A Negative Selection Algorithm-based Motor Fault Detection Scheme

摘要：

In this paper, we propose a Negative Selection Algorithm (NSA)-based motor fault detection system. Only the feature signals of the healthy motors are needed here for generating the NSA detectors. Different from the conventional fault detection approaches, no prior knowledge of the motor fault types is assumed to be known beforehand in the proposed scheme. Our motor fault detection method is examined using both the rotor and stator faults in computer simulations. We further explore its applicability in case of fault detection with varying motor loads.

关键词： Artificial Immune Systems (AIS) Negative Selection Algorithm (NSA) fault detection motors electrical machines

作者: X. Z. Gao X. Wang S. J. Ovaska A. Arkkio Kai Zenger Xiaofeng Wang

作者单位: Information Engineering College Shanghai Maritime University, Shanghai 200135, P. R. China Departmen Department of Automation and Systems Technology Aalto University School of Electrical Engineering, F Department of Electrical Engineering Aalto University School of Electrical Engineering, FI-00076 Aal Information Engineering College Shanghai Maritime University, Shanghai 200135, P. R. China

会议类型: 国际会议

会议名称: 2011 Seventh International Conference on Natural Computation(第七届自然计算国际会议 ICNC 2011)

会议地点: 上海

会议语种:英文

页码: 1609-1613

在线出版日期: 2011-07-26（万方平台首次上网日期，不代表论文的发表时间）