Low-Speed Mini-Motor Failure Recognition Using Fuzzy Theory

摘要

This paper proposal a method of fault diagnosis for low-speed mini-motor withacoustics signals under the motor is not disassembling condition. A new probability concept of fuzzy events is applied in the method. The condition of mini-motor running is described by membership grade set of feature value of acoustics signals. By using the inference method, a new membership set results. The new membership set not only can judges the motor quality, but also can recognize the kind of motor failure. The high frequency spectrum energy of acoustics signals and low frequency spectrum energy of acoustics signal is applied in the method as optimal feature value. Actual experiment results and numerical simulation's results show the method of the combination fuzzy theory is very effectively method for fault diagnosis of low-speed mini-motor.