DocumentCode :
569092
Title :
An Improved IGA-BP Algorithm Applied to Fault Diagnosis
Author :
Wu, Lichun ; Zhang, Li ; Yang, Yongbo ; Sun, Lijie ; Li, Fengman
Author_Institution :
Sch. of Inf., Liaoning Univ., Shenyang, China
fYear :
2012
fDate :
July 31 2012-Aug. 2 2012
Firstpage :
194
Lastpage :
197
Abstract :
In immune genetic algorithm of float coding, there would be no certain way to calculate the critical value based on the Euclidean distance similarity. For this problem, the paper puts forward a way on "3σ" method; inspired by the elitist strategy, the paper modifies the coefficient of arithmetic crossover method, which can adaptively incline toward the higher fitness value of two pairs of antibody. The improved IGA-BP algorithm is applied to the fault diagnosis of transmission gear. The experiment is simulated on MATLAB, and its result shows that the "3σ" method is an effective solution, and this improved algorithm has several advantages such as fast convergence, good adaptability, high accuracy on transmission gear\´s fault types.
Keywords :
fault diagnosis; genetic algorithms; Euclidean distance similarity; arithmetic crossover method; fault diagnosis; float coding; immune genetic algorithm; improved IGA-BP algorithm; Encoding; Euclidean distance; Fault diagnosis; Genetic algorithms; Neural networks; Sociology; Statistics; Arithmetic crossover; Euclidean Distance; Fault Diagnosis; Immune Genetic Algorithm; Neural Network; Self-Adaption;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Digital Manufacturing and Automation (ICDMA), 2012 Third International Conference on
Conference_Location :
GuiLin
Print_ISBN :
978-1-4673-2217-1
Type :
conf
DOI :
10.1109/ICDMA.2012.47
Filename :
6298287
Link To Document :
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