Baseline-Free Impact Localization in Plate Structures Using a Combined SA-GA Optimization Framework

Accurate impact localization remains challenging for structural health monitoring (SHM) systems due to wave propagation complexities and high measurement uncertainties. This study presents a novel baseline-free framework that combines simulated annealing (SA) and genetic algorithm (GA) to characterize low-velocity impacts in plate structures. The proposed framework provides robust impact localization without relying on baseline signals, material properties, or detailed geometric parameters. Experimental impact tests were conducted using a coarse network of piezoelectric sensors arranged in multiple configurations to evaluate the performance of the proposed framework for impact characterization, full-field group velocity mapping, and computational efficiency. The framework predicted impact locations with an average relative error of less than 5% and R-values of about 0.98 under the optimal sensor configuration. The analysis of sensor placement indicated asymmetric sensor layouts yield 50% higher performance compared to symmetric layouts. The combined SA-GA framework successfully identified various impacts both inside and outside the regions confined by active sensor network with probabilities exceeding 90%. Additionally, the results demonstrated that the proposed framework consistently outperformed standalone SA and GA algorithms in both impact identification accuracy and the consistency of the velocity field.