Hidden semi-markov models for machinery health diagnosis and prognosis

Transactions of the North American Manufacturing Research Institute of SME

Volumn 32, Issue , 2004, Pages 199-206

  Dong, Ming ^a   He, David ^a  

^a 1120 Science and Engineering Offices   (United States)

Author keywords

Condition based maintenance; Diagnosis; Hidden semi Markov model; Prognosis

Indexed keywords

CONDITION-BASED MAINTENANCE (CBM); HIDDEN SEMI-MARKOV MODELS (HSMM); PROGNOSIS;

ALGORITHMS; COMPUTATIONAL COMPLEXITY; HEALTH; MAINTENANCE; PARAMETER ESTIMATION; PROBABILITY DISTRIBUTIONS; STATISTICAL METHODS;

DIAGNOSIS;

EID: 10044223220     PISSN: 10473025     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (12)

1. Atlas, L., M. Ostendorf and G.D. Bernard, (2000), "Hidden Markov models for monitoring machining tool-wear", ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, Vol.6, P3887-3890.
2. Baruah, P. and R.B. Chinnam, (2003), "HMMs for diagnostics and prognostics in machining processes", Proc. of the 57th Society for Machine Failure Prevention Technology Conference, Virginia Beach, VA, April 14-18.
3. Begg, C.D., T. Merdes, C. Byington and K. Maynard, (1999), "Dynamic modeling for mechanical diagnostics and prognostics", Maintenance and Reliability Conference (MARCON99).
4. Bunks, C., D. Mccarthy and A. Tarik, (2000), "Condition based maintenance of machines using Hidden Markov Models," Mechanical Systems and Signal Processing, 14(4): 597-612.
5. Dong, M. and D. He, (2003), "Hidden semi-Markov model (HSMM) based diagnostics and prognostics framework and methodology", Working Paper, Intelligent Systems Modeling & Development Laboratory, University of Illinois at Chicago.
6. Ertunc, H.M. and K.A. Loparo, (2001 a), "A decision fusion algorithm for tool wear condition monitoring in drilling", International Journal of Machine Tools and Manufacture, 41: 1347-1362.
7. Ertunc, H.M., K.A. Loparo and H. Ocak, (2001b), Tool wear condition monitoring in drilling operations using hidden Markov models (HMMs)", International Journal of Machine Tools and Manufacture, 41: 1363-1384.
8. Ferguson, J.D., (1980), "Variable duration models for speech", In Proc. Symposium on the Application of Hidden Markov Models to Text and Speech, pages 143-179.
9. Rabiner, L.R., (1989), "A tutorial on hidden Markov models and selected applications in speech recognition", Proceedings of the IEEE, 77(2):257-286.
10. Roemer, M.J. and G.J. Kacprzynski, (2000), "Advanced diagnostics and prognostics for gas turbine engine risk assessment", Proceedings of the 2000 IEEE Aerospace Conference, Big Sky, Montana, March 18-25.
11. Roemer, M.J., E.O. Nwadiogbu and G. Bloor, (2001), "Development of diagnostic and prognostic technologies for aerospace health management applications", Proceedings of the 2001 IEEE Aerospace Conference, Big Sky, Montana, March 10-17.
12. Wang, L., M.G. Mehrabi and Jr., E. Kannatey-Asibu, (2002), "Hidden Markov model-based tool wear monitoring in machining", ASME Journal of Manufacturing Science and Engineering, 124: 651-658.