Optimization of Sensor Network for Velocity-Free Acoustic Emission Source Localization in Construction Materials

Acoustic emission (AE) source localization provides important spatial information for damage characterization and fracture evolution analysis in construction materials, while its accuracy and applicability are strongly dependent on sensor network design. This study proposes an optimization framework for selecting an effective six-sensor network for velocity-free AE source localization in construction materials. The source coordinates are determined by solving a nonlinear inverse problem using the Levenberg–Marquardt algorithm, and candidate sensor subsets are evaluated by combining location error metrics with the number of effective localization results to quantify the effective monitoring range for damage characterization. The framework is investigated through numerical simulations and pencil-lead break tests on a 600 mm × 600 mm ceramic tile. Among different six-sensor configurations, the best-performing layouts place four sensors at the outer corners and two sensors at the horizontal or vertical inner corners. A benchmark comparison with the Fisher-information-based optimized sensor network and sensitivity analyses further show that the optimized sensor network maintains higher effective monitoring ranges under arrival-time noise, velocity uncertainty, and sensor coordinate perturbations. The proposed approach provides a useful reference for robust and cost-effective AE sensor network design in damage monitoring, fracture characterization, and nondestructive evaluation of construction materials.