Dissertation of fault detection in induction motor using neural network

Dissertation of fault detection in induction motor using neural network
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Stator winding inter-turn short-circuit detection in

For accurate fault diagnosis, time-frequency signal analysis based on the discrete wavelet transform (DWT) is adopted to extract the most salient features related to faults, and the artificial neural network (ANN) is used for faults classification.

Dissertation of fault detection in induction motor using neural network
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CiteSeerX — Fault Detection and Diagnosis in an Induction

The Pennsylvania State University The Graduate School A PROBABILISTIC FRAMEWORK FOR FAULT DETECTION IN INDUCTION MOTORS A Thesis in Electrical Engineering

Dissertation of fault detection in induction motor using neural network
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Detection of Induction Motor Faults: A Comparison of

In this section, the proposed method using energy level of high frequency signal extracted by discrete wavelet transform and neural network configuration for detection system will be explained. The flowchart of our proposed method is shown in Fig. 1. In this figure, motor current signal is measured and converted to digital data.

Dissertation of fault detection in induction motor using neural network
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CiteSeerX — Fault Classification of a Doubly FED Induction

10 Designing Artificial Neural Networks for Fault Detection in Induction Motors Artificial Neural Networks and the Analysis of Faults in Induction Motors The first using of ANN can be taken away to the 1940’s. However. the main works in this area (ANN) have been done recent ten years. One of the major paradigms of it is feed-forward networks.

Dissertation of fault detection in induction motor using neural network
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Broken Rotor Bar Fault Detection of Induction Motors Using

Condition monitoring of induction motors is a fast emerging technology in the field of electrical equipment maintenance and has attracted more and more attention worldwide as the number of unexpected failure of a critical system can be avoided. Keeping this in mind a bearing fault detection scheme of three-phase induction motor has been attempted.

Dissertation of fault detection in induction motor using neural network
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Vibration signal analysis for electrical fault detection

Dissertation Of Fault Detection In Induction Motor Using Neural Network You may also order essay now by contacting our support team and saying write essays for me. Thanks for friendly and qualitative service! We are looking for an efficient, courteous Cashier who …

Dissertation of fault detection in induction motor using neural network
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Induction motors bearing fault detection using pattern

Feb 01, 2006 · In this paper we present the comparison results of induction motor fault detection using stator current, vibration, and acoustic methods. A broken rotor bar fault and a combination of bearing faults (inner race, outer race, and rolling element faults) were induced into variable speed three-phase induction motors. Both healthy and faulty signatures were acquired under different speed and …

Dissertation of fault detection in induction motor using neural network
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Fourier and wavelet transformations application to fault

In this paper bearing fault detection algorithm of an induction motor using CWT as an advanced signal-processing tool is presented. With scale variation excellent results were obtained as compared

Dissertation of fault detection in induction motor using neural network
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Stator inter-turn fault detection of an induction motor

Apr 01, 2012 · Read "Temporary short circuit detection in induction motor winding using combination of wavelet transform and neural network, Expert Systems with Applications" on DeepDyve, the largest online rental service for scholarly research with thousands of academic publications available at …

Dissertation of fault detection in induction motor using neural network
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Rotor failure detection of induction motors by wavelet

Sep 23, 2004 · In this paper, we introduce a new bearing fault detection and diagnosis scheme based on hidden Markov modeling (HMM) of vibration signals. Features extracted from amplitude demodulated vibration signals from both normal and faulty bearings were used to train HMMs to represent various bearing conditions.

Dissertation of fault detection in induction motor using neural network
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Real-time condition monitoring on VSD-fed induction motors

Feb 12, 2010 · Read "Fourier and wavelet transformations application to fault detection of induction motor with stator current, Journal of Central South University of Technology" on DeepDyve, the largest online rental service for scholarly research with thousands of academic publications available at …

Dissertation of fault detection in induction motor using neural network
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Noninvasive Methods for Condition Monitoring and

This study deals with a simple technique for detection of IMs stator turn-faults. The proposed approach is based on analysis of modal voltage (MV) and modal current (MC) of the stator. Envelope of the MC is derived and its autocorrelations are considered as the fault detection criterion.

Dissertation of fault detection in induction motor using neural network
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Shock and Vibration - hindawi.com

based on current and vibration monitoring have been proposed using FFT and wavelet analysis for preventive monitoring of induction motors resulting in countless techniques for diagnosing specific faults, arising the necessity for a generalized technique that allows multiple fault detection. The paper is focused on the so-

Dissertation of fault detection in induction motor using neural network
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Stator Winding Inter-turn Insulation Fault Detection in

Three Phase Induction motor is the major running part in the Industries and is the most used electrical machines. Hence detection of faults in the motor is very important in order to improve the performance of the induction motor, avoid the production lost and also to reduce the operational costs. The

Dissertation of fault detection in induction motor using neural network
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A Survey Paper on FPGA-Based Broken Bar Detection of

Abstract. This paper describes an approach for detection of the supply unbalance condition in induction motors by using data mining process. Simulation results have shown that a good indicator of the fault is the amplitude of the second harmonic of the supply frequency component (2 f ) in the signal obtained by the differences in supply current zero crossing instants.

Dissertation of fault detection in induction motor using neural network
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Industrial Robot Backlash Fault Diagnosis Based on

Vibration signal analysis for electrical fault detection of induction machine using neural networks Article in Neural Computing and Applications 20(2):183-194 · March 2011 with 126 Reads

Dissertation of fault detection in induction motor using neural network
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The Pennsylvania State University The Graduate School A

forms in each element of a three-phase energy-saving small-size induction motor. Other techniques that have also been used for induction motor fault detection are statistical analyses. In [28], a neural-network-based fault-detection scheme is developed, which receives simple statistical parame-

Dissertation of fault detection in induction motor using neural network
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DESIGNING ARTIFICIAL NEURAL NETWORKS FOR FAULT

This paper proposes an intelligent method based on artificial neural networks (ANNs) to detect bearing defects of induction motors. In this method, the vibration signal passes through removing non-bearing fault component (RNFC) filter, designed by neural networks, in order to remove its non-bearing fault components, and then enters the second neural network that uses pattern recognition

Dissertation of fault detection in induction motor using neural network
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Detection of Induction Motor Faults: A Comparison of

This paper describes several artificial neural network architectures for real time application in incipient fault detection of induction machines. The artificial neural networks perform the fault detection in real time, based on direct measurements from the motor, and no rigorous mathematical model of the motor …

Dissertation of fault detection in induction motor using neural network
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Fault Detection (Condition Monitoring) of Induction Motor

REAL TIME APPLICATION OF ARTIFICIAL NEURAL NETWORKS FOR INCIPIENT FAULT DETECTION OF INDUCTION MACHINES Mo-yuen Chow Sui Oi Yee Department of Electrical and Computer Engineering North Carolina State University ABSTRACT This paper describes several artificial neural network architectures for real time application in incipient

Dissertation of fault detection in induction motor using neural network
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HMM-Based Fault Detection and Diagnosis Scheme for Rolling

Jan 18, 2011 · This paper presents the development of an online electrical fault detection system that uses neural network modeling of induction motor in vibration spectra. The short-time Fourier transform is used to process the quasi-steady vibration signals for continuous spectra so that the neural network model can be trained.

Dissertation of fault detection in induction motor using neural network
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Temporary short circuit detection in induction motor

such as support vector machine [17], [20], neural networks [21], genetic algorithms [22] and fuzzy logic are developed to increase the accuracy of fault detection. The state of the art in condition monitoring of induction motor uses wired sensors, usually of a single modality, to track faults …

Dissertation of fault detection in induction motor using neural network
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Megha Singh - Senior Research Fellow - Micro-grid and Real

Fault Detection of Induction Motor Using Fuzzy Logic - written by Mr. Chavan Mayur D, Mr. Swami P.S., Dr. Thosar A.G. published on 2013/12/25 download full article with reference data and citations

Dissertation of fault detection in induction motor using neural network
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Data mining approach for supply unbalance detection in

Free Online Library: Fault detection of induction motor ball bearings. by "Advances in Environmental Biology"; Environmental issues Algorithms Artificial neural networks Usage Ball bearings Analysis Ball-bearings Induction electric motors Induction motors Neural networks Vibration Vibration (Physics)

Dissertation of fault detection in induction motor using neural network
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Online fault detection of induction motors using

Feb 18, 2019 · A precise detection of the fault feature parameter of motor current is a new research hotspot in the broken rotor bar (BRB) fault diagnosis of induction motors. Discrete Fourier transform (DFT) is the most popular technique in this field, owing to low computation and easy realization. However, its accuracy is often limited by the data window length, spectral leakage, fence effect, etc

Dissertation of fault detection in induction motor using neural network
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REAL TIME APPLICATION OF ARTIFICIAL NEURAL NETWORKS

I am a PhD student in the Department of Electrical Engineering, IIT Jodhpur and have submitted my thesis titled 'Fault diagnosis of a three-phase induction motor using Stockwell transform and machine learning techniques'. My work has been focused on developing algorithms for fault diagnosis of bearing, stator and rotor faults in the induction

Dissertation of fault detection in induction motor using neural network
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Vibration Signal Analysis for Electrical Fault Detection

Abstract: This paper presents the development of an online electrical fault detection system that uses neural network (NN) modeling of induction motor in vibration spectra. The short-time Fourier transform (STFT) is used to process the quasi-steady vibration signals for …

Dissertation of fault detection in induction motor using neural network
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Fourier and wavelet transformations application to fault

Optimal MLP neural network classifier for fault detection of three phase induction motor. Authors: Vilas N. Ghate: Faculty in Electrical Engineering, Government …

Dissertation of fault detection in induction motor using neural network
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Dissertation Of Fault Detection In Induction Motor Using

In this paper, an application of the motor current signature analysis (MCSA) method and the fuzzy min–max (FMM) neural network to detection and classification of induction motor faults is described.

Dissertation of fault detection in induction motor using neural network
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Bearing fault detection of induction motor using wavelet

Feb 12, 2010 · Fault detection of an induction motor was carried out using the information of the stator current. After synchronizing the actual data, Fourier and wavelet transformations were adopted in order to obtain the sideband or detail value characteristics under healthy and various faulty operating conditions.

Dissertation of fault detection in induction motor using neural network
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Vibration analysis for bearing fault detection and

Induction motors are critical components for most industries and the condition monitoring has become necessary to detect faults. There are several techniques for fault diagnosis of induction motors and analyzing the startup transient vibration signals is not as widely used as other techniques like motor current signature analysis. Vibration analysis gives a fault diagnosis focused on the

Dissertation of fault detection in induction motor using neural network
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(PDF) Bearing Fault Detection of Induction Motor using

1) Master Thesis (Research Project): Online condition monitoring and fault detection of Induction motor in process control using Artificial Neural Network. Skills used C, C++, Python, Matlab/Simulink, LabVIEW and Image Processing . Tasks: Vibration analysis, Matlab, LabView, Artificial Neural Network.

Dissertation of fault detection in induction motor using neural network
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Data mining approach for supply unbalance detection in

system as data base and the discovery of potentially faults through neural network used for classification purposes during the period of work directly. Two cases considered which are no load and full load case, also design indicators showing the type of the load applyingon the mo- Bearing fault detection of induction motor using ANN based

Dissertation of fault detection in induction motor using neural network
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Vibration signal analysis for electrical fault detection

Oil Whirl Fault Detection in Induction Motors 291 A training database with 270 patterns was created for training the proposed arti fi cial neural network using measurements from different

Dissertation of fault detection in induction motor using neural network
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Multi sensor Wireless System for Eccentricity and Bearing

This paper proposes the use of independent component analysis and fuzzy neural network for online fault detection of induction motors. The most dominating components of the stator currents