Dynamic Modelling of Squirrel Cage Induction Motors for Studying Motor Current Signature Analysis

Abstract

This study investigates dynamic modelling of induction motors with a variety of different defects and condition monitoring of these. The focus is directed at squirrel cage induction motors(SCIM) which is the most used electric motor in the world. A motor with this importance needs to be monitored to decrease downtime. The condition monitoring technique used in this study is known as motor current signature analysis(MCSA). MCSA is an on-line condition monitoring technique which uses the frequency spectrum to detect abnormalities. One of its advantages is that measuring the supply current is enough, releasing the need for extra sensors with the motor. This gives the technique an edge, especially in hazardous or difficult accessible areas. There are four main categories of failure in the SCIM, these are modelled separately before being integrated to a generic model which can be used as a tool in SCIM diagnostics. The models are based on direct-quadrature(DQ) transformation in an ideal and symmetrical machine before being modified in a way that introduces different defects. Every aspect of the model is thoroughly explained with the following assumptions. The results are validated against proven scientific papers on MCSA. Since MCSA is a promising technique in monitoring of subsea induction motors, a cable model with transformers and a pulse-width modulator(PWM) source is also tested with the generic model.