时变负载下笼型电机转子断条故障诊断方法.

Under time-varying loads, the stator current of cage motors shows non-stationary and non-periodic, which makes the existing rotor broken bar fault identification method under time- varying loads fail to diagnose due to the influence of the fundamental frequency modulation of the current. This paper proposes a time-varying load cage motor diagnostic method based on the Teager-Kaiser energy operator (TKEO), a new method for rotor broken bar fault diagnosis. The method used TKEO to extract the instantaneous frequency of the current signal to determine the severity of the broken bar fault of the motor. In order to verify the effectiveness and superiority of the method the current signals under different health states and different load conditions were ex- perimentally obtained and diagnosed. The analysis results were also compared with the traditional method. In multiple dimensions. The results show that this method is able to distinguish the health state of the motor more accurately under time-varying loads and has stronger robustness. to load disturbances; especially under light-load operation. the numerical difference of the relative change gradient of the method is 4~6 times higher in comparison with that of the traditional method. In addition, the extracted fluctuation range of the fault frequency is more concentrated in the range between 0~5 Hz. [ABSTRACT FROM AUTHOR]