Deep learning based optimum fault diagnosis of electrical and mechanical faults in induction motor

Among all the motors Induction motor (IM) plays a vital role in industry and the demand for their reliability and safe operation is increasing day by day. They are reliable but they do wear out if not maintained timely which in turn will lead to excessive loss of revenue and also man power and this motivates us to develop an intelligent methodology for diagnostic of incipient faults in Induction Motor. This paper focuses on the development of optimum Deep Learning based diagnostic technique to detect the mechanical and electrical faults in Induction Motor. Here, mechanical and electrical faults of different severity level are being tested on machine fault simulator using acquired current and vibrational signals. In this work, optimum model of Deep Neural Network (DNN) based on critical vibration and current features is developed and finally used to timely and effectively detect that which kind of faults the given IM is dealing with. The results are added and discussed in the result and discussions.