DocumentCode
554166
Title
A Negative Selection Algorithm-based motor fault detection scheme
Author
Gao, X.Z. ; Wang, Xiongfei ; Ovaska, S.J. ; Arkkio, Antero ; Zenger, Kai ; Xiaofeng Wang
Author_Institution
Inf. Eng. Coll., Shanghai Maritime Univ., Shanghai, China
Volume
3
fYear
2011
fDate
26-28 July 2011
Firstpage
1583
Lastpage
1587
Abstract
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.
Keywords
artificial immune systems; electric machines; fault diagnosis; rotors; signal processing; stators; NSA detector; artificial immune system; electrical machine; healthy motor; motor fault detection; motor fault type; motor load; negative selection algorithm; rotor fault; signal; stator fault; Detectors; Educational institutions; Fault detection; Feature extraction; Immune system; Rotors; Stators; Artificial Immune Systems (AIS); Negative Selection Algorithm (NSA); electrical machines; fault detection; motors;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation (ICNC), 2011 Seventh International Conference on
Conference_Location
Shanghai
ISSN
2157-9555
Print_ISBN
978-1-4244-9950-2
Type
conf
DOI
10.1109/ICNC.2011.6022383
Filename
6022383
Link To Document