In order to improve the work efficiency of non-destructive testing(NDT)and the reliability of NDT results,an automatic method to detect defects in the ultrasonic image was researched.According to the characterization of ultrasonic D-scan image,clutter wave suppression and de-noising were presented firstly.Then,the image is processed by binaryzation using KSW 2 D entropy based on image segmentation method.The results showed that,the global threshold based segmentation method was somewhat ineffective for D-scan image because of under-segmentation.Especially,when the image is big in size,small targets which are composed by a small amount of pixels are often undetected.Whereas,local threshold based image segmentation method is effective in recognizing small defects because it takes local image character into account.
针对常规超声TOFD法存在近表面检测盲区的问题,提出一种纵波三次反射的TOFDW检测模式.分析了TOFDW模式的声传播特性,并阐明了该模式的检测原理.通过人工缺陷检测,研究了该模式检测信号和图像特征及检测灵敏度和精度.对实际焊缝进行了检测,并通过破坏性试验对无损检测结果进行了验证.结果表明,TOFDW模式能够识别常规模式下无法辨别的近表面缺陷,可有效检测到埋藏深度1.0 mm的人工缺陷;同时,该模式具有较高的量化测量精度,近表面人工缺陷埋藏深度测量的平均绝对误差不超过0.3 mm.
