基于超声导波传感器阵列和GSA-CoSaMP算法的管道缺陷评估方法

IF 5.9 2区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Zhirong Lin;Yishou Wang;Linlin Fang;Xiaodie Hu;Xinlin Qing
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引用次数: 0

摘要

管道缺陷的准确表征对于维护管道结构完整性和保证运行安全至关重要。为了提高超声导波(UGW)信号分解重建的精度和鲁棒性,提出了一种将重力搜索算法(GSA)与压缩采样匹配追踪(CoSaMP)相结合的管道缺陷评估方法。GSA用于动态优化信号稀疏度,克服了传统方法依赖预定义稀疏度水平的局限性。在此基础上,利用导波反射特性先验知识构建了优化的波形字典,提高了缺陷信号分解和重构的精度。该方法有效地分离了管道缺陷前后边缘的重叠反射信号,实现了缺陷轴向尺寸的精确表征。采用安装在不锈钢管道表面的压电(PZT)传感器阵列进行有限元(FE)仿真和实验验证表明,该方法的有效性得到了提高,缺陷尺寸评估的平均误差分别为0.68和2.20 mm,显著优于传统的匹配追踪(MP)、标准CoSaMP、正交匹配追踪(OMP)和基追踪(BP)算法。该方法通过自适应优化信号稀疏性,增强抗噪声鲁棒性,解决了现有方法的局限性,并为管道完整性评估提供了可靠的工具。这些发现有助于开发预测性维护策略,并推进复杂管网的实时缺陷监测应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Pipeline Defect Assessment Method Based on Ultrasonic Guided Wave Sensor Array and GSA-CoSaMP Algorithm
Accurate characterization of pipeline defects is crucial for maintaining structural integrity and ensuring operational safety. This study introduces an innovative pipeline defect evaluation method integrating the gravitational search algorithm (GSA) with the compressed sampling matching pursuit (CoSaMP), aimed at improving the accuracy and robustness of ultrasonic guided wave (UGW) signal decomposition and reconstruction. GSA is applied to dynamically optimize signal sparsity, overcoming the limitations of traditional methods that rely on predefined sparsity levels. Moreover, an optimized waveform dictionary, which incorporates prior knowledge of guided wave reflection characteristics, is constructed to improve the accuracy of defect signal decomposition and reconstruction. The proposed method effectively separates overlapping reflection signals from the front and rear edges of pipeline defects, enabling precise characterization of defect axial dimensions. Finite element (FE) simulations and experimental validations using a piezoelectric (PZT) sensor array installed on the surface of a stainless steel pipeline illustrate the enhanced effectiveness of the proposed methodology, achieving average defect size evaluation errors of 0.68 and 2.20 mm, respectively, significantly outperforming conventional matching pursuit (MP), standard CoSaMP, orthogonal matching pursuit (OMP), and basis pursuit (BP) algorithms. This method addresses the limitations of existing approaches by adaptively optimizing signal sparsity, enhancing robustness against noise, and providing a reliable tool for pipeline integrity assessment. The findings contribute to the development of predictive maintenance strategies and advance real-time defect monitoring applications for complex pipeline networks.
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来源期刊
IEEE Transactions on Instrumentation and Measurement
IEEE Transactions on Instrumentation and Measurement 工程技术-工程:电子与电气
CiteScore
9.00
自引率
23.20%
发文量
1294
审稿时长
3.9 months
期刊介绍: Papers are sought that address innovative solutions to the development and use of electrical and electronic instruments and equipment to measure, monitor and/or record physical phenomena for the purpose of advancing measurement science, methods, functionality and applications. The scope of these papers may encompass: (1) theory, methodology, and practice of measurement; (2) design, development and evaluation of instrumentation and measurement systems and components used in generating, acquiring, conditioning and processing signals; (3) analysis, representation, display, and preservation of the information obtained from a set of measurements; and (4) scientific and technical support to establishment and maintenance of technical standards in the field of Instrumentation and Measurement.
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