A STUDY OF NEGATIVE SELECTION ALGORITHM-BASED MOTOR FAULT DETECTION AND DIAGNOSIS

被引：0
|
作者：
Gao, Xiao-Zhi [1 ]
Xu, He [2 ]
Wang, Xiaolei [1 ]
Zenger, Kai [1 ]
机构：
[1] Aalto Univ, Sch Elect Engn, Dept Automat & Syst Technol, Aalto 00076, Finland
[2] Harbin Engn Univ, Coll Mech & Elect Engn, Harbin 150001, Heilongjiang, Peoples R China
来源：
INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL | 2013年 / 9卷 / 02期
基金：
芬兰科学院; 美国国家科学基金会;
关键词：
Artificial Immune Systems (AIS); Negative Selection Algorithm (NSA); Fault detection; Fault diagnosis; Motors; Electrical machines; Mobile robots;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we present a comprehensive study of the Negative Selection Algorithm (NSA)-based motor fault detection and diagnosis. The NSA only needs the feature signals of the healthy motors for generating the motor fault detectors. Different from the conventional fault detection approaches, no prior knowledge of the motor fault types is assumed to be known beforehand. Based on the motor fault detection results, the NSA can be further applied for the fault diagnosis. The applicability of our motor fault detection and diagnosis method is examined using the Fisher's iris data classification and three real-world motor fault detection and diagnosis problems in computer simulations.
引用
收藏
页码：875 / 901
页数：27
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