DocumentCode :
537230
Title :
Study on Danger Theory Condition Monitoring Algorithm Adapted to Mechanical System
Author :
Meng, Qinghua
Author_Institution :
Sch. of Mech. Eng., Hangzhou Dianzi Univ., Hangzhou, China
fYear :
2010
fDate :
7-9 Nov. 2010
Firstpage :
1
Lastpage :
4
Abstract :
According to biological immune danger theory, a condition monitoring algorithm based on immune danger theory was presented. In the algorithm, the whole diagnosis feature space is divided into danger feature space, normal feature space and abnormal feature space. The algorithm consists of primary testing module, APC testing module and self-adapting testing module. The algorithm can make judgment according to whether existing danger signals. So the algorithm can reduce false rate and adjust databases online. The algorithm was applied to axle driving of Farm machinery condition monitoring. Compared with testing result of advanced negative selection algorithm which based on self-nonself recognition, the testing result has a lower false rate.
Keywords :
agricultural machinery; condition monitoring; mechanical engineering computing; APC testing module; abnormal feature space; biological immune danger theory; danger feature space; danger theory condition monitoring algorithm; farm machinery condition monitoring; normal feature space; primary testing module; self-adapting testing module; Axles; Condition monitoring; DNA; Immune system; Mechanical systems; Testing; Vehicles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
E-Product E-Service and E-Entertainment (ICEEE), 2010 International Conference on
Conference_Location :
Henan
Print_ISBN :
978-1-4244-7159-1
Type :
conf
DOI :
10.1109/ICEEE.2010.5661182
Filename :
5661182
Link To Document :
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