Analysis And Research Of Economic Operation For Copper Tube Annealing Furnace Units Based On Data Mining

With the increase of data, the application domain of data mining has been extended from traditional financial services, telecommunications, electric power to the pharmaceutical, non-ferrous metal processing industries and so on. Copper production and processing enterprises are the key energy-consuming units, which produce a large number of historical data stored in the unit running energy management system (ENMS) database in the process of production. Finding out the objective laws of economic operation from these data by data mining techniques, not only brings the dawn to small profit enterprise in competitive era, but it also has important significance in implement the energy conservation and emissions reduction.This paper combining the realistic demand of saving energy and reducing consumption in the progress of non-ferrous metals processing with the collected data of copper production and processing enterprise energy management systems (ENMS), taking data mining techniques applied to brass production and processing equipment-continuous annealing line for optimal operation, which has conquered many shortcomings in traditional optimization parameters. Firstly, this article describes the brass production process, structure and operating principle of continuous annealing unit. Secondly, it dentifies the main influencing to reduce the energy consumption of the unit for annealing optimization objectives. And then, according to the characteristics of the brass production and processing plant operation data generated, it proposes improvement association rules-incremental chain based on fuzzy association rule mining algorithm been applicated. Incremental chain based on fuzzy association rules mining algorithm is the core of operation for the entire unit of economic research, the algorithm,linguistic fuzzy association rule mining algorithm and FP-growth algorithm is applied separately to the actual operating data annealing line, we can see that the algorithm has great advantages in the interpretation of the results of mining and the mining efficiency of new data. Because of the introduction of vague understanding of the rule is enhanced, chain store improves memory utilization,and incremental mining improves the efficiency of the new rules to generate the data.Finally, using the algorithm finds rule parameters strongly associated with the unit energy consumption, and explores the parameters of the target, and then achieves the target of reducing the energy consumption of the unit through the combination of parameters.And simulating the energy consumption curves of the optimization before and after in the MATLAB, by contrast, we can see that the algorithm can effectively realize the economic operation of the unit rules mining.