Broken Rotor Bar Fault Detection and Classification Using Wavelet Packet Signature Analysis Based on Fourier Transform and Multi-Layer Perceptron Neural Network
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Title
Broken Rotor Bar Fault Detection and Classification Using Wavelet Packet Signature Analysis Based on Fourier Transform and Multi-Layer Perceptron Neural Network
Authors
Keywords
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Journal
Applied Sciences-Basel
Volume 8, Issue 1, Pages 25
Publisher
MDPI AG
Online
2017-12-26
DOI
10.3390/app8010025
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Related references
Note: Only part of the references are listed.- A survey on time and frequency characteristics of induction motors with broken rotor bars in line-start and inverter-fed modes
- (2015) Vahid Ghorbanian et al. MECHANICAL SYSTEMS AND SIGNAL PROCESSING
- Condition monitoring of induction motors: A review and an application of an ensemble of hybrid intelligent models
- (2014) Manjeevan Seera et al. EXPERT SYSTEMS WITH APPLICATIONS
- An algorithm for improving the coefficient accuracy of wavelet packet analysis
- (2013) Xintao Jiao et al. MEASUREMENT
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- (2013) Zhipeng Feng et al. MECHANICAL SYSTEMS AND SIGNAL PROCESSING
- A new diagnosis of broken rotor bar fault extent in three phase squirrel cage induction motor
- (2013) Pu Shi et al. MECHANICAL SYSTEMS AND SIGNAL PROCESSING
- Wavelets for fault diagnosis of rotary machines: A review with applications
- (2013) Ruqiang Yan et al. SIGNAL PROCESSING
- Fault diagnosis and prognosis using wavelet packet decomposition, Fourier transform and artificial neural network
- (2012) Zhenyou Zhang et al. JOURNAL OF INTELLIGENT MANUFACTURING
- Novel indices for broken rotor bars fault diagnosis in induction motors using wavelet transform
- (2012) Bashir Mahdi Ebrahimi et al. MECHANICAL SYSTEMS AND SIGNAL PROCESSING
- A new method for early fault detection and diagnosis of broken rotor bars
- (2011) Ilhan Aydin et al. ENERGY CONVERSION AND MANAGEMENT
- Temporary short circuit detection in induction motor winding using combination of wavelet transform and neural network
- (2011) D.A. Asfani et al. EXPERT SYSTEMS WITH APPLICATIONS
- Rotor fault condition monitoring techniques for squirrel-cage induction machine—A review
- (2011) Mohammad Rezazadeh Mehrjou et al. MECHANICAL SYSTEMS AND SIGNAL PROCESSING
- Early fault diagnosis of rotating machinery based on wavelet packets—Empirical mode decomposition feature extraction and neural network
- (2011) G.F. Bin et al. MECHANICAL SYSTEMS AND SIGNAL PROCESSING
- Online Detection of Broken Rotor Bars in Induction Motors by Wavelet Packet Decomposition and Artificial Neural Networks
- (2009) A. Sadeghian et al. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
- Use of autocorrelation of wavelet coefficients for fault diagnosis
- (2009) J. Rafiee et al. MECHANICAL SYSTEMS AND SIGNAL PROCESSING
- A novel technique for selecting mother wavelet function using an intelli gent fault diagnosis system
- (2008) J. Rafiee et al. EXPERT SYSTEMS WITH APPLICATIONS
- On the Use of a Lower Sampling Rate for Broken Rotor Bar Detection With DTFT and AR-Based Spectrum Methods
- (2008) B. Ayhan et al. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
- Advances in Diagnostic Techniques for Induction Machines
- (2008) A. Bellini et al. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
- Unified time–scale–frequency analysis for machine defect signature extraction: Theoretical framework
- (2008) Changting Wang et al. MECHANICAL SYSTEMS AND SIGNAL PROCESSING
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