In this article, multivariate empirical mode decomposition is proposed for damage localization in structures using limited measurements. Multivariate empirical mode decomposition is first used to decompose the acceleration responses into their mono-component modal responses. The major contributing modal responses are then used to evaluate the modal energy for the respective modes. A damage localization feature is proposed by calculating the percentage difference in the modal energies of damaged and undamaged structures, followed by the determination of the threshold value of the feature. The feature of the specific sensor location exceeding the threshold value is finally used to identify the location of structural damage. The proposed method is validated using a suite of numerical and full-scale studies. The validation is further explored using various limited measurement cases for evaluating the feasibility of using a fewer number of sensors to enable cost-effective structural health monitoring. The results show the capability of the proposed method in identifying as minimal as 2% change in global modal parameters of structures, outperforming the existing time–frequency methods to delineate such minor global damage.

在本文中，针对使用有限测量的结构损伤定位提出了多元经验模态分解。多元经验模态分解首先用于将加速度响应分解为其单分量模态响应。然后使用主要贡献的模态响应来评估各个模态的模态能量。通过计算受损和未受损结构的模态能量百分比差异，然后确定特征的阈值，提出了一种损伤定位特征。最后利用特定传感器位置超过阈值的特征来识别结构损伤的位置。所提出的方法使用一套数值和全面研究进行了验证。使用各种有限的测量案例进一步探索验证，以评估使用较少数量的传感器实现具有成本效益的结构健康监测的可行性。结果表明，所提出的方法能够识别结构的全局模态参数变化最小 2%，优于现有的时频方法来描绘这种轻微的全局损伤。