ADACTA—Advanced component analysis technique for damage detection

In structural health monitoring (SHM), the integration of a model-free approach with blind source separation (BSS) offers a potent combination for damage detection. A model-free approach, devoid of reliance on predefined structural models, provides flexibility and adaptability, especially when dealing with complex structures or those with evolving characteristics. In addition, BSS is particularly suited for isolating individual sources from mixed signals, even in noisy environments. In this context, this research presents ADACTA (ADvAnced ComponenT Analysis), a method for SHM that combines the capabilities of principal component analysis (PCA) and independent component analysis (ICA). First, PCA is employed for data normalization and dimensionality reduction; then, ICA emphasizes damage-induced vibration signatures. Together, PCA and ICA offer a robust combination to extract reliable damage-sensitive features: PCA streamlines data, while ICA ensures that separated signals best represent underlying structural changes, as mathematically proved in the present work. Appropriate metrics (i.e., city block distance and Pearson correlation coefficient) are introduced to quantify the distance between signals acquired in different time intervals, serving as damage indicators. The technique can be applied for detecting early-stage damages, allowing the examination of the temporal evolution of the introduced damage indicators. The ADACTA method was tested on the Z24 bridge database, demonstrating its potential for improved early-stage damage detection in real-world structures.