Research On Fault Prediction Algorithm Based On Continuous Hidden Markov Model

With the rapid development of science and technology,engineering systems applied in various fields are more complicated and the degree of integration is becoming higher and higher,and people's demand for system reliability and safety is also increasing.In order to avoid economic losses and serious accidents,early detection of failures and anticipation of failures are indispensable and important steps in modern industrial production.In view of this,this paper studies the fault detection and fault prediction of continuous hidden Markov model,compares them with PCA fault detection method and Hidden Markov model multi-step fault prediction,respectively and performs corresponding simulation verification in TE procedure.This paper mainly studies two aspects of fault detection and fault prediction algorithm in fault prediction.This paper proposes a new fault detection algorithm based on continuous hidden Markov model.Firstly,it uses PCA to reduce the dimension of data,and then it performs model training.Under the condition of obtaining the continuous hidden Markov model,a new conditional probability is constructed.The fault detection index compares the threshold and test data statistics to determine whether the system is faulty.The simulation results are compared with the fault detection algorithm based on principal component analysis to verify the feasibility of this method.Finally,based on hidden Markov model,using the structure and relationship between hidden Markov models,a multi-step fault prediction algorithm based on continuous hidden Markov model is proposed.The multi-step fault prediction of the Markov model is compared in the TE process and it is Shows the effectiveness of the proposed method.