An online detection method for incipient motor faults based on multitaper spectrum estimates

In order to detect weak fault eigenfrequency submerged in noises environment, a multitaper-based detection method was developed for incipient motor faults. The tradeoff problem between frequency resolution and variance was studied, and the optimal tradeoff value was chosen to be applied on detecting motor faults. By selecting high energy tapers, the root leakage of eigenfrequency was eliminated, and the shape of eigenfrequency was changed to be distinguishable. Simulation studies were conducted and results show that multi-taper method has a more steady and antinoise performance compared with other methods. Finally, an experiment was arranged in laboratory, and the bear faults were put into the motor. By using the method proposed, it is validated that multi-taper method is effective for detecting the motor incipient faults.