Transportation System Risk Analysis And Path Optimization Of Open-pit Mine

Regarded as the "artery" of all production links, transportation system, whose cost accounts for more than half of the total mining cost, is a critical and weak sector to an open-pit mine. With the mining turning into deep rock mass from shallow surface, transportation environment deteriorating constantly, transport distance prolonging continuously, transportation risks and costs increasing gradually. Thus, researching on the risk analysis and route optimization of open-pit mine transportation system has great impact on reducing accident risks, ensuring transport safety and decreasing transport costs.Based on the field investigation of a transport system in a domestic open-pit mine, the paper analyzed the system risk and optimized transport paths with methods like theory analysis, model construction and program optimization to reduce systemic risks and transport costs. Results are as follows:(1) After investigating routes distribution and property of the mine transport system, the route nodes information was extracted, road sections were divided and the transport system network model was developed. Turning the model into a edge weight matrix, using Matlab to search out the possible transport path from mining point to excavating point, and then, the foundation of the total research was laid.(2) Exploring the accident mechanism under the investigation of transport accidents of the open-pit mine, introducing the “5M” factors affecting open-pit mine transport risks, where unsafe human behaviors(Man), unsafe equipment conditions(Machine), unsafe environment elements(Media), security management defects(Management) and hazardous material factors(Material) included. Based on “5M” factors, a risks index system was built together with 17 secondary indicators.(3) In order to assess open-pit mine transportation risk degree, a new assessment method based on the model of PSO- BP neural net was proposed. Twelve transportation routes of an open-pit mine were selected as a training sample, and three transportation routes were chosen as test sample. The second- level indicators of risk index system were quantitatively processed. The BP neural net model was built, the weights values of which were optimized with PSO algorithm. Depended on the risk scores of fuzzy comprehensive evaluation, a comparison of training results and test results between PSO-BP model and BP model was made respectively, Results show that the assessment results of PSO-BP model is greatly consistent with the actual situation has higher assessment accuracy than that of BP model.(4) Study on the problem related to route optimization of open-pit transportation for a given origin and destination under the static condition. Taking transport distance, transport costs and transport risk as optimization goal, based on the open-pit actual production. Depended on Dijkstra algorithm and risk assessment, single objective path optimization was solved respectively. In order to solve the problem of interference between multiple optimization goals, the grey relation analysis method was applied to identify the most satisfied route.