Diagnosis of bearing fault of brushless DC motor based on dynamic neural network and orthogonal fuzzy neighborhood discriminant analysis

2014 UKACC International Conference on Control, CONTROL 2014 - Proceedings

Volumn , Issue , 2014, Pages 378-383

  Abed, Wathiq ^a   Sharma, Sanjay ^a   Sutton, Robert ^a  

^a UNIVERSITY OF PLYMOUTH   (United Kingdom)

Author keywords

dynamic neural network; Fault diagnosis; feature extraction; feature reduction; rolling element bearing

Indexed keywords

AC MOTORS; DISCRETE WAVELET TRANSFORMS; DISCRIMINANT ANALYSIS; EXTRACTION; FAILURE ANALYSIS; FAULT DETECTION; FEATURE EXTRACTION; FUZZY NEURAL NETWORKS; ROLLER BEARINGS;

DYNAMIC NEURAL NETWORKS; FAULT CLASSIFICATION; FEATURE REDUCTION; FEATURE REDUNDANCY; FUZZY NEIGHBOURHOOD; REAL TIME SIMULATIONS; ROLLING ELEMENT BEARING; VIBRATION SPECTRUM;

BRUSHLESS DC MOTORS;

EID: 84921487050     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CONTROL.2014.6915170     Document Type: Conference Paper

References (18)

1. N. Subhasis., T. Hamid A, and L. Xiaodong, "Condition Monitoring and Fault Diagnosis of Electrical Motors-A Review," IEEE Transactions on Energy Conversion vol. 20, pp. 719-729, 2005.
2. Y. Wu, H. Lai, and S. Lin, "Featur Extracrtion for Bearing detection Iden-Tification Under variable Rotation Speed " presented at the 20th International Congress on sound and Vibration Thailand, 2013.
3. Y. Zhenyu, C. Uffe., T. Morten., P. Gerulf, and B. Hakon, "A Study of Rolling-Element Bearing Fault Diagnosis Using Motors Vibration and Current Signatures," presented at the Preprints of the 7th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes, Spain, 2009.
4. I. Bediaga, X. Mendizabal, A. Arnaiz, and J. Munoa, "Ball bearing damage detection using traditional signal processing algorithms," IEEE Instrumentation & Measurement Magazine, vol. 16, pp. 20-25, 2013.
5. B. Trajin, J. Regnier, and J. Faucher, "Comparison Between Stator Current and Estimated Mechanical Speed for the Detection of Bearing Wear in Asynchronous Drives," IEEE Transactions on Industrial Electronics, vol. 56, pp. 4700-4709, 2009.
6. A. Lemos, W. Caminhas, and F. Gomide, "Adaptive fault detection and diagnosis using an evolving fuzzy classifier," Information Sciences, vol. 220, pp. 64-85, 2013.
7. A. Mahammed and T. Hiyama, "Fault Classification Based Artificial Intelligent Methods of Induction Motor " International journal of Innovative computing information and Control, vol. 7, pp. 5477-5493, 2011.
8. R. Ziani, R. Zegadi, A. Felkaoui, and M. Djouada, "Bearing Fault Diagnosis Using Neural Network and Genetic Algorithms with the Trace Criterion," Springer Berlin Heidelberg, pp. 89-96, 2012.
9. V. Sugumaran and I. Ramachandran, "Effect of number of features on classification of roller bearing faults using SVM and PSVM," Expert Systems with Applications, vol. 38, pp. 4088-4096, 2011.
10. Y. Yang, H. Wang, J. Cheng, and K. Zhang, "A fault diagnosis approach for roller bearing based on VPMCD under variable speed condition," Measurement, vol. 46, pp. 2306-2312, 2013.
11. S. Rajagopalan, J. M. Aller, J. A. Restrepo, T. G. Habetler, and R. G. Harley, "Detection of Rotor Faults in Brushless DC Motors Operating Under Nonstationary Conditions," IEEE Transactions on Industry Applications, vol. 42, pp. 1464-1477, 2006.
12. W. Xuhong and H. Yigang, "Diagonal recurrent neural network based on-line stator winding turn fault detection for induction motors," in the Eighth International Conference on Electrical Machines and Systems, 2005, pp. 2266-2269.
13. S. Gohshi, "A new signal processing method for video: reproduce the frequency spectrum exceeding the Nyquist frequency," presented at the 3rd Multimedia Systems Conference, USA, 2012.
14. Z. Zhang, Y. Wang, and K. Wang, "Fault diagnosis and prognosis using wavelet packet decomposition, Fourier transform and artificial neural network," Journal of Intelligent Manufacturing, vol. 24, pp. 1213-1227, 2013.
15. H. Ghazali, M. Mustafa, and A. Hussain, "Feature Extraction Technique using Discrete Wavelet Transform for Image Classification " in 5th Student Conference on Research and Development., Malaysia 2007.
16. M. Delgado , G. Cirrincione, and A. Garcia Espinosa, "Bearing faults detection by a novel condition monitoring scheme based on statistical-time features and neural networks," IEEE Transactions on Industrial Electronics, vol. 60, pp. 3398-3407, 2013.
17. N. Khushaba, A. Al-Ani, and A. Al-Jumaily, "Orthogonal Fuzzy Neighborhood Discriminant Analysis for Multifunction Myoelectric Hand Control," IEEE Transactions on Biomedical Engineering, vol. 57, pp. 1410-1419, 2010.
18. C. Cheol, J. Knowles, S. Fadali, and L. Kwon-Soon, "Fault Detection and Isolation of Induction Motors Using Recurrent Neural Networks and Dynamic Bayesian Modeling," IEEE Transactions on Control Systems Technology, vol. 18, pp. 430-437, 2010.