Diagnosis and fault detection in electrical machines and. E cient sensor fault diagnosis in wireless sensor networks by chun lo a dissertation submitted in partial ful llment of the requirements for the degree of doctor of philosophy electrical engineering. Principles of systematic fault diagnosis diagnosis of faults requires a logical and disciplined approach. Then we combine the advantages of kernel density estimation.
Implementing an expert system for fault diagnosis of. In order to verity the validity of the proposed method of fault diagnosis in power electronic circuits, we take the following three classes of fault sample sets. With increasing demands for efficiency and product quality plus progress in the integration of automatic control systems in highcost mechatronic and safetycritical processes. Fault detection and diagnosis of induction motors based on higherorder spectrum juggrapong treetrong abstract the number of research studies have shown that the fault in the stator or rotor generally show sideband frequencies around the mains frequency 50hz and it higher harmonics in the spectrum of the motor current signature. A study of fault detection and diagnosis for plc controlled. Any attempt of developing an expert system dealing with car failure detection has to overcome various difficulties. An expert system for fault diagnosis, repairing and. Basic electrical measurements e80 feb 26, 2012 prof. The procedure of fault diagnosis for analog circuits can be generally classified into four stages. The flow chart of the proposed software for fault diagnosis, repairing and maintenance of electrical machines is shown in fig.
Pdf testing methods for fault detection in electronic. Finally, the diagnosis system can be used to diagnose the fault type of airconditioning system. In generally, detection and diagnosis of incipient faults is desirable for product quality assurance and. Neuralnetworkbased motor rolling bearing fault diagnosis bo li, student member, ieee, moyuen chow, senior member, ieee, yodyium tipsuwan, student member, ieee, and james c.
One of those testing methods is the quiescent current testing which is now widely used due to the high fault coverage it. Find machakos institute of technology electrical measurements and fault diagnosis previous year question paper. Fault diagnosis the fault diagnosis module produces a diagnosis of the detected faults so that appropriate actions may be undertaken to correct the faults fig. Artificial neural networks for power transformers fault. Put the line and neutral in the jaws, and you can measure the imbalance between the two and hence the total leakage to earth of the system. Vibration and current monitoring for faults diagnosis of. E cient sensor fault diagnosis in wireless sensor networks. Various techniques for condition monitoring of three phase.
Electronic testing and fault diagnosis 3rd edition 3rd edition. Their study results showed that fuzzy logic can be used for accurate bearing fault diagnosis if the input data are processed in an advantageous way. Then, fault types are identified through the pattern recognition classifier, based on svm. The authors combine it with additional diagnostic test generation to improve the precision and. Subramanyam defence metallurgical research laboratory, india k. Most of the time this involves an extensive examination of the gasinoil concentrations, and compare the results of. Generally the fault diagnosis has been analysed directly with machines parts. Input design for active fault diagnosis squarespace. Most engine faults can be classified into two categories. Sinclair electronics fault diagnosis fountain press argus books ltd. Chapter 4 neural network based transformer fault diagnosis. Hung, fellow, ieee abstract motor systems are very important in modern society. Fault detection and diagnosis of induction motors using.
A matlab and simulink based threephase inverter fault. Keywords fault diagnostics, fault detection, test methods, buildings, hvac, simulation, energy economy. Numerous researches have indicated that analog circuit fault diagnosis is a significant fundamental for design validation and performance evaluation in the integrated circuit manufacturing fields. Any attempt of developing an expert system dealing with car failure detection has to. Various testing methods have been proposed for testing digital circuits. Demonstrating a fault diagnostic method in an automated, computer.
Non destructive analysis of three phase induction machine. Pattern recognition for fault detection, classification. Motor current signature analysis and its applications in induction motor fault diagnosis neelam mehala, ratna dahiya abstractthe motor current signature analysis mcsa is considered the most popular fault detection method now a day because it can easily detect the common machine fault such as turn to turn short ckt. The proposed fault diagnostic system requires about six cycles to clear an opencircuit or shortcircuit fault. Thermal imaging for electrical mechanical diagnostics. An algorithm for multiple fault diagnosis has been described in 21, the method is based on very precise measurements at test points.
Traditional methods for fault detection and diagnosis rely on nominal input output. Deep pca based realtime incipient fault detection and. A sample screen of automatic diagnosis procedure is shown in fig. Automatic channel fault detection and diagnosis system for. Fault type code r 1 r 2 r 3 1 no fault 0 0 0 3 partial discharge with low energy density 0 1 0 4 partial discharge with high energy density 1 1 0 5 arcing discharge with low energy 1or 2 0 1 6 arcing discharge with high energy 1 0 2 7 thermal fault with temperature less than 150 oc 0 0 1 8. The experimental results show that the proposed system performs satisfactorily to detect the fault type, fault location, and recon. Pdf merger lite is a very easy to use application that enables you to quickly combine multiple pdfs in order to create a single document. The hypothesis test of the gaussian distribution is carried out for the submodes that are obtained. With the input of the related relay signals, the fault certainness has been increased dramatically. There are various methods for converting vibrational signals into usable information for fault diagnosis, one of which is the empirical mode decomposition method emd. Feel free to use the past paper as you prepare for your upcoming examinations. Based on the analysis and the induction of electronic control fuel injection engine common failure which cant start, and according to the engines working principle and failure mechanism, established the electronic control fuel injection engines fault tree, and having made qualitative analysis about the working reliability of the engine by using the fault tree analysis method.
Consider 3, the fault diagnosis problem consists of designing a detection. Incipient fault detection and diagnosis fdd is a key technology for enhancing safety and reliability of highspeed trains. An introduction from fault detection to fault tolerance rolf isermann on. Also an intuitive approach can be used but must be accompanied by a deductive technique. A novel fault diagnosis method of rolling bearings based. See all 7 formats and editions hide other formats and editions. A method based on s transforms and support vector machines was presented for fault diagnosis of power electronics circuits in which the s transform timefrequency analysis of the fault signal is used to extract the features corresponding to various faults. Fault diagnosis of airconditioning system using cmac. Introduction 1 test instruments 1 test instrument 1 electronic test equipment 1 chapter one 7 multimeter 7 operation of multimeter 9 quantities measured 9 power. Diagnosis and fault detection in electrical machines and drives based on advanced signal processing techniques tutor. The fourth edition of electronic fault diagnosis will assist the reader in gaining a working knowledge of fault finding on electronic instruments, circuits and systems. Artificial neural networks are potential tools for the automated fault diagnosis of ic engines, as they can learn the patterns corresponding to various faults.
Electrical measurements and fault diagnosis question. Fault detection and diagnosis of induction motors using motor. Whereas, faultmodel based test, is designed to target a specific set of. Table 3 shows codes for gas ratios used in this method while table 4hows the shows the fault diagnosis s according to rogers ratio method. Observerbased fault diagnosis of power electronics systems. Motor current signature analysis for fault diagnosis and. Using this technique you can find the problem circuit and either isolate it or go on to discover if there is a particular problem appliance. In this work, a fault detection and diagnostic module is described based on internal plc program signal data which is acquired through opc server. The proposed system is a diagnosis method for the detection of stator faults occurring in three phase squirrel cage induction motors and correction of extra signatures in the current spectrum using the combination of multisim and labview. The book presents the application of neural networks to the modelling and fault diagnosis of industrial processes. This paper discusses electrical power system fault diagnosis by means of probabilistic techniques. Fault diagnosis fault diagnosis is stage that identified the causes of faults and it can be distinguished from other irrelevant alarms. Car failure detection is a complicated process and requires high level of expertise. To avoid the unwanted shutdown and increases the serviceable life of equipment, one must go for predictive maintenance instead of the conventional time based maintenance.
Application of s transform in fault diagnosis of power. Pattern recognition for fault detection, classification, and localization in electrical power systems qais hashim alsafasfeh, phd western michigan university, 2010 the longer it takes to identify and repair a fault, the more damage may result in the electrical power system, especially in periods of peak loads, which could lead. Electronic testing and fault diagnosis 3rd edition loveday, g. The application is based on expert system techniques and its main characteristic is specialized knowledge processing through automatic evaluation. Now a days the use of condition monitoring of electrical machines are increasing due to its potential to reduce operating costs, enhance the reliability of operation and improve service to customers. This paper presents a fault detection technique and fault classification algorithm. This article is about diagnosing bearing faults using the emd method, employing nondestructive test. Sep 25, 2016 a fault diagnosis system is essential for safe and efficient usage of these inverters.
This paper develops a realtime incipient fdd method named deep principal component analysis dpca for electrical drive in highspeed trains. Based on the analysis and the induction of electronic control fuel injection engine common failure which cant start, and according to the engines working principle and failure mechanism, established the electronic control fuel injection engines fault tree, and having made qualitative analysis about the working reliability of the engine by using the fault tree analysis. Pattern recognition for fault detection, classification, and. Another technique for fault diagnosis has been proposed in 18, where measurements are transformed in multidimentional space. Sarah harriss lecture from 2009 overview circuits electrical building blocks. Frequently, past experience or detailed knowledge will help. Fault diagnosis for analog circuits by using eemd, relative. This method can effectively detect incipient faults in electrical. A new feature extraction approach is proposed by using threephase load current in threedimensional space and neural network is used to diagnose the fault. Electronic testing and fault diagnosis 3rd edition. Neuralnetworkbased motor rolling bearing fault diagnosis.
Index termsfault diagnosis, multilevel inverter, neural network nn, recon. Fault diagnosis of airconditioning system using cmac neural. Machine learning support for logic diagnosis e l i b. Faultdriven test fdt, where the main purpose is to find a faulty component which usually causes system failure. Professor mingyan liu, cochair associate professor jerome p. Specically, we discuss our development of a diagnostic capability for an electricalpowersystemtestbed,adapt,locatedatnasaames. Chapter 4 neural network based transformer fault diagnosis knowledge based power transformer incipient fault diagnosis became popular because of its simplicity, but the application of these standards requires experiences. R, l, c voltage division experimental plots time domain frequency domain bode plots. Following a brief introduction, the second chapter. The samples in which the firing angle deviates within. A fault diagnosis system is essential for safe and efficient usage of these inverters. Fault diagnosis of electric transmission lines using modular neural networks.
Sankavaram et al fault diagnosis in hybrid electric vehicle regenerative braking system there are a total of 14001 data points for each nominal and faulty case. Each combination of diagnosis code indicates a certain condition of the power transformer. Data driven fault diagnosis and fault tolerant control. In contrast to the welldeveloped diagnostic methods for digital circuits, diagnosis for analog circuits is an extremely difficult problem and an active research. Fiorenzo filippetti final dissertation on march 2014 ph. Artificial neural network based fault diagnosis of ic. Specificationdriven test sdt, where the system functionality is checked. Artificial neural network based fault diagnosis of ic engines.
These testers combine the features of the ict and the functional tester into one system. Frank where is the system state vector, with the system matrix, is the known input vector, with the input matrix, is the measurement vector, with the output matrix c, x t. To help the operator interpret the diagnosis, it includes the probability of the selected diagnosis and also provides detailed explanations of the reasons leading to the diagnosis. Fault detection and diagnosis of induction motors using motor current signature analysis and a hybrid fmmcart model. As one of the foremost stages in fault diagnosis, feature extraction methods are closely related to the efficiency of fault diagnosis. Approaches to fault diagnosis generally speaking, one can characterize approaches to fault diagnosis as databased. To avoid the unwanted shutdown and increases the serviceable life of equipment, one must go for predictive maintenance instead of the. Developed fault finding and diagnostic modules depending on measured data from the inspection machines and sensor data. Fault detection in wsn mainly depends on the different type of applications and failures. Satyanarayana defence metallurgical research laboratory, india g. By using the characteristic of selflearning, association and generalization, like the cerebellum of human being, the proposed cmac neural network fault diagnosis scheme enables a powerful, straightforward, and efficient fault diagnosis. Printed in great britain brief paper implementing an expert system for fault diagnosis of electronic equipment t.
The fundamental aspects of a wide range of circuits are explored, from simple circuits and measurements to electronic systems, oscillators, power supplies and amplifiers. Different alternatives to detect and diagnose faults in induction machines have been proposed and implemented in the last years. In short circuit fault analysis the winding will be faulted manually because of this in some cases the machine will be failed or it may affect the nearby system. Systems in the university of michigan 2014 doctoral committee. We emphasize how we have tackled two challenges, regarding modelling and realtime performance, often encountered. Electronic testing and fault diagnosis ebook, 1995. This kind of early fault diagnosis can increase machinery availability and performance, reduce consequential damage and breakdown maintenance. The system under test must meet the device requirements in order to pass the sdt. This is in response to the ever increasing requirements on the reliable.
Fault recovery after fault detection and diagnosis, fault recovery comes in picture and specify that how faults. In this paper, a novel approach to detect and classify comprehensive fault conditions of induction motors using a hybrid fuzzy minmax fmm neural network and classification and regression. A high level scheme of the model can be seen in fig. Based on the fta of electroniccontrol engine start fault. Electrical measurements and fault diagnosis question papers. They convert almost 60% of the electricity produced in the u. Condition monitoring, current spectrum, diagnostic, mcsa, stator fault, fault detection. This barcode number lets you verify that youre getting exactly the right version or.