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使用多频涡流检测对铝蜂窝夹层飞机面板进行表面轮廓分析和芯部评估

Surface Profiling and Core Evaluation of Aluminum Honeycomb Sandwich Aircraft Panels Using Multi-Frequency Eddy Current Testing.

作者信息

Reyno Tyler, Underhill P Ross, Krause Thomas W, Marsden Catharine, Wowk Diane

机构信息

Department of Mechanical and Aerospace Engineering, Royal Military College of Canada, Kingston, ON K7K 7B4, Canada.

Department of Physics, Royal Military College of Canada, Kingston, ON K7K 7B4, Canada.

出版信息

Sensors (Basel). 2017 Sep 14;17(9):2114. doi: 10.3390/s17092114.

DOI:10.3390/s17092114
PMID:28906434
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5620663/
Abstract

Surface damage on honeycomb aircraft panels is often measured manually, and is therefore subject to variation based on inspection personnel. Eddy current testing (ECT) is sensitive to variations in probe-to-specimen spacing, or lift-off, and is thus promising for high-resolution profiling of surface damage on aluminum panels. Lower frequency testing also allows inspection through the face sheet, an advantage over optical 3D scanning methods. This paper presents results from the ECT inspection of surface damage on an approximately flat aluminum honeycomb aircraft panel, and compares the measurements to those taken using optical 3D scanning technology. An ECT C-Scan of the dented panel surface was obtained by attaching the probe to a robotic scanning apparatus. Data was taken simultaneously at four frequencies of 25, 100, 400 and 1600 kHz. A reference surface was then defined that approximated the original, undamaged panel surface, which also compensated for the effects of specimen tilt and thermal drift within the ECT instrument. Data was converted to lift-off using height calibration curves developed for each probe frequency. A damage region of 22,550 mm² area with dents ranging in depth from 0.13-1.01 mm was analyzed. The method was accurate at 1600 kHz to within 0.05 mm (2σ) when compared with 231 measurements taken via optical 3D scanning. Testing at 25 kHz revealed a 3.2 mm cell size within the honeycomb core, which was confirmed via destructive evaluation. As a result, ECT demonstrates potential for implementation as a method for rapid in-field aircraft panel surface damage assessment.

摘要

蜂窝状飞机面板的表面损伤通常采用人工测量,因此会因检查人员的不同而产生差异。涡流检测(ECT)对探头与试样间距的变化(即提离)很敏感,因此有望用于对铝板表面损伤进行高分辨率成像。低频检测还允许透过面板进行检测,这是优于光学三维扫描方法的一个优势。本文介绍了对一块近似平整的铝制蜂窝状飞机面板表面损伤进行涡流检测的结果,并将测量结果与使用光学三维扫描技术获得的测量结果进行了比较。通过将探头连接到机器人扫描设备上,获得了凹陷面板表面的ECT C扫描图像。在25、100、400和1600 kHz四个频率下同时采集数据。然后定义了一个参考表面,该表面近似于原始的未损坏面板表面,这也补偿了ECT仪器内试样倾斜和热漂移的影响。利用为每个探头频率绘制的高度校准曲线将数据转换为提离值。分析了一个面积为22550 mm²、凹痕深度在0.13 - 1.01 mm范围内的损伤区域。与通过光学三维扫描进行的231次测量相比,该方法在1600 kHz时的精度可达0.05 mm(2σ)以内。在25 kHz下进行的测试显示蜂窝芯内的单元尺寸为3.2 mm,这通过破坏性评估得到了证实。因此,ECT显示出作为一种快速现场飞机面板表面损伤评估方法的应用潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/47bc/5620663/cd83c74190ba/sensors-17-02114-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/47bc/5620663/ffcd1b0e15ef/sensors-17-02114-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/47bc/5620663/63dedc92d317/sensors-17-02114-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/47bc/5620663/5c67f59e18a5/sensors-17-02114-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/47bc/5620663/154429909d3e/sensors-17-02114-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/47bc/5620663/c57764da909a/sensors-17-02114-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/47bc/5620663/f01beddc47a3/sensors-17-02114-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/47bc/5620663/b9dec7eeba21/sensors-17-02114-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/47bc/5620663/e31c7acd85d4/sensors-17-02114-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/47bc/5620663/54c04306d00f/sensors-17-02114-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/47bc/5620663/bd19be5d21a2/sensors-17-02114-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/47bc/5620663/cd83c74190ba/sensors-17-02114-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/47bc/5620663/ffcd1b0e15ef/sensors-17-02114-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/47bc/5620663/63dedc92d317/sensors-17-02114-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/47bc/5620663/5c67f59e18a5/sensors-17-02114-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/47bc/5620663/154429909d3e/sensors-17-02114-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/47bc/5620663/c57764da909a/sensors-17-02114-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/47bc/5620663/f01beddc47a3/sensors-17-02114-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/47bc/5620663/b9dec7eeba21/sensors-17-02114-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/47bc/5620663/e31c7acd85d4/sensors-17-02114-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/47bc/5620663/54c04306d00f/sensors-17-02114-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/47bc/5620663/bd19be5d21a2/sensors-17-02114-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/47bc/5620663/cd83c74190ba/sensors-17-02114-g011.jpg

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