Predictive Analysis of Induction Motor using Current, Vibration and Acoustic Signals

Abstract

Predictive maintenance (PdM) is a strategy for predicting when machinery will malfunction so that the part can be replaced before it fails. This helps in reducing downtime and maximizes the component lifetime. The main objective of this paper is to present a procedure to acquire and analyze electrical signals for condition monitoring of electrical machines through motor current, sound and vibration signature analysis. The parameters are monitored using sensors and the data is analysed. The data is sent to alert the user by using appropriate techniques. The benefits of the above proposed idea are increased lifetime, reduced downtime, better reliability, better profit margin and encourages a proactive workforce. This paper is mainly applicable in industries using induction motor drives like FACT, refineries, chemical industries and so on. The advantage of this method is that testing is carried out during the conventional operation of the motor and there is no need to stop and interrupt the production process which can increase the overall performance.