Institute of Materials and Structures, Riga Technical University, LV-1048 Riga, Latvia.
Sensors (Basel). 2023 Jul 3;23(13):6121. doi: 10.3390/s23136121.
Health monitoring of structures operating in ambient environments is performed through operational modal analysis, where the identified modal parameters, such as resonant frequencies, damping ratios and operation deflection shapes, characterize the state of structural integrity. The current study shows that, first, time-frequency methods, such as continuous wavelet transform, can be used to identify these parameters and may even provide a large amount of such data, increasing the reliability of structural health monitoring systems. Second, the identified resonant frequencies and damping ratios are used as features in a damage-detection scheme, utilizing the kernel density estimate (KDE) of an underlying probability distribution of features. The Euclidean distance between the centroids of the KDEs, at reference and in various other cases of structural integrity, is used as an indicator of deviation from reference. Validation of the algorithm was carried out in a vast experimental campaign on glass fibre-reinforced polymer samples with a cylindrical shell structure subjected to varying degrees of damage. The proposed damage indicator, when compared with the well-known Mahalanobis distance metric, yielded comparable damage detection accuracy, while at the same time being not only simpler to calculate but also able to capture the severity of damage.
结构在环境中运行的健康监测是通过运行模态分析来实现的，其中识别出的模态参数，如共振频率、阻尼比和工作挠曲形状，表征了结构完整性的状态。本研究表明，首先，可以使用时频方法，如连续小波变换，来识别这些参数，甚至可能提供大量此类数据，从而提高结构健康监测系统的可靠性。其次，所识别的共振频率和阻尼比被用作损伤检测方案中的特征，利用特征的基础概率分布的核密度估计 (KDE)。在参考和各种其他结构完整性情况下的 KDE 质心之间的欧几里得距离被用作与参考的偏差的指标。该算法在对具有圆柱壳结构的玻璃纤维增强聚合物样本进行的广泛实验中得到了验证，这些样本受到不同程度的损伤。与著名的马氏距离度量标准相比，所提出的损伤指标具有相当的损伤检测准确性，同时不仅计算更简单，而且能够捕捉损伤的严重程度。
