Hidden Markov Models for the Prediction of Impending Faults

Reliability and safety are two important concepts in industrial applications. Thus, the development of monitoring tools, which are able to ensure the continuity of service by predicting faults, should improve competitiveness. This paper presents two probabilistic methods based on hidden Markov models (HMMs) for the prediction of impending faults. This paper shows that a prediction of faults is not limited to the estimation of the remaining useful life but is also extended to the estimation of the risk of an imminent appearance of faults in the future. The first method consists in modeling the degradation process of the studied system by a single HMM. A probabilistic model is proposed to predict an imminent appearance of a fault. The second method consists in modeling the degradation states by a set of HMMs. Another probabilistic model is proposed to predict an imminent appearance of a fault. An experimental application is proposed to demonstrate their applicability. The obtained results show their effectiveness to predict the imminent appearance of faults.