Negative selection algorithm-based motor fault diagnosis

Abstract

In this paper, a Negative Selection Algorithm (NSA)-based motor fault diagnosis scheme is proposed. The hierarchical fault diagnosis scheme takes advantage of the feature signals of the healthy motors so as to generate the NSA detectors, and uses the analysis of the activated detectors for fault diagnosis. It can not only efficiently detect incipient motor faults but also correctly identify the corresponding fault types. Our method has been investigated using one practical motor fault diagnosis example. © 2011 Springer-Verlag Berlin Heidelberg.