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基于奇异谱分析的压电主动传感管道腐蚀监测

Piezoelectric Active Sensing-Based Pipeline Corrosion Monitoring Using Singular Spectrum Analysis.

作者信息

Yang Dan, Wang Hu, Wang Tao, Lu Guangtao

机构信息

Key Laboratory for Metallurgical Equipment and Control of Ministry of Education, Wuhan University of Science and Technology, Wuhan 430081, China.

Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering, Wuhan University of Science and Technology, Wuhan 430081, China.

出版信息

Sensors (Basel). 2024 Jun 27;24(13):4192. doi: 10.3390/s24134192.

DOI:10.3390/s24134192
PMID:39000971
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11244410/
Abstract

Pipelines are an important transportation form in industry. However, pipeline corrosion, particularly that occurring internally, poses a significant threat to safe operations. To detect the internal corrosion of a pipeline, a method utilizing piezoelectric sensors alongside singular spectrum analysis is proposed. Two piezoelectric patches are affixed to the exterior surface of the pipeline, serving the roles of an actuator and a sensor, respectively. During the detection, the signals excited by the actuator are transmitted through the pipeline's wall and are received by PZT2 through different paths, and the corresponding piezoelectric sensor captures the signals. Then, the response signals are denoised by singular spectrum analysis, and the first several wave packets in the response signals are selected to establish a feature for pipeline corrosion detection. At last, the envelope area of the selected packets is calculated as a feature to detect corrosion. To validate the proposed method, corrosion monitoring experiments are performed. The experimental results indicate that the envelope area of the first several wave packets from the response signals, following singular spectrum analysis, can serve as a feature to assess the degree of pipeline corrosion, and the index has a monotonic relationship with the corrosion depth of the pipeline. This method provides an effective way for pipeline corrosion monitoring.

摘要

管道是工业中一种重要的运输形式。然而,管道腐蚀,尤其是内部发生的腐蚀,对安全运行构成重大威胁。为了检测管道的内部腐蚀,提出了一种利用压电传感器并结合奇异谱分析的方法。两个压电片分别粘贴在管道外表面,分别充当激励器和传感器。在检测过程中,激励器激发的信号通过管道壁传输,并由PZT2通过不同路径接收,相应的压电传感器捕获信号。然后,通过奇异谱分析对响应信号进行去噪,并选择响应信号中的前几个波包来建立管道腐蚀检测的特征。最后,计算所选波包的包络面积作为检测腐蚀的特征。为了验证所提出的方法,进行了腐蚀监测实验。实验结果表明,经过奇异谱分析后,响应信号中前几个波包的包络面积可作为评估管道腐蚀程度的特征,该指标与管道腐蚀深度呈单调关系。该方法为管道腐蚀监测提供了一种有效的途径。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab51/11244410/f2617741cb0d/sensors-24-04192-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab51/11244410/c305a193ffa5/sensors-24-04192-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab51/11244410/d1574991e889/sensors-24-04192-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab51/11244410/0b6970f9bee9/sensors-24-04192-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab51/11244410/96063094c2bc/sensors-24-04192-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab51/11244410/8bb4a9588ca8/sensors-24-04192-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab51/11244410/8d83fd1fb275/sensors-24-04192-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab51/11244410/faca72e99532/sensors-24-04192-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab51/11244410/2ead2427ef5c/sensors-24-04192-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab51/11244410/f2617741cb0d/sensors-24-04192-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab51/11244410/c305a193ffa5/sensors-24-04192-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab51/11244410/b29c17f56650/sensors-24-04192-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab51/11244410/dcfa2889bc8f/sensors-24-04192-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab51/11244410/d1574991e889/sensors-24-04192-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab51/11244410/0b6970f9bee9/sensors-24-04192-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab51/11244410/96063094c2bc/sensors-24-04192-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab51/11244410/8bb4a9588ca8/sensors-24-04192-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab51/11244410/8d83fd1fb275/sensors-24-04192-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab51/11244410/faca72e99532/sensors-24-04192-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab51/11244410/2ead2427ef5c/sensors-24-04192-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab51/11244410/f2617741cb0d/sensors-24-04192-g011.jpg

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