Damage localization in plate-type structures via full-field vibration measurements has attracted much more attention. Traditionally, the damage-induced local shape singularities at a certain mode are harnessed for damage localization, but this is not reliable and robust for multi-damage localization. Therefore, a general strategy is that the damage features in different modes should be accurately extracted and integrated for a robust damage localization. However, the damage features are naturally contaminated by the measurement noise and the baseline-data on pristine state is commonly unavailable, which degrade the accuracy of damage feature extraction. Furthermore, the damage features in different modes normally contain conflicting damage location evidence, which leads to misleading damage localization results. To address these issues, an enhanced robust principal component analysis (RPCA) with contiguous outlier constraint is proposed to accurately extract the damage-caused local features without requiring the baseline-data of healthy state. Moreover, a novel data fusion approach based on cosine similarity measure is developed to effectively integrate the damage features of different modes for robust damage localization. In addition, a multiscale denoising approach is proposed to evaluate the noise-robust full-field vibration measurements for damage localization. Finally, numerical and experimental studies of cantilever plates with two damage zones are studied to verify the feasibility and effectiveness of the proposed damage localization method. It is found that the proposed damage localization method is robust in two aspects: damage feature extraction from noisy measurements and detecting all the possible damage zones.

通过全场振动测量在板式结构中的损伤定位引起了更多的关注。传统上，利用某种模式下的损伤引起的局部形状奇异点进行损伤定位，但这对于多损伤定位并不可靠和鲁棒。因此，一般的策略是准确提取和整合不同模式下的损伤特征，以实现稳健的损伤定位。然而，损伤特征自然受到测量噪声的污染，原始状态的基线数据通常不可用，这降低了损伤特征提取的准确性。此外，不同模式下的损伤特征通常包含相互冲突的损伤位置证据，这会导致误导性的损伤定位结果。为了解决这些问题，提出了一种具有连续异常值约束的增强型稳健主成分分析（RPCA），以准确提取损坏引起的局部特征，而无需健康状态的基线数据。此外，开发了一种基于余弦相似性度量的新型数据融合方法，以有效整合不同模式的损伤特征，实现稳健的损伤定位。此外，提出了一种多尺度去噪方法来评估噪声鲁棒的全场振动测量以进行损伤定位。最后，研究了具有两个损伤区的悬臂板的数值和实验研究，以验证所提出的损伤定位方法的可行性和有效性。发现所提出的损伤定位方法在两个方面是稳健的：