On-line Quality Control of DC Permanent Magnet Motor Using Neural Networks

摘要

This paper addresses the use of neural network methods to perform real-time quality control in industrial assembly lines of DC Permanent Magnet Motors (PM). This task can be viewed as a difficult non-linear inverse identification problem. Due to long parameter setting time, noisy environment and in some cases human supervision requirements, these methods are not adequate for real-time applications. Moreover, PM quality control requires the satisfaction of particular specifications rather than simple model parameter identification. So neural networks seem to be a promising paradigm.