摘要
Lamb波具有较强的抗干扰能力,被广泛应用于碳纤维增强树脂(Carbon Fiber Reinforced Polymer,CFRP)结构健康监测中。采用汉宁窗形式的窄带Lamb波激励完整CFRP板与含内置损伤的损伤CFRP板,通过比较PZT压电片采集到的健康信号与损伤信号之间的信号差异系数,根据改进的损伤概率重建算法(Reconstruction Algorithm for the Probabilistic Inspection of Damage,RAPID)实现CFRP结构的内部损伤成像。得到以下结论:建立CFRP板Lamb波有限元模型对内置损伤的大小和区域进行定位,并根据CFRP板Lamb波结构健康监测试验平台验证有限元模型的正确性;提出一种阈值化改进RAPID算法,对损伤板的内置损伤大小和轮廓进行准确预测,预测结果最大误差仅为6.56%;随着结构内置损伤孔厚度的增加,结构损伤信号与健康信号的差异越发明显,预测损伤参数与实际损伤参数的最小误差仅为5.20 mm。
The anti-interference ability of Lamb waves makes them widely used in the structural health monitoring of CFRP materials.This study uses narrowband Lamb waves modulated by a Hanning window to excite intact CFRP laminates and damaged CFRP laminates with built-in damage.By comparing the difference coefficients between the healthy and the damaged signals collected by PZT piezoelectric sheets,the internal damage images of the CFRP structure are reconstructed by using an improved Reconstruction Algorithm for the Probabilistic Inspection of Damage(RAPID).The following conclusions are drawn.A finite element model of CFRP Lamb waves is established to locate the size and area of internal damage,and its accuracy is validated through a CFRP Lamb wave structural health monitoring platform.A threshold-based modification of the RAPID algorithm is proposed to accurately predict the size and contour of the internal damage,with a maximum prediction error of only 6.56%.As the thickness of the internal damage hole in the structure increases,the difference between the damaged and the healthy signals becomes more pronounced,and the error between the predicted damage parameters and the actual damage parameters decreases.The minimum error between the predicted and actual damage parameters is as low as 5.20 mm.
作者
闫兰兰
文振华
孙振辉
赵竹君
陈庆远
YAN Lanlan;WEN Zhenhua;SUN Zhenhui;ZHAO Zhujun;CHEN Qingyuan(School of Aero-Engine,Zhengzhou University of Aeronautics,Zhengzhou 450046,China)
出处
《郑州航空工业管理学院学报》
2025年第4期25-32,共8页
Journal of Zhengzhou University of Aeronautics
基金
国家自然科学基金(51975539)
河南省高校科技创新团队支持计划(25IRTSTHN020)
航空科学基金(2018ZD55008)
河南省科技攻关项目(252102220085)
河南省通用航空技术重点实验室平台开放基金(ZHKF-240209)
河南省高等学校重点项目科研计划(25A590006)
郑州航空工业管理学院科研团队支持计划专项资助(23ZHTD01004)。
作者简介
闫兰兰,女,硕士研究生,研究方向为结构健康监测、无损检测;通讯作者:文振华,男,博士,教授,研究方向为电子信息材料与检测技术。
