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基于自适应信号截断的超声导波缺陷定位新概率椭圆成像方法在压力容器上的应用。

A New Probabilistic Ellipse Imaging Method Based on Adaptive Signal Truncation for Ultrasonic Guided Wave Defect Localization on Pressure Vessels.

机构信息

School of Mechanical and Power Engineering, East China University of Science and Technology, Shanghai 200237, China.

出版信息

Sensors (Basel). 2022 Feb 17;22(4):1540. doi: 10.3390/s22041540.

Abstract

Pressure vessels are prone to defects due to environmental conditions, which may cause serious safety hazards to industrial production. The probabilistic ellipse imaging method, based on ultrasonic guided wave, is a common method for locating defects on plate-like structures. In this paper, the research showed that the accuracy of the traditional probabilistic ellipse imaging method was severely affected by the truncation length of the signal. In order to improve the defect location accuracy of the probabilistic elliptic imaging algorithm, an adaptive signal truncation method based on signal difference analysis was proposed, and a novel probabilistic elliptic imaging method was developed. Firstly, the relationship model between the signal difference coefficient (SDC) and the distance coefficient was constructed. Through this model, the distance coefficient of each group signal can be calculated, so that the adaptive truncation length for each group of signals can be determined and the truncated signals used for defect imaging. Secondly, in order to improve the robustness of the new imaging method, the relationship between the defect location accuracy and SDC thresholds were investigated and the optimal threshold was determined. The experimental results showed that the probabilistic ellipse imaging algorithm, based on the new adaptive signal truncation method, can effectively locate a single defect on a pressure vessel.

摘要

压力容器由于环境条件容易出现缺陷,这可能对工业生产造成严重的安全隐患。基于超声波导波的概率椭圆成像方法是一种常见的板状结构缺陷定位方法。本文研究表明,传统概率椭圆成像方法的准确性受到信号截断长度的严重影响。为了提高概率椭圆成像算法的缺陷定位精度,提出了一种基于信号差分分析的自适应信号截断方法,并开发了一种新的概率椭圆成像方法。首先,构建了信号差分系数(SDC)与距离系数的关系模型。通过该模型,可以计算每组信号的距离系数,从而确定每组信号的自适应截断长度,并使用截断信号进行缺陷成像。其次,为了提高新成像方法的鲁棒性,研究了缺陷定位精度与 SDC 阈值之间的关系,并确定了最优阈值。实验结果表明,基于新的自适应信号截断方法的概率椭圆成像算法可以有效地定位压力容器上的单个缺陷。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e90/8877118/93767a63f751/sensors-22-01540-g001.jpg

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