基于遗传算法优化稀疏分解的防护涂层测厚研究

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Abstract In the simulation experiment of using high-frequency ultrasonic water immersion method to detect the thickness of protective coatings of assembled steel structures, the interfacial reflected echoes of the protective coatings are overlapped with each other, resulting in the inability to extract the time-domain information of the coatings, and the genetic algorithm-based optimization of the matching tracking process in the sparse decomposition is used to separate and reconstruct the overlapped signals. The algorithm optimizes the search process of the optimal atomic parameters in the constructed Gabor atom library by using genetic algorithm, and optimizes the inner product operation in the traditional sparse decomposition matching tracking algorithm to a mutual correlation operation, thus optimizing the operational efficiency of the sparse decomposition. Compared with the results of metallographic inspection of coating thickness, the inspection relative error of this improved algorithm is 2.50%, which is within the acceptable range and has a higher detection accuracy than the traditional sparse decomposition matching tracking algorithm with a large inspection relative error of 5.01%, while the computing speed is greatly improved.

Key words： protective coatings ultrasonic immersion sparse decomposition genetic algorithm cross-correlation operation

Received: 24 July 2023 Published: 15 June 2024

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	Articles by authors
	LIU Yiyi1
	CHEN Yao1
	LI Qiufeng1
	WANG Zhigang2
	WANG Haitao3

Cite this article:

LIU Yiyi1,CHEN Yao1,LI Qiufeng1, et al. Protective coating thickness measurement based on genetic algorithm optimization in sparse decomposition[J]. JOURNAL OF VIBRATION AND SHOCK, 2024, 43(11): 279-287.

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http://jvs.sjtu.edu.cn/EN/ OR http://jvs.sjtu.edu.cn/EN/Y2024/V43/I11/279

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