In this work, using AVT data, a health monitoring method for concrete dams based on two different blind source separation (BSS)\nmethods, that is, second-order blind identification (SOBI) and independent component analysis (ICA), is proposed. A modal\nidentification procedure, which integrates the SOBI algorithm and modal contribution, is first adopted to extract structural modal\nfeatures using AVT data.The method to calculate the modal contribution index for SOBI-based modal identification methods is\nstudied, and the calculated modal contribution index is used to determine the system order.The selected modes are then used to\ncalculate modal features and are analysed using ICA to extract some independent components (ICs). The square prediction error\n(SPE) index and its control limits are then calculated to construct a control chart for the structural dynamic features. For new AVT\ndata of a damin an unknown health state, the newly calculated SPE is compared with the control limits to judge whether the damis\nnormal.With the simulated AVT data of the numericalmodel for a concrete gravity damand the measured AVT data of a practical\nengineering project, the performance of the dam health monitoring method proposed in this paper is validated.
Loading....