Book ChapterDOI
Fourier and wavelet transformations for the fault detection of induction motor with stator current
Sanghyuk Lee,Sungshin Kim,Jang Mok Kim,Man Hyung Lee +3 more
- Vol. 1, pp 383-388
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TLDR
In this paper, a fault detection of an induction motor is carried out using the information of stator current, and the results of the proposed approach based on Fourier and wavelet transformations show that the faults are properly classified into six categories.Abstract:
In this literature, fault detection of an induction motor is carried out using the information of stator current. After preprocessing actual data, Fourier and wavelet transforms are applied to detect characteristics under the healthy and various faulted conditions. The most reliable phase current among 3-phase currents is selected by the fuzzy entropy. Data are trained with a neural network system, and the fault detection algorithm is carried out under the unknown data. The results of the proposed approach based on Fourier and wavelet transformations show that the faults are properly classified into six categories.read more
Citations
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Journal ArticleDOI
Rotor fault condition monitoring techniques for squirrel-cage induction machine—A review
TL;DR: A broad outlook on rotor fault monitoring techniques for the researchers and engineers can be found in this paper, where the authors review and summarize the recent researches and developments performed in condition monitoring of the induction machine with the purpose of rotor faults detection.
Journal ArticleDOI
Fault Detection and Isolation of Induction Motors Using Recurrent Neural Networks and Dynamic Bayesian Modeling
TL;DR: A new approach based on this well known scheme where a Bayesian network is used to evaluate the residuals is applied to fault detection in a three-phase induction motor.
Proceedings ArticleDOI
Short-term wind speed forecasting model for wind farm based on wavelet decomposition
TL;DR: Wavelet theory is described to decompose highly nonlinear wind speed time series into several approximate stationary time series and results indicate that wavelet Theory is a useful tool in wind speed forecasting and possesses certain actual value.
Journal ArticleDOI
Speed/position sensor fault tolerant control in adjustable speed drives - A review.
Manef Bourogaoui,Manef Bourogaoui,H. Ben Attia Sethom,H. Ben Attia Sethom,I. Slama Belkhodja +4 more
TL;DR: A bibliographical review, about Fault Detection and Isolation (FDI) and Fault Tolerant Control (FTC) in ASDs, is presented and deals with position sensor FDI and sensorless control-based FTC inASDs.
Proceedings ArticleDOI
Online current and vibration signal monitoring based fault detection of bowed rotor induction motor
TL;DR: In this paper, an online condition monitoring based fault detection of induction motor (IM) is presented, where the motor current and vibration signals are analyzed using Fast Fourier Transform (FFT) and Hilbert Transform (HT) to detect the severity of the fault.
References
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Book
A wavelet tour of signal processing
TL;DR: An introduction to a Transient World and an Approximation Tour of Wavelet Packet and Local Cosine Bases.
Book
Ten lectures on wavelets
TL;DR: This paper presents a meta-analyses of the wavelet transforms of Coxeter’s inequality and its applications to multiresolutional analysis and orthonormal bases.
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Ten Lectures on Wavelets
TL;DR: In this article, the regularity of compactly supported wavelets and symmetry of wavelet bases are discussed. But the authors focus on the orthonormal bases of wavelets, rather than the continuous wavelet transform.
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The Fourier Transform and Its Applications
TL;DR: In this paper, the authors provide a broad overview of Fourier Transform and its relation with the FFT and the Hartley Transform, as well as the Laplace Transform and the Laplacian Transform.
Journal ArticleDOI
The Fourier Transform and Its Applications
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