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基于遗传算法优化稀疏分解的防护涂层测厚研究

Protective coating thickness measurement based on genetic algorithmoptimization in sparse decomposition
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摘要 针对采用高频超声水浸法检测装配式钢结构的防护涂层厚度的仿真试验中,防护涂层的界面反射回波相互混叠,导致无法提取涂层的时域信息的问题,利用基于遗传算法优化稀疏分解中的匹配追踪过程对混叠信号进行分离与重构。该算法在构建的Gabor原子库中,利用遗传算法对最佳原子参数的搜索过程进行优化,同时将传统稀疏分解匹配追踪算法中的内积运算优化为互相关运算,从而优化了稀疏分解的运算效率。与金相检测涂层厚度的结果相比较,该改进算法的检测相对误差为2.50%,在可接受的范围内,且较传统稀疏分解匹配追踪算法5.01%的检测相对误差的检测精度高,同时运算速度得到较大提升。 In simulation experiments of using high-frequency ultrasonic water immersion method to detect thickness of protective coating on prefabricated steel structure,interface reflection echoes of protective coating are overlapped to cause coating time-domain information being unable to extract.Here,the genetic algorithm-based optimization of the matching tracking process in sparse decomposition was used to separate and reconstruct the overlapped signals.This improved algorithm could optimize the search process for the optimal atomic parameters in the constructed Gabor atomic library using genetic algorithm,and optimize inner product operation in the traditional sparse decomposition matching tracking algorithm into cross-correlation operation,and thereby the operational efficiency of sparse decomposition was optimized.It was shown that compared with the results of metallographic detection of coating thickness,the improved algorithm has a detection relative error of 2.50%,while the traditional sparse decomposition matching tracking algorithm has a detection relative error of 5.01%,so the detection accuracy of the former is higher than that of the latter;meanwhile,the former’s computational speed is more largely improved.
作者 刘易奕 陈尧 李秋锋 王志刚 王海涛 LIU Yiyi;CHEN Yao;LI Qiufeng;WANG Zhigang;WANG Haitao(MOE Key Lab of Nondestructive Testing,Nanchang Hangkong University,Nanchang 330063,China;Nanchang Architecture Science Institute Co.,Ltd.,Nanchang 330096,China;The Second Construction Co.,Ltd.,China Construction First Bureau Group,Beijing 100161,China)
出处 《振动与冲击》 EI CSCD 北大核心 2024年第11期279-287,共9页 Journal of Vibration and Shock
基金 国家自然科学基金(12364056 11764030) 江西省自然科学基金重点项目(20212ACB204014) 江西省重点研发计划项目(20212BBE51006)。
关键词 防护涂层 超声水浸 稀疏分解 遗传算法 互相关运算 protective coating ultrasonic water immersion sparse decomposition genetic algorithm cross-correlation operation
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