In order to monitor states of the rotary machine in time and ensure its performance, it is very important to analyze the evolution from the normal state to the fault state. In the paper, a new method is proposed to improve the precision of fault diagnosis. Firstly, the character extraction with mutative scales (CEMS) is applied to achieve the characteristic values. Secondly, the Hidden Semi-Markov model is built to identify the different running states. Thirdly, the new method is compared with the traditional one by the example of bushing abrasion of the connecting rod in diesel engine. According to the simulation and experiment researches, it indicates that the signal characters with more state information can be obtained pertinently by using the CEMS. And the accuracy of recognition is 97.33% in the 150 test samples, improved evidently than the traditional one. And the new character extraction method can be used in the technology domain widely.
Fault Diagnosis of Elevator Doors Using Control State Information
