Degradation State Identification for Ceramic in Ultrasonic Motor Based on Morphological Boundary Span Analysis
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Piezoelectric ceramic cracking (PCC) is the main reason leading to failure of ultrasonic motors. To solve the problem that the fault information is too weak to reflect the cracking condition especially in the early degradation stage, a degradation state identification method based on morphological boundary span coverage statistics was proposed in this paper. Firstly, the average morphological cover area of standard data was adopted as the degradation feature for PCC. Then standard degradation state rectangles (SDSRs) were constructed based on the degradation feature. The height of SDSR was optimized to improve the classification accuracy via training data with the help of genetic algorithm. Lastly, the coverage statistics obtained by the relationship between test data’s morphological boundary span signal and the constructed SDSR can be taken as a fair indicator for the actual degradation state. The experimental results show that this method is feasible and effective, and could achieve a satisfying performance to identify the different degradation states of PCC.
KeywordsUltrasonic motor Piezoelectric ceramics Degradation state identification Morphological mathematics Genetic algorithm
This project is supported by the National Natural Science Foundation of China (Grant No. 51877070), China Postdoctoral Science Foundation (Grant No. 2017M623404), the Natural Science Youth Foundation of Hebei (Grant No. E2017208086) and the Science and Technology Research Youth Foundation for Hebei College (Grant No. QN2017329).
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