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在对冲击激励声发射应力波在铝合金板上的传播机理进行分析的基础上,利用ABAQUS软件构建了钢球冲击铝合金板几何模型,仿真分析了冲击应力波传播过程.理论分析了冲击应力波与FBG传感器的作用机理,基于边缘滤波原理构建了声发射传感系统,采集冲击激励声发射应力波,建立了声发射区域定位模型,提出了基于扩散映射与支持向量机(SVM)的声发射区域定位方法并进行了实验验证.在300 mm300 mm2 mm的铝合金板上对36个测试区域进行了多次声发射区域定位实验,实验结果表明,扩散映射结合SVM的定位结果较优,区域定位精度为30 mm30 mm,定位正确率为97.5%,耗时0.781 s.研究结果为声发射区域定位检测提供了一种有效方法.Based on the analysis of the propagation mechanism of acoustic emission stress waves caused by impact excitation on aluminum alloy plates, The geometrical model of steel ball impacted aluminum alloy plate was built by ABAQUS software, and the stress wave propagation process is simulated and analyzed. The stress wave propagation process is simulated and analyzed and an acoustic emission sensing system based on the principle of edge filtering is constructed. The acoustic emission stress waves were collected to establish the acoustic emission region localization model. The localization method of acoustic emission region based on diffusion mapping and support vector machine is proposed and verified experimentally. Multiple acoustic emission localization experiments were performed on an aluminum alloy plate of 300 mm300 mm2 mm, which was divided into 36 test area. The results show that the localization accuracy is 30 mm30 mm and the positioning accuracy was 97.5%, while consuming 0.781 s. The study provides an effective method for acoustic emission localization.
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Keywords:
- fiber Bragg grating /
- acoustic emission sensing /
- impact location /
- support vector machine
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[19] Lafon S, Lee A B 2006 IEEE Trans. Pattern Anal. Machine Intellig. 28 1393
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[1] Zhang J R, Ma H Y, Yan W J, Li Z J 2016 Appl. Acoust. 105 67
[2] Loutas T H, Panopoulou A, Roulias D, Kostopoulos V 2012 Expert Syst. Appl. 39 8412
[3] Wiggins S M, Leifer I, Linke P, Hildebrand J A 2015 Marine and Petroleum Geology 68 776
[4] Fu T 2014 Ph. D. Dissertation (Haerbin:Harbin Institute of Technology) (in Chinese)[付涛2014博士学位论文(哈尔滨:哈尔滨工业大学)]
[5] Yu F M, Okabe Y, Wu Q, Shigeta N 2016 Composites Sci. Technol. 135 116
[6] Gao X, Zhang X P, Li N, Xin P 2014 Asia-Pacific International Symposium on Aerospace Technology China September 24-36, 2014 p1203
[7] Munoz V, Vales B, Perrin M, Pastor M, Welmane H, Cantarel A, Karama M 2016 Composites Part B 85 68
[8] Shrestha P, Kim J, Park Y, Kim C 2015 Composite Struct. 125 159
[9] Hafizi Z, Epaarachchi J, Lau K 2015 Measurement 61 51
[10] Jiang M S, Sui Q M, Jia L, Peng P, Cao Y Q 2012 Optoelectron. Lett. 8 220
[11] Cheng X M, Zhang X D, Zhao L, Deng A D, Bao Y Q, Liu Y, Jiang Y L 2014 Comptes Rendus Mecanique 342 229
[12] Jiang Y, Xu F Y, Xu B S 2015 Mechanical Systems and Signal Processing 64 452
[13] Sadegh H, Mehdi A, Mehdi A 2016 Tribology International 95 426
[14] Li Z B, Ma H L, Cao Z S, Sun M G, Huang Y B, Zhu W Y, Liu Q 2016 Acta Phys. Sin. 65 053301 (in Chinese)[李志彬, 马宏亮, 曹振松, 孙明国, 黄印博, 朱文越, 刘强2016 65 053301]
[15] Jin Z W 2014 M. S. Dissertation (Shandong:Shandong University) (in Chinese)[金中薇2014硕士学位论文(山东:山东大学)]
[16] Cao Y, Pei Y W, Tong Z R 2014 Acta Phys. Sin. 63 024206(in Chinese) (in Chinese)[曹晔, 裴庸惟, 童峥嵘2014 63 024206]
[17] Gu B, Sun X, Sheng V S 2016 IEEE Trans. Neural Networks Learning Systems 1 1
[18] Scholkopf B, Smola A, Williamson R, Bartlett 2000 Neural Comput. 15 1207
[19] Lafon S, Lee A B 2006 IEEE Trans. Pattern Anal. Machine Intellig. 28 1393
[20] Nadler B, Lafon S, Coifman R R, Kevrekidis I G 2006 Appl. Computat. Harmonic Anal. 21 113
[21] Jia B, Yu B T, Wu Q, Yang X S, Wei C F, Law R, Fu S 2016 Neurocomputing 189 106
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