In this paper, two prognostics algorithms to accurately predict the state of a complex system as a function of time are presented. The algorithms are developed based on a hidden semi-Markov model (HSMM) and validated on a real-world helicopter rotor track and balance prognosis problem. It is shown that the developed prognostic algorithms provide a good performance in predicting the time to the next required rotor track and balance action for two different application scenarios.
Probabilistic model based algorithms for prognostics
2006 IEEE Aerospace Conference ; 10 pp.
2006-01-01
316525 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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