一种消除材料属性对脉冲涡流缺陷轮廓重构影响的方法

doi:10.3969/j.issn.1000-1093.2015.09.023

兵工学报 ›› 2015, Vol. 36 ›› Issue (9): 1766-1771.doi: 10.3969/j.issn.1000-1093.2015.09.023

一种消除材料属性对脉冲涡流缺陷轮廓重构影响的方法

朱红运，王长龙，王建斌，江涛

（军械工程学院无人机工程系，河北石家庄 050003）

收稿日期:2014-12-12 修回日期:2014-12-12 上线日期:2015-11-20
作者简介:朱红运（1988—），男，博士研究生
基金资助:
装备“十二五”预先研究项目(51325010602)

A Method to Eliminate the Influence of Material Properties on Pulsed Eddy Current Defect Profile Reconstruction

ZHU Hong-yun, WANG Chang-long, WANG Jian-bin, JIANG Tao

(Unmanned Aerial System Engineering Department, Ordnance Engineering College, Shijiazhuang 050003, Hebei, China)

Received:2014-12-12 Revised:2014-12-12 Online:2015-11-20

摘要/Abstract

摘要： 采用脉冲涡流技术对缺陷轮廓进行重构时，不同属性材料中相同尺寸缺陷的检测信号特征存在较大的差别，缺陷轮廓重构的精度会受被测试件材料属性的影响，为有效地消除其影响，提出了一种基于不变函数的缺陷轮廓重构方法。该方法通过采用表征同一缺陷的两个不同特征量构建了能够消除材料属性影响的不变函数，而后通过建立由检测信号到缺陷轮廓的非线性映射关系模型，实现了不同属性材料的缺陷轮廓重构。将该方法应用于不同材料的缺陷重构实验，结果表明：该方法不仅可以有效地消除材料属性对缺陷轮廓重构的影响，而且具有较高的重构精度和较强的抗噪声干扰能力，是一种有效可行的缺陷重构方法。

关键词: 电磁学, 脉冲涡流检测, 轮廓重构, 材料属性, 径向基函数

Abstract: When pulsed eddy current testing signal is used to reconstruct defect profile, the signal features of the same defect for different materials are different, and the reconstruction accuracy of defect profile is influenced by the material properties. In order to eliminate the influence of material properties on defect profile reconstruction, a defect profile reconstruction method based on invariance function is proposed. The two features that can characterize the same defect are utilized to construct the invariance function which can eliminate the influence of material properties. A nonlinear mapping model from testing signal to defect profile is established, and the defect profiles of different materials are reconstructed. The approach is utilized to reconstruct the defect profiles of different materials. The results indicate that the proposed approach can eliminate the influence of material properties effectively and reconstruct the defect accurately, and the performance of noise interference suppression of the method is high. It is an effective and feasible approach for defect reconstruction.

Key words: electromagnetics, pulsed eddy current testing, profile reconstruction, material property, radial basis function

中图分类号:

TG115.28

朱红运，王长龙，王建斌，江涛. 一种消除材料属性对脉冲涡流缺陷轮廓重构影响的方法[J]. 兵工学报, 2015, 36(9): 1766-1771.

ZHU Hong-yun, WANG Chang-long, WANG Jian-bin, JIANG Tao. A Method to Eliminate the Influence of Material Properties on Pulsed Eddy Current Defect Profile Reconstruction[J]. Acta Armamentarii, 2015, 36(9): 1766-1771.

参考文献

［1］ Zhang J H, Kim W J, Yuan M D, et al. Analytical approach to pulsed eddy current nondestructive evaluation of multilayered conductive structures [J]. Journal of Mechanical Science and Technology, 2012,26(12): 3953-3958.
[2] Qiu X B, Zhang P, Wei J L, et al. Defect classification by pulsed eddy current technique in con-casting slabs based on spectrum analysis and wavelet decomposition[J]. Sensors and Actuators A:Physical, 2013, 203:272-281.
[3] 徐志远, 武新军, 康宜华, 等. 脉冲涡流检测集总参数模型[J]. 华中科技大学学报, 2013, 41(5): 1-5.
XU Zhi-yuan, WU Xin-jun, KANG Yi-hua, et al. Lumped-parameter model for pulsed eddy current testing[J]. Journal of Huazhong University of Science and Technology, 2013, 41(5): 1-5.(in Chinese)
[4] Bilicz S, Lambert M, Gyimothy S, et al. Solution of inverse problems in nondestructive testing by a kriging-based surrogate model[J]. IEEE Transactions on Magnetics, 2012,48(2):495-498.
[5] Bai L B, Tian G Y, Simm A, et al. Fast crack profile reconstruction using pulsed eddy current signals[J]. NDT & E International, 2013,54:37-44.
[6] Preda G, Hantila F I. Nonlinear integral formulation and neural network-based solution for reconstruction of deep defects with pulsed eddy currents[J]. IEEE Transactions on Magnetics, 2014,50(2):604-608.
[7] Wang L, Xie S J, Chen Z M, et al. Reconstruction of stress corrosion cracks using signals of pulsed eddy current testing[J]. Nondestructive Testing and Evaluation, 2013,28(2):145-154.
[8] Adewale I D, Tian G Y. Decoupling the influence of permeability and conductivity in pulsed eddy current measurements[J]. IEEE Transactions on Magnetics, 2013,49(3):1119-1127.
[9] 付跃文, 喻星星. 油套管腐蚀脉冲涡流检测中探头类型的影响 [J]. 仪器仪表学报, 2014, 35(1): 208-217.
FU Yue-wen, YU Xing-xing. Effect of probe type on corrosion inspection of tubing and casing string with pulsed eddy current[J]. Chinese Journal of Scientific Instrument, 2014, 35(1): 208-217.(in Chinese)
[10] 周德强,田贵云,尤丽华,等. 基于频谱分析的脉冲涡流缺陷检测研究 [J]. 仪器仪表学报, 2011,32(9):1948-1953.
ZHOU De-qiang, TIAN Gui-yun, YOU Li-hua, et al. Study on pulsed eddy current defect signal detection technology based on spectrum analysis[J]. Chinese Journal of Scientific Instrument, 2011,32(9):1948-1953.(in Chinese)
[11] 苑希超, 王长龙, 王建斌. 基于贝叶斯估计的漏磁缺陷轮廓重构方法研究[J]. 兵工学报, 2012,33(1):116-120.
YUAN Xi-chao, WANG Chang-long, WANG Jian-bin. Defect profile reconstruction from magnetic flux leakage signals based on bayesian estimation[J]. Acta Armamentarii, 2012, 33(1): 116-120.(in Chinese)
[12] Angani C S, Park D G, Kim G D, et al. Differential pulsed eddy current sensor for the detection of wall thinning in an insulated stainless steel pipe[J]. Journal of Applied Physics, 2010,107(9):721-723.
[13] 周德强, 张斌强, 田贵云, 等. 脉冲涡流检测中裂纹的深度定量及分类识别[J]. 仪器仪表学报, 2009, 30(6):1190-1194.
ZHOU De-qiang, ZHANG Bin-qiang, TIAN Gui-yun, et al. Quantification of depth and classification of cracks using pulsed eddy current test technology[J]. Chinese Journal of Scientific Instrument, 2009, 30(6):1190-1194.(in Chinese)
[14] 阮晓钢. 自组织径向基网络及其混合学习算法[J]. 北京工业大学学报, 1999, 25(2):31-37.
Ruan Xiao-gang. An organizing radial basis function network and it's hybrid learning algorithm[J]. Journal of Beijing Polytechnic University, 1999, 25(2):31-37.(in Chinese)
[15] 徐超, 王长龙, 孙世宇, 等. 双小波神经网络迭代的漏磁缺陷轮廓重构技术[J]. 兵工学报, 2012,33(6):730-735.
XU Chao, WANG Chang-long, SUN Shi-yu, et al. Magnetic flux leakage defect reconstruction method based on wavelet neural network iteration[J]. Acta Armamentarii, 2012, 33(6): 730-735.(in Chinese)

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一种消除材料属性对脉冲涡流缺陷轮廓重构影响的方法

A Method to Eliminate the Influence of Material Properties on Pulsed Eddy Current Defect Profile Reconstruction

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