摘要
针对复合材料层合板的分层损伤,提出了一种基于互相关函数幅值向量的损伤统计检测方法。首先建立了复合材料层合板有限元模型并模拟其局部的分层损伤,求得随机激励下结构的加速度响应信号。然后,以结构的多个结点为参考点,计算结构损伤前后的CorV。利用互相关函数幅值向量置信度准则(Correlation function amplitude Vector Assurance Criterion,CVAC)来度量其变化程度,以此来识别损伤并根据结构CorV损伤前后的相对变化来确定产生分层损伤的区域,结合统计学原理最终确定损伤位置。通过对不同位置处的单损伤和多损伤检测仿真算例以及抗噪能力检验,验证了该文提出的损伤统计检测方法的有效性和稳定性。
A statistic strategy based on the correlation function amplitude vector （CorV） is proposed to detect the local delamination damage of a composite laminate. In the numerical simulation, the cantilevered composite laminate is excited by a steady random excitation. The finite element model is established to calculate the acceleration responses of the intact and damaged laminate, respectively. Then the CorVs of the intact and damaged laminate are calculated by taking several nodes as the reference points. The correlation function amplitude vector assurance criterion is adopted to determine the damage degree. The relative changes between the CorVs of the intact and damaged laminate are used together with a statistic evaluation formula to determine the damage location. The validity and Stability of the proposed statistic detection approach are demonstrated by given examples under single and multiple damage conditions. The anti-noise ability of the proposed approach is also checked.
出处
《工程力学》
EI
CSCD
北大核心
2009年第3期218-223,256,共7页
Engineering Mechanics
基金
高等学校博士学科点专项科研基金(20060699001)
教育部新世纪优秀人才支持计划项目(NCET-04-0965)
航空科学基金项目(04I53072)
关键词
损伤检测
复合材料结构
互相关函数幅值向量
随机激励
统计检测
damage detection
composite structure
correlation function amplitude vector （CorV）
randomexcitation
statistic detection
