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金属中多微裂纹的传统涡流-脉冲涡流融合诊断技术。

Traditional Eddy Current⁻Pulsed Eddy Current Fusion Diagnostic Technique for Multiple Micro-Cracks in Metals.

机构信息

School of Aeronautics and Astronautics, University of Electronic Science and Technology of China, Chengdu 611731, China.

School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China.

出版信息

Sensors (Basel). 2018 Sep 1;18(9):2909. doi: 10.3390/s18092909.

DOI:10.3390/s18092909
PMID:30200510
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6164897/
Abstract

Due to a harsh working environment, micro-cracks in metal structures (e.g., airplane, oil/gas pipeline, hydro-turbine) often lead to serious accidents, so health monitoring of the metals is of great significance to ensure their safe operation. However, it is hard to perform quantitative detection of multiple micro-cracks by a single nondestructive testing (NDT) technique because of their limits. To monitor for multiple micro-cracks in metals, a Traditional Eddy Current (TEC) and Pulsed Eddy Current (PEC) fusion NDT technique is proposed in this paper. In the proposed technique, the TEC technique is adopted to seek the locations of the micro-cracks in the whole of the metal, while the PEC technique is adopted to acquire information on the depth of micro-cracks automatically according to the location information by the TEC. The experiments indicate that the TEC⁻PEC fusion NDT system can localize the micro-cracks as well as detect the micro-cracks quantitatively and automatically; therefore, it can be applied in structural health monitoring of metal equipment or in picking candidate components in re-manufacturing engineering.

摘要

由于工作环境恶劣,金属结构(如飞机、石油/天然气管道、水轮机)中的微裂纹经常导致严重事故,因此对金属进行健康监测对于确保其安全运行具有重要意义。然而,由于其局限性,单一的无损检测(NDT)技术很难对多个微裂纹进行定量检测。为了监测金属中的多个微裂纹,本文提出了一种传统涡流(TEC)和脉冲涡流(PEC)融合 NDT 技术。在提出的技术中,采用 TEC 技术寻找金属整体中微裂纹的位置,而采用 PEC 技术根据 TEC 的位置信息自动获取微裂纹深度的信息。实验表明,TEC⁻PEC 融合 NDT 系统既能定位微裂纹,又能对微裂纹进行定量和自动检测;因此,它可应用于金属设备的结构健康监测或再制造工程中候选部件的选择。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c477/6164897/7bb4eaacb7f8/sensors-18-02909-g011.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c477/6164897/9ec77910bdb4/sensors-18-02909-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c477/6164897/13f8434cad3e/sensors-18-02909-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c477/6164897/8b997a9a44b6/sensors-18-02909-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c477/6164897/15e37e6d1f2f/sensors-18-02909-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c477/6164897/863b449fe52f/sensors-18-02909-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c477/6164897/1181c145f374/sensors-18-02909-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c477/6164897/ae138aaef9a2/sensors-18-02909-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c477/6164897/7bb4eaacb7f8/sensors-18-02909-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c477/6164897/8144aa9a75f5/sensors-18-02909-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c477/6164897/bac39d09c7f7/sensors-18-02909-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c477/6164897/1f3c9b19f82b/sensors-18-02909-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c477/6164897/9ec77910bdb4/sensors-18-02909-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c477/6164897/13f8434cad3e/sensors-18-02909-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c477/6164897/8b997a9a44b6/sensors-18-02909-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c477/6164897/15e37e6d1f2f/sensors-18-02909-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c477/6164897/863b449fe52f/sensors-18-02909-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c477/6164897/1181c145f374/sensors-18-02909-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c477/6164897/ae138aaef9a2/sensors-18-02909-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c477/6164897/7bb4eaacb7f8/sensors-18-02909-g011.jpg

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