基于非线性小波收缩的超声信号缺陷识别方法  

Non-linear Wavelet Shrinkage Based Method for Defect Detection in Ultrasonic Signal

作　　者：迟大钊[1,2] 刚铁[1] 姚英学[2] 

机构地区：[1]哈尔滨工业大学先进焊接与连接国家重点实验室,哈尔滨150001 [2]哈尔滨工业大学机电工程学院,哈尔滨150001

出　　处：《机械工程学报》2011年第18期1-6,共6页Journal of Mechanical Engineering

基　　金：国家自然科学基金(51005056;50775054);国际合作(2007DFR70070);黑龙江省自然科学基金(QC2010081)资助项目

摘　　要：超声检测回波中的噪声信号是影响焊接缺陷无损检测的主要因素之一。为了更好地抑制回波中的噪声成分,从而有效地识别缺陷信号,在传统非线性小波收缩(Nonlinear wavelet shrinkage,NWS)方法的基础上,提出一种基于子波相关的改进噪声抑制方法。改进方法具备小波分析的多分辨特性,同时兼顾相邻测点回波中缺陷信号间具强相关性的特点。分别利用传统及改进的NWS方法对计算机仿真信号及焊缝超声检测信号进行处理,研究不同母小波及阈值估计方法对信号处理效果的影响。结果表明,改进方法对不同母小波的敏感性小,受不同阈值估计方法的影响小,且对复杂成分的噪声更具适应性。改进方法的噪声信号抑制及缺陷信号恢复效果明显优于传统方法,为缺陷的有效识别及精确量化测量提供可靠的依据。In the weld tested ultrasonic signal,noise is the leading factors that interfering defect detection.In order to suppress ultrasonic noise and recognize defect signal effectively,an improved non-linear wavelet shrinkage（NWS） method is proposed on the basis of the cross-correlation of sub-waves.The proposed method inherits the merit of multi-resolution of wavelet,and takes cross-correlation between defects waves in the two adjacent signals into account at the same time.By employing the conventional and improved NWS methods,both computer simulated data and weldment tested ultrasonic signal are de-noising processed.The effects of mother wavelets and threshold estimation methods on the noise suppression are researched.Compared with conventional NWS,the improved method is robust to mother wavelets and threshold estimation methods,and shows wide adaptability to noise of complicated frequency.The proposed method has the technical advantage of both noise suppression and defect wave reconstruction,and can effectively identify and quantitatively detect of defects in ultrasonic tested signal.

关 键 词：超声信号 噪声抑制 缺陷识别 小波 

分 类 号：TG115[金属学及工艺—物理冶金]