超声TOFD(time of flight diffraction,衍射时差)法检测的D扫描图像中,作为背景杂波的侧向波与近表面缺陷波会发生混叠,致使近表面缺陷不易于检测.针对这一问题,提出一种基于杂波抑制的缺陷检测方法.该方法通过图像能量分布统计,确定背...超声TOFD(time of flight diffraction,衍射时差)法检测的D扫描图像中,作为背景杂波的侧向波与近表面缺陷波会发生混叠,致使近表面缺陷不易于检测.针对这一问题,提出一种基于杂波抑制的缺陷检测方法.该方法通过图像能量分布统计,确定背景杂波分量并予以去除,从而分离出与其混叠的缺陷信号,实现近表面缺陷的检测.建立了的超声TOFD法检测信号的数学模型,阐明了基于图像能量分布的杂波抑制原理.制作了人工缺陷试块及实际焊缝试块,并对其检测获取的图像进行了杂波抑制处理.结果表明,提出的方法可有效去除图像中的非缺陷目标、提取近表面缺陷波,从而提高系统的有效检测范围.展开更多
Wood nondestructive testing （NDT） is one of the high efficient methods in utilizing wood. This paper explained the principle of log defect testing by using stress wave, and analyzed the effects of sensor quantity on...Wood nondestructive testing （NDT） is one of the high efficient methods in utilizing wood. This paper explained the principle of log defect testing by using stress wave, and analyzed the effects of sensor quantity on defect testing results by using stress wave in terms of image fitting degree and error rate. The results showed that for logs with diameter ranging from 20 to 40 cm, at least 12 sensors were needed to meet the requirement which ensure a high testing accuracy of roughly 90% of fitness with 0.1 of error rate. And 10 sensors were recommended to judge the possible locations of defects and 6 sensors were sufficient to decide whether there were defects or not.展开更多
文摘超声TOFD(time of flight diffraction,衍射时差)法检测的D扫描图像中,作为背景杂波的侧向波与近表面缺陷波会发生混叠,致使近表面缺陷不易于检测.针对这一问题,提出一种基于杂波抑制的缺陷检测方法.该方法通过图像能量分布统计,确定背景杂波分量并予以去除,从而分离出与其混叠的缺陷信号,实现近表面缺陷的检测.建立了的超声TOFD法检测信号的数学模型,阐明了基于图像能量分布的杂波抑制原理.制作了人工缺陷试块及实际焊缝试块,并对其检测获取的图像进行了杂波抑制处理.结果表明,提出的方法可有效去除图像中的非缺陷目标、提取近表面缺陷波,从而提高系统的有效检测范围.
基金This paper was supported by the project "Devel-opment of Portable NDT Instrument (2002(39-1))" sponsored by Na-tional Forestry Administrative Bureau of China
文摘Wood nondestructive testing （NDT） is one of the high efficient methods in utilizing wood. This paper explained the principle of log defect testing by using stress wave, and analyzed the effects of sensor quantity on defect testing results by using stress wave in terms of image fitting degree and error rate. The results showed that for logs with diameter ranging from 20 to 40 cm, at least 12 sensors were needed to meet the requirement which ensure a high testing accuracy of roughly 90% of fitness with 0.1 of error rate. And 10 sensors were recommended to judge the possible locations of defects and 6 sensors were sufficient to decide whether there were defects or not.
