Fault prognostic of bearings by using support vector data description

PHM 2012 - 2012 IEEE Int. Conf.on Prognostics and Health Management: Enhancing Safety, Efficiency, Availability, and Effectiveness of Systems Through PHM Technology and Application, Conference Program

Volumn , Issue , 2012, Pages

  Benkedjouh, T ^a   Medjaher, K ^b   Zerhouni, N ^b   Rechak, S ^c  

^a ECOLE MILITAIRE POLYTECHNIQUE   (Algeria)

^b FEMTO ST INSTITUTE   (France)

^c ENSP   (Algeria)

Author keywords

Condition Based Maintenance; Diagnostic; Feature extraction and reduction; Prognostic; Remaining Useful Life; Support Vector Data Description

Indexed keywords

CONDITION BASED MAINTENANCE; DIAGNOSTIC; PROGNOSTIC; REMAINING USEFUL LIVES; SUPPORT VECTOR DATA DESCRIPTION;

FEATURE EXTRACTION; PRINCIPAL COMPONENT ANALYSIS; SYSTEMS ENGINEERING; TESTING;

HEALTH;

EID: 84868227291     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICPHM.2012.6299511     Document Type: Conference Paper

References (13)

1. M. Lebold, M. Thurston, Open standards for condition-based maintenance and prognostic systems, in: Proc. 5th Maintenance and Reliability Conference (MARCON), 2001.
2. A. K. Jardine, D. Lin, D. Banjevic, A review on machinery diagnostics and prognostics implementing condition-based maintenance, Mechanical Systems and Signal Processing 20 (7) (2006) 1483-1510.
3. A. Heng, A. C. Tan, J. Mathew, N. Montgomery, D. Banjevic, A. K. Jardine, Intelligent condition-based prediction of machinery reliability, Mechanical Systems and Signal Processing 23 (5) (2009) 1600-1614.
4. D. Tax, R. Duin, Support vector data description, Machine Learning 54 (1) (2004) 45-66.
5. S. W. Lee, J. Park, S. W. Lee, Low resolution face recognition based on support vector data description, Pattern Recognition 39 (9) (2006) 1809-1812.
6. X. Dong, H. Zhao, Z. Wan, Support vector domain description for speaker recognition, in: Proceedings of the 2001 IEEE Signal Processing Society Workshop, 2001, pp. 481-488.
7. K. Sjöstrand, M. S. Hansen, H. B. Larsson, R. Larsen, A path algorithm for the support vector domain description and its application to medical imaging, Med. Image Anal. 11 (2007) 417-428.
8. L. Lingjun, H. Jie, H. Wei, D. Xinmin, H. Zhengjia, Condition evaluation for mechanical equipment by means of support vector data description, Chinese Journal of Mechanical Science and Technology 24 (12) (2005) 1426-1429.
9. D. Tax, R. Duin, Support vector domain description, Pattern Recognition Letters 20 (11-13) (1999) 1191-1199.
10. V. Vapnik, The Nature of Statistical Learning Theory, Springer, New York, 1995.
11. S. Guo, L. Chen, J. Tsai, A boundary method for outlier detection based on support vector domain description, Pattern Recognition 42 (2009) 77-83.
12. A. Malhi, R. Gao, PCA-based feature selection scheme for machine defect classification, IEEE Transactions on Instrumentation and Measurement 53 (2004) 1517-1525.
13. Ddtool, in: http://www-ict.ewi.tudelft.nl/-davidt/dd-tools.html.