Cable Insulation Thickness Detection Based on ALA-GA
Aiming at the low efficiency and poor accuracy of traditional cable insulation thickness measurement methods,an insu-lation thickness detection method based on adaptive local alternating genetic algorithm(ALA-GA)is proposed.The method uses the ALA-GA algorithm to alternately search the inner and outer edges of the specimen image so as to obtain the optimal insulation thick-ness position;The algorithm introduces the priori structural knowledge of the specimen,adaptively selects the initial population ac-cording to the curvature characteristics of the specimen cross-section edges,and ensures the high quality and diversity of the initial population genes.The crossover and mutation operations are placed in the front,and the crossover and mutation modes are changed locally and adaptively for the inner and outer edges of the specimen section,so as to improve the solution speed of the genetic algo-rithm;In order not to lose the high-quality genes of any edge,the post-selection operation is achieved by the original population and new population obtained after the crossover and mutation;An optimal detection position is obtained every time,and other solutions near the position are eliminated,the ALA-GA algorithm is iterated to obtain the result of accurate insulation thickness detection.Comparison experiments and capability verification show that the ALA-GA-based method has a time cost of 0.6～0.7 s,a thinnest point measurement error of 0.001 2～0.001 5 mm,an average measurement error of 0.001 3～0.001 7 mm,and a measurement re-peatability of 0.001 8～0.002 1 mm,the method is superior to existing advanced methods,and has a good general capability for irreg-ular cables.
machine visiongenetic algorithmelectric or optical cableautomatic measurementinsulation thicknessinspec-tion and testing
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