超声非线性效应表征的动态小波指纹分析方法

发布时间：2018-05-27 06:23

本文选题：非线性效应 + 指纹分析　；参考：《声学学报》2017年05期

【摘要】：针对结构早期损伤超声非线性检测中损伤表征问题,发展了一种基于动态小波指纹的超声信号分析方法,从超声信号的动态小波指纹分布中提取出一种可用于结构早期损伤表征的超声非线性特征参数。研究了小波基函数及分析尺度对超声非线性效应提取效果的影响,优选出对结构早期损伤敏感的小波基函数以及尺度范围。将提出的动态小波指纹分析方法应用于二次谐波及混频非线性超声检测信号分析,结果表明,动态小波指纹分析方法可有效提取出检测信号中的二次谐波及混频分量,基于小波指纹分布的非线性特征参数可用于板结构中微裂纹的定量表征.本文研究工作为结构早期损伤超声非线性检测中的弱非线性效应提取作了有益探索。
[Abstract]:A method of ultrasonic signal analysis based on dynamic wavelet fingerprint is developed to solve the problem of damage characterization in ultrasonic nonlinear detection of early structural damage. An ultrasonic nonlinear characteristic parameter, which can be used to characterize the early damage of structures, is extracted from the dynamic wavelet fingerprint distribution of ultrasonic signals. The influence of wavelet basis function and analysis scale on the extraction effect of ultrasonic nonlinear effect is studied. The wavelet basis function and scale range which are sensitive to the early damage of structure are selected. The proposed dynamic wavelet fingerprint analysis method is applied to the analysis of the second harmonic and mixed nonlinear ultrasonic signal. The results show that the dynamic wavelet fingerprint analysis method can effectively extract the second harmonic and mixing components from the detection signal. The nonlinear characteristic parameters based on wavelet fingerprint distribution can be used to quantitatively characterize microcracks in plate structures. The research work in this paper is useful for the extraction of weak nonlinear effects in ultrasonic nonlinear detection of early structural damage.
【作者单位】：北京工业大学机械工程与应用电子技术学院;北京工业大学北京市精密测控技术与仪器工程技术研究中心;
【基金】：国家自然科学基金项目(11572010,11272017) 国家重点研发计划项目(2016YFF0203002)资助
【分类号】：TB559;TP391.41

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