The Research Of Data Mining Technology In Trend Control Of The Aluminum Electrolyte Pot Condition

In the traditional aluminum electrolysis systems, there were many problems, such as data un-sharable, low integration, difficulty to extract characteristic in mass data was exit in the present system which only can carry on simple data input, inquiry, statistics ,and more important guidable rules for the management and production of the enterprises in the mass data cannot be discovered. The decision-maker urgently needs the valuable information and the knowledge which should be extracted from the massive data and can be used to instruct the management for aluminum reduction cells to enhance the production benefit and so on. To solve the problems, this dissertation introduced data mining concepts into the aluminum electrolysis systems. Combined with network technology, a thorough study was made in theory and experimentation. The main contents and innovations of this dissertation were summarized as follows:1) In the data preprocessing of data warehouse, based on the influence of the old and new information on the missing data, arithmetic operators with weight were built to fill in the missing for the formation of the equal interval sequence and the completion of the data mining in the end.2) The association rules algorithm based on the Apriori, the FP-Growth and the improved Apriori, get the rules about the data in different Aluminum Reduction Cells' states. And accounting for the time attribute of mining data, the improved Apriori based on mining time series data was designed. These rules have more instructive value to the production.3) Referencing the concept of time window sliding, Established similarity search in time series model based on the sliding of Aluminum electrolyte pot condition's window, and achieved predict about the Aluminum Reduction cell's state.4) Established the classification model based on ID3 algorithm, and used the rules which this model mined, to achieve predict about the series Aluminum Reduction Cells' states.5) The gray association analysis was introduced into data mining, and the framework of the gray association rules was put forward. The gray association rules obtained from the result in mining the data produced from the control systems in such framework showed the degree to which the non-main attributes affected the main attribute in a certain area of time attribute, and provided the decision support for adjusting the control parameters of the aluminum electrolysis cells. And finally implemented the trend control of the Aluminum Electrolyte Pot Condition.On this basis, designed and developed an aluminum electrolysis data mining system, and applied to process the data in the aluminum electrolysis production field to instruct the production effectively and enhance the production efficiency and prolong the life of the cells and provide the basis for the scientific management.