In this paper, the stator winding failure diagnosis, rotor bar failure diagnosis and bearing outer ring failure diagnosis were studied.
Diagnosis experiments were performed using a Park''s vector that transforms a phase current signal into a single phase signal. The DR of the Park''s vector pattern was calculated to diagnose short-circuit failure of the stator winding fault.
The DR of the Park''s vector pattern was calculated to diagnose the short-circuit failure of the stator winding failure.
The d-q current signal, a Park''s vector conversion component, was FFT converted, and sensorless rotation speed estimation, rotor bar failure diagnosis, and bearing outer ring failure diagnosis test were performed. In addition, considering the load change condition, the test was performed by adjusting the operating speed of the motor with a dynamometer.
The stator winding fault diagnosis was performed by converting the three-phase current signal into the Park''s vector pattern and using the DR of the converted pattern.
In order to diagnose rotor bar failure and bearing outer ring failure, the rotor RSH frequency detection zone was set, and the rotation speed was estimated by detecting the frequency band where the largest amplitude occurred in the RSH zone.
Rotor bar failure was diagnosed using the frequency band of fb2, which has little interference from power frequency. Bearing failure was diagnosed by comparing normal motor amplitude and outer ring failure amplitude.
The distortion data, which are the diagnostic data of each fault, and the amplitude magnitude of each fault are averaged to remove irregular values to increase the efficiency of diagnosis. Using the moving averaged values, the prediction threshold was set as an index to measure the next data to be generated and used for diagnosis. Based on the above results, an development of electrical diagnosis system for fault detection in induction motors.