Abstract
Induction motors play an important role in the safe and efficient operation of industrial plants because they are considered inherently reliable due to their robust and relatively simple design. Therefore, there is an indispensable need to monitor their health and performance. And the detection and diagnosis of motor faults is the base to improve the efficiency of industrial plants. In this paper, a residual model-based fault detection method is proposed for steady state vibration signals of induction motors. The stationary signal had been extracted from the entire signal using data segmentation. The reference model in spectra is obtained statistically to represent the healthy condition. The ratio of RMS of residuals is used as a fault indicator for detecting motor faults. The effectiveness of the proposed approach in detecting a wide range of mechanical faults is demonstrated through the experiments applied on an 800 hp motor, and it is shown that a robust and reliable induction motor fault detection system has been produced.