Fatigue crack fault diagnosis and prognosis based on hidden semi‐Markov model

Abstract

Aiming at the fault diagnosis and remaining useful life (RUL) prediction of fatigue cracks of a helicopter main gearbox planet carrier, this article proposes a hidden semi-Markov model (HSMM) methodology, which introduces the explicit state durational distribution parameters into the traditional hidden Markov model (HMM), thus overcoming the limitation of exponential distribution in HMM, retaining strong pattern recognition and classification ability, and improving the diagnostic and prognostic accuracy, and the effectiveness of the method was verified through experiments.