DocumentCode :
1962580
Title :
Fault diagnosis based on Danger Model Immune wavelet neural network
Author :
Zhang, Chuang ; GUO, Chen ; Xu, Qingyang
Author_Institution :
Coll. of Inf. Sci. & Technol., Dalian Maritime Univ., Dalian, China
fYear :
2010
fDate :
13-15 Aug. 2010
Firstpage :
217
Lastpage :
221
Abstract :
Danger Model Immune Algorithm (DMIA) is an algorithm based on the danger theory of biological immune system, and it has a good performance in optimization. DMIA is proposed to initialize the weights and biases of wavelet neural network (WNN), the ergodic weights and biases are used for further net-training. The fault diagnosis for marine diesel engine is conducted by using the well-trained wavelet network. The results indicate that this algorithm is efficient in fault diagnosis.
Keywords :
biology computing; diesel engines; fault diagnosis; genetic engineering; living systems; neural nets; optimisation; wavelet transforms; biological immune system; danger model immune wavelet neural network; danger theory; ergodic weights; fault diagnosis; marine diesel engine; net-training; optimization; Accuracy; Artificial neural networks; Diesel engines; Fault diagnosis; Immune system; Optimization; Training;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Information Processing (ICICIP), 2010 International Conference on
Conference_Location :
Dalian
Print_ISBN :
978-1-4244-7047-1
Type :
conf
DOI :
10.1109/ICICIP.2010.5565265
Filename :
5565265
Link To Document :
بازگشت