融合循环自相关函数的小波分析算法在微裂缝检测中的应用  

Wavelet Analysis Algorithm Integrating Cyclic Autocorrelation Function for Micro Crack Detection

作　　者：柴艳丽 朱岩 王建强 CHAI Yanli;ZHU Yan;WANG Jianqiang(Aviation Industry Corporation of China, Changcheng Institute of Metrology & Measurement, Beijing 100095, China)

机构地区：[1]中国航空工业集团公司北京长城计量测试技术研究所,北京100095

出　　处：《测试技术学报》2019年第2期116-120,共5页Journal of Test and Measurement Technology

基　　金：航空科学基金资助项目(2016ZD44006)

摘　　要：针对激光超声信号中存在大量的噪声成分,信号自身的频谱结构比较复杂,单一算法检测效果不佳的问题,为了提高激光外差干涉法检测材料表面微裂缝的能力,研究了将小波分析算法与循环自相关函数算法相结合实现激光外差干涉检测微裂缝的算法.该算法利用循环自相关函数判断激光超声信号中的微裂缝信息成分的频带,并由此选取合适的小波基函数,改善了小波分析算法对包含微裂缝信息的信号的提取能力.利用该算法进行实验,提取了包含微裂缝信息的信号,得到了被测样件微裂缝的位置信息.实验结果表明,利用该算法得到的被测样件微裂缝的距离与实际距离的误差率为1.04%,验证了算法的可行性和准确性.The spectrum structure of the Laser ultrasound signal is rather complicated and contains a large amount of noise components, single demodulation algorithm can not achieve effective detection, in order to enhance the ability of laser heterodyne interferometry to detect micro-crack on the material surface, the algorithm that combining wavelet analysis algorithm and cyclic autocorrelation function algorithm is presented to realize laser heterodyne interference detection micro-crack algorithm. The algorithm uses the cyclic autocorrelation function to determine the frequency band of the micro-crack imformation components, and then selects the appropriate wavelet basis function, which can improve the ability of the wavelet analysis algorithm to extract micro-crack information. The laser ultrasound signal is obtained from the experiment by using the new algorithm, the ultrasonic signal was extracted and the position information of the micro-crack was obtained. The experimental results show that the error rate of the distance between the actual distance and the distance of the micro-crack obtained by the wavelet transform algorithm is 1.04%, which verifies the feasibility and accuracy of the algorithm.

关 键 词：光外差干涉 微裂缝 小波分析 循环自相关函数 

分 类 号：TN247[电子电信—物理电子学]