A monitoring platform for induction motor diagnostic.

There is currently research in progress at the University of South Carolina to develop advanced algorithms to monitor the health of an induction motor. The goal of this research is to implement a new diagnostic tool that may help detect a failure on an induction motor at an incipient stage.

The main problem is to acquire significant data to create the experience of the ANN. In particular, for our project, we needed data of both healthy and malfunctioned motor. We plan to get the healthy motor parameters by taking appropriate measurements on a well working motor while we had to get the broken motor data via simulation because it is expensive and dangerous to test real malfunctioning motors undergoing various faulty conditions. The simulation data were obtained by using the simulation platform virtual Test Bed developed at the EE Department.

To acquire data from a healthy motor and to validate such algorithms we built a prototype monitoring platform to perform data acquisition in real-time. As part of my work at the EE Department I actually built the electronics and participated to the testing activity and preliminary data acquisition. The data gathered with the board was off by certain margin from the expected values because of the time delay. However, overall, the board was a success. The board is currently being used to more efficiently gather data for future research in monitoring the health of an induction motor.