficiency of decomposition methods, it also has visual clarity, which is inherent in both topological models and structural matrices, as well as the resiliency of linear algebra as part of the matrix-based research. The focus of the study is on the design of automated machine workstations, systems, machines and units, which can be broken into interrelated parts and presented as algebraic, topological and set-theoretical models. Every model can be transformed into a model of another type, and, as a result, can be interpreted as a system of linear and non-linear equations which solutions determine the system parameters. This paper analyses the dynamic parameters of the 1716PF4 machine at the stages of design and exploitation. Having researched the impact of the system dynamics on the component quality, the authors have developed a range of practical recommendations which have enabled one to reduce considerably the amplitude of relative motion, exclude some resonance zones within the spindle speed range of 0...6000 min-1 and improve machining accuracy.

Machinability of nickel based alloys using electrical discharge machining process

Science.gov (United States)

Khan, M. Adam; Gokul, A. K.; Bharani Dharan, M. P.; Jeevakarthikeyan, R. V. S.; Uthayakumar, M.; Thirumalai Kumaran, S.; Duraiselvam, M.

2018-04-01

The high temperature materials such as nickel based alloys and austenitic steel are frequently used for manufacturing critical aero engine turbine components. Literature on conventional and unconventional machining of steel materials is abundant over the past three decades. However the machining studies on superalloy is still a challenging task due to its inherent property and quality. Thus this material is difficult to be cut in conventional processes. Study on unconventional machining process for nickel alloys is focused in this proposed research. Inconel718 and Monel 400 are the two different candidate materials used for electrical discharge machining (EDM) process. Investigation is to prepare a blind hole using copper electrode of 6mm diameter. Electrical parameters are varied to produce plasma spark for diffusion process and machining time is made constant to calculate the experimental results of both the material. Influence of process parameters on tool wear mechanism and material removal are considered from the proposed experimental design. While machining the tool has prone to discharge more materials due to production of high energy plasma spark and eddy current effect. The surface morphology of the machined surface were observed with high resolution FE SEM. Fused electrode found to be a spherical structure over the machined surface as clumps. Surface roughness were also measured with surface profile using profilometer. It is confirmed that there is no deviation and precise roundness of drilling is maintained.

The achievements of the Z-machine; Les exploits de la Z-machine

Energy Technology Data Exchange (ETDEWEB)

Larousserie, D

2008-03-15

The ZR-machine that represents the latest generation of Z-pinch machines has recently begun preliminary testing before its full commissioning in Albuquerque (Usa). During its test the machine has well operated with electrical currents whose intensities of 26 million Ampere are already 2 times as high as the intensity of the operating current of the previous Z-machine. In 2006 the Z-machine reached temperatures of 2 billions Kelvin while 100 million Kelvin would be sufficient to ignite thermonuclear fusion. In fact the concept of Z-pinch machines was imagined in the fifties but the technological breakthrough that has allowed this recent success and the reborn of Z-machine, was the replacement of gas by an array of metal wires through which the electrical current flows and vaporizes it creating an imploding plasma. It is not well understood why Z-pinch machines generate far more radiation than theoretically expected. (A.C.)

Characterization and monitoring of selected rhizobial strains ...

African Journals Online (AJOL)

SERVER

2007-06-18

Jun 18, 2007 ... Fax: +66-44-216345. fixing symbiosis with bacteria known as rhizobia. ... Rhizobial strains were cultured on Yeast-Malt extract agar contain- ing bromthymol blue ... Colony form-ing was observed every day as well as the ...

Quantum machine learning.

Science.gov (United States)

Biamonte, Jacob; Wittek, Peter; Pancotti, Nicola; Rebentrost, Patrick; Wiebe, Nathan; Lloyd, Seth

2017-09-13

Fuelled by increasing computer power and algorithmic advances, machine learning techniques have become powerful tools for finding patterns in data. Quantum systems produce atypical patterns that classical systems are thought not to produce efficiently, so it is reasonable to postulate that quantum computers may outperform classical computers on machine learning tasks. The field of quantum machine learning explores how to devise and implement quantum software that could enable machine learning that is faster than that of classical computers. Recent work has produced quantum algorithms that could act as the building blocks of machine learning programs, but the hardware and software challenges are still considerable.

Machine protection systems

CERN Document Server

Macpherson, A L

2010-01-01

A summary of the Machine Protection System of the LHC is given, with particular attention given to the outstanding issues to be addressed, rather than the successes of the machine protection system from the 2009 run. In particular, the issues of Safe Machine Parameter system, collimation and beam cleaning, the beam dump system and abort gap cleaning, injection and dump protection, and the overall machine protection program for the upcoming run are summarised.

Multi-dimensional Aggregation for DNS Monitoring

OpenAIRE

Dolberg , Lautaro; François , Jérôme; Engel , Thomas

2013-01-01

International audience; DNS is an essential service in the Internet as it allows to translate human language based domain names into IP addresses. DNS traffic reflects the user activities and behaviors. It is thus a helpful source of information in the context of large scale network monitoring. In particular, passive DNS monitoring garnered much interest for the security perspectives by highlighting the services the machines want to access. In this paper, we propose a new method for assessing...

Real time power consumption monitoring for energy efficiency analysis in micro EDM milling

DEFF Research Database (Denmark)

Tristo, Gianluca; Bissacco, Giuliano; Lebar, Andrej

2015-01-01

for manufacturing sustainability. Electrical discharge machining (EDM) is considered an attractive solution for the manufacturing of microcomponents. In this paper, a low cost and modular data acquisition system, based on open-hardware and open-source software, for online energy consumption monitoring, is presented......Sustainability has become a major concern in many countries and is leading to strict regulations regarding the impact of products and services during their manufacturing, use, and disposal. Power consumption monitoring in manufacturing companies can lead to a reduction of machine tools energy...

A comparison of machine learning and Bayesian modelling for molecular serotyping.

Science.gov (United States)

Newton, Richard; Wernisch, Lorenz

2017-08-11

Streptococcus pneumoniae is a human pathogen that is a major cause of infant mortality. Identifying the pneumococcal serotype is an important step in monitoring the impact of vaccines used to protect against disease. Genomic microarrays provide an effective method for molecular serotyping. Previously we developed an empirical Bayesian model for the classification of serotypes from a molecular serotyping array. With only few samples available, a model driven approach was the only option. In the meanwhile, several thousand samples have been made available to us, providing an opportunity to investigate serotype classification by machine learning methods, which could complement the Bayesian model. We compare the performance of the original Bayesian model with two machine learning algorithms: Gradient Boosting Machines and Random Forests. We present our results as an example of a generic strategy whereby a preliminary probabilistic model is complemented or replaced by a machine learning classifier once enough data are available. Despite the availability of thousands of serotyping arrays, a problem encountered when applying machine learning methods is the lack of training data containing mixtures of serotypes; due to the large number of possible combinations. Most of the available training data comprises samples with only a single serotype. To overcome the lack of training data we implemented an iterative analysis, creating artificial training data of serotype mixtures by combining raw data from single serotype arrays. With the enhanced training set the machine learning algorithms out perform the original Bayesian model. However, for serotypes currently lacking sufficient training data the best performing implementation was a combination of the results of the Bayesian Model and the Gradient Boosting Machine. As well as being an effective method for classifying biological data, machine learning can also be used as an efficient method for revealing subtle biological

PC based vibration monitoring system

International Nuclear Information System (INIS)

Jain, Sanjay K.; Roy, D.A.; Pithawa, C.K.; Patil, R.K.

2004-01-01

Health of large rotating machinery gets reflected in the vibration signature of the rotor and supporting structures and proper recording of these signals and their analysis can give a clear picture of the health of the machine. Using these data and their trending, it is possible to predict an impending trouble in the machine so that preventive action can be taken in time and catastrophic failure can be avoided. Continuous monitoring and analysis can give quick warning and enable operator to take preventive measures. Reactor Control Division, BARC is developing a PC based Vibration monitoring system for turbo generator machinery. The System can acquire 20 vibration signals at a rate of 5000 samples per second and also 15 process signals at a rate of 100 samples/ sec. The software for vibration monitoring system includes acquisition modules, analysis modules and Graphical User Interface module. The acquisition module involves initialization, setting of required parameters and acquiring the data from PC-based data acquisition cards. The acquired raw vibration data is then stored for analysis using various software packages. The display and analysis of acquired data is done in LabVIEW 7.0 where the data is displayed in time as well as frequency domain along with the RMS value of the signal. (author)

Preliminary Test of Upgraded Conventional Milling Machine into PC Based CNC Milling Machine

International Nuclear Information System (INIS)

Abdul Hafid

2008-01-01

CNC (Computerized Numerical Control) milling machine yields a challenge to make an innovation in the field of machining. With an action job is machining quality equivalent to CNC milling machine, the conventional milling machine ability was improved to be based on PC CNC milling machine. Mechanically and instrumentally change. As a control replacing was conducted by servo drive and proximity were used. Computer programme was constructed to give instruction into milling machine. The program structure of consists GUI model and ladder diagram. Program was put on programming systems called RTX software. The result of up-grade is computer programming and CNC instruction job. The result was beginning step and it will be continued in next time. With upgrading ability milling machine becomes user can be done safe and optimal from accident risk. By improving performance of milling machine, the user will be more working optimal and safely against accident risk. (author)

Performance Monitoring Of A Computer Numerically Controlled (CNC) Lathe Using Pattern Recognition Techniques

Science.gov (United States)

Daneshmend, L. K.; Pak, H. A.

1984-02-01

On-line monitoring of the cutting process in CNC lathe is desirable to ensure unattended fault-free operation in an automated environment. The state of the cutting tool is one of the most important parameters which characterises the cutting process. Direct monitoring of the cutting tool or workpiece is not feasible during machining. However several variables related to the state of the tool can be measured on-line. A novel monitoring technique is presented which uses cutting torque as the variable for on-line monitoring. A classifier is designed on the basis of the empirical relationship between cutting torque and flank wear. The empirical model required by the on-line classifier is established during an automated training cycle using machine vision for off-line direct inspection of the tool.

Antibiotic Residues in Milk from Three Popular Kenyan Milk Vending Machines.

Science.gov (United States)

Kosgey, Amos; Shitandi, Anakalo; Marion, Jason W

2018-05-01

Milk vending machines (MVMs) are growing in popularity in Kenya and worldwide. Milk vending machines dispense varying quantities of locally sourced, pasteurized milk. The Kenya Dairy Board has a regulatory framework, but surveillance is weak because of several factors. Milk vending machines' milk is not routinely screened for antibiotics, thereby increasing potential for antibiotic misuse. To investigate, a total of 80 milk samples from four commercial providers ( N = 25), street vendors ( N = 21), and three MVMs ( N = 34) were collected and screened in Eldoret, Kenya. Antibiotic residue surveillance occurred during December 2016 and January 2017 using Idexx SNAP ® tests for tetracyclines, sulfamethazine, beta-lactams, and gentamicin. Overall, 24% of MVM samples and 24% of street vendor samples were presumably positive for at least one antibiotic. No commercial samples were positive. Research into cost-effective screening methods and increased monitoring by food safety agencies are needed to uphold hazard analysis and critical control point for improving antibiotic stewardship throughout the Kenyan private dairy industry.

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

International Nuclear Information System (INIS)

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

2016-01-01

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

National Machine Guarding Program: Part 1. Machine safeguarding practices in small metal fabrication businesses.

Science.gov (United States)

Parker, David L; Yamin, Samuel C; Brosseau, Lisa M; Xi, Min; Gordon, Robert; Most, Ivan G; Stanley, Rodney

2015-11-01

Metal fabrication workers experience high rates of traumatic occupational injuries. Machine operators in particular face high risks, often stemming from the absence or improper use of machine safeguarding or the failure to implement lockout procedures. The National Machine Guarding Program (NMGP) was a translational research initiative implemented in conjunction with two workers' compensation insures. Insurance safety consultants trained in machine guarding used standardized checklists to conduct a baseline inspection of machine-related hazards in 221 business. Safeguards at the point of operation were missing or inadequate on 33% of machines. Safeguards for other mechanical hazards were missing on 28% of machines. Older machines were both widely used and less likely than newer machines to be properly guarded. Lockout/tagout procedures were posted at only 9% of machine workstations. The NMGP demonstrates a need for improvement in many aspects of machine safety and lockout in small metal fabrication businesses. © 2015 The Authors. American Journal of Industrial Medicine published by Wiley Periodicals, Inc.

Condition Monitoring of Machinery in Non-Stationary Operations : Proceedings of the Second International Conference "Condition Monitoring of Machinery in Non-Stationnary Operations"

CERN Document Server

Bartelmus, Walter; Chaari, Fakher; Zimroz, Radoslaw; Haddar, Mohamed

2012-01-01

Condition monitoring of machines in non-stationary operations (CMMNO) can be seen as the major challenge for research in the field of machinery diagnostics. Condition monitoring of machines in non-stationary operations is the title of the presented book and the title of the Conference held in Hammamet - Tunisia March 26 – 28, 2012. It is the second conference under this title, first took place in Wroclaw - Poland , March 2011. The subject CMMNO comes directly from industry needs and observation of real objects. Most monitored and diagnosed objects used in industry works in non-stationary operations condition. The non-stationary operations come from fulfillment of machinery tasks, for which they are designed for. All machinery used in different kind of mines, transport systems, vehicles like: cars, buses etc, helicopters, ships and battleships and so on work in non-stationary operations. The papers included in the book are shaped by the organizing board of the conference and authors of the papers. The papers...

Non-conventional electrical machines

CERN Document Server

Rezzoug, Abderrezak

2013-01-01

The developments of electrical machines are due to the convergence of material progress, improved calculation tools, and new feeding sources. Among the many recent machines, the authors have chosen, in this first book, to relate the progress in slow speed machines, high speed machines, and superconducting machines. The first part of the book is dedicated to materials and an overview of magnetism, mechanic, and heat transfer.

Technology News; Distance Education Project: Extending Extension Programming via Telecommunications Technology; [and] Fax for Library Services.

Science.gov (United States)

Coyle, Larry; Spitzer, Kathleen L.

1992-01-01

Three articles discuss (1) the numbers of microcomputers installed in elementary and secondary schools; (2) a distance education project in the Minnesota Extension Service that used a satellite delivery system and integrated it with a computer information network; and (3) the use of facsimile machines for library services. (LRW)

Design of a cardiac monitor in terms of parameters of QRS complex.

Science.gov (United States)

Chen, Zhen-cheng; Ni, Li-li; Su, Ke-ping; Wang, Hong-yan; Jiang, Da-zong

2002-08-01

Objective. To design a portable cardiac monitor system based on the available ordinary ECG machine and works on the basis of QRS parameters. Method. The 80196 single chip microcomputer was used as the central microprocessor and real time electrocardiac signal was collected and analyzed [correction of analysized] in the system. Result. Apart from the performance of an ordinary monitor, this machine possesses also the following functions: arrhythmia analysis, HRV analysis, alarm, freeze, and record of automatic papering. Convenient in carrying, the system is powered by AC or DC sources. Stability, low power and low cost are emphasized in the hardware design; and modularization method is applied in software design. Conclusion. Popular in usage and low cost made the portable monitor system suitable for use under simple conditions.

Micro Electro Discharge Machining of Electrically Nonconductive Ceramics

International Nuclear Information System (INIS)

Schubert, A.; Zeidler, H.; Hackert, M.; Wolf, N.

2011-01-01

EDM is a known process for machining of hard and brittle materials. Due to its noncontact and nearly forceless behaviour, it has been introduced into micro manufacturing and through constant development it is now an important means for producing high-precision micro geometries. One restriction of EDM is its limitation to electrically conducting materials.Today many applications, especially in the biomedical field, make use of the benefits of ceramic materials, such as high strength, very low wear and biocompatibility. Common ceramic materials such as Zirconium dioxide are, due to their hardness in the sintered state, difficult to machine with conventional cutting techniques. A demand for the introduction of EDM to these materials could so far not be satisfied because of their nonconductive nature.At the Chemnitz University of Technology and the Fraunhofer IWU, investigations in the applicability of micro-EDM for the machining of nonconductive ceramics are being conducted. Tests are undertaken using micro-EDM drilling with Tungsten carbide tool electrodes and ZrO 2 ceramic workpieces. A starting layer, in literature often referred to as 'assisting electrode' is used to set up a closed electric circuit to start the EDM process. Combining carbon hydride based dielectric and a specially designed low-frequency vibration setup to excite the workpiece, the process environment can be held within parameters to allow for a constant EDM process even after the starting layer is machined. In the experiments a cylindrical 120 μm diameter Tungsten carbide tool electrode and Y 2 O 3 - and MgO- stabilized ZrO 2 worpieces are used. The current and voltage signals of the discharges within the different stages of the process (machining of the starting layer, machining of the base material, transition stage) are recorded and their characteristics compared to discharges in metallic material. Additionally, the electrode feed is monitored. The influences of the process parameters are

Beam-machine Interaction at the CERN LHC

CERN Document Server

Boccone, V; Brugger, M; Calviani, M; Cerutti, F; Esposito, L S; Ferrari, A; Lechner, A; Mereghetti, A; Nowak, E; Shetty, N V; Skordis, E; Versaci, R; Vlachoudis, V

2014-01-01

The radiation field generated by a high energy and intensity accelerator is of concern in terms of element functionality threat, component damage, electronics reliability, and material activation, but also provides signatures that allow actual operating conditions to be monitored. The shower initiated by an energetic hadron involves many different physical processes, down to slow neutron interactions and fragment de-excitation, which need to be accurately described for design purposes and to interpret operation events. The experience with the transport and interaction Monte Carlo code FLUKA at the Large Hadron Collider (LHC), operating at CERN with 4 TeV proton beams (and equivalent magnetic rigidity Pb beams) and approaching nominal luminosity and energy, is presented. Design, operation and upgrade challenges are reviewed in the context of beam-machine interaction account and relevant benchmarking examples based on radiation monitor measurements are shown.

The Impact of Modern Information and Communication Technologies on Social Movements

Science.gov (United States)

Konieczny, Piotr

2012-01-01

Information and communication technologies (ICTs) have empowered non-state social actors, notably, social movements. They were quick to seize ICTs in the past (printing presses, television, fax machines), which was a major factor in their successes. Mass email campaigns, blogs, their audio- and video- variants (the podcasts and the videocasts),…

A Wavelet Bicoherence-Based Quadratic Nonlinearity Feature for Translational Axis Condition Monitoring

Directory of Open Access Journals (Sweden)

Yong Li

2014-01-01

Full Text Available The translational axis is one of the most important subsystems in modern machine tools, as its degradation may result in the loss of the product qualification and lower the control precision. Condition-based maintenance (CBM has been considered as one of the advanced maintenance schemes to achieve effective, reliable and cost-effective operation of machine systems, however, current vibration-based maintenance schemes cannot be employed directly in the translational axis system, due to its complex structure and the inefficiency of commonly used condition monitoring features. In this paper, a wavelet bicoherence-based quadratic nonlinearity feature is proposed for translational axis condition monitoring by using the torque signature of the drive servomotor. Firstly, the quadratic nonlinearity of the servomotor torque signature is discussed, and then, a biphase randomization wavelet bicoherence is introduced for its quadratic nonlinear detection. On this basis, a quadratic nonlinearity feature is proposed for condition monitoring of the translational axis. The properties of the proposed quadratic nonlinearity feature are investigated by simulations. Subsequently, this feature is applied to the real-world servomotor torque data collected from the X-axis on a high precision vertical machining centre. All the results show that the performance of the proposed feature is much better than that of original condition monitoring features.

Electrical machines & drives

CERN Document Server

Hammond, P

1985-01-01

Containing approximately 200 problems (100 worked), the text covers a wide range of topics concerning electrical machines, placing particular emphasis upon electrical-machine drive applications. The theory is concisely reviewed and focuses on features common to all machine types. The problems are arranged in order of increasing levels of complexity and discussions of the solutions are included where appropriate to illustrate the engineering implications. This second edition includes an important new chapter on mathematical and computer simulation of machine systems and revised discussions o

DNA-based machines.

Science.gov (United States)

Wang, Fuan; Willner, Bilha; Willner, Itamar

2014-01-01

The base sequence in nucleic acids encodes substantial structural and functional information into the biopolymer. This encoded information provides the basis for the tailoring and assembly of DNA machines. A DNA machine is defined as a molecular device that exhibits the following fundamental features. (1) It performs a fuel-driven mechanical process that mimics macroscopic machines. (2) The mechanical process requires an energy input, "fuel." (3) The mechanical operation is accompanied by an energy consumption process that leads to "waste products." (4) The cyclic operation of the DNA devices, involves the use of "fuel" and "anti-fuel" ingredients. A variety of DNA-based machines are described, including the construction of "tweezers," "walkers," "robots," "cranes," "transporters," "springs," "gears," and interlocked cyclic DNA structures acting as reconfigurable catenanes, rotaxanes, and rotors. Different "fuels", such as nucleic acid strands, pH (H⁺/OH⁻), metal ions, and light, are used to trigger the mechanical functions of the DNA devices. The operation of the devices in solution and on surfaces is described, and a variety of optical, electrical, and photoelectrochemical methods to follow the operations of the DNA machines are presented. We further address the possible applications of DNA machines and the future perspectives of molecular DNA devices. These include the application of DNA machines as functional structures for the construction of logic gates and computing, for the programmed organization of metallic nanoparticle structures and the control of plasmonic properties, and for controlling chemical transformations by DNA machines. We further discuss the future applications of DNA machines for intracellular sensing, controlling intracellular metabolic pathways, and the use of the functional nanostructures for drug delivery and medical applications.

Cyber Situation Awareness through Instance-Based Learning: Modeling the Security Analyst in a Cyber-Attack Scenario

Science.gov (United States)

2012-01-01

Chocolate Avenue Hershey PA 17033 Tel: 717-533-8845 Fax: 717-533-8661 E-mail: cust@igi-global.com Web site: http://www.igi-global.com Copyright © 2011...program and obtain control on the machine (event 21st out of 25). During the course of this simple scenario, a security analyst is able to observe...G. A. (1989). Recognition-primed deci- sions. In Rouse, W. B. (Ed.), Advances in man- machine system research (Vol. 5, pp. 47–92). Greenwich, CT

Machine translation

Energy Technology Data Exchange (ETDEWEB)

Nagao, M

1982-04-01

Each language has its own structure. In translating one language into another one, language attributes and grammatical interpretation must be defined in an unambiguous form. In order to parse a sentence, it is necessary to recognize its structure. A so-called context-free grammar can help in this respect for machine translation and machine-aided translation. Problems to be solved in studying machine translation are taken up in the paper, which discusses subjects for semantics and for syntactic analysis and translation software. 14 references.

WWER NPPs fuel handling machine control system

International Nuclear Information System (INIS)

Mini, G.; Rossi, G.; Barabino, M.; Casalini, M.

2001-01-01

of 1090 Workstations (APMS - Advanced Plant Monitoring System, or Tenore NT) has been successfully used to interface the operator with the control of the fuel handling machine. (authors)

VVER NPPs fuel handling machine control system

International Nuclear Information System (INIS)

Mini, G.; Rossi, G.; Barabino, M.; Casalini, M.

2002-01-01

In order to increase the safety level of the fuel handling machine on WWER NPPs, Ansaldo Nucleare was asked to design and supply a new Control System. Two Fuel Handling Machine (FHM) Control System units have been already supplied for Temelin NPP and others supply are in process for the Atommash company, which has in charge the supply of FHMs for NPPs located in Russia, Ukraine and China.The computer-based system takes into account all the operational safety interlocks so that it is able to avoid incorrect and dangerous manoeuvres in the case of operator error. Control system design criteria, hardware and software architecture, and quality assurance control, are in accordance with the most recent international requirements and standards, and in particular for electromagnetic disturbance immunity demands and seismic compatibility. The hardware architecture of the control system is based on ABB INFI 90 system. The microprocessor-based ABB INFI 90 system incorporates and improves upon many of the time proven control capabilities of Bailey Network 90, validated over 14,000 installations world-wide.The control system complies all the former designed sensors and devices of the machine and markedly the angular position measurement sensors named 'selsyn' of Russian design. Nevertheless it is fully compatible with all the most recent sensors and devices currently available on the market (for ex. Multiturn absolute encoders).All control logic were developed using standard INFI 90 Engineering Work Station, interconnecting blocks extracted from an extensive SAMA library by using a graphical approach (CAD) and allowing and easier intelligibility, more flexibility and updated and coherent documentation. The data acquisition system and the Man Machine Interface are implemented by ABB in co-operation with Ansaldo. The flexible and powerful software structure of 1090 Work-stations (APMS - Advanced Plant Monitoring System, or Tenore NT) has been successfully used to interface the

Beam Loss Monitoring for Run 2 of the LHC

CERN Document Server

Kalliokoski, Matti; Dehning, Bernd; Domingues Sousa, Fernando; Effinger, Ewald; Emery, Jonathan; Grishin, Viatcheslav; Holzer, Eva Barbara; Jackson, Stephen; Kolad, Blazej; Nebot Del Busto, Eduardo; Picha, Ondrej; Roderick, Chris; Sapinski, Mariusz; Sobieszek, Marcin; Zamantzas, Christos

2015-01-01

The Beam Loss Monitoring (BLM) system of the LHC consists of over 3600 ionization chambers. The main task of the system is to prevent the superconducting magnets from quenching and protect the machine components from damage, as a result of critical beam losses. The BLM system therefore requests a beam abort when the measured dose in the chambers exceeds a threshold value. During Long Shutdown 1 (LS1) a series of modifications were made to the system. Based on the experience from Run 1 and from improved simulation models, all the threshold settings were revised, and modified where required. This was done to improve the machine safety at 7 TeV, and to reduce beam abort requests when neither a magnet quench or damage to machine components is expected. In addition to the updates of the threshold values, about 800 monitors were relocated. This improves the response to unforeseen beam losses in the millisecond time scale due to micron size dust particles present in the vacuum chamber. This contribution will discuss...

Induction machine handbook

CERN Document Server

Boldea, Ion

2002-01-01

Often called the workhorse of industry, the advent of power electronics and advances in digital control are transforming the induction motor into the racehorse of industrial motion control. Now, the classic texts on induction machines are nearly three decades old, while more recent books on electric motors lack the necessary depth and detail on induction machines.The Induction Machine Handbook fills industry's long-standing need for a comprehensive treatise embracing the many intricate facets of induction machine analysis and design. Moving gradually from simple to complex and from standard to

Chaotic Boltzmann machines

Science.gov (United States)

Suzuki, Hideyuki; Imura, Jun-ichi; Horio, Yoshihiko; Aihara, Kazuyuki

2013-01-01

The chaotic Boltzmann machine proposed in this paper is a chaotic pseudo-billiard system that works as a Boltzmann machine. Chaotic Boltzmann machines are shown numerically to have computing abilities comparable to conventional (stochastic) Boltzmann machines. Since no randomness is required, efficient hardware implementation is expected. Moreover, the ferromagnetic phase transition of the Ising model is shown to be characterised by the largest Lyapunov exponent of the proposed system. In general, a method to relate probabilistic models to nonlinear dynamics by derandomising Gibbs sampling is presented. PMID:23558425

Rotating electrical machines

CERN Document Server

Le Doeuff, René

2013-01-01

In this book a general matrix-based approach to modeling electrical machines is promulgated. The model uses instantaneous quantities for key variables and enables the user to easily take into account associations between rotating machines and static converters (such as in variable speed drives).   General equations of electromechanical energy conversion are established early in the treatment of the topic and then applied to synchronous, induction and DC machines. The primary characteristics of these machines are established for steady state behavior as well as for variable speed scenarios. I

Correlation between use time of machine and decline curve for emerging enterprise information systems

Science.gov (United States)

Chang, Yao-Chung; Lai, Chin-Feng; Chuang, Chi-Cheng; Hou, Cheng-Yu

2018-04-01

With the progress of science and technology, more and more machines are adpot to help human life better and more convenient. When the machines have been used for a longer period of time so that the machine components are getting old, the amount of power comsumption will increase and easily cause the machine to overheat. This also causes a waste of invisible resources. If the Internet of Everything (IoE) technologies are able to be applied into the enterprise information systems for monitoring the machines use time, it can not only make energy can be effectively used, but aslo create a safer living environment. To solve the above problem, the correlation predict model is established to collect the data of power consumption converted into power eigenvalues. This study takes the power eigenvalue as the independent variable and use time as the dependent variable in order to establish the decline curve. Ultimately, the scoring and estimation modules are employed to seek the best power eigenvalue as the independent variable. To predict use time, the correlation is discussed between the use time and the decline curve to improve the entire behavioural analysis of the facilitate recognition of the use time of machines.

Using Expert Systems in Evaluation of the State of High Voltage Machine Insulation Systems

Directory of Open Access Journals (Sweden)

K. Záliš

2000-01-01

Full Text Available Expert systems are used for evaluating the actual state and future behavior of insulating systems of high voltage electrical machines and equipment. Several rule-based expert systems have been developed in cooperation with top diagnostic workplaces in the Czech Republic for this purpose. The IZOLEX expert system evaluates diagnostic measurement data from commonly used offline diagnostic methods for the diagnostic of high voltage insulation of rotating machines, non-rotating machines and insulating oils. The CVEX expert system evaluates the discharge activity on high voltage electrical machines and equipment by means of an off-line measurement. The CVEXON expert system is for evaluating the discharge activity by on-line measurement, and the ALTONEX expert system is the expert system for on-line monitoring of rotating machines. These developed expert systems are also used for educating students (in bachelor, master and post-graduate studies and in courses which are organized for practicing engineers and technicians and for specialists in the electrical power engineering branch. A complex project has recently been set up to evaluate the measurement of partial discharges. Two parallel expert systems for evaluating partial dischatge activity on high voltage electrical machines will work at the same time in this complex evaluating system.

Your Sewing Machine.

Science.gov (United States)

Peacock, Marion E.

The programed instruction manual is designed to aid the student in learning the parts, uses, and operation of the sewing machine. Drawings of sewing machine parts are presented, and space is provided for the student's written responses. Following an introductory section identifying sewing machine parts, the manual deals with each part and its…

Commonality and Variability Analysis for Xenon Family of Separation Virtual Machine Monitors (CVAX)

Science.gov (United States)

2017-07-18

the sponsor (e.g., military, intelligence community, other government, commercial, medical ) and upon the type of system (e.g., application in the...loads. • Machine memory. Xen’s terminology for hardware memory present on a chip. • Misuse case. Abuse case. Attacker-product interaction that the...on connections between domains. • Physical memory. Xen’s terminology , short for pseudo-physical memory. Physical memory is the Xen term for the

Investigation of the Machining Stability of a Milling Machine with Hybrid Guideway Systems

Directory of Open Access Journals (Sweden)

Jui-Pin Hung

2016-03-01

Full Text Available This study was aimed to investigate the machining stability of a horizontal milling machine with hybrid guideway systems by finite element method. To this purpose, we first created finite element model of the milling machine with the introduction of the contact stiffness defined at the sliding and rolling interfaces, respectively. Also, the motorized built-in spindle model was created and implemented in the whole machine model. Results of finite element simulations reveal that linear guides with different preloads greatly affect the dynamic responses and machining stability of the horizontal milling machine. The critical cutting depth predicted at the vibration mode associated with the machine tool structure is about 10 mm and 25 mm in the X and Y direction, respectively, while the cutting depth predicted at the vibration mode associated with the spindle structure is about 6.0 mm. Also, the machining stability can be increased when the preload of linear roller guides of the feeding mechanism is changed from lower to higher amount.

Introduction to AC machine design

CERN Document Server

Lipo, Thomas A

2018-01-01

AC electrical machine design is a key skill set for developing competitive electric motors and generators for applications in industry, aerospace, and defense. This book presents a thorough treatment of AC machine design, starting from basic electromagnetic principles and continuing through the various design aspects of an induction machine. Introduction to AC Machine Design includes one chapter each on the design of permanent magnet machines, synchronous machines, and thermal design. It also offers a basic treatment of the use of finite elements to compute the magnetic field within a machine without interfering with the initial comprehension of the core subject matter. Based on the author's notes, as well as after years of classroom instruction, Introduction to AC Machine Design: * Brings to light more advanced principles of machine design--not just the basic principles of AC and DC machine behavior * Introduces electrical machine design to neophytes while also being a resource for experienced designers * ...

Precision machining commercialization

International Nuclear Information System (INIS)

1978-01-01

To accelerate precision machining development so as to realize more of the potential savings within the next few years of known Department of Defense (DOD) part procurement, the Air Force Materials Laboratory (AFML) is sponsoring the Precision Machining Commercialization Project (PMC). PMC is part of the Tri-Service Precision Machine Tool Program of the DOD Manufacturing Technology Five-Year Plan. The technical resources supporting PMC are provided under sponsorship of the Department of Energy (DOE). The goal of PMC is to minimize precision machining development time and cost risk for interested vendors. PMC will do this by making available the high precision machining technology as developed in two DOE contractor facilities, the Lawrence Livermore Laboratory of the University of California and the Union Carbide Corporation, Nuclear Division, Y-12 Plant, at Oak Ridge, Tennessee

Comparison of four machine learning methods for object-oriented change detection in high-resolution satellite imagery

Science.gov (United States)

Bai, Ting; Sun, Kaimin; Deng, Shiquan; Chen, Yan

2018-03-01

High resolution image change detection is one of the key technologies of remote sensing application, which is of great significance for resource survey, environmental monitoring, fine agriculture, military mapping and battlefield environment detection. In this paper, for high-resolution satellite imagery, Random Forest (RF), Support Vector Machine (SVM), Deep belief network (DBN), and Adaboost models were established to verify the possibility of different machine learning applications in change detection. In order to compare detection accuracy of four machine learning Method, we applied these four machine learning methods for two high-resolution images. The results shows that SVM has higher overall accuracy at small samples compared to RF, Adaboost, and DBN for binary and from-to change detection. With the increase in the number of samples, RF has higher overall accuracy compared to Adaboost, SVM and DBN.

Are there intelligent Turing machines?

OpenAIRE

Bátfai, Norbert

2015-01-01

This paper introduces a new computing model based on the cooperation among Turing machines called orchestrated machines. Like universal Turing machines, orchestrated machines are also designed to simulate Turing machines but they can also modify the original operation of the included Turing machines to create a new layer of some kind of collective behavior. Using this new model we can define some interested notions related to cooperation ability of Turing machines such as the intelligence quo...

Machine health prognostics using the Bayesian-inference-based probabilistic indication and high-order particle filtering framework

Science.gov (United States)

Yu, Jianbo

2015-12-01

Prognostics is much efficient to achieve zero-downtime performance, maximum productivity and proactive maintenance of machines. Prognostics intends to assess and predict the time evolution of machine health degradation so that machine failures can be predicted and prevented. A novel prognostics system is developed based on the data-model-fusion scheme using the Bayesian inference-based self-organizing map (SOM) and an integration of logistic regression (LR) and high-order particle filtering (HOPF). In this prognostics system, a baseline SOM is constructed to model the data distribution space of healthy machine under an assumption that predictable fault patterns are not available. Bayesian inference-based probability (BIP) derived from the baseline SOM is developed as a quantification indication of machine health degradation. BIP is capable of offering failure probability for the monitored machine, which has intuitionist explanation related to health degradation state. Based on those historic BIPs, the constructed LR and its modeling noise constitute a high-order Markov process (HOMP) to describe machine health propagation. HOPF is used to solve the HOMP estimation to predict the evolution of the machine health in the form of a probability density function (PDF). An on-line model update scheme is developed to adapt the Markov process changes to machine health dynamics quickly. The experimental results on a bearing test-bed illustrate the potential applications of the proposed system as an effective and simple tool for machine health prognostics.

Coldness production and heat revalorization: particular machines; Production de froid et revalorisation de la chaleur: machines particulieres

Energy Technology Data Exchange (ETDEWEB)

Feidt, M. [Universite Henri Poincare - Nancy-1, 54 - Nancy (France)

2003-10-01

The machines presented in this article are not the common reverse cycle machines. They use some systems based on different physical principles which have some consequences on the analysis of cycles: 1 - permanent gas machines (thermal separators, pulse gas tube, thermal-acoustic machines); 2 - phase change machines (mechanical vapor compression machines, absorption machines, ejection machines, adsorption machines); 3 - thermoelectric machines (thermoelectric effects, thermodynamic model of a thermoelectric machine). (J.S.)

An intelligent man-machine system for future nuclear power plants

International Nuclear Information System (INIS)

Takizawa, Yoji; Hattori, Yoshiaki; Itoh, Juichiro; Fukumoto, Akira

1994-01-01

The objective of the development of an intelligent man-machine system for future nuclear power plants is enhancement of operational reliability by applying recent advances in cognitive science, artificial intelligence, and computer technologies. To realize this objective, the intelligent man-machine system, aiming to support a knowledge-based decision making process in an operator's supervisory plant control tasks, consists of three main functions, i.e., a cognitive model-based advisor, a robust automatic sequence controller, and an ecological interface. These three functions have been integrated into a console-type nuclear power plant monitoring and control system as a validation test bed. The validation tests in which experienced operator crews participated were carried out in 1991 and 1992. The test results show the usefulness of the support functions and the validity of the system design approach

Methods of In-Process On-Machine Auto-Inspection of Dimensional Error and Auto-Compensation of Tool Wear for Precision Turning

Directory of Open Access Journals (Sweden)

Shih-Ming Wang

2016-04-01

Full Text Available The purpose of this study is mainly to develop an information and communication technology (ICT-based intelligent dimension inspection and tool wear compensation method for precision tuning. With the use of vibration signal processing/characteristics analysis technology combined with ICT, statistical analysis, and diagnosis algorithms, the method can be used to proceed with an on-line dimension inspection and on-machine tool wear auto-compensation for the turning process. Meanwhile, the method can also monitor critical tool life to identify the appropriate time for cutter replacement to reduce machining costs and improve the production efficiency of the turning process. Compared to the traditional ways, the method offers the advantages of requiring less manpower, and having better production efficiency, high tool life, fewer scrap parts, and low costs for inspection instruments. Algorithms and diagnosis threshold values for the detection, cutter wear compensation, and cutter life monitoring were developed. In addition, a bilateral communication module utilizing FANUC Open CNC (computer numerical control Application Programming Interface (API Spec was developed for the on-line extraction of instant NC (numerical control codes for monitoring and transmit commands to CNC controllers for cutter wear compensation. With use of local area networks (LAN to deliver the detection and correction information, the proposed method was able to remotely control the on-machine monitoring process and upload the machining and inspection data to a remote central platform for further production optimization. The verification experiments were conducted on a turning production line. The results showed that the system provided 93% correction for size inspection and 100% correction for cutter wear compensation.

Fault diagnosis of automobile hydraulic brake system using statistical features and support vector machines

Science.gov (United States)

Jegadeeshwaran, R.; Sugumaran, V.

2015-02-01

Hydraulic brakes in automobiles are important components for the safety of passengers; therefore, the brakes are a good subject for condition monitoring. The condition of the brake components can be monitored by using the vibration characteristics. On-line condition monitoring by using machine learning approach is proposed in this paper as a possible solution to such problems. The vibration signals for both good as well as faulty conditions of brakes were acquired from a hydraulic brake test setup with the help of a piezoelectric transducer and a data acquisition system. Descriptive statistical features were extracted from the acquired vibration signals and the feature selection was carried out using the C4.5 decision tree algorithm. There is no specific method to find the right number of features required for classification for a given problem. Hence an extensive study is needed to find the optimum number of features. The effect of the number of features was also studied, by using the decision tree as well as Support Vector Machines (SVM). The selected features were classified using the C-SVM and Nu-SVM with different kernel functions. The results are discussed and the conclusion of the study is presented.

NSLS Control Monitor and its upgrade

International Nuclear Information System (INIS)

Ramamoorthy, S.; Smith, J.D.

1993-01-01

The NSLS Control Monitor is a real-time operating system designed for the microprocessor subsystems that control the machine hardware in the NSLS facility. Its major functions are to control the hardware in response to the commands from the host computers, monitor hardware status and report errors to the alarm handler. The software originally developed for the Multibus micros has been upgraded to run on the VME-based systems. The upgraded monitor provides ethernet communication with the new system and serial link with the old system. The dual link is the key feature for a smooth and nondisruptive transition at all levels of the control system. This paper describes the functions of the various modules of the monitor and future plans

National machine guarding program: Part 1. Machine safeguarding practices in small metal fabrication businesses

Science.gov (United States)

Yamin, Samuel C.; Brosseau, Lisa M.; Xi, Min; Gordon, Robert; Most, Ivan G.; Stanley, Rodney

2015-01-01

Background Metal fabrication workers experience high rates of traumatic occupational injuries. Machine operators in particular face high risks, often stemming from the absence or improper use of machine safeguarding or the failure to implement lockout procedures. Methods The National Machine Guarding Program (NMGP) was a translational research initiative implemented in conjunction with two workers' compensation insures. Insurance safety consultants trained in machine guarding used standardized checklists to conduct a baseline inspection of machine‐related hazards in 221 business. Results Safeguards at the point of operation were missing or inadequate on 33% of machines. Safeguards for other mechanical hazards were missing on 28% of machines. Older machines were both widely used and less likely than newer machines to be properly guarded. Lockout/tagout procedures were posted at only 9% of machine workstations. Conclusions The NMGP demonstrates a need for improvement in many aspects of machine safety and lockout in small metal fabrication businesses. Am. J. Ind. Med. 58:1174–1183, 2015. © 2015 The Authors. American Journal of Industrial Medicine published by Wiley Periodicals, Inc. PMID:26332060

‘Machinic Trajectories’: Appropriated Devices as Post-Digital Drawing Machines

Directory of Open Access Journals (Sweden)

Andres Wanner

2014-12-01

Full Text Available This article presents a series of works called Machinic Trajectories, consisting of domestic devices appropriated as mechanical drawing machines. These are contextualized within the post-digital discourse, which integrates messy analog conditions into the digital realm. The role of eliciting and examining glitches for investigating a technology is pointed out. Glitches are defined as short-lived, unpremeditated aesthetic results of a failure; they are mostly known as digital phenomena, but I argue that the concept is equally applicable to the output of mechanical machines. Three drawing machines will be presented: The Opener, The Mixer and The Ventilator. In analyzing their drawings, emergent patterns consisting of unpremeditated visual artifacts will be identified and connected to irregularities of the specific technologies. Several other artists who work with mechanical and robotic drawing machines are introduced, to situate the presented works and reflections in a larger context of practice and to investigate how glitch concepts are applicable to such mechanical systems. 

77 FR 46995 - Termination, Limited Reductions in Funding, and Debarment Procedures; Recompetition; Enforcement...

Science.gov (United States)

2012-08-07

... INFORMATION: Introduction The Legal Services Corporation (LSC) Act (the Act) provides general authority to the...'' from fax machines or email systems do not guarantee that the document was in fact seen by a person at... Duties of the Corporation. (a) Whenever the Corporation learns that there is reason to believe that a...

Commissioning and operational scenarios of the LHC beam loss monitor system

International Nuclear Information System (INIS)

Holzer, E.B.

2007-01-01

One of the most critical elements for the protection of CERN's Large Hadron Collider (LHC) is its beam loss monitoring (BLM) system. It must prevent quenches in the super conducting magnets and damage of machine components due to beam losses. The contribution will discuss the commissioning procedures of the BLM system and envisaged operational scenarios. About 4000 monitors will be installed around the ring. When the loss rate exceeds a predefined threshold value, a beam abort is requested. Magnet quench and damage levels vary as a function of beam energy and loss duration. Consequently, the beam abort threshold values vary accordingly. By measuring the loss pattern, the BLM system helps to identify the loss mechanism. Furthermore, it will be an important tool for commissioning, machine setup and studies. Special monitors will be used for the setup and control of the collimators. (author)

Satellite monitoring of remote volcanoes improves study efforts in Alaska

Science.gov (United States)

Dean, K.; Servilla, M.; Roach, A.; Foster, B.; Engle, K.

Satellite monitoring of remote volcanoes is greatly benefitting the Alaska Volcano Observatory (AVO), and last year's eruption of the Okmok Volcano in the Aleutian Islands is a good case in point. The facility was able to issue and refine warnings of the eruption and related activity quickly, something that could not have been done using conventional seismic surveillance techniques, since seismometers have not been installed at these locations.AVO monitors about 100 active volcanoes in the North Pacific (NOPAC) region, but only a handful are observed by costly and logistically complex conventional means. The region is remote and vast, about 5000 × 2500 km, extending from Alaska west to the Kamchatka Peninsula in Russia (Figure 1). Warnings are transmitted to local communities and airlines that might be endangered by eruptions. More than 70,000 passenger and cargo flights fly over the region annually, and airborne volcanic ash is a threat to them. Many remote eruptions have been detected shortly after the initial magmatic activity using satellite data, and eruption clouds have been tracked across air traffic routes. Within minutes after eruptions are detected, information is relayed to government agencies, private companies, and the general public using telephone, fax, and e-mail. Monitoring of volcanoes using satellite image data involves direct reception, real-time monitoring, and data analysis. Two satellite data receiving stations, located at the Geophysical Institute, University of Alaska Fairbanks (UAF), are capable of receiving data from the advanced very high resolution radiometer (AVHRR) on National Oceanic and Atmospheric Administration (NOAA) polar orbiting satellites and from synthetic aperture radar (SAR) equipped satellites.

Statistical analysis of dragline monitoring data

Energy Technology Data Exchange (ETDEWEB)

Mirabediny, H.; Baafi, E.Y. [University of Tehran, Tehran (Iran)

1998-07-01

Dragline monitoring systems are normally the best tool used to collect data on the machine performance and operational parameters of a dragline operation. This paper discusses results of a time study using data from a dragline monitoring system captured over a four month period. Statistical summaries of the time study in terms of average values, standard deviation and frequency distributions showed that the mode of operation and the geological conditions have a significant influence on the dragline performance parameters. 6 refs., 14 figs., 3 tabs.

Self-Improving CNC Milling Machine

OpenAIRE

Spilling, Torjus

2014-01-01

This thesis is a study of the ability of a CNC milling machine to create parts for itself, and an evaluation of whether or not the machine is able to improve itself by creating new machine parts. This will be explored by using off-the-shelf parts to build an initial machine, using 3D printing/rapid prototyping to create any special parts needed for the initial build. After an initial working machine is completed, the design of the machine parts will be adjusted so that the machine can start p...

Machine Learning.

Science.gov (United States)

Kirrane, Diane E.

1990-01-01

As scientists seek to develop machines that can "learn," that is, solve problems by imitating the human brain, a gold mine of information on the processes of human learning is being discovered, expert systems are being improved, and human-machine interactions are being enhanced. (SK)

Machining of Metal Matrix Composites

CERN Document Server

2012-01-01

Machining of Metal Matrix Composites provides the fundamentals and recent advances in the study of machining of metal matrix composites (MMCs). Each chapter is written by an international expert in this important field of research. Machining of Metal Matrix Composites gives the reader information on machining of MMCs with a special emphasis on aluminium matrix composites. Chapter 1 provides the mechanics and modelling of chip formation for traditional machining processes. Chapter 2 is dedicated to surface integrity when machining MMCs. Chapter 3 describes the machinability aspects of MMCs. Chapter 4 contains information on traditional machining processes and Chapter 5 is dedicated to the grinding of MMCs. Chapter 6 describes the dry cutting of MMCs with SiC particulate reinforcement. Finally, Chapter 7 is dedicated to computational methods and optimization in the machining of MMCs. Machining of Metal Matrix Composites can serve as a useful reference for academics, manufacturing and materials researchers, manu...

Machine technology: a survey

International Nuclear Information System (INIS)

Barbier, M.M.

1981-01-01

An attempt was made to find existing machines that have been upgraded and that could be used for large-scale decontamination operations outdoors. Such machines are in the building industry, the mining industry, and the road construction industry. The road construction industry has yielded the machines in this presentation. A review is given of operations that can be done with the machines available

Characteristics of laser assisted machining for silicon nitride ceramic according to machining parameters

International Nuclear Information System (INIS)

Kim, Jong Do; Lee, Su Jin; Suh, Jeong

2011-01-01

This paper describes the Laser Assisted Machining (LAM) that cuts and removes softened parts by locally heating the ceramic with laser. Silicon nitride ceramics can be machined with general machining tools as well, because YSiAlON, which was made up ceramics, is soften at about 1,000 .deg. C. In particular, the laser, which concentrates on highly dense energy, can locally heat materials and very effectively control the temperature of the heated part of specimen. Therefore, this paper intends to propose an efficient machining method of ceramic by deducing the machining governing factors of laser assisted machining and understanding its mechanism. While laser power is the machining factor that controls the temperature, the CBN cutting tool could cut the material more easily as the material gets deteriorated from the temperature increase by increasing the laser power, but excessive oxidation can negatively affect the quality of the material surface after machining. As the feed rate and cutting depth increase, the cutting force increases and tool lifespan decreases, but surface oxidation also decreases. In this experiment, the material can be cut to 3 mm of cutting depth. And based on the results of the experiment, the laser assisted machining mechanism is clarified

Condition Monitoring Using Computational Intelligence Methods Applications in Mechanical and Electrical Systems

CERN Document Server

Marwala, Tshilidzi

2012-01-01

Condition monitoring uses the observed operating characteristics of a machine or structure to diagnose trends in the signal being monitored and to predict the need for maintenance before a breakdown occurs. This reduces the risk, inherent in a fixed maintenance schedule, of performing maintenance needlessly early or of having a machine fail before maintenance is due either of which can be expensive with the latter also posing a risk of serious accident especially in systems like aeroengines in which a catastrophic failure would put lives at risk. The technique also measures responses from the whole of the system under observation so it can detect the effects of faults which might be hidden deep within a system, hidden from traditional methods of inspection. Condition Monitoring Using Computational Intelligence Methods promotes the various approaches gathered under the umbrella of computational intelligence to show how condition monitoring can be used to avoid equipment failures and lengthen its useful life, m...

Stack monitor for the Proof-of-Breeding Project

International Nuclear Information System (INIS)

Fergus, R.W.

1985-01-01

This stack monitor system is a coordinated arrangement of hardware and software to monitor four hot cells (8 stacks) during the fuel dissection for the Proof-of-Breeding Project. The cell monitors, which are located in fan lofts, contain a microprocessor, radiation detectors, air flow sensors, and air flow control equipment. Design criteria included maximizing microprocessor control while minimizing the hardware complexity. The monitors have been programmed to produce concentration and total activity release data based on several detector measurements and flow rates. Although each monitor can function independently, a microcomputer can also be used to control each cell monitor including reprogramming if necessary. All programming is software, as opposed to firmware, with machine language for compactness in the cell monitors and Basic language for adaptability in the microcomputer controller

Automatic optical detection and classification of marine animals around MHK converters using machine vision

Energy Technology Data Exchange (ETDEWEB)

Brunton, Steven [Univ. of Washington, Seattle, WA (United States)

2018-01-15

Optical systems provide valuable information for evaluating interactions and associations between organisms and MHK energy converters and for capturing potentially rare encounters between marine organisms and MHK device. The deluge of optical data from cabled monitoring packages makes expert review time-consuming and expensive. We propose algorithms and a processing framework to automatically extract events of interest from underwater video. The open-source software framework consists of background subtraction, filtering, feature extraction and hierarchical classification algorithms. This principle classification pipeline was validated on real-world data collected with an experimental underwater monitoring package. An event detection rate of 100% was achieved using robust principal components analysis (RPCA), Fourier feature extraction and a support vector machine (SVM) binary classifier. The detected events were then further classified into more complex classes – algae | invertebrate | vertebrate, one species | multiple species of fish, and interest rank. Greater than 80% accuracy was achieved using a combination of machine learning techniques.

A real time status monitor for transistor bank driver power limit resistor in boost injection kicker power supply

Energy Technology Data Exchange (ETDEWEB)

Mi, J.; Tan, Y.; Zhang, W.

2011-03-28

For years suffering of Booster Injection Kicker transistor bank driver regulator troubleshooting, a new real time monitor system has been developed. A simple and floating circuit has been designed and tested. This circuit monitor system can monitor the driver regulator power limit resistor status in real time and warn machine operator if the power limit resistor changes values. This paper will mainly introduce the power supply and the new designed monitoring system. This real time resistor monitor circuit shows a useful method to monitor some critical parts in the booster pulse power supply. After two years accelerator operation, it shows that this monitor works well. Previously, we spent a lot of time in booster machine trouble shooting. We will reinstall all 4 PCB into Euro Card Standard Chassis when the power supply system will be updated.

Laundry monitor for nuclear facilities

Energy Technology Data Exchange (ETDEWEB)

Ishibashi, Mitsuo (Toshiba Corp., Fuchu (Japan). Fuchu Works)

1984-06-01

A laundry monitor has been developed for the detection and cleansification of radiation contamination on the clothes, headgear, footgear, etc. of workers in nuclear facilities. With this monitor, measurement is made irrespective of the size and shape of the objects; a large-area plastic scintillation detector is incorporated; it has stable and highly sensitive characteristics, with the merits of swift measurement, economical operation and easy maintenance. Connected with a folding machine, automatic carrying and storing compartment through a conveyor, it is capable of saving energy and man power, contributing to scheduled operation, and improving the efficiency of the facilities.

Laundry monitor for nuclear facilities

International Nuclear Information System (INIS)

Ishibashi, Mitsuo

1984-01-01

A laundry monitor has been developed for the detection and cleansification of radiation contamination on the clothes, headgear, footgear, etc. of workers in nuclear facilities. With this monitor, measurement is made irrespective of the size and shape of the objects ; a large-area plastic scintillation detector is incorporated ; it has stable and highly sensitive characteristics, with the merits of swift measurement, economical operation and easy maintenance. Connected with a folding machine, automatic carrying and storing compartment through a conveyor, it is capable of saving energy and man power, contributing to scheduled operation, and improving the efficiency of the facilities. (author)

Energy-efficient electrical machines by new materials. Superconductivity in large electrical machines

International Nuclear Information System (INIS)

Frauenhofer, Joachim; Arndt, Tabea; Grundmann, Joern

2013-01-01

The implementation of superconducting materials in high-power electrical machines results in significant advantages regarding efficiency, size and dynamic behavior when compared to conventional machines. The application of HTS (high-temperature superconductors) in electrical machines allows significantly higher power densities to be achieved for synchronous machines. In order to gain experience with the new technology, Siemens carried out a series of development projects. A 400 kW model motor for the verification of a concept for the new technology was followed by a 4000 kV A generator as highspeed machine - as well as a low-speed 4000 kW propeller motor with high torque. The 4000 kVA generator is still employed to carry out long-term tests and to check components. Superconducting machines have significantly lower weight and envelope dimensions compared to conventional machines, and for this reason alone, they utilize resources better. At the same time, operating losses are slashed to about half and the efficiency increases. Beyond this, they set themselves apart as a result of their special features in operation, such as high overload capability, stiff alternating load behavior and low noise. HTS machines provide significant advantages where the reduction of footprint, weight and losses or the improved dynamic behavior results in significant improvements of the overall system. Propeller motors and generators,for ships, offshore plants, in wind turbine and hydroelectric plants and in large power stations are just some examples. HTS machines can therefore play a significant role when it comes to efficiently using resources and energy as well as reducing the CO 2 emissions.

Assessment of LTE Wireless Access for Monitoring of Energy Distribution in the Smart Grid

DEFF Research Database (Denmark)

Madueño, Germán Corrales; Nielsen, Jimmy Jessen; Min Kim, Dong

2016-01-01

While LTE is becoming widely rolled out for human-type services, it is also a promising solution for cost-efficient connectivity of the smart grid monitoring equipment. This is a type of machine-to-machine (M2M) traffic that consists mainly of sporadic uplink transmissions. In such a setting...

Bunch monitor for an S-band electron linear accelerator

International Nuclear Information System (INIS)

Otake, Yuji; Nakahara, Kazuo

1991-01-01

The measurement of bunch characteristics in an S-band electron linear accelerator is required in order to evaluate the quality of accelerated electron beams. A new-type bunch monitor has been developed which combines micro-stripline technology with an air insulator and wall-current monitoring technology. The obtained time resolution of the monitor was more than 150 ps. This result shows that the monitor can handle the bunch number of an S-band linac. The structure of the monitor is suitable for being installed in the vacuum area, since it is constructed of only metal and ceramic parts. It can therefore easily be employed in an actual machine

Methodological evolutions in human-machine cooperative problem solving with applications to nuclear plants

International Nuclear Information System (INIS)

Kitamura, Masaharu; Takahashi, Makoto

2002-01-01

A new framework for attaining higher safety of nuclear plants through introducing machine intelligence and robots has been proposed in this paper. The main emphasis of the framework is placed on user-centered human-machine cooperation in solving problems experienced during conducting operation, monitoring and maintenance activities in nuclear plants. In this framework, human operator is supposed to take initiative of actions at any moment of operation. No attempt has been made to replace human experts by machine intelligence and robots. Efforts have been paid to clarify the expertise and behavioral model of human experts so that the developed techniques are consistent with human mental activities in solving highly complicated operational and maintenance problems. Several techniques essential to the functioning of the framework have also been introduced. Modification of environment to provide support information has also been pursued to realize the concept of ubiquitous computing. (author)

VIRTUAL MACHINES IN EDUCATION – CNC MILLING MACHINE WITH SINUMERIK 840D CONTROL SYSTEM

Directory of Open Access Journals (Sweden)

Ireneusz Zagórski

2014-11-01

Full Text Available Machining process nowadays could not be conducted without its inseparable element: cutting edge and frequently numerically controlled milling machines. Milling and lathe machining centres comprise standard equipment in many companies of the machinery industry, e.g. automotive or aircraft. It is for that reason that tertiary education should account for this rising demand. This entails the introduction into the curricula the forms which enable visualisation of machining, milling process and virtual production as well as virtual machining centres simulation. Siemens Virtual Machine (Virtual Workshop sets an example of such software, whose high functionality offers a range of learning experience, such as: learning the design of machine tools, their configuration, basic operation functions as well as basics of CNC.

Scheduling of hybrid types of machines with two-machine flowshop as the first type and a single machine as the second type

Science.gov (United States)

Hsiao, Ming-Chih; Su, Ling-Huey

2018-02-01

This research addresses the problem of scheduling hybrid machine types, in which one type is a two-machine flowshop and another type is a single machine. A job is either processed on the two-machine flowshop or on the single machine. The objective is to determine a production schedule for all jobs so as to minimize the makespan. The problem is NP-hard since the two parallel machines problem was proved to be NP-hard. Simulated annealing algorithms are developed to solve the problem optimally. A mixed integer programming (MIP) is developed and used to evaluate the performance for two SAs. Computational experiments demonstrate the efficiency of the simulated annealing algorithms, the quality of the simulated annealing algorithms will also be reported.

MPS Vax monitor and control software architecture

International Nuclear Information System (INIS)

Allison, S.; Spencer, N.; Underwood, K.; VanOlst, D.; Zelanzy, M.

1993-04-01

The new Machine Protection System (MPS) now being tested at the SLAC Linear Collider (SLC) includes monitoring and controlling facilities integrated into the existing VAX control system. The actual machine protection is performed by VME micros which control the beam repetition rate on a pulse-by-pulse basis based on measurements from fault detectors. The VAX is used to control and configure the VME micros, configure custom CAMAC modules providing the fault detector inputs, monitor and report faults and system errors, update the SLC database, and interface with the user. The design goals of the VAX software include a database-driven system to allow configuration changes without code changes, use of a standard TCP/IP-based message service for communication, use of existing SLCNET micros for CAMAC configuration, security and verification features to prevent unauthorized access, error and alarm logging and display updates as quickly as possible, and use of touch panels and X-windows displays for the user interface

BNL ALARA Center experience with an information exchange system on dose control at nuclear power plants

International Nuclear Information System (INIS)

Baum, J.W.; Khan, T.A.

1992-01-01

The essential elements of an international information exchange system on dose control at nuclear power plants are summarized. Information was collected from literature abstracting services, by attending technical meetings, by circulating data collection forms, and through personal contacts. Data are assembled in various databases and periodically disseminated to several hundred interested participants through a variety of publications and at technical meetings. Immediate on-line access to the data is available to participants with modems, commercially available communications software, and a password that is provided by the Brookhaven National Laboratory (BNL) ALARA Center to authorized users of the system. Since January 1992, rapid access also has been provided to persons with fax machines. Some information is available for ''polling'' the BNL system at any time, and other data can be installed for polling on request. Most information disseminated to data has been through publications; however, new protocols, simplified by the ALARA Center staff, and the convenience of fax machines are likely to make the earlier availability of information through these mechanisms increasingly important

Machine-to-machine communications architectures, technology, standards, and applications

CERN Document Server

Misic, Vojislav B

2014-01-01

With the number of machine-to-machine (M2M)-enabled devices projected to reach 20 to 50 billion by 2020, there is a critical need to understand the demands imposed by such systems. Machine-to-Machine Communications: Architectures, Technology, Standards, and Applications offers rigorous treatment of the many facets of M2M communication, including its integration with current technology.Presenting the work of a different group of international experts in each chapter, the book begins by supplying an overview of M2M technology. It considers proposed standards, cutting-edge applications, architectures, and traffic modeling and includes case studies that highlight the differences between traditional and M2M communications technology.Details a practical scheme for the forward error correction code designInvestigates the effectiveness of the IEEE 802.15.4 low data rate wireless personal area network standard for use in M2M communicationsIdentifies algorithms that will ensure functionality, performance, reliability, ...

Advanced Monitoring to Improve Combustion Turbine/Combined Cycle Reliability, Availability & Maintainability

Energy Technology Data Exchange (ETDEWEB)

Leonard Angello

2005-09-30

Power generators are concerned with the maintenance costs associated with the advanced turbines that they are purchasing. Since these machines do not have fully established Operation and Maintenance (O&M) track records, power generators face financial risk due to uncertain future maintenance costs. This risk is of particular concern, as the electricity industry transitions to a competitive business environment in which unexpected O&M costs cannot be passed through to consumers. These concerns have accelerated the need for intelligent software-based diagnostic systems that can monitor the health of a combustion turbine in real time and provide valuable information on the machine's performance to its owner/operators. EPRI, Impact Technologies, Boyce Engineering, and Progress Energy have teamed to develop a suite of intelligent software tools integrated with a diagnostic monitoring platform that, in real time, interpret data to assess the 'total health' of combustion turbines. The 'Combustion Turbine Health Management System' (CTHMS) will consist of a series of 'Dynamic Link Library' (DLL) programs residing on a diagnostic monitoring platform that accepts turbine health data from existing monitoring instrumentation. CTHMS interprets sensor and instrument outputs, correlates them to a machine's condition, provide interpretative analyses, project servicing intervals, and estimate remaining component life. In addition, the CTHMS enables real-time anomaly detection and diagnostics of performance and mechanical faults, enabling power producers to more accurately predict critical component remaining useful life and turbine degradation.

Nonplanar machines

International Nuclear Information System (INIS)

Ritson, D.

1989-05-01

This talk examines methods available to minimize, but never entirely eliminate, degradation of machine performance caused by terrain following. Breaking of planar machine symmetry for engineering convenience and/or monetary savings must be balanced against small performance degradation, and can only be decided on a case-by-case basis. 5 refs

Ultraprecision machining. Cho seimitsu kako

Energy Technology Data Exchange (ETDEWEB)

Suga, T [The Univ. of Tokyo, Tokyo (Japan). Research Center for Advanced Science and Technology

1992-10-05

It is said that the image of ultraprecision improved from 0.1[mu]m to 0.01[mu]m within recent years. Ultraprecision machining is a production technology which forms what is called nanotechnology with ultraprecision measuring and ultraprecision control. Accuracy means average machined sizes close to a required value, namely the deflection errors are small; precision means the scattered errors of machined sizes agree very closely. The errors of machining are related to both of the above errors and ultraprecision means the combined errors are very small. In the present ultraprecision machining, the relative precision to the size of a machined object is said to be in the order of 10[sup -6]. The flatness of silicon wafers is usually less than 0.5[mu]m. It is the fact that the appearance of atomic scale machining is awaited as the limit of ultraprecision machining. The machining of removing and adding atomic units using scanning probe microscopes are expected to reach the limit actually. 2 refs.

Theory and practice in machining systems

CERN Document Server

Ito, Yoshimi

2017-01-01

This book describes machining technology from a wider perspective by considering it within the machining space. Machining technology is one of the metal removal activities that occur at the machining point within the machining space. The machining space consists of structural configuration entities, e.g., the main spindle, the turret head and attachments such the chuck and mandrel, and also the form-generating movement of the machine tool itself. The book describes fundamental topics, including the form-generating movement of the machine tool and the important roles of the attachments, before moving on to consider the supply of raw materials into the machining space, and the discharge of swarf from it, and then machining technology itself. Building on the latest research findings “Theory and Practice in Machining System” discusses current challenges in machining. Thus, with the inclusion of introductory and advanced topics, the book can be used as a guide and survey of machining technology for students an...

Mechanical and thermal characteristics of JT-60 tokamak machine demonstrated in its power tests

International Nuclear Information System (INIS)

Takatsu, Hideyuki; Yamamoto, Masahiro; Ohkubo, Minoru

1985-09-01

JT-60 power tests were carried out from Dec. 10, 1984 to Feb. 20, 1985 to demonstrate, in advance of actual plasma operation, satisfactory performance of tokamak machine, power suppliers and control system in combination. The tests began with low power test of individual coil systems and progressed to full power tests. Power tests were successfully concluded with the following conclusions. (1) All of the coil systems were raised up to full power operation in combination and system performance was verified including thermal and structural integrity of tokamak machine. (2) Measured strain and deflection showed good agreements with those predicted in the design, which was an evidence that electromagnetic loads were supported adequately as expected in the design. (3) Vibration of lateral port was found to be large up to 50 m/s 2 and caused excessive vibration of gate-valves. (4) A few limitations to machine operation were made clear quantatively. (5) It was found that the existing detectors were insufficient to monitor the machine integrity and a few kinds of detectors were necessary to be installed. (author)

Machine learning for the automatic detection of anomalous events

Science.gov (United States)

Fisher, Wendy D.

In this dissertation, we describe our research contributions for a novel approach to the application of machine learning for the automatic detection of anomalous events. We work in two different domains to ensure a robust data-driven workflow that could be generalized for monitoring other systems. Specifically, in our first domain, we begin with the identification of internal erosion events in earth dams and levees (EDLs) using geophysical data collected from sensors located on the surface of the levee. As EDLs across the globe reach the end of their design lives, effectively monitoring their structural integrity is of critical importance. The second domain of interest is related to mobile telecommunications, where we investigate a system for automatically detecting non-commercial base station routers (BSRs) operating in protected frequency space. The presence of non-commercial BSRs can disrupt the connectivity of end users, cause service issues for the commercial providers, and introduce significant security concerns. We provide our motivation, experimentation, and results from investigating a generalized novel data-driven workflow using several machine learning techniques. In Chapter 2, we present results from our performance study that uses popular unsupervised clustering algorithms to gain insights to our real-world problems, and evaluate our results using internal and external validation techniques. Using EDL passive seismic data from an experimental laboratory earth embankment, results consistently show a clear separation of events from non-events in four of the five clustering algorithms applied. Chapter 3 uses a multivariate Gaussian machine learning model to identify anomalies in our experimental data sets. For the EDL work, we used experimental data from two different laboratory earth embankments. Additionally, we explore five wavelet transform methods for signal denoising. The best performance is achieved with the Haar wavelets. We achieve up to 97

Tattoo machines, needles and utilities.

Science.gov (United States)

Rosenkilde, Frank

2015-01-01

Starting out as a professional tattooist back in 1977 in Copenhagen, Denmark, Frank Rosenkilde has personally experienced the remarkable development of tattoo machines, needles and utilities: all the way from home-made equipment to industrial products of substantially improved quality. Machines can be constructed like the traditional dual-coil and single-coil machines or can be e-coil, rotary and hybrid machines, with the more convenient and precise rotary machines being the recent trend. This development has resulted in disposable needles and utilities. Newer machines are more easily kept clean and protected with foil to prevent crosscontaminations and infections. The machines and the tattooists' knowledge and awareness about prevention of infection have developed hand-in-hand. For decades, Frank Rosenkilde has been collecting tattoo machines. Part of his collection is presented here, supplemented by his personal notes. © 2015 S. Karger AG, Basel.

Design of rotating electrical machines

CERN Document Server

Pyrhonen , Juha; Hrabovcova , Valeria

2013-01-01

In one complete volume, this essential reference presents an in-depth overview of the theoretical principles and techniques of electrical machine design. This timely new edition offers up-to-date theory and guidelines for the design of electrical machines, taking into account recent advances in permanent magnet machines as well as synchronous reluctance machines. New coverage includes: Brand new material on the ecological impact of the motors, covering the eco-design principles of rotating electrical machinesAn expanded section on the design of permanent magnet synchronous machines, now repo

Determining the Efficiency of Adaptation of Foreign Economic Activity of Machine-Building Enterprises in Conditions of Deepening the European Integration Process of Ukraine

Directory of Open Access Journals (Sweden)

Semeniuk Iryna Yu.

2018-02-01

Full Text Available The article determines that introduction and implementation of the mechanism for foreign economic adaptation of machine-building enterprises to the conditions of the European integration processes requires constant monitoring of the processes of export-import operations and the adaptation activities to identify current problems and avoid risks. It has been found that one of the monitoring instruments is the system of indicators, which provides to evaluate the efficiency of use of the mechanism for foreign economic adaptation of a machine-building enterprise by comparing the values of the obtained indicators after accomplishing adaptation changes with the values of the indicators of previous periods. It is suggested to determine efficiency of adaptation of foreign economic activity of machine-building enterprises to conditions of deepening of the European integration process of Ukraine by means of: index of change of volume of exported production of a machine-building enterprise to the EU countries; weighted average of the change in the share of the European market, which is covered by the enterprise’s products; indicator of efficiency of exports of production of a machine-building enterprise to the European Union countries; indicator of the index of changes in the volume of permanent orders from European partners; integral indicator of efficiency of use of adaptive potential of a machine-building enterprise in conditions of integration processes.

VIRTUAL MODELING OF A NUMERICAL CONTROL MACHINE TOOL USED FOR COMPLEX MACHINING OPERATIONS

Directory of Open Access Journals (Sweden)

POPESCU Adrian

2015-11-01

Full Text Available This paper presents the 3D virtual model of the numerical control machine Modustar 100, in terms of machine elements. This is a CNC machine of modular construction, all components allowing the assembly in various configurations. The paper focused on the design of the subassemblies specific to the axes numerically controlled by means of CATIA v5, which contained different drive kinematic chains of different translation modules that ensures translation on X, Y and Z axis. Machine tool development for high speed and highly precise cutting demands employment of advanced simulation techniques witch it reflect on cost of total development of the machine.

Precision intercomparison of beam current monitors at CEBAF

International Nuclear Information System (INIS)

Kazimi, R.; Dunham, B.; Krafft, G.A.; Legg, R.; Liang, C.; Sinclair, C.; Mamosser, J.

1995-01-01

The CEBAF accelerator delivers a CW electron beam at fundamental 1497 MHz, with average beam current up to 200 μA. Accurate, stable nonintercepting beam current monitors are required for: setup/control, monitoring of beam current and beam losses for machine protection and personnel safety, and providing beam current information to experimental users. Fundamental frequency stainless steel RF cavities have been chosen for these beam current monitors. This paper reports on precision intercomparison between two such RF cavities, an Unser monitor, and two Faraday cups, all located in the injector area. At the low beam energy in the injector, it is straightforward to verify the high efficiency of the Faraday cups, and the Unser monitor included a wire through it to permit an absolute calibration. The cavity intensity monitors have proven capable of stable, high precision monitoring of the beam current

CDF run II run control and online monitor

International Nuclear Information System (INIS)

Arisawa, T.; Ikado, K.; Badgett, W.; Chlebana, F.; Maeshima, K.; McCrory, E.; Meyer, A.; Patrick, J.; Wenzel, H.; Stadie, H.; Wagner, W.; Veramendi, G.

2001-01-01

The authors discuss the CDF Run II Run Control and online event monitoring system. Run Control is the top level application that controls the data acquisition activities across 150 front end VME crates and related service processes. Run Control is a real-time multi-threaded application implemented in Java with flexible state machines, using JDBC database connections to configure clients, and including a user friendly and powerful graphical user interface. The CDF online event monitoring system consists of several parts: the event monitoring programs, the display to browse their results, the server program which communicates with the display via socket connections, the error receiver which displays error messages and communicates with Run Control, and the state manager which monitors the state of the monitor programs

HP 2671G GRAPHICS

CERN Multimedia

1981-01-01

The 2671 was a text-only printer with a maximum print speed of 120 characters per second. The 2671 printers are very robust. For paper, they use normal thermal roll paper sold in most office supply stores for older fax machines. Although thermal printing is a quiet technology, the paper advance mechanism of these printers is plenty loud.

MITS machine operations

International Nuclear Information System (INIS)

Flinchem, J.

1980-01-01

This document contains procedures which apply to operations performed on individual P-1c machines in the Machine Interface Test System (MITS) at AiResearch Manufacturing Company's Torrance, California Facility

Coordinate measuring machines

DEFF Research Database (Denmark)

De Chiffre, Leonardo

This document is used in connection with three exercises of 2 hours duration as a part of the course GEOMETRICAL METROLOGY AND MACHINE TESTING. The exercises concern three aspects of coordinate measuring: 1) Measuring and verification of tolerances on coordinate measuring machines, 2) Traceabilit...... and uncertainty during coordinate measurements, 3) Digitalisation and Reverse Engineering. This document contains a short description of each step in the exercise and schemes with room for taking notes of the results.......This document is used in connection with three exercises of 2 hours duration as a part of the course GEOMETRICAL METROLOGY AND MACHINE TESTING. The exercises concern three aspects of coordinate measuring: 1) Measuring and verification of tolerances on coordinate measuring machines, 2) Traceability...

Electric machine

Science.gov (United States)

El-Refaie, Ayman Mohamed Fawzi [Niskayuna, NY; Reddy, Patel Bhageerath [Madison, WI

2012-07-17

An interior permanent magnet electric machine is disclosed. The interior permanent magnet electric machine comprises a rotor comprising a plurality of radially placed magnets each having a proximal end and a distal end, wherein each magnet comprises a plurality of magnetic segments and at least one magnetic segment towards the distal end comprises a high resistivity magnetic material.

Machine Learning and Radiology

Science.gov (United States)

Wang, Shijun; Summers, Ronald M.

2012-01-01

In this paper, we give a short introduction to machine learning and survey its applications in radiology. We focused on six categories of applications in radiology: medical image segmentation, registration, computer aided detection and diagnosis, brain function or activity analysis and neurological disease diagnosis from fMR images, content-based image retrieval systems for CT or MRI images, and text analysis of radiology reports using natural language processing (NLP) and natural language understanding (NLU). This survey shows that machine learning plays a key role in many radiology applications. Machine learning identifies complex patterns automatically and helps radiologists make intelligent decisions on radiology data such as conventional radiographs, CT, MRI, and PET images and radiology reports. In many applications, the performance of machine learning-based automatic detection and diagnosis systems has shown to be comparable to that of a well-trained and experienced radiologist. Technology development in machine learning and radiology will benefit from each other in the long run. Key contributions and common characteristics of machine learning techniques in radiology are discussed. We also discuss the problem of translating machine learning applications to the radiology clinical setting, including advantages and potential barriers. PMID:22465077

Tribology in machine design

CERN Document Server

Stolarski, Tadeusz

1999-01-01

""Tribology in Machine Design is strongly recommended for machine designers, and engineers and scientists interested in tribology. It should be in the engineering library of companies producing mechanical equipment.""Applied Mechanics ReviewTribology in Machine Design explains the role of tribology in the design of machine elements. It shows how algorithms developed from the basic principles of tribology can be used in a range of practical applications within mechanical devices and systems.The computer offers today's designer the possibility of greater stringen

Short-Term Prediction of Air Pollution in Macau Using Support Vector Machines

Directory of Open Access Journals (Sweden)

Chi-Man Vong

2012-01-01

Full Text Available Forecasting of air pollution is a popular and important topic in recent years due to the health impact caused by air pollution. It is necessary to build an early warning system, which provides forecast and also alerts health alarm to local inhabitants by medical practitioners and the local government. Meteorological and pollutions data collected daily at monitoring stations of Macau can be used in this study to build a forecasting system. Support vector machines (SVMs, a novel type of machine learning technique based on statistical learning theory, can be used for regression and time series prediction. SVM is capable of good generalization while the performance of the SVM model is often hinged on the appropriate choice of the kernel.

Quadrilateral Micro-Hole Array Machining on Invar Thin Film: Wet Etching and Electrochemical Fusion Machining

Directory of Open Access Journals (Sweden)

Woong-Kirl Choi

2018-01-01

Full Text Available Ultra-precision products which contain a micro-hole array have recently shown remarkable demand growth in many fields, especially in the semiconductor and display industries. Photoresist etching and electrochemical machining are widely known as precision methods for machining micro-holes with no residual stress and lower surface roughness on the fabricated products. The Invar shadow masks used for organic light-emitting diodes (OLEDs contain numerous micro-holes and are currently machined by a photoresist etching method. However, this method has several problems, such as uncontrollable hole machining accuracy, non-etched areas, and overcutting. To solve these problems, a machining method that combines photoresist etching and electrochemical machining can be applied. In this study, negative photoresist with a quadrilateral hole array pattern was dry coated onto 30-µm-thick Invar thin film, and then exposure and development were carried out. After that, photoresist single-side wet etching and a fusion method of wet etching-electrochemical machining were used to machine micro-holes on the Invar. The hole machining geometry, surface quality, and overcutting characteristics of the methods were studied. Wet etching and electrochemical fusion machining can improve the accuracy and surface quality. The overcutting phenomenon can also be controlled by the fusion machining. Experimental results show that the proposed method is promising for the fabrication of Invar film shadow masks.

A Universal Reactive Machine

DEFF Research Database (Denmark)

Andersen, Henrik Reif; Mørk, Simon; Sørensen, Morten U.

1997-01-01

Turing showed the existence of a model universal for the set of Turing machines in the sense that given an encoding of any Turing machine asinput the universal Turing machine simulates it. We introduce the concept of universality for reactive systems and construct a CCS processuniversal...

An intelligent condition monitoring system for on-line classification of machine tool wear

Energy Technology Data Exchange (ETDEWEB)

Pan, Fu; Hope, A D; Javed, M [Systems Engineering Faculty, Southampton Institute (United Kingdom)

1998-12-31

The development of intelligent tool condition monitoring systems is a necessary requirement for successful automation of manufacturing processes. This presentation introduces a tool wear monitoring system for milling operations. The system utilizes power, force, acoustic emission and vibration sensors to monitor tool condition comprehensively. Features relevant to tool wear are drawn from time and frequency domain signals and a fuzzy pattern recognition technique is applied to combine the multisensor information and provide reliable classification results of tool wear states. (orig.) 10 refs.

An intelligent condition monitoring system for on-line classification of machine tool wear

Energy Technology Data Exchange (ETDEWEB)

Fu Pan; Hope, A.D.; Javed, M. [Systems Engineering Faculty, Southampton Institute (United Kingdom)

1997-12-31

The development of intelligent tool condition monitoring systems is a necessary requirement for successful automation of manufacturing processes. This presentation introduces a tool wear monitoring system for milling operations. The system utilizes power, force, acoustic emission and vibration sensors to monitor tool condition comprehensively. Features relevant to tool wear are drawn from time and frequency domain signals and a fuzzy pattern recognition technique is applied to combine the multisensor information and provide reliable classification results of tool wear states. (orig.) 10 refs.

Consequences of heavy machining vis à vis the machine structure – typical applications

International Nuclear Information System (INIS)

Leuch, M

2011-01-01

StarragHeckert has built 5 axis machines since the middle of the 80s for heavy duty milling. The STC-Centres are predominantly utilised in the aerospace industry, especially for milling structural workpieces, casings or Impellers made out of titanium and steel. StarragHeckert has a history of building machines for high performance milling. The machining of these components includes high forces thus spreading the wheat from the chaff. Although FEM calculations and multi-body simulations are carried out in the early stages of development, this paper will illustrate how the real process stability with modal analysis and cutting trials is determined. The experiment observes chatter stability to identify if the machine devices are adequate for the application or if the design has to be improved. Machining parameters of industrial applications are demonstrating the process stability for five axis heavy duties milling of StarragHeckert machine.

Virtual Machine in Automation Projects

OpenAIRE

Xing, Xiaoyuan

2010-01-01

Virtual machine, as an engineering tool, has recently been introduced into automation projects in Tetra Pak Processing System AB. The goal of this paper is to examine how to better utilize virtual machine for the automation projects. This paper designs different project scenarios using virtual machine. It analyzes installability, performance and stability of virtual machine from the test results. Technical solutions concerning virtual machine are discussed such as the conversion with physical...

CONTROL SYSTEM EVALUATION AND IMPLEMENTATION FOR THE ABRASIVE MACHINING PROCESS ON WOOD

Directory of Open Access Journals (Sweden)

Stephen Jackson

2011-06-01

Full Text Available Continuous process improvement and automation have proven to be powerful tools for the wood processing industries in order to obtain better final product quality and thus increase profits. Abrasive machining represents an important and relevant process in the manufacturing and processing of wood products, which also implies high cost of materials and labor; therefore, special attention to this process is necessary. The objective of this work was to evaluate and demonstrate a process control system for use in the abrasive machining of wood and wood-based products. A control system was created on LabView® to integrate the monitoring process and the actions required, depending on the abrasive machining process conditions. The system acquires information from the optical sensor to detect loading and activate the cleaning system. The system continuously monitors the condition of the abrasive belt (tool wear by using an acoustic emission sensor and alerts the operator of the status of the belt (green, yellow, and red lights indicating satisfactory, medium, and poor belt condition. The system also incorporates an additional safety device, which helps prevent permanent damage to the belt, equipment, or workpiece by alerting the operator when an excessive temperature has been reached. The process control system proved that automation permits enhancement in the consistency of the belt cleaning technique by the elimination of the human errors. Furthermore, this improvement also affects the cost by extending the life of the belt, which reduces setup time, belt cost, operation cost, as well as others.

The Buttonhole Machine. Module 13.

Science.gov (United States)

South Carolina State Dept. of Education, Columbia. Office of Vocational Education.

This module on the bottonhole machine, one in a series dealing with industrial sewing machines, their attachments, and operation, covers two topics: performing special operations on the buttonhole machine (parts and purpose) and performing special operations on the buttonhole machine (gauged buttonholes). For each topic these components are…

Introduction to machine learning.

Science.gov (United States)

Baştanlar, Yalin; Ozuysal, Mustafa

2014-01-01

The machine learning field, which can be briefly defined as enabling computers make successful predictions using past experiences, has exhibited an impressive development recently with the help of the rapid increase in the storage capacity and processing power of computers. Together with many other disciplines, machine learning methods have been widely employed in bioinformatics. The difficulties and cost of biological analyses have led to the development of sophisticated machine learning approaches for this application area. In this chapter, we first review the fundamental concepts of machine learning such as feature assessment, unsupervised versus supervised learning and types of classification. Then, we point out the main issues of designing machine learning experiments and their performance evaluation. Finally, we introduce some supervised learning methods.

Miniaturisation of Pressure-Sensitive Paint Measurement Systems Using Low-Cost, Miniaturised Machine Vision Cameras.

Science.gov (United States)

Quinn, Mark Kenneth; Spinosa, Emanuele; Roberts, David A

2017-07-25

Measurements of pressure-sensitive paint (PSP) have been performed using new or non-scientific imaging technology based on machine vision tools. Machine vision camera systems are typically used for automated inspection or process monitoring. Such devices offer the benefits of lower cost and reduced size compared with typically scientific-grade cameras; however, their optical qualities and suitability have yet to be determined. This research intends to show relevant imaging characteristics and also show the applicability of such imaging technology for PSP. Details of camera performance are benchmarked and compared to standard scientific imaging equipment and subsequent PSP tests are conducted using a static calibration chamber. The findings demonstrate that machine vision technology can be used for PSP measurements, opening up the possibility of performing measurements on-board small-scale model such as those used for wind tunnel testing or measurements in confined spaces with limited optical access.

Miniaturisation of Pressure-Sensitive Paint Measurement Systems Using Low-Cost, Miniaturised Machine Vision Cameras

Directory of Open Access Journals (Sweden)

Mark Kenneth Quinn

2017-07-01

Full Text Available Measurements of pressure-sensitive paint (PSP have been performed using new or non-scientific imaging technology based on machine vision tools. Machine vision camera systems are typically used for automated inspection or process monitoring. Such devices offer the benefits of lower cost and reduced size compared with typically scientific-grade cameras; however, their optical qualities and suitability have yet to be determined. This research intends to show relevant imaging characteristics and also show the applicability of such imaging technology for PSP. Details of camera performance are benchmarked and compared to standard scientific imaging equipment and subsequent PSP tests are conducted using a static calibration chamber. The findings demonstrate that machine vision technology can be used for PSP measurements, opening up the possibility of performing measurements on-board small-scale model such as those used for wind tunnel testing or measurements in confined spaces with limited optical access.

Instrumentation for status monitoring and protection of SST-1 superconducting magnets

Energy Technology Data Exchange (ETDEWEB)

Sharma, A.N., E-mail: aashoo.sharma@yahoo.com; Prasad, U.; Doshi, K.; Varmora, P.; Khristi, Y.; Patel, D.; Pradhan, S.

2016-11-15

Highlights: • Details of status monitoring instrumentation are presented. • Protection instrumentation details are presented. • Instrumentation installation details, signal conditioning and DAQ system details and the results during SST-1 operation are presented. - Abstract: Superconducting magnets of SST-1 are extensively instrumented to continuously monitor the health of magnets during machine cool-down, plasma experiments and also during the machine warm-up phase. These instrumentations include temperature sensors, flow meters, hall probes, strain gages, displacement sensors, pressure sensors and voltage taps. The number of sensors and their locations has been optimized to systematically monitor all important magnet parameters to ensure its safety. In-house developed modular signal conditioning cards have been developed for these instrumentations. The data is acquired on a Versa Module Europa bus based data acquisition system (VME DAQ). This paper gives an overview of selection, installation, laboratory scale validations, and distribution logics of these instrumentations. Results during plasma campaigns and the up-gradation aspects of these instrumentations are also discussed in this paper.

Applied machining technology

CERN Document Server

Tschätsch, Heinz

2010-01-01

Machining and cutting technologies are still crucial for many manufacturing processes. This reference presents all important machining processes in a comprehensive and coherent way. It includes many examples of concrete calculations, problems and solutions.

All about FAX: a Female Adult voXel phantom for Monte Carlo calculation in radiation protection dosimetry.

Science.gov (United States)

Kramer, R; Khoury, H J; Vieira, J W; Loureiro, E C M; Lima, V J M; Lima, F R A; Hoff, G

2004-12-07

The International Commission on Radiological Protection (ICRP) has created a task group on dose calculations, which, among other objectives, should replace the currently used mathematical MIRD phantoms by voxel phantoms. Voxel phantoms are based on digital images recorded from scanning of real persons by computed tomography or magnetic resonance imaging (MRI). Compared to the mathematical MIRD phantoms, voxel phantoms are true to the natural representations of a human body. Connected to a radiation transport code, voxel phantoms serve as virtual humans for which equivalent dose to organs and tissues from exposure to ionizing radiation can be calculated. The principal database for the construction of the FAX (Female Adult voXel) phantom consisted of 151 CT images recorded from scanning of trunk and head of a female patient, whose body weight and height were close to the corresponding data recommended by the ICRP in Publication 89. All 22 organs and tissues at risk, except for the red bone marrow and the osteogenic cells on the endosteal surface of bone ('bone surface'), have been segmented manually with a technique recently developed at the Departamento de Energia Nuclear of the UFPE in Recife, Brazil. After segmentation the volumes of the organs and tissues have been adjusted to agree with the organ and tissue masses recommended by ICRP for the Reference Adult Female in Publication 89. Comparisons have been made with the organ and tissue masses of the mathematical EVA phantom, as well as with the corresponding data for other female voxel phantoms. The three-dimensional matrix of the segmented images has eventually been connected to the EGS4 Monte Carlo code. Effective dose conversion coefficients have been calculated for exposures to photons, and compared to data determined for the mathematical MIRD-type phantoms, as well as for other voxel phantoms.

Assessment of Machine Learning Algorithms for Automatic Benthic Cover Monitoring and Mapping Using Towed Underwater Video Camera and High-Resolution Satellite Images

Directory of Open Access Journals (Sweden)

Hassan Mohamed

2018-05-01

Full Text Available Benthic habitat monitoring is essential for many applications involving biodiversity, marine resource management, and the estimation of variations over temporal and spatial scales. Nevertheless, both automatic and semi-automatic analytical methods for deriving ecologically significant information from towed camera images are still limited. This study proposes a methodology that enables a high-resolution towed camera with a Global Navigation Satellite System (GNSS to adaptively monitor and map benthic habitats. First, the towed camera finishes a pre-programmed initial survey to collect benthic habitat videos, which can then be converted to geo-located benthic habitat images. Second, an expert labels a number of benthic habitat images to class habitats manually. Third, attributes for categorizing these images are extracted automatically using the Bag of Features (BOF algorithm. Fourth, benthic cover categories are detected automatically using Weighted Majority Voting (WMV ensembles for Support Vector Machines (SVM, K-Nearest Neighbor (K-NN, and Bagging (BAG classifiers. Fifth, WMV-trained ensembles can be used for categorizing more benthic cover images automatically. Finally, correctly categorized geo-located images can provide ground truth samples for benthic cover mapping using high-resolution satellite imagery. The proposed methodology was tested over Shiraho, Ishigaki Island, Japan, a heterogeneous coastal area. The WMV ensemble exhibited 89% overall accuracy for categorizing corals, sediments, seagrass, and algae species. Furthermore, the same WMV ensemble produced a benthic cover map using a Quickbird satellite image with 92.7% overall accuracy.

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.

Machine Protection

International Nuclear Information System (INIS)

Zerlauth, Markus; Schmidt, Rüdiger; Wenninger, Jörg

2012-01-01

The present architecture of the machine protection system is being recalled and the performance of the associated systems during the 2011 run will be briefly summarized. An analysis of the causes of beam dumps as well as an assessment of the dependability of the machine protection systems (MPS) itself is being presented. Emphasis will be given to events that risked exposing parts of the machine to damage. Further improvements and mitigations of potential holes in the protection systems will be evaluated along with their impact on the 2012 run. The role of rMPP during the various operational phases (commissioning, intensity ramp up, MDs...) will be discussed along with a proposal for the intensity ramp up for the start of beam operation in 2012

Machine Protection

Energy Technology Data Exchange (ETDEWEB)

Zerlauth, Markus; Schmidt, Rüdiger; Wenninger, Jörg [European Organization for Nuclear Research, Geneva (Switzerland)

2012-07-01

The present architecture of the machine protection system is being recalled and the performance of the associated systems during the 2011 run will be briefly summarized. An analysis of the causes of beam dumps as well as an assessment of the dependability of the machine protection systems (MPS) itself is being presented. Emphasis will be given to events that risked exposing parts of the machine to damage. Further improvements and mitigations of potential holes in the protection systems will be evaluated along with their impact on the 2012 run. The role of rMPP during the various operational phases (commissioning, intensity ramp up, MDs...) will be discussed along with a proposal for the intensity ramp up for the start of beam operation in 2012.

Machine Protection

CERN Document Server

Zerlauth, Markus; Wenninger, Jörg

2012-01-01

The present architecture of the machine protection system is being recalled and the performance of the associated systems during the 2011 run will be briefly summarized. An analysis of the causes of beam dumps as well as an assessment of the dependability of the machine protection systems (MPS) itself is being presented. Emphasis will be given to events that risked exposing parts of the machine to damage. Further improvements and mitigations of potential holes in the protection systems will be evaluated along with their impact on the 2012 run. The role of rMPP during the various operational phases (commissioning, intensity ramp up, MDs...) will be discussed along with a proposal for the intensity ramp up for the start of beam operation in 2012.

Dictionary of machine terms

International Nuclear Information System (INIS)

1990-06-01

This book has introduction of dictionary of machine terms, and a compilation committee and introductory remarks. It gives descriptions of the machine terms in alphabetical order from a to Z and also includes abbreviation of machine terms and symbol table, way to read mathematical symbols and abbreviation and terms of drawings.

HTS machine laboratory prototype

DEFF Research Database (Denmark)

machine. The machine comprises six stationary HTS field windings wound from both YBCO and BiSCOO tape operated at liquid nitrogen temperature and enclosed in a cryostat, and a three phase armature winding spinning at up to 300 rpm. This design has full functionality of HTS synchronous machines. The design...

Probability Machines: Consistent Probability Estimation Using Nonparametric Learning Machines

Science.gov (United States)

Malley, J. D.; Kruppa, J.; Dasgupta, A.; Malley, K. G.; Ziegler, A.

2011-01-01

Summary Background Most machine learning approaches only provide a classification for binary responses. However, probabilities are required for risk estimation using individual patient characteristics. It has been shown recently that every statistical learning machine known to be consistent for a nonparametric regression problem is a probability machine that is provably consistent for this estimation problem. Objectives The aim of this paper is to show how random forests and nearest neighbors can be used for consistent estimation of individual probabilities. Methods Two random forest algorithms and two nearest neighbor algorithms are described in detail for estimation of individual probabilities. We discuss the consistency of random forests, nearest neighbors and other learning machines in detail. We conduct a simulation study to illustrate the validity of the methods. We exemplify the algorithms by analyzing two well-known data sets on the diagnosis of appendicitis and the diagnosis of diabetes in Pima Indians. Results Simulations demonstrate the validity of the method. With the real data application, we show the accuracy and practicality of this approach. We provide sample code from R packages in which the probability estimation is already available. This means that all calculations can be performed using existing software. Conclusions Random forest algorithms as well as nearest neighbor approaches are valid machine learning methods for estimating individual probabilities for binary responses. Freely available implementations are available in R and may be used for applications. PMID:21915433

National machine guarding program: Part 1. Machine safeguarding practices in small metal fabrication businesses

OpenAIRE

Parker, David L.; Yamin, Samuel C.; Brosseau, Lisa M.; Xi, Min; Gordon, Robert; Most, Ivan G.; Stanley, Rodney

2015-01-01

Background Metal fabrication workers experience high rates of traumatic occupational injuries. Machine operators in particular face high risks, often stemming from the absence or improper use of machine safeguarding or the failure to implement lockout procedures. Methods The National Machine Guarding Program (NMGP) was a translational research initiative implemented in conjunction with two workers' compensation insures. Insurance safety consultants trained in machine guarding used standardize...

A hybrid prognostic model for multistep ahead prediction of machine condition

Science.gov (United States)

Roulias, D.; Loutas, T. H.; Kostopoulos, V.

2012-05-01

Prognostics are the future trend in condition based maintenance. In the current framework a data driven prognostic model is developed. The typical procedure of developing such a model comprises a) the selection of features which correlate well with the gradual degradation of the machine and b) the training of a mathematical tool. In this work the data are taken from a laboratory scale single stage gearbox under multi-sensor monitoring. Tests monitoring the condition of the gear pair from healthy state until total brake down following several days of continuous operation were conducted. After basic pre-processing of the derived data, an indicator that correlated well with the gearbox condition was obtained. Consecutively the time series is split in few distinguishable time regions via an intelligent data clustering scheme. Each operating region is modelled with a feed-forward artificial neural network (FFANN) scheme. The performance of the proposed model is tested by applying the system to predict the machine degradation level on unseen data. The results show the plausibility and effectiveness of the model in following the trend of the timeseries even in the case that a sudden change occurs. Moreover the model shows ability to generalise for application in similar mechanical assets.

A modern concept for status oriented vibration monitoring of big turbogenerators

International Nuclear Information System (INIS)

Herz, F.; Theodor, P.

1997-01-01

The investigation of mechanical vibrations is an excellent method of showing the current condition of a machine. This paper deals with the vibrations monitoring of large turbo-generators. First the general aspects of monitoring, as well as diagnostic strategies and impact on the operation of the installation is discussed. An example of a condition-oriented vibration monitoring is the description of the 'Vibroview' system recently developed and installed in the Leibstadt nuclear power plant. (author) 16 figs., tabs., refs

Machine vision systems using machine learning for industrial product inspection

Science.gov (United States)

Lu, Yi; Chen, Tie Q.; Chen, Jie; Zhang, Jian; Tisler, Anthony

2002-02-01

Machine vision inspection requires efficient processing time and accurate results. In this paper, we present a machine vision inspection architecture, SMV (Smart Machine Vision). SMV decomposes a machine vision inspection problem into two stages, Learning Inspection Features (LIF), and On-Line Inspection (OLI). The LIF is designed to learn visual inspection features from design data and/or from inspection products. During the OLI stage, the inspection system uses the knowledge learnt by the LIF component to inspect the visual features of products. In this paper we will present two machine vision inspection systems developed under the SMV architecture for two different types of products, Printed Circuit Board (PCB) and Vacuum Florescent Displaying (VFD) boards. In the VFD board inspection system, the LIF component learns inspection features from a VFD board and its displaying patterns. In the PCB board inspection system, the LIF learns the inspection features from the CAD file of a PCB board. In both systems, the LIF component also incorporates interactive learning to make the inspection system more powerful and efficient. The VFD system has been deployed successfully in three different manufacturing companies and the PCB inspection system is the process of being deployed in a manufacturing plant.

Machine Directional Register System Modeling for Shaft-Less Drive Gravure Printing Machines

Directory of Open Access Journals (Sweden)

Shanhui Liu

2013-01-01

Full Text Available In the latest type of gravure printing machines referred to as the shaft-less drive system, each gravure printing roller is driven by an individual servo motor, and all motors are electrically synchronized. The register error is regulated by a speed difference between the adjacent printing rollers. In order to improve the control accuracy of register system, an accurate mathematical model of the register system should be investigated for the latest machines. Therefore, the mathematical model of the machine directional register (MDR system is studied for the multicolor gravure printing machines in this paper. According to the definition of the MDR error, the model is derived, and then it is validated by the numerical simulation and experiments carried out in the experimental setup of the four-color gravure printing machines. The results show that the established MDR system model is accurate and reliable.

Machine learning and radiology.

Science.gov (United States)

Wang, Shijun; Summers, Ronald M

2012-07-01

In this paper, we give a short introduction to machine learning and survey its applications in radiology. We focused on six categories of applications in radiology: medical image segmentation, registration, computer aided detection and diagnosis, brain function or activity analysis and neurological disease diagnosis from fMR images, content-based image retrieval systems for CT or MRI images, and text analysis of radiology reports using natural language processing (NLP) and natural language understanding (NLU). This survey shows that machine learning plays a key role in many radiology applications. Machine learning identifies complex patterns automatically and helps radiologists make intelligent decisions on radiology data such as conventional radiographs, CT, MRI, and PET images and radiology reports. In many applications, the performance of machine learning-based automatic detection and diagnosis systems has shown to be comparable to that of a well-trained and experienced radiologist. Technology development in machine learning and radiology will benefit from each other in the long run. Key contributions and common characteristics of machine learning techniques in radiology are discussed. We also discuss the problem of translating machine learning applications to the radiology clinical setting, including advantages and potential barriers. Copyright © 2012. Published by Elsevier B.V.

Coupling Impedance of the CERN SPS beam position monitors

CERN Document Server

Salvant, B; Boccard, C; Caspers, Friedhelm; Grudiev, A; Jones, R; Métral, E; Rumolo, G; Zannini, C; Spataro, B; Alesini, D; Migliorati, M; Roncarolo, F; Calaga, R

2010-01-01

A detailed knowledge of the beam coupling impedance of the CERN Super Proton Synchrotron (SPS) is required in order to operate this machine with a higher intensity for the foreseen Large Hadron Collider (LHC) luminosity upgrade. A large number of Beam Position Monitors (BPMs) is currently installed in the SPS, and this is why their contribution to the SPS impedance has to be assessed. This paper focuses on electromagnetic (EM) simulations and bench measurements of the longitudinal and transverse impedance generated by the horizontal and vertical BPMs installed in the SPS machine.

Machining with abrasives

CERN Document Server

Jackson, Mark J

2011-01-01

Abrasive machining is key to obtaining the desired geometry and surface quality in manufacturing. This book discusses the fundamentals and advances in the abrasive machining processes. It provides a complete overview of developing areas in the field.

The Knife Machine. Module 15.

Science.gov (United States)

South Carolina State Dept. of Education, Columbia. Office of Vocational Education.

This module on the knife machine, one in a series dealing with industrial sewing machines, their attachments, and operation, covers one topic: performing special operations on the knife machine (a single needle or multi-needle machine which sews and cuts at the same time). These components are provided: an introduction, directions, an objective,…

Stochastic Estimation Methods for Induction Motor Transient Thermal Monitoring Under Non Linear Condition

Directory of Open Access Journals (Sweden)

Mellah HACEN

2012-08-01

Full Text Available The induction machine, because of its robustness and low-cost, is commonly used in the industry. Nevertheless, as every type of electrical machine, this machine suffers of some limitations. The most important one is the working temperature which is the dimensioning parameter for the definition of the nominal working point and the machine lifetime. Due to a strong demand concerning thermal monitoring methods appeared in the industry sector. In this context, the adding of temperature sensors is not acceptable and the studied methods tend to use sensorless approaches such as observators or parameters estimators like the extended Kalman Filter (EKF. Then the important criteria are reliability, computational cost ad real time implementation.

ADVANCED MONITORING TO IMPROVE COMBUSTION TURBINE/COMBINED CYCLE CT/(CC) RELIABILITY, AVAILABILITY AND MAINTAINABILITY (RAM)

Energy Technology Data Exchange (ETDEWEB)

Leonard Angello

2003-09-30

Power generators are concerned with the maintenance costs associated with the advanced turbines that they are purchasing. Since these machines do not have fully established operation and maintenance (O&M) track records, power generators face financial risk due to uncertain future maintenance costs. This risk is of particular concern, as the electricity industry transitions to a competitive business environment in which unexpected O&M costs cannot be passed through to consumers. These concerns have accelerated the need for intelligent software-based diagnostic systems that can monitor the health of a combustion turbine in real time and provide valuable information on the machine's performance to its owner/operators. Such systems would interpret sensor and instrument outputs, correlate them to the machine's condition, provide interpretative analyses, forward projections of servicing intervals, estimate remaining component life, and identify faults. EPRI, Impact Technologies, Boyce Engineering, and Progress Energy have teamed to develop a suite of intelligent software tools integrated with a diagnostic monitoring platform that will, in real time, interpret data to assess the ''total health'' of combustion turbines. The Combustion Turbine Health Management System (CTHM) will consist of a series of dynamic link library (DLL) programs residing on a diagnostic monitoring platform that accepts turbine health data from existing monitoring instrumentation. The CTHM system will be a significant improvement over currently available techniques for turbine monitoring and diagnostics. CTHM will interpret sensor and instrument outputs, correlate them to a machine's condition, provide interpretative analyses, project servicing intervals, and estimate remaining component life. In addition, it will enable real-time anomaly detection and diagnostics of performance and mechanical faults, enabling power producers to more accurately predict critical

Restrictions of process machine retooling at machine-building enterprises

Directory of Open Access Journals (Sweden)

Kuznetsova Elena

2017-01-01

Full Text Available The competitiveness of the national economy depends on the technological level of the machine-building enterprises production equipment. Today in Russia there are objective and subjective restrictions for the optimum policy formation of the manufacturing equipment renewal. The analysis of the manufacturing equipment age structure dynamics in the Russian machine-building complex indicates the negative tendencies intensification: increase in the equipment service life, reduction in the share of up-to-date equipment, and drop in its use efficiency. The article investigates and classifies the main restrictions of the manufacturing equipment renewal process, such as regulatory and legislative, financial, organizational, competency-based. The economic consequences of the revealed restrictions influence on the machine-building enterprises activity are shown.

3rd International Conference on Condition Monitoring of Machinery in Non-Stationary Operations

CERN Document Server

Rubini, Riccardo; D'Elia, Gianluca; Cocconcelli, Marco; Chaari, Fakher; Zimroz, Radoslaw; Bartelmus, Walter; Haddar, Mohamed

2014-01-01

This book presents the processings of the third edition of the Condition Monitoring of Machinery in Non-Stationary Operations (CMMNO13) which was held in Ferrara, Italy. This yearly event merges an international community of researchers who met – in 2011 in Wroclaw (Poland) and in 2012 in Hammamet (Tunisia) – to discuss issues of diagnostics of rotating machines operating in complex motion and/or load conditions. The growing interest of the industrial world on the topics covered by the CMMNO13 involves the fields of packaging, automotive, agricultural, mining, processing and wind machines in addition to that of the systems for data acquisition.The participation of speakers and visitors from industry makes the event an opportunity for immediate assessment of the potential applications of advanced methodologies for the signal analysis. Signals acquired from machines often contain contributions from several different components as well as noise. Therefore, the major challenge of condition monitoring is to po...

Mechanical design of machine components

CERN Document Server

Ugural, Ansel C

2015-01-01

Mechanical Design of Machine Components, Second Edition strikes a balance between theory and application, and prepares students for more advanced study or professional practice. It outlines the basic concepts in the design and analysis of machine elements using traditional methods, based on the principles of mechanics of materials. The text combines the theory needed to gain insight into mechanics with numerical methods in design. It presents real-world engineering applications, and reveals the link between basic mechanics and the specific design of machine components and machines. Divided into three parts, this revised text presents basic background topics, deals with failure prevention in a variety of machine elements and covers applications in design of machine components as well as entire machines. Optional sections treating special and advanced topics are also included.Key Features of the Second Edition:Incorporates material that has been completely updated with new chapters, problems, practical examples...

Soft computing in machine learning

CERN Document Server

Park, Jooyoung; Inoue, Atsushi

2014-01-01

As users or consumers are now demanding smarter devices, intelligent systems are revolutionizing by utilizing machine learning. Machine learning as part of intelligent systems is already one of the most critical components in everyday tools ranging from search engines and credit card fraud detection to stock market analysis. You can train machines to perform some things, so that they can automatically detect, diagnose, and solve a variety of problems. The intelligent systems have made rapid progress in developing the state of the art in machine learning based on smart and deep perception. Using machine learning, the intelligent systems make widely applications in automated speech recognition, natural language processing, medical diagnosis, bioinformatics, and robot locomotion. This book aims at introducing how to treat a substantial amount of data, to teach machines and to improve decision making models. And this book specializes in the developments of advanced intelligent systems through machine learning. It...

On-line Cutting Tool Condition Monitoring in Machining Processes Using Artificial Intelligence

OpenAIRE

Vallejo, Antonio J.; Morales-Menéndez, Rub&#;n; Alique, J.R.

2008-01-01

This chapter presented new ideas for monitoring and diagnosis of the cutting tool condition with two different algorithms for pattern recognition: HMM, and ANN. The monitoring and diagnosis system was implemented for peripheral milling process in HSM, where several Aluminium alloys and cutting tools were used. The flank wear (VB) was selected as the criterion to evaluate the tool's life and four cutting tool conditions were defined to be recognized: New, half new, half worn, and worn conditio...

Mankind, machines and people

Energy Technology Data Exchange (ETDEWEB)

Hugli, A

1984-01-01

The following questions are addressed: is there a difference between machines and men, between human communication and communication with machines. Will we ever reach the point when the dream of artificial intelligence becomes a reality. Will thinking machines be able to replace the human spirit in all its aspects. Social consequences and philosophical aspects are addressed. 8 references.

A Concrete Framework for Environment Machines

DEFF Research Database (Denmark)

Biernacka, Malgorzata; Danvy, Olivier

2007-01-01

calculus with explicit substitutions), we extend it minimally so that it can also express one-step reduction strategies, and we methodically derive a series of environment machines from the specification of two one-step reduction strategies for the lambda-calculus: normal order and applicative order....... The derivation extends Danvy and Nielsen’s refocusing-based construction of abstract machines with two new steps: one for coalescing two successive transitions into one, and the other for unfolding a closure into a term and an environment in the resulting abstract machine. The resulting environment machines...... include both the Krivine machine and the original version of Krivine’s machine, Felleisen et al.’s CEK machine, and Leroy’s Zinc abstract machine....

A generic finite state machine framework for the ACNET control system

International Nuclear Information System (INIS)

Carmichael, L.; Warner, A.

2009-01-01

A significant level of automation and flexibility has been added to the ACNET control system through the development of a Java-based Finite State Machine (FSM) infrastructure. These FSMs are integrated into ACNET and allow users to easily build, test and execute scripts that have full access to ACNET's functionality. In this paper, a description will be given of the FSM design and its ties to the Java-based Data Acquisition Engine (DAE) framework. Each FSM is part of a client-server model with FSM display clients using Remote Method Invocation (RMI) to communicate with DAE servers heavily coupled to ACNET. A web-based monitoring system that allows users to utilize browsers to observe persistent FSMs will also be discussed. Finally, some key implementations such as the crash recovery FSM developed for the Electron Cooling machine protection system will be presented.

Failure prediction using machine learning and time series in optical network.

Science.gov (United States)

Wang, Zhilong; Zhang, Min; Wang, Danshi; Song, Chuang; Liu, Min; Li, Jin; Lou, Liqi; Liu, Zhuo

2017-08-07

In this paper, we propose a performance monitoring and failure prediction method in optical networks based on machine learning. The primary algorithms of this method are the support vector machine (SVM) and double exponential smoothing (DES). With a focus on risk-aware models in optical networks, the proposed protection plan primarily investigates how to predict the risk of an equipment failure. To the best of our knowledge, this important problem has not yet been fully considered. Experimental results showed that the average prediction accuracy of our method was 95% when predicting the optical equipment failure state. This finding means that our method can forecast an equipment failure risk with high accuracy. Therefore, our proposed DES-SVM method can effectively improve traditional risk-aware models to protect services from possible failures and enhance the optical network stability.

Characteristics of the Arcing Plasma Formation Effect in Spark-Assisted Chemical Engraving of Glass, Based on Machine Vision.

Science.gov (United States)

Ho, Chao-Ching; Wu, Dung-Sheng

2018-03-22

Spark-assisted chemical engraving (SACE) is a non-traditional machining technology that is used to machine electrically non-conducting materials including glass, ceramics, and quartz. The processing accuracy, machining efficiency, and reproducibility are the key factors in the SACE process. In the present study, a machine vision method is applied to monitor and estimate the status of a SACE-drilled hole in quartz glass. During the machining of quartz glass, the spring-fed tool electrode was pre-pressured on the quartz glass surface to feed the electrode that was in contact with the machining surface of the quartz glass. In situ image acquisition and analysis of the SACE drilling processes were used to analyze the captured image of the state of the spark discharge at the tip and sidewall of the electrode. The results indicated an association between the accumulative size of the SACE-induced spark area and deepness of the hole. The results indicated that the evaluated depths of the SACE-machined holes were a proportional function of the accumulative spark size with a high degree of correlation. The study proposes an innovative computer vision-based method to estimate the deepness and status of SACE-drilled holes in real time.

Characteristics of the Arcing Plasma Formation Effect in Spark-Assisted Chemical Engraving of Glass, Based on Machine Vision

Directory of Open Access Journals (Sweden)

Chao-Ching Ho

2018-03-01

Full Text Available Spark-assisted chemical engraving (SACE is a non-traditional machining technology that is used to machine electrically non-conducting materials including glass, ceramics, and quartz. The processing accuracy, machining efficiency, and reproducibility are the key factors in the SACE process. In the present study, a machine vision method is applied to monitor and estimate the status of a SACE-drilled hole in quartz glass. During the machining of quartz glass, the spring-fed tool electrode was pre-pressured on the quartz glass surface to feed the electrode that was in contact with the machining surface of the quartz glass. In situ image acquisition and analysis of the SACE drilling processes were used to analyze the captured image of the state of the spark discharge at the tip and sidewall of the electrode. The results indicated an association between the accumulative size of the SACE-induced spark area and deepness of the hole. The results indicated that the evaluated depths of the SACE-machined holes were a proportional function of the accumulative spark size with a high degree of correlation. The study proposes an innovative computer vision-based method to estimate the deepness and status of SACE-drilled holes in real time.

Semi-supervised vibration-based classification and condition monitoring of compressors

Science.gov (United States)

Potočnik, Primož; Govekar, Edvard

2017-09-01

Semi-supervised vibration-based classification and condition monitoring of the reciprocating compressors installed in refrigeration appliances is proposed in this paper. The method addresses the problem of industrial condition monitoring where prior class definitions are often not available or difficult to obtain from local experts. The proposed method combines feature extraction, principal component analysis, and statistical analysis for the extraction of initial class representatives, and compares the capability of various classification methods, including discriminant analysis (DA), neural networks (NN), support vector machines (SVM), and extreme learning machines (ELM). The use of the method is demonstrated on a case study which was based on industrially acquired vibration measurements of reciprocating compressors during the production of refrigeration appliances. The paper presents a comparative qualitative analysis of the applied classifiers, confirming the good performance of several nonlinear classifiers. If the model parameters are properly selected, then very good classification performance can be obtained from NN trained by Bayesian regularization, SVM and ELM classifiers. The method can be effectively applied for the industrial condition monitoring of compressors.

Findings From the National Machine Guarding Program-A Small Business Intervention: Machine Safety.

Science.gov (United States)

Parker, David L; Yamin, Samuel C; Xi, Min; Brosseau, Lisa M; Gordon, Robert; Most, Ivan G; Stanley, Rodney

2016-09-01

The purpose of this nationwide intervention was to improve machine safety in small metal fabrication businesses (3 to 150 employees). The failure to implement machine safety programs related to guarding and lockout/tagout (LOTO) are frequent causes of Occupational Safety and Health Administration (OSHA) citations and may result in serious traumatic injury. Insurance safety consultants conducted a standardized evaluation of machine guarding, safety programs, and LOTO. Businesses received a baseline evaluation, two intervention visits, and a 12-month follow-up evaluation. The intervention was completed by 160 businesses. Adding a safety committee was associated with a 10% point increase in business-level machine scores (P increase in LOTO program scores (P < 0.0001). Insurance safety consultants proved effective at disseminating a machine safety and LOTO intervention via management-employee safety committees.

MACHINE LEARNING METHODS IN DIGITAL AGRICULTURE: ALGORITHMS AND CASES

Directory of Open Access Journals (Sweden)

Aleksandr Vasilyevich Koshkarov

2018-05-01

Full Text Available Ensuring food security is a major challenge in many countries. With a growing global population, the issues of improving the efficiency of agriculture have become most relevant. Farmers are looking for new ways to increase yields, and governments of different countries are developing new programs to support agriculture. This contributes to a more active implementation of digital technologies in agriculture, helping farmers to make better decisions, increase yields and take care of the environment. The central point is the collection and analysis of data. In the industry of agriculture, data can be collected from different sources and may contain useful patterns that identify potential problems or opportunities. Data should be analyzed using machine learning algorithms to extract useful insights. Such methods of precision farming allow the farmer to monitor individual parts of the field, optimize the consumption of water and chemicals, and identify problems quickly. Purpose: to make an overview of the machine learning algorithms used for data analysis in agriculture. Methodology: an overview of the relevant literature; a survey of farmers. Results: relevant algorithms of machine learning for the analysis of data in agriculture at various levels were identified: soil analysis (soil assessment, soil classification, soil fertility predictions, weather forecast (simulation of climate change, temperature and precipitation prediction, and analysis of vegetation (weed identification, vegetation classification, plant disease identification, crop forecasting. Practical implications: agriculture, crop production.

Tracking an open quantum system using a finite state machine: Stability analysis

International Nuclear Information System (INIS)

Karasik, R. I.; Wiseman, H. M.

2011-01-01

A finite-dimensional Markovian open quantum system will undergo quantum jumps between pure states, if we can monitor the bath to which it is coupled with sufficient precision. In general these jumps, plus the between-jump evolution, create a trajectory which passes through infinitely many different pure states, even for ergodic systems. However, as shown recently by us [Phys. Rev. Lett. 106, 020406 (2011)], it is possible to construct adaptive monitorings which restrict the system to jumping between a finite number of states. That is, it is possible to track the system using a finite state machine as the apparatus. In this paper we consider the question of the stability of these monitoring schemes. Restricting to cyclic jumps for a qubit, we give a strong analytical argument that these schemes are always stable and supporting analytical and numerical evidence for the example of resonance fluorescence. This example also enables us to explore a range of behaviors in the evolution of individual trajectories, for several different monitoring schemes.

Behavioral Modeling for Mental Health using Machine Learning Algorithms.

Science.gov (United States)

Srividya, M; Mohanavalli, S; Bhalaji, N

2018-04-03

Mental health is an indicator of emotional, psychological and social well-being of an individual. It determines how an individual thinks, feels and handle situations. Positive mental health helps one to work productively and realize their full potential. Mental health is important at every stage of life, from childhood and adolescence through adulthood. Many factors contribute to mental health problems which lead to mental illness like stress, social anxiety, depression, obsessive compulsive disorder, drug addiction, and personality disorders. It is becoming increasingly important to determine the onset of the mental illness to maintain proper life balance. The nature of machine learning algorithms and Artificial Intelligence (AI) can be fully harnessed for predicting the onset of mental illness. Such applications when implemented in real time will benefit the society by serving as a monitoring tool for individuals with deviant behavior. This research work proposes to apply various machine learning algorithms such as support vector machines, decision trees, naïve bayes classifier, K-nearest neighbor classifier and logistic regression to identify state of mental health in a target group. The responses obtained from the target group for the designed questionnaire were first subject to unsupervised learning techniques. The labels obtained as a result of clustering were validated by computing the Mean Opinion Score. These cluster labels were then used to build classifiers to predict the mental health of an individual. Population from various groups like high school students, college students and working professionals were considered as target groups. The research presents an analysis of applying the aforementioned machine learning algorithms on the target groups and also suggests directions for future work.

Network Challenges for Cyber Physical Systems with Tiny Wireless Devices: A Case Study on Reliable Pipeline Condition Monitoring

Directory of Open Access Journals (Sweden)

Salman Ali

2015-03-01

Full Text Available The synergy of computational and physical network components leading to the Internet of Things, Data and Services has been made feasible by the use of Cyber Physical Systems (CPSs. CPS engineering promises to impact system condition monitoring for a diverse range of fields from healthcare, manufacturing, and transportation to aerospace and warfare. CPS for environment monitoring applications completely transforms human-to-human, human-to-machine and machine-to-machine interactions with the use of Internet Cloud. A recent trend is to gain assistance from mergers between virtual networking and physical actuation to reliably perform all conventional and complex sensing and communication tasks. Oil and gas pipeline monitoring provides a novel example of the benefits of CPS, providing a reliable remote monitoring platform to leverage environment, strategic and economic benefits. In this paper, we evaluate the applications and technical requirements for seamlessly integrating CPS with sensor network plane from a reliability perspective and review the strategies for communicating information between remote monitoring sites and the widely deployed sensor nodes. Related challenges and issues in network architecture design and relevant protocols are also provided with classification. This is supported by a case study on implementing reliable monitoring of oil and gas pipeline installations. Network parameters like node-discovery, node-mobility, data security, link connectivity, data aggregation, information knowledge discovery and quality of service provisioning have been reviewed.

Network challenges for cyber physical systems with tiny wireless devices: a case study on reliable pipeline condition monitoring.

Science.gov (United States)

Ali, Salman; Qaisar, Saad Bin; Saeed, Husnain; Khan, Muhammad Farhan; Naeem, Muhammad; Anpalagan, Alagan

2015-03-25

The synergy of computational and physical network components leading to the Internet of Things, Data and Services has been made feasible by the use of Cyber Physical Systems (CPSs). CPS engineering promises to impact system condition monitoring for a diverse range of fields from healthcare, manufacturing, and transportation to aerospace and warfare. CPS for environment monitoring applications completely transforms human-to-human, human-to-machine and machine-to-machine interactions with the use of Internet Cloud. A recent trend is to gain assistance from mergers between virtual networking and physical actuation to reliably perform all conventional and complex sensing and communication tasks. Oil and gas pipeline monitoring provides a novel example of the benefits of CPS, providing a reliable remote monitoring platform to leverage environment, strategic and economic benefits. In this paper, we evaluate the applications and technical requirements for seamlessly integrating CPS with sensor network plane from a reliability perspective and review the strategies for communicating information between remote monitoring sites and the widely deployed sensor nodes. Related challenges and issues in network architecture design and relevant protocols are also provided with classification. This is supported by a case study on implementing reliable monitoring of oil and gas pipeline installations. Network parameters like node-discovery, node-mobility, data security, link connectivity, data aggregation, information knowledge discovery and quality of service provisioning have been reviewed.

Research on the proficient machine system. Theoretical part; Jukutatsu machine system no chosa kenkyu. Rironhen

Energy Technology Data Exchange (ETDEWEB)

NONE

1996-03-01

The basic theory of the proficient machine system to be developed was studied. Important proficient techniques in manufacturing industries are becoming extinct because of insufficient succession to next generation. The proficient machine system was proposed to cope with such situation. This machine system includes the mechanism for progress and evolution of techniques and sensibilities to be adaptable to environmental changes by learning and recognizing various motions such as work and process. Consequently, the basic research fields are composed of thought, learning, perception and action. This machine requires not only deigned fixed functions but also introduction of the same proficient concept as human being to be adaptable to changes in situation, purpose, time and machine`s complexity. This report explains in detail the basic concept, system principle, approaching procedure and practical elemental technologies of the proficient machine system, and also describes the future prospect. 133 refs., 110 figs., 7 tabs.

Machining of uranium and uranium alloys

International Nuclear Information System (INIS)

Morris, T.O.

1981-01-01

Uranium and uranium alloys can be readily machined by conventional methods in the standard machine shop when proper safety and operating techniques are used. Material properties that affect machining processes and recommended machining parameters are discussed. Safety procedures and precautions necessary in machining uranium and uranium alloys are also covered. 30 figures

[Comparison of machinability of two types of dental machinable ceramic].

Science.gov (United States)

Fu, Qiang; Zhao, Yunfeng; Li, Yong; Fan, Xinping; Li, Yan; Lin, Xuefeng

2002-11-01

In terms of the problems of now available dental machinable ceramics, a new type of calcium-mica glass-ceramic, PMC-I ceramic, was developed, and its machinability was compared with that of Vita MKII quantitatively. Moreover, the relationship between the strength and the machinability of PMC-I ceramic was studied. Samples of PMC-I ceramic were divided into four groups according to their nucleation procedures. 600-seconds drilling tests were conducted with high-speed steel tools (Phi = 2.3 mm) to measure the drilling depths of Vita MKII ceramic and PMC-I ceramic, while constant drilling speed of 600 rpm and constant axial load of 39.2 N were used. And the 3-point bending strength of the four groups of PMC-I ceramic were recorded. Drilling depth of Vita MKII was 0.71 mm, while the depths of the four groups of PMC-I ceramic were 0.88 mm, 1.40 mm, 0.40 mm and 0.90 mm, respectively. Group B of PMC-I ceramic showed the largest depth of 1.40 mm and was statistically different from other groups and Vita MKII. And the strength of the four groups of PMC-I ceramic were 137.7, 210.2, 118.0 and 106.0 MPa, respectively. The machinability of the new developed dental machinable ceramic of PMC-I could meet the need of the clinic.

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

OpenAIRE

Ming Cheng; Le Sun; Giuseppe Buja; Lihua Song

2015-01-01

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 perm...

Design of a real-time tax-data monitoring intelligent card system

Science.gov (United States)

Gu, Yajun; Bi, Guotang; Chen, Liwei; Wang, Zhiyuan

2009-07-01