Fault detection and prognosis methods for a monitoring system of rotating electrical machines

IEEE International Symposium on Industrial Electronics

Volumn , Issue , 2010, Pages 2085-2090

  Ciandrini, Chiara ^a   Gallieri, Marco ^a   Giantomassi, Andrea ^a   Ippoliti, Gianluca ^a   Longhi, Sauro ^a  

^a UNIVERSITÀ POLITECNICA DELLE MARCHE   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

COST OF PRODUCTIONS; EXPERIMENTAL SYSTEM; LABORATORY SCALE; MACHINE BREAKDOWN; MARKET SHARE; MONITORING SYSTEM; PRODUCTION COST; ROTATING ELECTRICAL MACHINES; SPARE PARTS;

ACCELEROMETERS; COMPETITION; COSTS; ELECTRIC MACHINERY; FAULT DETECTION; INDUSTRIAL ELECTRONICS; INDUSTRY; MAINTENANCE; ROTATION;

MONITORING;

EID: 78650376249     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISIE.2010.5637762     Document Type: Conference Paper

References (22)

1. Bagheri F. and Khaloozaded H. and Abbaszadeh K., Stator fault detection in induction machines by parameter estimation, using adaptive kalman filter, MED Conference on Control & Automation, 2007, Athens.
2. Taniguchi, S. and Akhmetov D. and Dote Y, Fault detection of rotating machine parts using novel fuzzy neural network, Proc of IEEE Int. Conf. on Systems, Man, and Cybernetics, 1999, vol.1, 365-369.
3. Benloucif M.L. and Balaska H., Robust Fault Detection for an Induction Machine, World Automation Congress WAC '06, 2006, Budapest.
4. Verucchi C. J. and Acosta G. G., Fault Detection and Diagnosis Techniques in Induction Electrical Machines, IEEE Trans. Latin America, 2008, Vol. 5, 41-49.
5. P.J. Tavner, Review of condition monitoring of rotating electrical machines, Electric Power Applications IET, 2008, Vol. 2, 215-247. 2
6. Liu H. and Li Z. and Zhaowei, Time frequency distribution for vibration signal analysis with application to turbo-generator fault diagnosis, Chinese Control and Decision Conference CCDC '09, 2009, Guilin.
7. Wan S. and Li H. and Li Y., Adaptive radial basis function network and its application in turbine-generator vibration fault diagnosis, Proc. on Int. Conf. on Power System Technology, 2002, Vol.3, 1607-1610.
8. Bellini, A. and Immovilli, F. and Rubini, R. and Tassoni, C., Diagnosis of Bearing Faults of Induction Machines by Vibration or Current Signals: A Critical Comparison, IEEE Industry Applications Society Annual Meeting, IAS '08, Edmonton, Alta.
9. Wu Z. and Li F. and Yan S. and Wang B., Motor Fault Diagnosis Based on the Vibration Signal Testing and Analysis, Third Int. Symposium on Intelligent Information Technology Application, 2009, Vol.2, 433-436.
10. A. Gani and M.J.E. Salami, Vibration faults simulation system (VFSS): a system for teaching and training on fault detection and diagnosis, Student Conf. on Research and Devel. Proceed., 2002, 15-18, Shah Alam, Malaysia.
11. Wei W. and Jingtao H. and Jilong Z., Prognostics of Machine Health Condition using an Improved ARIMA-based Prediction method, 2nd IEEE Conf. on Industrial Electronics and Applications ICIEA 2007, 2007, Harbin.
12. Hang X. and Guangrui W., Long-Term Vibration Trend Prediction of Rotor System State Based on Support Vector Regression and Discrete Wavelet Decomposition, International Workshop on Intelligent Systems and Applications, ISA 2009, Wuhan.
13. P. W. Tse and D. P. Atherton, Preditcion of Machine Deterioration Using Vibration Based Fault Trends and Recurrent Neural Networks, J. Vib., 1999, Vol. 121, 355-362.
14. C. S. Kallesoe, V. Cocquempot, R. I. Zamanabadi Model Based Fault Detection in a Centrifugal Pump Application, IEEE Trans. on Contr. Sys. Tech., 2006, Vol. 14, No. 2, 204-215.
15. M. A. A. Elmaleeh, N. Saad, N. Ahmed, M. Awan, On-line Fault Detection & Diagnosis of Rotating Machines using Acoustic Emission Monitoring Techniques, Int. Conf. on Intelligent and Advanced Systems, 2007, Kuala Lumpur.
16. A. Sadoughil, H. Behbahanifardl, A Pratical Bearing Fault Di-agnoser, Int. Conf. on Condition Monitoring and Diagnosis, 2008, Beijing China.
17. S. Goto and Y. Afachi and S. Katafuchi and T. Furue and Y. Uchida and M. Sueyoushi and H. Hatazaki and Masatoshi Nakamura On-Line Deterioration Prediction and Residual Life Evaluation of Rotating Equipment Based on Vibration Measurement, Proceedings of the SICE Conference, 2008, pp. 812: 817, Japan.
18. A. Lachouri, K. Baiche, R. Djeghader, N. Doghmane, S. Ouhtati Analyze and Fault Diagnosis by Multi-scale PCA, Int. Conf. on Information and Communication Technologies: From Theory to Applications, 2008, Damascus Syria.
19. J.E. Jackson and G.S. Mudholkar Control procedures for residuals associated with principal component analysis, Technometrics, Vol. 21, 341-349, 1979.
20. H. Su, K. To Chong, Induction Machine Condition Monitoring Using Neural Network Modeling, IEEE Trans. Indust. Ele., 2007, vol. 54, no. 1.
21. PCB Piezotronics, Inc., http://www.pcb.com/, 2009.
22. National Instruments, Inc., http://www.ni.com, 2009.