摘要
针对基于结构振型参数的损伤定位方法抗噪性差、对微小损伤不敏感以及对多损伤识别性能低等问题,基于振型低秩性与损伤分布稀疏性提出了一种复合材料层合板多损伤识别方法。首先,使用高斯-拉普拉斯算子(Laplacian of Gaussian,简称LoG)求解曲率模态;其次,利用鲁棒主成分分析提取曲率模态中损伤诱导产生的奇异值进行损伤定位;然后,提出了一个鲁棒损伤定位指标用于融合多个曲率模态的损伤信息;最后,使用带损伤复合材料层合板数值模拟与实验数据验证了方法的有效性。结果表明,该方法无需无损结构参考信息,便可准确地定位复合材料层合板中多个小面积损伤。
In order to solve the problems such as poor anti-noise,insensitivity to incipient damage and low perfor⁃mance of multiple damage localization by using modal shapes or their derivatives,a multi-damage identification method for composite laminates based on low-rank property of vibration modes and sparse damage distribution is proposed.Here,Laplacian of Gaussian(LoG)filter is adopted to evaluate the noise-robust curvature of modal shapes.Meanwhile,robust principal component analysis is utilized to examine the local damage-caused features of modal shape curvatures for damage localization.In addition,a damage localization index is developed to inte⁃grate the damage evidences of multiple modal shapes.Finally,the effectiveness of the proposed method is veri⁃fied by numerical simulations and experimental data of composite laminates with damage.The results show that this method can accurately pinpoint the multiple small area damage in composite laminates without reference in⁃formation on pristine state.
作者
颜津玮
曹善成
徐超
YAN Jinwei;CAO Shancheng;XU Chao(School of Aerospace,Northwestern Polytechnical University Xi′an,710072,China)
出处
《振动．测试与诊断》
EI
CSCD
北大核心
2022年第6期1220-1225,1250,共7页
Journal of Vibration,Measurement & Diagnosis
基金
中央高校基本科研业务费资助项目(3102019HTQD011)
陕西省自然科学基础研究计划资助项目(2020JQ-109)
国家自然科学基金资助项目(12102346)。
关键词
复合层合板
高斯-拉普拉斯算子
曲率模态
损伤定位
鲁棒主成分分析
composite laminates
Laplacian of Gaussian
mode shape curvatures
damage localization
robust principal component analysis
