Study on Hidden Markov Models for faults diagnosis of rotor machine in the whole run-up process

If latent defects exist in the rotor machinery system,rotor vibration signals in the whole runup process can present abnormal phenomenon. Therefore study on metbods for diagnosing rotor faults in the runup process is crucial for the selection of appropriate response actions. The rotor machine faults in this process can be conridered as timedependent dynamical patterns related to the principal variables. Hidden Markov models have proven to be one of the most widely used tools for learning probabilistic models of dynamics time series. HMM can model dynamical behavior variation existing in the system through a latent variable (hidden states). It was verified that HMM can effectively model and identify the rotor machine faults in the runup process. 