Defect detection of honeycomb composites based on laser speckle detection
摘 要
通过基于激光散斑检测技术的缺陷信息提取方法,可快速判断缺陷的位置及大小。基于散斑干涉原理,对图像降噪进行了研究分析,试验结果表明,通过傅里叶滤波、图像线性趋势处理、灰度处理、分步解包等图像综合处理技术可有效提取散斑干涉信息,缺陷信号比较清晰。针对该研究结果,对飞机雷达罩进行检测时,运用图像综合处理技术获得缺陷的相关信息,验证了采用该方法提取层压结构和纸蜂窝结构缺陷信息的可行性,有效提高了激光散斑检测的工作效率和可靠性。
Abstract
In order to quickly determine the location and size of defects by nondestructive testing, defect information extraction method based on laser speckle detection technology can be adopted. Based on the principle of speckle interferometry, image denoising is studied and analyzed in this paper. The experimental results show that the speckle interferometry information can be effectively extracted by Fourier filtering, image linear trend processing, gray processing and step-by-step unwrapping, and the defect signal is relatively clear. In view of the research results, the integrated image processing technology is used to detect and process the airplane radome, and the relevant information of the defects is obtained. The feasibility of this method in extracting the defects of laminated structure and paper honeycomb structure is verified, and the efficiency and reliability of laser speckle detection are effectively improved.
中图分类号 TG115.28 DOI 10.11973/wsjc202003009
所属栏目 试验研究
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收稿日期 2019/4/25
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备注杨庆峰(1985-),男,博士研究生,主要从事复合材料无损检测技术研究
引用该论文: YANG Qingfeng,SUN Jinli,SONG Jianjun,LI Jinhao. Defect detection of honeycomb composites based on laser speckle detection[J]. Nondestructive Testing, 2020, 42(3): 38~42
杨庆峰,孙金立,宋建俊,李金浩. 基于激光散斑的蜂窝复合材料缺陷检测[J]. 无损检测, 2020, 42(3): 38~42
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参考文献
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