基于FBG单传感器的复合材料板低速冲击定位研究
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摘要
由于复合材料结构先验知识获取的困难性及多传感器动态监测的冗余性,提出了一种基于归一化互相关的单传感器冲击定位方法,并搭建了单传感器复合材料板低速冲击定位系统。首先,利用归一化互相关方法提取基于冲击位置的信号特征,并有效去除传感器的温度交叉敏感和冲击能量影响因素;然后,计算样本信号和待定信号的归一化互相关值,并进行比较;最后,选择待定位信号角度范围内前三个最大相关值的样本点组成定位参考区域,以三角区域质心来评估冲击位置。在600 mm×600复合材料层合板上进行单传感器低速冲击定位验证实验,结果表明利用该定位方法可以准确进行冲击定位,其中最大误差为45.91 mm,平均误差为24.99 mm。通过单传感器定位性能实验结果显示:单传感器位置变化不会影响平均误差范围变化;单传感器定位平均误差和最大误差等大于双传感器,但均符合工程应用范围。结果证明,此方法能够在保证监测准确率的情况下尽可能减少大型复合材料结构传感网络中传感器的数目,同时大大减小布线和数据处理的复杂性,为大型结构健康监测提供了依据。
Aiming at the difficulties of getting priori knowledge of composite structure and the redundancy of multisensor dynamic monitoring,a single-sensor impact localization method based on normalized cross-correlation is proposed and a low velocity localization system of composite laminates with single-sensor is built. Firstly,the signal features of impact positions were extracted,the sensor temperature cross sensitivity and impact energy influence factors were removed effectively by using normalized cross-correlation method. Then,the normalized cross-correlation values of sample signals and undetermined signals were calculated and compared. Finally,the sample points of the first three correlation values within the range of the undetermined signal were selected to form the localization reference area and the impact position were estimated by the center of the triangle area. A single-sensor low velocity impact localization experiment was conducted on a 600 mm×600 mm composite laminate. The experimental results showed that the proposed method could localize impact position accurately,the maximum error was 45.91 mm,the average error was 24. 99 mm. The single-sensor localization experiment results showed that the position changes of single sensor would not affect the average error range,the average and maximum errors of single-sensor localization results were larger than dual-sensor,but met the engineering application requirements. The results show that this method can reduce the number of sensors in the sensing network of large composite structures as much as possible while ensuring the monitoring accuracy,and greatly reduce the complexity of wiring and data processing,and provide a basis for health monitoring of large composite structures.
Aiming at the difficulties of getting priori knowledge of composite structure and the redundancy of multisensor dynamic monitoring,a single-sensor impact localization method based on normalized cross-correlation is proposed and a low velocity localization system of composite laminates with single-sensor is built. Firstly,the signal features of impact positions were extracted,the sensor temperature cross sensitivity and impact energy influence factors were removed effectively by using normalized cross-correlation method. Then,the normalized cross-correlation values of sample signals and undetermined signals were calculated and compared. Finally,the sample points of the first three correlation values within the range of the undetermined signal were selected to form the localization reference area and the impact position were estimated by the center of the triangle area. A single-sensor low velocity impact localization experiment was conducted on a 600 mm×600 mm composite laminate. The experimental results showed that the proposed method could localize impact position accurately,the maximum error was 45.91 mm,the average error was 24. 99 mm. The single-sensor localization experiment results showed that the position changes of single sensor would not affect the average error range,the average and maximum errors of single-sensor localization results were larger than dual-sensor,but met the engineering application requirements. The results show that this method can reduce the number of sensors in the sensing network of large composite structures as much as possible while ensuring the monitoring accuracy,and greatly reduce the complexity of wiring and data processing,and provide a basis for health monitoring of large composite structures.
引文
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[14]Frieden J,Cugnoni J,Botsis J,et al.Low Energy Impact Damage Monitoring of Composites Using Dynamic Strain Signals from FBGSensors-PartⅡ:Damage identification[J].Composite Structures,2012,94(2):593-600.
[15]孙媛凯,李英娜,胡明耀,等.输电铁塔塔身光纤光栅结构监测与时序融合研究[J].传感技术学报,2016,29(3):451-455.
[16]路士增,林兰波,姜明顺,等.基于光纤光栅传感器的复合材料损伤识别系统[J].光学精密工程,2014,22(11):2894-2901.
[17]芦吉云,王帮峰,梁大开.基于小波包特征提取及支持向量回归机的光纤布拉格光栅冲击定位系统[J].光学精密工程,2012(4):712-718.
[18]Worden K,staszewski W J.Impact Location and Quantification on a Composite Panel Using Neural Networks and a Genetic Algorithm[J].Strain,2000,36(2):61-68.
[19]Kirikera G R,Balogun O,Krishnaswamy S.Adaptive Fiber Bragg Grating Sensor Network for Structural Health Monitoring:Applications to Impact Monitoring[J].Structural Health Monitoring,2010,9(3):5-16.
[20]Frieden J,Cugnoni J,Botsis J,et al.Low Energy Impact Damage Monitoring of Composites Using Dynamic Strain Signals from FBGSensors-PartⅠ:Impact Detection and Localization[J].Composite Structures,2012,94(2):438-445.
[2]周德强,吴佳龙,王俊,等.碳纤维增强复合材料冲击缺陷脉冲涡流无损检测仿真与试验研究[J].传感技术学报,2015,28(5):671-676.
[3]Diamanti K,Soutis C.Structural Health Monitoring Techniques for Aircraft Composite Structures[J].Progress in Aerospace Sciences,2010,46(8):342-352.
[4]Doyle D,Zagrai A,Arritt B,et al.Damage Detection in Bolted Space Structures[J].Journal of Intelligent Material Systems and Structures,2010,21(3):251-264.
[5]Djinovic Z,Scheerer M,Tomic M.Impact Damage Detection of Composite Materials by Fiber Bragg Gratings[J].Proceedings of SPIE-Smart Sensors,Actuators,And Mems V,2011,8066(3):487-504.
[6]Meo M,Zumpano G,Piggott M,et al.Impact Identification on a Sandwich Plate from Wave Propagation Responses[J].Composite Structures,2005,71(3-4):302-306.
[7]Yuan S,Zhong Y,Qiu L,et al.Two-Dimensional Near-Field Multiple Signal Classification Algorithm-Based Impact Localization[J].Journal of Intelligent Material Systems and Structures,2014,26(4):400-413.
[8]Ruiz M,Mujica L E,Berjaga X,et al.Partial Least Square/Projection to Latent Structures(PLS)Regression to Estimate Impact Localization in Structures[J].Smart Materials and Structures,2013,22(2):369-374.
[9]Park C Y,Kim J H,Jun S M,et al.Localizations and Force Reconstruction of Low-Velocity Impact in a Composite Panel Using Optical Fiber Sensors[J].Advanced Composite Materials,2012,21(5-6):357-369.
[10]Jang B W,Lee Y G,Kim J H,et al.Real-Time Impact Identification Algorithm for Composite Structures Using Fiber Bragg Grating Sensors[J].Structural Control&Health Monitoring,2012,19(7):580-591.
[11]Jeong H,Cho S.Impact Source Location of Composites Using a Single Sensor and Time Reversal Technique[C]//AIP Conference Proceedings 1511,246(2013).Denver,USA:2012.
[12]Park B,Sohn H,Olson S E,et al.Impact Localization in Complex Structures Using Laser-Based Time Reversal[J].Structural Health Monitoring,2012,11(5):577-588.
[13]Ciampa F,Meo M.Impact Localization on a Composite Tail Rotor Blade Using an Inverse Filtering Approach[J].Journal of Intelligent Material Systems and Structures,2014,25(15):1950-1958.
[14]Frieden J,Cugnoni J,Botsis J,et al.Low Energy Impact Damage Monitoring of Composites Using Dynamic Strain Signals from FBGSensors-PartⅡ:Damage identification[J].Composite Structures,2012,94(2):593-600.
[15]孙媛凯,李英娜,胡明耀,等.输电铁塔塔身光纤光栅结构监测与时序融合研究[J].传感技术学报,2016,29(3):451-455.
[16]路士增,林兰波,姜明顺,等.基于光纤光栅传感器的复合材料损伤识别系统[J].光学精密工程,2014,22(11):2894-2901.
[17]芦吉云,王帮峰,梁大开.基于小波包特征提取及支持向量回归机的光纤布拉格光栅冲击定位系统[J].光学精密工程,2012(4):712-718.
[18]Worden K,staszewski W J.Impact Location and Quantification on a Composite Panel Using Neural Networks and a Genetic Algorithm[J].Strain,2000,36(2):61-68.
[19]Kirikera G R,Balogun O,Krishnaswamy S.Adaptive Fiber Bragg Grating Sensor Network for Structural Health Monitoring:Applications to Impact Monitoring[J].Structural Health Monitoring,2010,9(3):5-16.
[20]Frieden J,Cugnoni J,Botsis J,et al.Low Energy Impact Damage Monitoring of Composites Using Dynamic Strain Signals from FBGSensors-PartⅠ:Impact Detection and Localization[J].Composite Structures,2012,94(2):438-445.