| Abstract:Drilling, loading and transportation are the cornerstone of the underground metal mining, and tend to be a direct influencing factor on the economic efficience of the mine. There is no denying that the device configuration in the three main components is especially important, the optimal mechanical configuration can not only ensure mining production capacity be completed timely and bring good economic benefits to the mine, but also have an important theoretical sense for underground metal mine drilling-loading-transportation equipment optimizing combination and further meaningful practical significance.Based on the mining design instructions of the Yunxi Laochang29-4#orebody, this article make a thorough study of the application of genetic algorithms to solve drilling-loading-transportation equipment system optimization issues. The main contents and conclusions include the following aspects:In the first place, according to the actual production characteristics of the underground metal mine, study on the optimization mechanism of mining equipment production system, and then value several usual optimum objective functions of the equipment system in mine.Secondly, according to the features of the underground metal mining devices data, utilizing Microsoft Access to built a underground metal mine device information system database, so as to manage, query and call diverse equipment data.More over, research on the theory and realization mechanism of genetic algorithm have been done, and establish a multi-objective optimizational model for the underground metal mine drilling-loading-transportation system. Set the minimum of equipment total acquisition cost as the optimization goals, and mine designed production capability and device affluence coefficient as constraints, to achieve the optimization of drilling-loading-transportation system in underground metal mine by Evolver. Last but not least, based on the optimal results of Yunxi Laochang29-4#orebody devices arrangement, conduct sensitivity analysis on mine production scale factors, considering corresponding mining class production capacity under different mining production scales, and a different drilling-loading-transportation equipment arrangement and the minimum total acquisition cost value curve is fitted with SPSS, additionally making error analysis for fitting results and the actual cost.In order to achieve the management of devices, this article build Yunxi Laochang29-4#orebody equipment information system database after collection and arrangement. Then calling the device information data from the database and matching equipment in the mining production processes, to find the best equipment configuration and to reach the optimization of production capacity and economic benefits in this mine. Finally fitting drilling-loading-transportation equipment configuration and minimum total acquisition cost value under different mining production scales, so as to provide reference for other mine enterprises which having comprehensive evalue and significance. The text is accompanied by49tables,33diagrams and72references. |
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