Lin Lingyan

The intelligent fault modeling of induction motor

The study of early intelligent obstacle diagnosis for large-sized mechanical equipment is of momentous social significance and far-reaching economic importance. The equipment directly influences production safety for enterprises, and concern economic efficiencies. So it is very important for the induction motor to guarantee non-failure work time and the whole cutting process without fault. The early-term fault and in-time diagnosis, however, is the most basic prerequisite for the amount ahead of schedule of maintenance.

The Early Fault Diagnosis Method of Induce Motor Based on Gray Prediction Nerve Network

It makes diagnosis of induce motor very complex that it’s fault omens and feature is non-linear. It is more difficult to get earlier period fault information and realize function reflection between information and running state. As the knowledge limitation and parameter change in running of induce motor, the gray prediction combined with the nerve network is used to predict feature parameter and future running state.