Defect imaging curved surface based on flexible eddy current array sensor
Defect imaging curved surface based on flexible eddy current array sensor
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DOI：
10.1016/j.measurement.2019.107280
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发表时间：
2020-02-01
期刊：
影响因子：
5.6
通讯作者：
Zhang, Huayu
中科院分区：
文献类型：
--
作者：
Zhang, Weipeng;Wang, Chenglong;Zhang, Huayu
针对复杂曲面表面质量检测中难以直观反映缺陷大小、分布、形状和位置的问题，采用柔性涡流阵列(FECA)探头结合笛卡尔坐标机器人对汽轮机末级叶片缺陷进行扫描。传感器探头设计为平行和交错排列，并焊接在柔性印刷电路板(FPCB)上。FECA传感器薄而灵活，因此它可以符合LSBST的表面几何形状。为了增加单探头线圈的电感值，在圆柱形线圈的中间增加了铁芯。在信号检测过程中，进行了起始点补偿和提离效应补偿，提高了缺陷检测的分辨率，实现了对LSBST表面自然缺陷的成像。最后，通过实验验证了缺陷成像对汽轮机叶片的影响。结果表明，缺陷的大小、位置和形状与实际情况一致，验证了成像算法的可行性。(C)2019爱思唯尔有限公司。保留所有权利。
Due to it is difficult to visually reflect the size, distribution shape and location of the defects in surface quality detection of complex surfaces, the flexible eddy current array (FECA) probe combined with the Cartesian coordinate robot is employed to scan the defects on last stage blades of steam turbine (LSBST) in this paper. The sensor probe is designed to parallel and stagger arrangement and weld onto a flexible printed circuit board (FPCB). The FECA sensor is thin and flexible, and thus it can conform to the surface geometries of the LSBST. To increase the inductance value of the single probe coil, Iron core is added in the middle of the cylindrical coil. In the process of detecting signal, the starting point compensation and lift-off effect compensation are carried out, which improves the resolution of defect detection and realizes the imaging of the natural defects on the surface of LSBST. Finally, the effect of defect imaging on steam turbine blades is verified through conducting experiments. Results demonstrate that the size, location and shape of defects are consistent with the actual situation which verifies the feasibility of the imaging algorithm. (C) 2019 Elsevier Ltd. All rights reserved.