Research on Risk Assessment of Multitarget Wireless Sensing Detection Auxiliary Engineering in Mine Geological Environment

Abstract

In this paper, we evaluate the risk of auxiliary engineering of mine geological environment utilizing multiobjective wireless sensing detection. After vectorization of each evaluation factor, we evaluate the geological environment of a high-top mountain mine by fuzzy comprehensive evaluation method and get the evaluation results of our geological environment. Firstly, an in-depth analysis is carried out for the tracking gate that most association methods pay little attention to. In terms of optimization of traditional tracking gate, an attempt is made to propose a genetic algorithm fusion coding for tracking gate optimization, and then, the principal characteristics of traditional data association algorithm are focused on, and a particle swarm annealing association algorithm is proposed. Finally, the image information fusion of multisensors is studied, and the image information fusion level, fusion technology, and fusion process are discussed in detail, and the optimized discrete wavelet and color space alignment method is proposed, and good results are achieved through experiments. Among them, the area of poor geological environment evaluation is 0.32 km2, accounting for 6.6% of the whole study area, the area of average geological environment evaluation is 0.63 km2, accounting for 12.7% of the whole study area, and the area of good geological environment evaluation is 3.98 km2, accounting for 80.7% of the whole study area. The evaluation results can fully reflect the degree of mining influence on the Gaodingshan mining area and provide a theoretical basis for the study of mine environment restoration and management.