Liu Kehai, Wu Zhanjun, Jiang Youqiang, Wang Yishou, Zhou Kai, Chen Yingpu
State Key Laboratory of Structural Analysis for Industrial Equipment, Dalian University of Technology, Dalian 116024, China.
State Key Laboratory of Structural Analysis for Industrial Equipment, Dalian University of Technology, Dalian 116024, China.
Ultrasonics. 2016 Feb;65:34-42. doi: 10.1016/j.ultras.2015.10.025. Epub 2015 Nov 2.
To improve the safety and reliability of pipeline structures, much work has been done using ultrasonic guided waves methods for pipe inspection. Though good for evaluating the defects in the pipes, most of the methods lack the capability to precisely identify the defects in the pipe features like welds or supports. Therefore, a novel guided wave based cross-sectional diagnostic imaging algorithm was developed to improve the ability of circumferential cracks identification in the pipe features. To ensure the accuracy of the imaging, an angular profile-based frequency selection method is presented. As validation, the approach was employed to identify the presence and location of a small circumferential crack with 1.13% cross sectional area (CSA) in the welding zone of a 48 mm diameter type 304 stainless steel pipe. Accurate identification results have demonstrated the effectiveness of the developed approach.
为提高管道结构的安全性和可靠性，人们利用超声导波方法进行管道检测开展了大量工作。尽管这些方法有助于评估管道中的缺陷，但大多数方法缺乏精确识别管道特征（如焊缝或支撑）中缺陷的能力。因此，开发了一种基于导波的新型横截面诊断成像算法，以提高对管道特征中周向裂纹的识别能力。为确保成像的准确性，提出了一种基于角向轮廓的频率选择方法。作为验证，该方法被用于识别一根直径48毫米的304型不锈钢管道焊接区中横截面面积为1.13%的小周向裂纹的存在和位置。准确的识别结果证明了所开发方法的有效性。
