贴附式涡流传感器损伤监测特性仿真与实验研究

推进技术 ›› 2015, Vol. 36 ›› Issue (11): 1705-1713.

贴附式涡流传感器损伤监测特性仿真与实验研究

焦胜博¹,程礼¹,何宇廷¹,李培源¹,李晓微²

空军工程大学航空航天工程学院，陕西西安 710038,空军工程大学航空航天工程学院，陕西西安 710038,空军工程大学航空航天工程学院，陕西西安 710038,空军工程大学航空航天工程学院，陕西西安 710038,西安电子科技大学软件学院，陕西西安 710038

发布日期:2021-08-15
作者简介:焦胜博(1988—)男，博士生，研究领域为军用飞机使用可靠性与安全性。
基金资助:
航空发动机刚度非线性转子动力学特性与参数识别研究(51175509)。

Characteristic Simulation and Experiment Study of Attached Eddy Current Sensor on Crack Monitoring

Aeronautic and Astronautic Engineering College，Airforce Engineering University，Xi’an 710038，China,Aeronautic and Astronautic Engineering College，Airforce Engineering University，Xi’an 710038，China,Aeronautic and Astronautic Engineering College，Airforce Engineering University，Xi’an 710038，China,Aeronautic and Astronautic Engineering College，Airforce Engineering University，Xi’an 710038，China and College of Software，Xidian University，Xi’an 710038，China

Published:2021-08-15

摘要/Abstract

摘要： 为满足飞机结构裂纹扩展定量化监测和工程化应用的需求，探索MWM(Meandering Winding Magnetometer)传感器进行结构健康监控的可行性，设计了一种贴附式涡流阵列传感器并为传感器的工程化应用开展了仿真优化和实验研究。基于裂纹扩展分段监测的思路，传感器的感应线圈和激励线圈采用阵列化设计。通过将材料的电导率提取为结构的等效损伤参数，构建了传感器损伤监测正向半解析模型，并对线圈厚度和基材层厚度进行了优化。为验证传感器的监测能力，开展了程序载荷谱下的2A12-T4铝合金阳极氧化试件的疲劳裂纹扩展监测实验。仿真优化结果表明，传感器监测灵敏度随提离距离的增加而减小，传感器最优工作频率范围为0.3～0.7MHz。裂纹扩展监测实验结果表明，贴附式涡流传感器具备对金属结构进行实时损伤监测的能力，感应线圈的阵列化布置方式实现了裂纹扩展的定量监测，精度达到毫米级，同断口分析结果相比，平均监测误差为3.85%。

关键词: 结构健康监测；基于状态维修；涡流传感器；半解析模型；监测灵敏度

Abstract: To monitor the crack extension quantitatively in real time and to explore the feasibility of MWM(Meandering Winding Magnetometer) for structure health monitoring，a kind of attached eddy current sensor was put forward and characteristic simulation was carried out as well as experimental study. According to the idea of segmented monitoring the crack，the excitation coils and induction coils of the sensor were arranged in an array. By exacting material’s conductivity as the damage feature，forward semi-analytical model was built and optimizations on thickness of coil were carried out as well as thickness of the substrate layer. In order to verify the sensor performance，crack extension experiment on 2A12-T4 aluminum alloy under the programmed load spectrum was conducted. The results show that the sensitivity decreases with the increase of liftoff，and the optimal working frequency ranges from 0.3MHz to 0.7MHz. The experiment indicates that the sensor is capable of monitoring the crack in real-time and the arrayed arrangement of induction coils allows to measure the crack quantitatively with the accuracy to millimeter. The general error is 3.85% compared with the result of fracture analysis.

Key words: Structure health monitor；Condition-based maintenance；Eddy current sensor；Semi-analytical model；Monitoring sensitivity

焦胜博,程礼,何宇廷,李培源,李晓微. 贴附式涡流传感器损伤监测特性仿真与实验研究[J]. 推进技术, 2015, 36(11): 1705-1713.

JIAO Sheng-bo¹,CHENG Li¹,HE Yu-ting¹,LI Pei-yuan¹,LI Xiao-wei². Characteristic Simulation and Experiment Study of Attached Eddy Current Sensor on Crack Monitoring[J]. Journal of Propulsion Technology, 2015, 36(11): 1705-1713.

参考文献

[1] 袁慎芳. 结构健康监控[M]. 北京:国防工业出版社,2007: 3-5.
[2] 康建设, 尹健, 王希星. CBM系统与设备状态监测[J]. 仪器与仪表学报, 2006, 27(6): 1748-1751.
[3] 刘昆, 张育林. 液体火箭发动机健康监控系统中的传感器技术[J]. 推进技术, 1997, 18(1): 61-64. (LIU Kun, ZHANG YU-lin. Sensor Technologies for Health Monitoring System of Liquid Rocket Engines[J]. Journal of Propulsion Technology, 1997, 18(1): 61-64.)
[4] Hong L G, Gao ZH X, Mrad N. Fiber Optic Sensors for Structure Health Monitoring of Air Platforms[J]. Sensors, 2011, 11(4): 3687-3705.
[5] Roach D. Real Time Crack Detection Using Mountable Comparative Vacuum Monitoring Sensors[J]. Smart Structures and Systems, 2009, 5(4): 317-328.
[6] Zdenek PREVOROVSKY. Nonlinear Ultrasonic Spectroscopy and Acoustic Emission in SHM of Aircrafts[C].Durban: 18th World Conference on Nondestructive Testing, 2012.
[7] Liu M B, Gao Q, Hu F. Flaw-Detected Coating and Its Application[C]. Nanjing: International Conference on Health Monitoring of Structure, 2007.
[8] Giurgiutiu V,LIN B, Santoni G, et al. Space Application of Piezoelectric Wafer Active Sensors for Structural Health Monitoring[J]. Journal of Intelligent Material Systems and Structures, 2011, 22(12): 1359-1370.
[9] Rick Russell, David Jablonski, Andy Washabaugh, et al. Development of Meandering Winding Magnetometer(MWM) Eddy Current Sensors for the Health Monitoring, Modeling and Damage Detection of High Temperature Composite Materials[C]. Palm Springs: 32nd High Temple Workshop, 2012.
[10] Speckmann H. Structure Health Monitoring[C]. Cologne: International Maintenance Review Board Policy Board Meeting, 2007.
[11] Ding T H, Chen X L, Huang Y P. Ultra-Thin Flexible Eddy Current Sensor Array for Gap Measurements[J]. Tsinghua Science and Technology, 2004, 9(6): 667-671.
[12] 刘波, 罗飞路, 候良洁. 涡流阵列检测修正C扫描成像技术研究[J]. 传感技术学报, 2011, 24(8): 1172-1177.
[13] 丁克勤, 赵娜. 电站锅炉不锈钢管氧化皮检测技术[J]. 无损检测, 2010, 32(8): 601-604.
[14] Goldfine N J. Uncalibrated Absolute Property Estimation and Measurement Optimization for Conducting and Magnetic Media Using imposed ω-k Magnetometry[D]. USA: Massachusetts Institute of Technology, 1990.
[15] 张晓娟, 谌广昌, 许俊华. HM109-1型密封剂在某直升机上的工程化应用与分析[J]. 直升机技术, 2010, 165(4): 52-55.
[16] 王劲, 唐屹, 曾晓丹. 挠性印刷电路基板用三层复合聚酰亚胺胶粘膜的制备及性能研究[J]. 绝缘材料, 2005, 38(1): 4-8.
[17] Udpa S, Upda L. Eddy Current Testing-Are We at the Limits[C]. Montreal: Proceedings of 16th World Conference on Nondestructive Testing, 2004.
[18] Nagaya Y, Takagi T, Uchimoto T, et al. Identification of Multiple Cracks from Eddy-Current Testing Signals with Noise Sources by Image Processing and Inverse Analysis[J]. IEEE Transactions on Magnetics, 2004, 40(2): l112-1115.
[19] Hoole S. Artificial Neural Networks in the Solution of Inverse Electromagnetic Field Problems[J]. IEEE Transactions on Magnetics, 1993, 29(2): 1931-1934.
[20] Li Y, Udpa L, Udpa S. Three-Dimensional Defect Reconstruction from Eddy-Current NDE Signals Using a Genetic Local Search Algorithm[J]. IEEE Transactions on Magnetics, 2004, 40(2): 410-417.
[21] Harrison D J. Transient Eddy Currents-Are They Here to Stay[J]. Insight, 2005, 47(3): 144-152.
[22] Lang Z Q, Agurto A, Tian G Y, et al. A System Identification Based Approach for Pulsed Eddy Current Non-Destructive Evaluation[J]. Measurement Science and Technology, 2007, 18(7): 2083-2091.
[23] Kaup P G, Samosa F, Vogelius M. Method for Imaging Corrosion Damage in Thin Plates from Electrostatic Data[J]. Inverse Problems, 1996, 12(3): 279-293.
[24] Ramuhalli P, Udpa L, Udpa S. Neural Network Algorithm for Electromagnetic NDE Signal Inversion[J].Electromagnetic Nondestructive Evaluation, Amsterdam, The Netherlands: IOS, 2001, 27(5): 121-128.
[25] Sabbagh H A , Treece J C, Murphy RK. Computer Modeling of Eddy Current Nondestructive Testing[J]. Materials Evaluation, 1993, 51(11): 1252-1257.
[26] Reboud C, Premel D, Lesselier D, et al. Recent Advances in Simulation of Eddy Current Testing of Tubes and Experimental Validations[C]. Portland: Review of Quantitative Nondestructive Evaluation, 2006.
[27] Song D Y, Takeda N, Kitano A. Correlation between Mechanical Damage Behavior and Electrical Resistance Change in CFRP Composites as a Health Monitoring Sensor[J]. Materials Science and Engineering A, 2007, 456(12): 286-291.
[28] 范孟豹. 多层导电结构电涡流检测的解析建模研究[D]. 杭州:浙江大学, 2009.(编辑:梅瑛)　　　　　　　　　　　　　*　收稿日期:2014-08-10；修订日期:2014-10-09。基金项目:航空发动机刚度非线性转子动力学特性与参数识别研究(51175509)。作者简介:焦胜博(1988—)男,博士生,研究领域为军用飞机使用可靠性与安全性。 E-mail: jsbkgd@163.com