Discrete Wavelet Transform Applied to 3-Phase Induction Motor for Air Gap Eccentricity Fault Diagnosis

Abstract

Induction motors consume about 60% of the energy in industry, indicating that they are an important part of the industry. Despite their sturdy construction, these induction motors are often susceptible to damage from prolonged use without maintenance. Bearing failure accounts for up to 40% of all failures and can result in serious engine damage if not treated promptly. For effective operation, this failure must be continuously monitored, otherwise it may cause serious damage to the induction motor. Normal vibration monitoring is difficult as it requires the use of expensive sensors. To detect and localize these faults, a new method of performing leakage flux analysis is widely used. In this paper, failure due to gap eccentricity is predicted by decomposing the waveform of the leakage flux spectrum using a discrete wavelet transform. The proposed method was evaluated based on the leakage flux obtained from a 1.5 kW induction motor. Experimental results have confirmed the effectiveness of the method used to detect eccentricity failures.