A novel structural damage detection strategy based on VMD-FastICA and ESSAWOA

This paper proposes a novel two-stage structural damage detection strategy based on variational mode decomposition (VMD), fast independent component analysis (FastICA) and enhanced whale optimization algorithm integrated with Salp swarm algorithm (ESSAWOA). In the first stage, VMD and FastICA are utilized to decompose and process the initial response signals of the structure to detect the damage time preliminary. In the second stage, ESSAWOA algorithm is employed to identify the structural parameters (e.g., stiffness, mass or damping ratio) at different periods of time to determine the location and extent of the damage. To investigate the performance of the strategy, the simulation tests in six damage scenarios are carried out on a three-story numerical model. Then, the superiority of the parameter identification method based on ESSAWOA is verified on a seven-story simulation model. Finally, experimental verification on a laboratory seven-story steel frame is conducted to further validate the accuracy of the proposed strategy. The results in both numerical simulations and experimental validation prove that the two-stage strategy can effectively detect the time, location and extent of the damage in the frame structure. Furthermore, it has good applicability and robustness.

Automated summary

This paper proposes a novel two-stage structural damage detection strategy using VMD, FastICA and ESSAWOA algorithm. The first stage applies VMD and FastICA to process the initial response signals of the structure and detect the damage time. In the second stage, ESSAWOA algorithm is used to identify the structural parameters and determine the location and extent of the damage. Numerical simulation and experimental verification show that the proposed strategy can effectively detect the damage information of the structure.