Artificial neural networks for real-time fault diagnostics in asynchronous electric drives

Abstract

The possibility of developing diagnostic systems for controllable asynchronous electric drives on the basis of neural networks combined in a decision-making system for the identification of various defects and determination of a rational diagnostic sequence is considered. The number of determinable diagnostic variables of the object permitting relatively reliable defect detection under external perturbations is optimized