Application of Data Mining for Optimization Settings of Controlled Variable in Shaft Furnace Roasting

The mechanism of Hematite furnace roasting process is complex and operating conditions change frequently which makes it difficult to get the set value of controlled variables in the furnace roasting process and makes it tough to control the controlled variable within the target range. In this paper, data mining technology is put forward to solve this issue. First, clustering method is used to deal with the sample data, and then the method of association rules in data mining is applied to obtain association rules which meet the conditions. In the process of production, the correct values can be acquired through the association rule table which provides new idea for the optimization settings of shaft furnace roasting controlled variable.