基于反转路径差信号的兰姆波成像方法

焦敬品; 李海平; 何存富; 吴斌; 薛岩

doi:10.7498/aps.68.20190101

摘要

针对传统基线相减成像方法受环境温度影响的问题, 考虑到反转路径下超声波在缺陷处散射场的差异性, 提出了一种基于反转路径差信号的兰姆波稀疏阵列成像方法. 通过数值仿真, 对反转路径差信号的来源进行了分析, 并研究了缺陷与两个传感器的夹角及路径差对反转路径差信号幅值的影响规律. 在此基础上, 通过数值仿真及检测实验, 研究了基于反转路径差信号的兰姆波成像方法对板中缺陷检测的有效性. 结果表明, 基于反转路径差信号的兰姆波成像方法可以很好地消除直达波对缺陷成像的影响, 实现板中不同位置的圆孔和矩形缺陷成像, 且成像分辨率较高, 定位较准确. 本文为板结构大范围健康监测提供了一种可行的新方案.

关键词:

Abstract

The traditional Lamb wave structure health monitoring imaging method based on reference signal is affected by environmental factors such as temperature change. To solve this problem, considering the difference in the scattered fields generated by the interaction between ultrasonic waves and defects in the reverse path, a Lamb wave imaging method is proposed in this paper based on the difference signal of sparse array in inverse path. Numerical simulations are carried out to determine the generation conditions of difference signal in inversion path, and the influences of the angles and distances between the defect and the two sensors on the amplitude of difference signal in inversion path. It is found that the difference signal in reverse path is much more obvious when the defect appears as asymmetric distribution towards the excitation sensor and receiving sensors; the amplitude of difference signal in inverse path is affected by distance difference of the Lamb wave propagating in reverse path and the scattering coefficient of the defect. On this basis, the effectiveness of the Lamb wave imaging method based on the difference signal in inverse path is studied numerically and experimentally. The results show that the Lamb wave imaging method based on the difference signal in inversion path can perfectly eliminate the interference between direct wave and the boundary reflection wave, and the imaging method can detect the defect at different positions in the plate. Moreover, the imaging resolution is higher and the defect location is accurate. The research work provides a new feasible scheme for the extensive health monitoring of plate structure.

Keywords:

作者及机构信息

1.
北京工业大学机械工程与应用电子技术学院, 北京　100124

2.
中国石油天然气管道科学研究院有限公司, 廊坊　065000

通信作者: 焦敬品, jiaojp@bjut.edu.cn

基金项目: 国家重点研发计划(批准号: 2016YFC0802102)和国家自然科学基金(批准号: 11572010)资助的课题.

Authors and contacts

1.
College of Mechanical Engineering and Applied Electronics Technology, Beijing University of Technology, Beijing 100124, China

2.
PetroChina Natural Gas Pipeline Science Research Institute Corporation Limited, Langfang 065000, China

Corresponding author: Jiao Jing-Pin, jiaojp@bjut.edu.cn

Funds: Project supported by the National Key Research and Development Program of China (Grant No. 2016YFC0802102) and the National Natural Science Foundation of China (Grant No. 11572010).

文章全文 : translate this paragraph

参考文献

[1]	Abbas M, Shafiee M 2018 Sensors 18 3958 Google Scholar
[2]	高广健, 邓明晰, 李明亮, 刘畅 2015 物理学报 64 224301 Google Scholar Gao G J, Deng M X, Li M L, Liu C 2015 Acta Phys. Sin. 64 224301 Google Scholar
[3]	Kudela P, Radzienski M, Ostachowicz W, Yang Z 2018 Mech. Syst. Signal Proc. 108 21 Google Scholar
[4]	Chen S J, Zhou S P, Li Y, Xiang Y X, Qi M X 2017 Chin. Phys. Lett. 34 044301 Google Scholar
[5]	Petrone G 2018 Aerosp. Sci. Technol. 82 304
[6]	Munian R K, Mahapatra D R, Gopalakrishnan S 2018 Compos. Struct. 206 484 Google Scholar
[7]	Mohammadi M, Pouyan A A, Khan N A, Abolghasemi V 2018 Signal Process. 150 85 Google Scholar
[8]	Kim C Y, Park K J 2015 NDT&E Int. 74 15
[9]	Wilcox P D, Lowe M, Cawley P 2003 IEEE Trans. Ultrason. Ferroelectr. 50 419 Google Scholar
[10]	Xu K, Ta D, Moilanen P, Wang W Q 2012 J. Acoust. Soc. Am. 131 2714 Google Scholar
[11]	Agrahari J K, Kapuria S 2018 Struct. Control HLTH. 25 e2064 Google Scholar
[12]	Salmanpour M S, Sharif K Z, Mhf A 2017 Sensors 17 1178 Google Scholar
[13]	Muller A, Robertson-Welsh B, Gaydecki P, Gresil M, Soutis C 2017 Appl. Compos. Mater. 24 553 Google Scholar
[14]	Zhao X L, Gao H D, Zhang G F, Ayhan B, Yan F, Kwan C, Rose J L 2007 Smart Mater. Struct. 16 1208 Google Scholar
[15]	Chen F, Wilcox P D 2007 Ultrasonics 47 111 Google Scholar
[16]	Douglass A C S, Harley J B 2018 IEEE Trans. Ultrason. Ferroelectr. 65 851 Google Scholar
[17]	Lu Y, Michaels J E 2009 IEEE Sens. J. 9 1462 Google Scholar
[18]	Sohn H 2007 Philos. Trans. R. Soc. A:-Math. Phys. 365 539 Google Scholar
[19]	Clarke T, Cawley P, Wilcox P, Croxford A 2009 IEEE Trans. Ultrason. Ferroelectr. Freq. Control 56 2666 Google Scholar
[20]	Konstantinidis G, Wilcox P D, Drinkwater B W 2007 IEEE Sens. J. 7 905 Google Scholar
[21]	Park H W, Sohn H, Law K H, Farrar C R 2007 J. Sound Vibr. 302 50 Google Scholar
[22]	Jan H, Morteza T, Steven D, van Koen D A 2016 Material 9 901 Google Scholar
[23]	Tabatabaeipour M, Hettler J, Delrue S, van Den Abeele K 2016 NDT&E Int. 80 23
[24]	Ciampa F, Pickering S G, Scarselli G, Meo M 2017 Struct. Control HLTH. 24 e1911 Google Scholar
[25]	Demetgul M, Senyurek V Y, Uyandik R, Tansel I N, Yazicioglu O 2015 Measurement 69 42 Google Scholar
[26]	Nguyen L T, Kocur G K, Saenger E H 2018 Ultrasonics 90 153 Google Scholar
[27]	Hongye L, Xin C, Michaels J E, Michaels T E, Cunfu H 2019 Ultrasonics 91 220 Google Scholar
[28]	Zhang J, Drinkwater B W, Wilcox P D 2008 IEEE Trans. Ultrason. Ferroelectr. Freq. Control. 55 2254 Google Scholar
[29]	郑阳, 何存富, 周进节, 张也弛 2013 工程力学 30 236 Zheng Y, He C F, Zhou J J, Zhang Y C 2013 Eng. Mech. 30 236
[30]	Harley J B, Moura J M 2013 J. Acoust. Soc. Am. 133 2732 Google Scholar
[31]	Harley J B, José M F 2014 J. Acoust. Soc. Am. 135 1231 Google Scholar
[32]	Soleimanpour R, Ng C T 2016 J. Civil Struct. Health Monit. 6 447 Google Scholar

施引文献

图 1 无限大薄板中兰姆波传播模型示意图

Fig. 1. Schematic diagram of Lamb wave propagation model in an infinite plate.

下载: 全尺寸图片幻灯片

图 2 接收信号模态分析数值仿真模型

Fig. 2. Numerical simulation model of modal analysis of received signals.

下载: 全尺寸图片幻灯片

图 3 不同位置接收到的z方向的去参考信号

Fig. 3. Dereference signals in the z direction received at different positions.

下载: 全尺寸图片幻灯片

图 4 不同位置接收到x方向的去参考信号

Fig. 4. Dereference signal in the x direction received at different positions.

下载: 全尺寸图片幻灯片

图 5 z方向去参考信号的2D-FFT

Fig. 5. 2D-FFT of the reference signal in the z direction.

下载: 全尺寸图片幻灯片

图 6 x方向去参考信号的2D-FFT

Fig. 6. 2D-FFT of the reference signal in the x direction.

下载: 全尺寸图片幻灯片

图 7 影响因素分析数值仿真模型　(a) 双因素综合影响模型; (b) 距离差影响因素模型

Fig. 7. Numerical simulation model of influencing factor analysis: (a) A model of two-factor comprehensive impact; (b) model of distance difference influencing factor.

下载: 全尺寸图片幻灯片

图 8 当l = 0时接收信号及反转路径差信号

Fig. 8. Received signal and reverse path delta signal when l = 0.

下载: 全尺寸图片幻灯片

图 9 当l ≠ 0时接收信号及反转路径差信号

Fig. 9. Received signal and reverse path delta signal when l ≠ 0.

下载: 全尺寸图片幻灯片

图 10 不同传播距离差下的差信号最大幅值

Fig. 10. Maximum amplitude of the delta signals under different propagation distance differences.

下载: 全尺寸图片幻灯片

图 11 不同传播距离差下的$\Delta A$计算结果

Fig. 11. Calculation results of $\Delta A$ under different propagation distance differences.

下载: 全尺寸图片幻灯片

图 12 不同缺陷位置下的差信号幅值

Fig. 12. Amplitude of delta signals at different defect locations.

下载: 全尺寸图片幻灯片

图 13 圆形通孔缺陷的散射系数

Fig. 13. Scattering coefficient of the circular through hole defect

下载: 全尺寸图片幻灯片

图 14 不同缺陷位置下的散射系数

Fig. 14. Scattering coefficients at different defect locations.

下载: 全尺寸图片幻灯片

图 15 不同缺陷位置下的$\Delta A$值

Fig. 15. Values of $\Delta A$ at different defect locations.

下载: 全尺寸图片幻灯片

图 16 板结构稀疏阵列兰姆波检测仿真模型

Fig. 16. Simulation model of lamb waves detection for sparse array of plate structure.

下载: 全尺寸图片幻灯片

图 17 圆形通孔缺陷成像结果　(a) 序号1 (基于参考信号); (b) 序号2; (c) 序号3; (d) 序号4

Fig. 17. Imaging results of circular through hole defects: (a) Number 1 (based on reference signal); (b) number 2; (c) number 3; (d) number 4.

下载: 全尺寸图片幻灯片

图 18 矩形缺陷成像结果　(a) 序号; (b) 序号2

Fig. 18. Imaging results of rectangular defect: (a) Number 1; (b) number 2.

下载: 全尺寸图片幻灯片

图 19 典型传感器对的反转路径差信号及其对成像的贡献　(a) 1号和3号传感器对的反转路径差信号; (b) 1号和3号传感器对的反转路径差信号对成像的贡献; (c) 2号和4号传感器对的反转路径差信号; (d) 2号和4号传感器对的反转路径差信号对成像的贡献

Fig. 19. Inverted path delta signal of a typical sensor pairs and its contribution to imaging: (a) Inverted path delta signal of sensor pairs of number1 and number 3; (b) contribution to imaging of inverted path delta signal of sensor pairs of number1 and number 3; (c) inverted path delta signal of sensor pairs of number 2 and number 4; (d)contribution to imaging of inverted path delta signal of sensor pairs of number 2 and number 4.

下载: 全尺寸图片幻灯片

图 20 基于反转路径差信号的成像结果

Fig. 20. Imaging results based on the inverted path delta signal.

下载: 全尺寸图片幻灯片

图 21 实验系统示意图

Fig. 21. Schematic diagram of the experimental system.

下载: 全尺寸图片幻灯片

图 23 实验成像结果　(a) 4个传感器; (b) 6个传感器

Fig. 23. Imaging results of the experiment: (a) Four sensors; (b) six sensors.

下载: 全尺寸图片幻灯片

图 22 2号和4号传感器对的接收信号及差信号

Fig. 22. Receiving signals and delta signal for sensor pairs 2 and 4.

下载: 全尺寸图片幻灯片

表 1 不同位置缺陷的坐标(单位mm)以及相应的夹角α (单位(°))

Table 1. Coordinates (unit: mm) of defects at different locations and corresponding angles α (unit: (°))

h	l
h	0	10	20	30	40	50	60	70	80	90
60	118.1	117.7	116.6	114.62	111.8	108.0	103.1	97.1	90.0	81.93
72	102.7	102.3	101.3	99.6	97.1	93.9	90.0	85.35	80.1	74.3
80	108.5	108.1	107.0	105.2	102.6	99.1	94.8	89.6	83.7	77.2
100	90.0	89.7	88.8	87.4	85.4	82.8	79.8	76.2	72.2	68.0

下载: 导出CSV

表 2 圆形缺陷检测时仿真参数及定位结果(单位: mm)

Table 2. Simulation parameters and positioning results for circular defect detection (unit: mm).

序号	传感器1	传感器2	传感器3	传感器4	缺陷P位置	定位结果	定位误差
1 (基于参考信号)	(150, 350)	(350, 350)	(150, 150)	(350, 150)	(280, 280)	(284, 281)	4.1
2	(150, 350)	(350, 350)	(150, 150)	(350, 150)	(280, 280)	(285, 285)	7.1
3	(150, 340)	(350, 340)	(150, 150)	(350, 150)	(240, 280)	(239, 282)	2.2
4	(170, 350)	(350, 335)	(140, 150)	(345, 160)	(240, 280)	(239, 281)	1.4

下载: 导出CSV

表 3 矩形缺陷检测时仿真参数及定位结果(单位: mm)

Table 3. Simulation parameters and positioning results for rectangular defect detection (unit: mm).

序号	传感器1	传感器2	传感器3	传感器4	缺陷P位置	定位结果	定位误差
1	(150, 340)	(350, 340)	(150, 150)	(350, 150)	(240, 280)	(239, 279)	1.4
2	(170, 350)	(350, 335)	(140, 150)	(345, 160)	(240, 280)	(241, 279)	1.4

下载: 导出CSV

表 4 考虑边界影响时仿真参数及定位结果(单位: mm)

Table 4. Simulation parameters and positioning results when considering boundary effects (unit: mm).

序号	传感器1	传感器2	传感器3	传感器4	缺陷位置	定位结果	定位误差
1	(140, 370)	(380, 3355)	(130, 140)	(360, 150)	(240, 280)	(240, 284)	4

下载: 导出CSV

[1]	Abbas M, Shafiee M 2018 Sensors 18 3958 Google Scholar
[2]	高广健, 邓明晰, 李明亮, 刘畅 2015 物理学报 64 224301 Google Scholar Gao G J, Deng M X, Li M L, Liu C 2015 Acta Phys. Sin. 64 224301 Google Scholar
[3]	Kudela P, Radzienski M, Ostachowicz W, Yang Z 2018 Mech. Syst. Signal Proc. 108 21 Google Scholar
[4]	Chen S J, Zhou S P, Li Y, Xiang Y X, Qi M X 2017 Chin. Phys. Lett. 34 044301 Google Scholar
[5]	Petrone G 2018 Aerosp. Sci. Technol. 82 304
[6]	Munian R K, Mahapatra D R, Gopalakrishnan S 2018 Compos. Struct. 206 484 Google Scholar
[7]	Mohammadi M, Pouyan A A, Khan N A, Abolghasemi V 2018 Signal Process. 150 85 Google Scholar
[8]	Kim C Y, Park K J 2015 NDT&E Int. 74 15
[9]	Wilcox P D, Lowe M, Cawley P 2003 IEEE Trans. Ultrason. Ferroelectr. 50 419 Google Scholar
[10]	Xu K, Ta D, Moilanen P, Wang W Q 2012 J. Acoust. Soc. Am. 131 2714 Google Scholar
[11]	Agrahari J K, Kapuria S 2018 Struct. Control HLTH. 25 e2064 Google Scholar
[12]	Salmanpour M S, Sharif K Z, Mhf A 2017 Sensors 17 1178 Google Scholar
[13]	Muller A, Robertson-Welsh B, Gaydecki P, Gresil M, Soutis C 2017 Appl. Compos. Mater. 24 553 Google Scholar
[14]	Zhao X L, Gao H D, Zhang G F, Ayhan B, Yan F, Kwan C, Rose J L 2007 Smart Mater. Struct. 16 1208 Google Scholar
[15]	Chen F, Wilcox P D 2007 Ultrasonics 47 111 Google Scholar
[16]	Douglass A C S, Harley J B 2018 IEEE Trans. Ultrason. Ferroelectr. 65 851 Google Scholar
[17]	Lu Y, Michaels J E 2009 IEEE Sens. J. 9 1462 Google Scholar
[18]	Sohn H 2007 Philos. Trans. R. Soc. A:-Math. Phys. 365 539 Google Scholar
[19]	Clarke T, Cawley P, Wilcox P, Croxford A 2009 IEEE Trans. Ultrason. Ferroelectr. Freq. Control 56 2666 Google Scholar
[20]	Konstantinidis G, Wilcox P D, Drinkwater B W 2007 IEEE Sens. J. 7 905 Google Scholar
[21]	Park H W, Sohn H, Law K H, Farrar C R 2007 J. Sound Vibr. 302 50 Google Scholar
[22]	Jan H, Morteza T, Steven D, van Koen D A 2016 Material 9 901 Google Scholar
[23]	Tabatabaeipour M, Hettler J, Delrue S, van Den Abeele K 2016 NDT&E Int. 80 23
[24]	Ciampa F, Pickering S G, Scarselli G, Meo M 2017 Struct. Control HLTH. 24 e1911 Google Scholar
[25]	Demetgul M, Senyurek V Y, Uyandik R, Tansel I N, Yazicioglu O 2015 Measurement 69 42 Google Scholar
[26]	Nguyen L T, Kocur G K, Saenger E H 2018 Ultrasonics 90 153 Google Scholar
[27]	Hongye L, Xin C, Michaels J E, Michaels T E, Cunfu H 2019 Ultrasonics 91 220 Google Scholar
[28]	Zhang J, Drinkwater B W, Wilcox P D 2008 IEEE Trans. Ultrason. Ferroelectr. Freq. Control. 55 2254 Google Scholar
[29]	郑阳, 何存富, 周进节, 张也弛 2013 工程力学 30 236 Zheng Y, He C F, Zhou J J, Zhang Y C 2013 Eng. Mech. 30 236
[30]	Harley J B, Moura J M 2013 J. Acoust. Soc. Am. 133 2732 Google Scholar
[31]	Harley J B, José M F 2014 J. Acoust. Soc. Am. 135 1231 Google Scholar
[32]	Soleimanpour R, Ng C T 2016 J. Civil Struct. Health Monit. 6 447 Google Scholar

[1]	计晨. 原子兰姆位移与超精细结构中的核结构效应. 物理学报, 2024, 73(20): 202101. doi: 10.7498/aps.73.20241063
[2]	李永飞, 郭瑞明, 赵航芳. 浅海内波环境下声场干涉条纹的稀疏重建. 物理学报, 2023, 72(7): 074301. doi: 10.7498/aps.72.20221932
[3]	谢前朋, 潘小义, 陈吉源, 肖顺平. 基于稀疏阵列的电磁矢量传感器多输入多输出雷达高分辨角度和极化参数联合估计. 物理学报, 2020, 69(7): 074302. doi: 10.7498/aps.69.20191895
[4]	崔岸婧, 李道京, 周凯, 王宇, 洪峻. 阵列结构下的低频信号合成方法研究. 物理学报, 2020, 69(19): 194101. doi: 10.7498/aps.69.20200501
[5]	张涛, 侯宏, 鲍明. 基于稀疏重构的尾波干涉成像方法. 物理学报, 2019, 68(19): 199101. doi: 10.7498/aps.68.20190831
[6]	郝未倩, 梁忠诚, 刘肖尧, 赵瑞, 孔梅梅, 关建飞, 张月. 分形结构稀疏孔径阵列的成像性能. 物理学报, 2019, 68(19): 199501. doi: 10.7498/aps.68.20190818
[7]	倪龙, 陈晓. 基于频散补偿和分数阶微分的多模式兰姆波分离. 物理学报, 2018, 67(20): 204301. doi: 10.7498/aps.67.20180561
[8]	张海燕, 徐梦云, 张辉, 朱文发, 柴晓冬. 利用扩散场信息的超声兰姆波全聚焦成像. 物理学报, 2018, 67(22): 224301. doi: 10.7498/aps.67.20181268
[9]	丰卉, 孙彪, 马书根. 分块稀疏信号1-bit压缩感知重建方法. 物理学报, 2017, 66(18): 180202. doi: 10.7498/aps.66.180202
[10]	侯兴民, 章程, 邱锦涛, 顾建伟, 王瑞雪, 邵涛. 大气压管板结构纳秒脉冲放电中时域X射线研究. 物理学报, 2017, 66(10): 105204. doi: 10.7498/aps.66.105204
[11]	张海燕, 杨杰, 范国鹏, 朱文发, 柴晓冬. 基于模式分离的兰姆波逆时偏移成像. 物理学报, 2017, 66(21): 214301. doi: 10.7498/aps.66.214301
[12]	陈典兵, 朱明, 高文, 王慧利, 杨航. 基于残差矩阵估计的稀疏表示目标跟踪算法. 物理学报, 2016, 65(19): 194201. doi: 10.7498/aps.65.194201
[13]	陈秋菊, 姜秋喜, 曾芳玲, 宋长宝. 基于时间反演电磁波的稀疏阵列单频信号空间功率合成. 物理学报, 2015, 64(20): 204101. doi: 10.7498/aps.64.204101
[14]	陈晓, 汪陈龙. 基于赛利斯模型和分数阶微分的兰姆波信号消噪. 物理学报, 2014, 63(18): 184301. doi: 10.7498/aps.63.184301
[15]	丁红星, 沈中华, 李加, 祝雪丰, 倪晓武. 复合兰姆波声子晶体中超宽部分禁带. 物理学报, 2012, 61(19): 196301. doi: 10.7498/aps.61.196301
[16]	张海燕, 曹亚萍, 于建波, 陈先华. 采用单个压电传感器的单模式兰姆波激发频率的选择. 物理学报, 2011, 60(11): 114301. doi: 10.7498/aps.60.114301
[17]	张海燕, 孙修立, 曹亚萍, 陈先华, 于建波. 基于时间反转理论的聚焦Lamb波结构损伤成像. 物理学报, 2010, 59(10): 7111-7119. doi: 10.7498/aps.59.7111
[18]	吕晓桂, 任春生, 马腾才, 朱海龙, 钱沐扬, 王德真. 石英管对空气中锥-板结构纳秒脉冲放电的影响. 物理学报, 2010, 59(11): 7917-7921. doi: 10.7498/aps.59.7917
[19]	魏巍, 郝跃, 冯倩, 张进城, 张金凤. AlGaN/GaN场板结构高电子迁移率晶体管的场板尺寸优化分析. 物理学报, 2008, 57(4): 2456-2461. doi: 10.7498/aps.57.2456
[20]	魏巍, 林若兵, 冯倩, 郝跃. 场板结构AlGaN/GaN HEMT的电流崩塌机理. 物理学报, 2008, 57(1): 467-471. doi: 10.7498/aps.57.467

计量

文章访问数: 7949
PDF下载量: 55
被引次数: 0

姓名
邮箱
手机号码
标题
留言内容
验证码

搜索

留言板