多層構造等価回路モデルの粒子群最適化による地中空洞推定

抄録

Inspection of the occurrence of underground cavities is important for preventing sudden road collapse accidents. As a non-excavation inspection method, there is a ground penetrating radar technology that observes the backscattering response when electromagnetic waves are directed into the ground. It is expected that accurate estimation of the underground structure will be possible by devising the analysis method of the response data obtained by the radar. In this paper, we approximate the underground structure as a parallel multilayer structure with layers stacked in the direction perpendicular to the ground surface, and construct two mathematical models that give the backscattering response when waves are radiated into the ground. The underground structure can be estimated by optimizing the structural parameters of the model so that the backscattering response given by the model matches the measured response. After comparing the accuracy of the two models, we propose a structure estimation method using Particle Swarm Optimization (PSO). PSO is one of the metaheuristic optimization algorithms with excellent global exploration performance in a multidimensional data space. In this paper, the existence of a cavity is estimated by optimizing the medium constants of many layers, assuming an underground structure model consisting of 21 layers. The possibility of precise inspection of underground cavities is demonstrated.