Research On Rotor Broken Bar Fault Diagnosis Of Asynchronous Motor

With the progress of modern science and technology as well as the development of production system, electric machines play a more and more important role in modern industrial plants. Asynchronous motors are widely used in the industrial and agricultural production because of its simple structure, low price, high reliability and convenient maintenance. With the rapid development of the modern industrial system, the capacity of a single motor is keeping increasing and the load is also becoming more complicated now. A motor failure not only can result in damage to the motor, but also can result in unscheduled machine downtime and the shutdown of a production line, which will cause heavy financial losses and catastrophic failure. Statistical studies have shown that the rotor broken bar fault, which account for nearly 10% of total asynchronous motor failures, is the most familiar fault for asynchronous motors. Consequently, researches on rotor broken bar fault diagnosis able to detect this kind of fault at an early stage and also to allow for carefully planed repair actions are of great theoretical significance and socioeconomic benefits, which has turned to be the hotspot of research for scholars in the world. This paper presents two methods to diagnose rotor broken bar fault based on normal and Breakdown Stator current signals of asynchronous motor.The transformation theory of wavelet has mainly been studied in this thesis. The characteristics of wavelet transformation and other transformation have been analyzed in principle, for example, Fourier, the short-time Fourier transformation and so on. In view of the fact that the wavelet transformation has the multi-resolution, it is advantageous that wavelet transformation can diagnose faults accurately and withdraw characteristic compared to Fourier transformation. As described, the Rotor breakdown diagnosis to motor is done using the wavelet transformation in this article. Author emphasized on de-noise way by the fluctuation threshold. It is necessary for the procedure computation to realize de-noise only using the way of improvement fluctuation threshold with no prior-knowledge. The method is proved that it can not only make signal no-distorted but also obtain good de-noise effect after comparing this kind of way with ones of wavelet packet de-noise.When carries on the fault signal diagnosis to the fault simulation laboratory bench, article basis electric motor rotor breakdown mechanism. After de-noised using the fluctuation threshold, Stator current signals which are obtained in the experiment are decomposed into six levels using wavelet packet. Author compares energy of specific frequency bands of fault with ones of normality and makes faults definite after unifying the spectrograph by restructuring. Therefore the faults are found accurately. Next, this article also introduced based on the Park's vector transform in rotor broken bar fault diagnosis of asynchronous machine. Because of the frequency spectrum is complex, the characteristic frequency ingredient's peak-to-peak value is often small, when and the base frequency component is very close, is easily submerged by base frequency and "side lobe". However, asynchronous motor breakdown monitoring method based on the Park's vector transform may overcome this shortcoming.