In this paper,a modified genetic local search algorithm(MGLSA) is proposed.The proposed algorithm is resulted from employing the simulated annealing technique to regulate the variance of the Gaussian mutation of the g...In this paper,a modified genetic local search algorithm(MGLSA) is proposed.The proposed algorithm is resulted from employing the simulated annealing technique to regulate the variance of the Gaussian mutation of the genetic local search algorithm(GLSA).Then,an MGLSA-based inverse algorithm is proposed for magnetic flux leakage(MFL) signal inversion of corrosive flaws,in which the MGLSA is used to solve the optimization problem in the MFL inverse problem.Experimental results demonstrate that the MGLSA-based inverse algorithm is more robust than GLSA-based inverse algorithm in the presence of noise in the measured MFL signals.展开更多
基金the Innovation Program of ShanghaiMunicipal Education Commission(No.09YZ340)the Leading Academic Discipline Project of ShanghaiMunicipal Education Commission(No.J51301)+2 种基金the Special Scientific Research Project of Scienceand Technology Commission of Shanghai Municipality(No.08240512000)the Shanghai Municipal EducationCommission Scientific Foundation Projection(No.06LZ009)the Shanghai Key Science and TechnologyProject(No.061612041)
文摘In this paper,a modified genetic local search algorithm(MGLSA) is proposed.The proposed algorithm is resulted from employing the simulated annealing technique to regulate the variance of the Gaussian mutation of the genetic local search algorithm(GLSA).Then,an MGLSA-based inverse algorithm is proposed for magnetic flux leakage(MFL) signal inversion of corrosive flaws,in which the MGLSA is used to solve the optimization problem in the MFL inverse problem.Experimental results demonstrate that the MGLSA-based inverse algorithm is more robust than GLSA-based inverse algorithm in the presence of noise in the measured MFL signals.