Title :
Optimization of Frequency Testing Stimulus Based on Improved Genetic Algorithm
Author_Institution :
Coll. of Electromech. & Automobile Eng., Chongqing Jiaotong Univ., Chongqing, China
Abstract :
In this paper, the theory of how to use an improved genetic algorithm to optimize the stimulus parameters of frequency testing in analog diagnose is studied. We code the parameters of a stimulus into a chromosome, and we use the genetic operators such as reproduction, crossover and mutation to create new stimulus. To improve the computation efficiency and reduce the possibility of trapping into the local optimums, the probability crossover and probability mutation is adaptive-self to the search process.
Keywords :
analogue circuits; circuit testing; genetic algorithms; probability; analog diagnose; frequency testing stimulus; genetic algorithm; probability crossover; probability mutation; Analog circuits; Biological cells; Circuit faults; Circuit testing; Fault diagnosis; Frequency response; Genetic algorithms; Genetic mutations; Information management; Optimization methods; analog circuit test; frequency testing; improved genetic algorithm; stimulus parameters;
Conference_Titel :
Information Management, Innovation Management and Industrial Engineering, 2009 International Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-0-7695-3876-1
DOI :
10.1109/ICIII.2009.239
