Research On Application Of Open-pit Mine Transportation Path Optimization Based On Oblique Photography

Mineral resources are an important material basis for social production.Open-pit mining occupies an important position in the mining industry with its high production efficiency and full utilization of resources.In open-pit mining operations,transportation operations connect all aspects of open-pit mining.According to statistics,the transportation cost accounts for more than half of the cost of the main production links in the mining area.With the development of open-pit mining,the mining point is gradually deepened from the surface,and the transportation distance and transportation cost are gradually increasing.It is very necessary to optimize the truck transportation path scientifically and reasonably.Optimizing the transportation path is an important part of managing the transportation system of open-pit mines.It can not only improve the production efficiency of mines,but also increase the production income of mining areas.Focusing on the optimization of open-pit mine transportation path,the following work has been done :(1)In order to obtain the open-pit mine transportation network model,the UAV oblique photography technology is used to carry out aerial survey of the mine to obtain the geospatial data of the open-pit mine area.Then the U-Net semantic segmentation algorithm is introduced to extract the open-pit mine road and establish a real open-pit mine transportation network model,which provides basic data for the optimization of the transportation path of the open-pit mine truck.(2)Considering safety,economy and environmental protection,a multi-objective optimization model of open-pit mine transportation path is established.Taking the geographical environment of the mining area,truck load,truck speed and other factors as constraints,the transportation cost and carbon emission of trucks are calculated according to the truck transportation work,and a multi-objective open-pit mine transportation path optimization model with the shortest transportation distance,the smallest transportation cost and the least transportation carbon emission is established.(3)According to the characteristics of multi-objective optimization model of openpit mine transportation path,the cellular genetic algorithm is used to solve the model.On the basis of studying the genetic algorithm,the cellular automata model is added,and the invisible migration mechanism of cellular automata is used to ensure the diversity of the population.The transportation distance,transportation cost and transportation carbon emission of the road section are taken as the objective function to calculate the fitness function value.Combining the advantages of the two algorithms,the optimization ability and solution efficiency of the algorithm are improved.(4)Taking an open-pit mine in Hubei Province as the research background,firstly,the road network model is rasterized based on GIS software,and the weights of each section are calculated.Then,according to different loading points,the improved cellular genetic algorithm is used to solve the optimal transportation path.The results show that the multi-objective optimization model of open-pit mine transportation path established in this study can better meet the production needs of mining areas,and the cellular genetic algorithm can intelligently output the optimal transportation path,which provides a new solution for solving the optimization problem of open-pit mine truck transportation path.