Bearing Fault Detection for Railway Traction Motors through Leakage Current

Many researches on detecting machinery faults in the early stage are being conducted for the purpose of preventing failure and reducing maintenance effort simultaneously. In this paper, a bearing fault detection method for a railway traction motor through leakage currents is proposed. The proposed detection method combines octave band analysis and machine learning. The abnormality simulation experiments with an inner race fault bearing are conducted and the effectiveness of the proposed method is verified. From the experiments, it is confirmed that the proposed method can detect failures of railway traction system well at specific conditions and leakage currents have potentials to be used for a bearing fault detection.