Copper Flash Smelting Process Based On Pattern Matching And The Evolution Of Operation Optimization Method

Copper flash smelting is the main pyrometallurgy technique to smelt copper. It is difficult to build model and optimize the process of copper flash smelting because the mechanism for copper flash smelting process is complicated and many technological parameters can not be measured which is also strong coupling. Copper flash smelting process has accumulated lots of production data, the condition and operating parameters of the smelting process is extracted from the data and described in the form of operational pattern, the superior operational patterns library based on the comprehensive working status evaluation model is huge, it is difficult to search the superior operational pattern appropriate to the current working status. To solve this problem, a pattern matching and evolution method is researched in this paper, and operation optimization for the copper flashing smelting process is achieved.Considering the low speed of pattern matching process and low matching accuracy because of the huge superior operational patterns library, a similarity measure criterion combined the Mahalanobis distance with Principal Component Analysis(PCA) is proposed to improve the accuracy of the pattern matching process; a hierarchical pattern matching strategy is proposed to accelerate the pattern matching process, clustering of the superior operational patterns library is the first step, compare the similarity of the working status and the center of sub-class to determine the sub-class that the working status belongs to, then search the optimal operational patterns in the sub-class based on the similarity measure criteria.The working status of the copper flashing smelting process changes frequently, it is possible that there is no operational pattern appropriate to the current working status, it is difficult to optimize. To solve this problem, a operational pattern evolution strategy is proposed, first the relation model between operational patterns and the comprehensive working status evaluation standards is built, then the optimal operational pattern and the optimal operational parameters appropriate to the current working status can be acquired using the Particle Swarm Optimization and the optimal operational guides the production, the superior operational pattern appropriate to the current working status is sent to the superior operational patterns library and renews the operational patterns library at the same time.Combined with the actual copper flash smelting process of a smelter, a operational pattern optimize system using the operation optimization method based on the operational pattern matching and evolution strategy for copper flash smelting process is exploited and is verified to be effective and feasible by operating data.