| Top-blown smelting system is a kind of equipment which is widely used in copper,lead,zinc and other smelting methods.The system has the advantages of compact structure,simple operation,high melting efficiency,good environmental protection effect,strong adaptability and many others.In 2002,the first domestic top-blown smelting equipment for copper smelting was introduced by a smelting company in Yunnan Province.For its operation in the process of failure is difficult to predict and affecting the normal production efficiency and economic benefits and other issues,thus,in this paper,the nearly four years' production data of Yunnan Copper Co.,Ltd.was used to achieve the research on Top-blown Smelting System Based on Reliability Analysis,Prediction of Core Parts Life and Preventive Opportunity Maintenance Strategy with Minimum Maintenance Cost as Optimized Targets,then the efficiency of top-blown smelting system resource utilization and the overall smelting process level were improved.So that the total cost of maintenance of the top blown smelting system was reduced.The main research contents are as following:(1)To solve the problems that there are many faults in the system of top-submerged smelting and it is difficult to predict,the reliability analysis model-Monte Carlo Method FTA and FMECA was proposed.Using Monte Carlo method FTA to construct probability model and make random experiments on it to solve the math problem of the fault tree.This method can take advantage of both FMECA and FTA.This two method can complete each other,so that the main factors and weakness to affect the reliability of top-blown smelting system are discovered quickly and effectively.The result meets the production practice,the effectiveness of the method was comfirmed.And the result laid the foundation for the proposing of the core component fault life prediction and maintenance strategy of the top-blown smelting system.(2)The KPCA and PSO-WLSSVM method are used to predict the life of the core components of the top-blown smelting system.Based on the data-driven life prediction of the top-blown smelting system,the data of the life span of the gun are analyzed by kernel principal component analysis.PSO is used to analyze the principal component information extracted by KPCA,so as to further optimize the two main parameters of WLS-SVM model(penalty factor and kernel function parameter),and finally establish KPCA-PSO-WLSSVM combination model.The results show that the KPCA-PSO-WLSSVM model can be used to predict the life of the gun by comparing the results of PSO-WLSSVM and WLS-SVM model.The experimental results show that the KPCA-PSO-WLSSVM model The gun life expectancy has a high accuracy.(3)This study puts forward the maintenance strategy of preventive service maintenance for top-blown smelting system based on reliability.This method summarizes the actual production operation and fault data of Yunnan Copper Co.,Ltd.in the past four years,and uses the reliability margin ?R to prevent the opportunity to repair the time to solve.Through its further maintenance time interval,so as to develop the top-blown smelting system preventive opportunity maintenance strategy,use quadratic interpolation method to optimize AR so that the optimal opportunity to maintain the number of maintenance and the minimum maintenance costs are got.The optimal preventive opportunity maintenance strategy of the top blown smelting system was obtained.Finally,through the preventive opportunity maintenance strategy and the traditional preventive maintenance policy comparison found that the total maintenance costs reduced by 33.6%,so as to provide a more maintenance maintenance staff a more feasible maintenance strategy. |
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