磁声电无损检测及改进的EMD消噪方法

doi:10.19595/j.cnki.1000-6753.tces.171126

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Abstract In this paper, a new non-destructive testing method referred to as magneto-acousto-electrical non-destructive testing (MAE-NDT) is proposed. This method has the high spatial resolution of ultrasonic testing and can overcome the skin effect of eddy current testing. It provides a new method for testing high conductivity materials. Firstly, according to the results of the study on magneto-acousto-electrical tomography in biological tissues, the forward problems of the sound field and the electromagnetic field were derived. So the feasibility of the method was proved. Secondly, aiming at the noise of the detected signals, the composition and characteristics of noise in magneto-acousto-electrical nondestructive testing signals were analyzed. A hybrid threshold EMD de-noising algorithm which combines the advantages of EMD-DT and EMD-IT was proposed. Finally, an experimental system was designed and the magneto-acousto electrical defect signal was measured. Therefore, the feasibility of the method was further verified. The results of simulated and measured signals show that the improved EMD de-noising method has better de-noising effect, improves the signal to noise ratio effectively.

Key words： Magneto-acousto-electrical non-destructive testing empirical mode decomposition de-noising

Received: 01 August 2017 Published: 14 September 2018

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TM93

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.171126 OR https://dgjsxb.ces-transaction.com/EN/Y2018/V33/I17/3935

[1] 张闯, 蒋盼, 刘素贞, 等. 电磁声发射信号的压缩与重构处理[J]. 电工技术学报, 2017, 32(9): 121-128.
Zhang Chuang, Jiang Pan, Liu Suzhen, et al.Compression and reconstruction processing of the electromagnetically induced acoustic emission signal[J]. Transactions of China Electrotechnical Society, 2017, 32(9): 121-128.
[2] 蔡智超, 刘素贞, 张闯, 等. 永磁扰动检测有限元分析及优化设计[J]. 电工技术学报, 2015, 30(3): 67-72.
Cai Zhichao, Liu Suzhen, Zhang Chuang, et al.Finite element analysis and optimum design of permanent magnetic field perturbation testing[J]. Transactions of China Electrotechnical Society, 2015, 30(3): 67-72.
[3] Kravcov A, Svoboda P, Konvalinka A, et al.Laser-ultrasonic testing of the structure and properties of concrete and carbon fiber-reinforced plastics[J]. Key Engineering Materials, 2016, 722: 267-272.
[4] Jiang Hongquan, Liang Zeming, Gao Jianmin, et al.Classification of weld defect based on information fusion technology for radiographic testing system[J]. Review of Scientific Instruments, 2016, 87(3): 035110.
[5] 范孟豹, 尹亚丹, 曹丙花. 金属管件电涡流检测偏心效应的解析建模与仿真[J]. 中国电机工程学报, 2012, 32(30): 133-138.
Fan Mengbao, Yin Yadan, Cao Binghua.Modeling and analysis of the effect of probe radial offset on eddy current nondestructive testing and evaluation of metallic tubes[J]. Proceedings of the CSEE, 2012, 32(30): 133-138.
[6] 陈兴乐, 雷银照. 铁磁平板脉冲涡流场感应电压时域近似式[J]. 电工技术学报, 2015, 30(10): 14-19.
Chen Xingle, Lei Yinzhao.Time-domain approximate expressions for voltage induced by pulsed eddy current field of ferromagnetic plate[J]. Transactions of China Electrotechnical Society, 2015, 30(10): 14-19.
[7] Manuello A, Lacidogna G, Niccolini G, et al.Wireless acoustic emission monitoring of structural behavior[J]. Proceedings of the National Academy of Sciences, 2007, 104(52): 20666-20671.
[8] Haider S, Hrbek A Y.Magneto-acousto-electrical tomography: a potential method for imaging current density and electrical impedance[J]. Physiological Measurement, 2008, 29(6): S41-S50.
[9] Li Xu, He Bin.Magnetoacoustic tomography with magnetic induction (MAT-MI) for electrical conductivity imaging[J]. IEEE Transactions on Medical Imaging, 2005, 50(21): 5175.
[10] Mariappan L, Shao Qi, Jiang Chunlan, et al.Magneto acoustic tomography with short pulsed magnetic field for in-vivo imaging of magnetic iron oxide nanoparticles[J]. Nanomedicine Nanotechnology Biology & Medicine, 2016, 12(3): 689-699.
[11] Guo Liang, Jiang Wencong, Liu Guoqiang, et al.Development of the pulse magnetic field excitation system in magnetoacoustic tomography[C]//IEEE International Conference on Electron Devices and Solid-State Circuits, Xi’an, China, 2015: 329-332.
[12] 刘国强. 基于电检测的磁声成像技术[M]. 北京: 科学出版社, 2016.
[13] Zheng Y, Basart J P.NDE X-ray modeling and adaptive filtering considering correlated noise: review of progress in quantitative nondestructive evaluation[J]. Gastroenterology, 1992, 124(4): 813-820.
[14] 张志刚, 周晓军, 杨富春, 等. 基于小波系数相关性和局部拉普拉斯模型降噪方法[J]. 振动与冲击, 2008, 27(11): 32-36.
Zhang Zhigang, Zhou Xiaojun, Yang Fuchun, et al.Denoising method based on wavelet transform coefficient correlation and local laplacian model[J]. Journal of Vibration & Shock, 2008, 27(11): 32-36.
[15] 李宏坤, 张晓雯, 贺长波, 等. 利用随机共振的叶片裂纹微弱信息增强方法[J]. 机械工程学报, 2016, 52(1): 94-101.
Li Hongkun, Zhang Xiaowen, He Changbo, et al.Weak fault enhancement method for blade crack by using stochastic resonance[J]. Journal of Mechanical Engineering, 2016, 52(1): 94-101.
[16] Pedram S K, Haig A, Lowe P S, et al.Split-spectrum signal processing for reduction of the effect of dispersive wave modes in long-range ultrasonic testing[J]. Physics Procedia, 2015, 70: 388-392.
[17] 刘柏年, 皇群博, 张卫民, 等. 集合背景误差方差中小波阈值去噪方法研究及试验[J]. 物理学报, 2017, 66(2): 85-93.
Liu Bainian, Huang Qunbo, Zhang Weimin, et al.Invesitgation and experiments of wavelet thresholding in ensemble-based background error variance[J]. Acta Physica Sinica. 2017, 66(2): 85-93.
[18] Yang Gongliu, Liu Yuanyuan, Wang Yanyong, et al.EMD interval thresholding denoising based on similarity measure to select relevant modes[J]. Signal Processing, 2015, 109: 95-109.
[19] Kopsinis Y, Mclaughlin S.Development of EMD-based denoising methods inspired by wavelet thresholding[J]. IEEE Transactions on Signal Processing, 2009, 57(4): 1351-1362.
[20] 沈建国. 应用声学基础——实轴积分法及二维谱技术[M]. 天津: 天津大学出版社, 2004.
[21] Saniie J, Wang T, Bilgutay N M.Statistical evaluation of backscattered ultrasonic grain signals[J]. Acoustical Society of America Journal, 1988, 84(1): 400-408.
[22] Flandrin P, Goncalves P, Rilling G.Detrending and denoising with empirical mode decompositions[C]// European Signal Processing Conference, 2004, Vienna, Austria, 2004: 1581-1584.