Using feature selection to determine optimal depth forwavelet packet decomposition of vibration signals for ocean system reliability

Proceedings of IEEE International Symposium on High Assurance Systems Engineering

Volumn , Issue , 2011, Pages 236-243

  Wald, Randall ^a   Khoshgoftaar, Taghi M ^a   Sloan, John C ^a  

^a FLORIDA ATLANTIC UNIVERSITY   (United States)

Author keywords

Feature selection; MCM PHM; Vibration monitoring; Wavelet packet decomposition

Indexed keywords

CLASSIFICATION MODELS; COMPUTATIONAL TIME; DECOMPOSITION TREES; FREQUENCY DOMAINS; HEALTH MONITORING; HIGHER RESOLUTION; LEVEL OF DETAIL; MACHINE CONDITION MONITORING; OCEAN SYSTEM; OPTIMAL DEPTH; PREDICTION MODEL; VIBRATION DATA; VIBRATION MONITORING; VIBRATION SIGNAL; WAVE FORMS; WAVELET PACKET DECOMPOSITION; WAVELET TRANSFORMATIONS;

FEATURE EXTRACTION; MATHEMATICAL MODELS; SYSTEMS ENGINEERING; WAVELET ANALYSIS;

WAVELET DECOMPOSITION;

EID: 84856524346     PISSN: 15302059     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/HASE.2011.60     Document Type: Conference Paper

References (18)

1. R. Coifman and M. Wickerhauser. Entropy-based algorithms for best basis selection. IEEE Transactions on Information Theory, 38(2):713-718, Mar. 1992.
2. L. Eren and M. Devaney. Bearing damage detection via wavelet packet decomposition of the stator current. IEEE Transactions on Instrumentation and Measurement, 53(2):431-436, April 2004.
3. K. Gao, T. M. Khoshgoftaar, H. Wang, and N. Seliya. Choosing software metrics for defect prediction: an investigation on feature selection techniques. Software: Practice and Experience, 41(5):579-606, 2011.
4. M. Hall, E. Frank, G. Holmes, B. Pfahringer, P. Reutemann, and I. H. Witten. The WEKA data mining software: An update. SIGKDD Explor. Newsl., 11(1):10-18, 2009.
5. J.-G. Han, W.-X. Ren, and Z.-S. Sun. Wavelet packet based damage identification of beam structures. International Journal of Solids and Structures, 42(26):6610-6627, 2005. (Pubitemid 41455674)
6. P. Jayaswal, S. Verma, and A. Wadhwani. Application of ANN, fuzzy logic and wavelet transform in machine fault diagnosis using vibration signal analysis. Journal of Quality in Maintenance Engineering, 16(2):190-213, 2010.
7. T. M. Khoshgoftaar, K. Gao, and A. Napolitano. An empirical study of predictive modeling techniques of software quality. In Proceedings of the 5th International ICST Conference on Bio-Inspired Models of Network, Information, and Computing Systems (BIONETICS'10), December 2010.
8. X. Li, L. Qu, G. Wen, and C. Li. Application of wavelet packet analysis for fault detection in electro-mechanical systems based on torsional vibration measurement. Mechanical Systems and Signal Processing, 17(6):1219-1235, 2003.
9. B. Liu. Selection of wavelet packet basis for rotating machinery fault diagnosis. Journal of Sound and Vibration, 284(3-5):567-582, 2005. (Pubitemid 40643826)
10. H. Liu and L. Yu. Toward integrating feature selection algorithms for classification and clustering. IEEE Transactions on Knowledge and Data Engineering, 17(4):491-502, April 2005. (Pubitemid 40495592)
11. O. Renaud, J.-L. Starck, and F. Murtagh. Wavelet-based combined signal filtering and prediction. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 35(6):1241-1251, dec. 2005. (Pubitemid 41800423)
12. N. Seliya, T. Khoshgoftaar, and J. Van Hulse. A study on the relationships of classifier performance metrics. In 21st International Conference on Tools with Artificial Intelligence, pages 59-66, Nov. 2009.
13. Z. Sun and C. C. Chang. Structural damage assessment based on wavelet packet transform. Journal of Structural Engineering, 128(10):1354-1361, 2002. (Pubitemid 40001125)
14. J. Van Hulse, T. Khoshgoftaar, A. Napolitano, and R. Wald. Feature selection with high-dimensional imbalanced data. In Data Mining Workshops, 2009. ICDMW '09. IEEE International Conference on, pages 507 -514, dec. 2009.
15. R. Wald, T. M. Khoshgoftaar, J. C. Sloan, and P.-P. Beaujean. A streaming wavelet packet decomposition approach for real-time vibration analysis. In Proceedings of the 17th ISSAT International Reliability and Quality in Design Conference, pages 359-363, August 2011.
16. H.Wang, T. Khoshgoftaar, and K. Gao. A comparative study of filter-based feature ranking techniques. In Proceedings of the 11th IEEE International Conference on Information Reuse and Integration (IRI), pages 43-48, August 2010.
17. I. H. Witten and E. Frank. Data mining: Practical machine learning tools and techniques with Java implementations. SIGMOD Rec., 31(1):76-77, 2002.
18. G. Yen and K.-C. Lin. Conditional health monitoring using vibration signatures. In Proceedings of the 38th IEEE Conference on Decision and Control, volume 5, pages 4493-4498, 1999. (Pubitemid 30574903)