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Preliminary Research on the Nonlinear Ultrasonic Detection of the Porosity of Porous Material Based on Dynamic Wavelet Fingerprint Technology

机译:基于动态小波指纹技术的多孔材料孔隙非线性超声波检测初步研究

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摘要

Porosity is an important characteristic of porous material, which affects mechanical and material properties. In order to solve the problem that the large distribution range of pore size of porous materials leads to the large detection errors of porosity, the non-linear ultrasonic testing technique is applied. A graphite composite was used as the experimental object in the study. As the accuracy of porosity is directly related with feature extraction, the dynamic wavelet fingerprint (DWFP) technology was utilized to extract the feature parameter of the ultrasonic signals. The effects of the wavelet function, scale factor, and white slice ratio on the extraction of the nonlinear feature are discussed. The SEM photos were conducted using gray value to identify the aperture. The relationship between pore diameter and detection accuracy was studied. Its results show that the DWFP technology could identify the second harmonic component well, and the extracted nonlinear feature could be used for the quantitative trait of porosity. The larger the proportion of the small diameter holes and the smaller the aperture distribution range was, the smaller the error was. This preliminary research aimed to improve the nondestructive testing accuracy of porosity and it is beneficial to the application of porous material in the manufacturing field.
机译:孔隙率是多孔材料的重要特征,其影响机械和材料性质。为了解决多孔材料的孔径的大分配范围导致孔隙率的大检测误差,应用了非线性超声波检测技术。将石墨复合材料用作研究中的实验对象。由于孔隙率的精度与特征提取直接相关,因此利用动态小波指纹(DWFP)技术提取超声波信号的特征参数。讨论了小波函数,比例因子和白色切片比对非线性特征提取的影响。使用灰度值进行SEM照片以识别光圈。研究了孔径与检测精度之间的关系。其结果表明,DWFP技术可以识别第二谐波成分井,并且提取的非线性特征可用于孔隙率的定量性状。小直径孔的比例越大,孔径分布范围越小,误差越小。这种初步研究旨在提高孔隙率的无损检测精度,有利于在制造场中的应用在制造场中的应用。

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