Application Research Of Data Warehouse And Data Mining In The New Type Of Aluminum Electrolysis Control Systems

In the traditional aluminum electrolysis control systems, there were many problems, such as bad abilities of network processing, phenomena of information alone islands, shortcomings of data analysis. To solve the problems, this dissertation introduced data warehouse and data mining concepts into the aluminum electrolysis control 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 process of introducing the technology of data warehouse and data mining into the aluminum electrolysis control systems, the aluminum electrolysis data miner was designed and developed, which combined with experience and knowledge of aluminum electrolysis experts, and made full use of all kinds of data produced by the control systems.2. The concepts of the measure of attributes repeating and the measure of records repeating were brought forward to process the repeating records in the data preprocessing of data warehouse, and the algorithms correlated with identifying of repeating records and noise were designed. Based on the influence of the old and new information on the cavity data, arithmetic operators with weight were built to fill in the cavity for the formation of the equal interval sequence and the completion of the data mining in the end.3. 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. The algorithm for mining the gray association rules named GrayCTL wasdesigned.4. A model of cluster analysis based on connected components was proposed. The cell conditions of a single one or a series of cells was grouped into classes by this model. The outliers not belonging to any connected component showed the abnormity cell condition. Moving the time-window could complete a tendency analysis of the cell conditions. The clustering algorithm called CCCTL was designed, and it could discover clusters with arbitrary shape since the algorithm regarded the regions of points in the data space as connected component.5. A model of offset coefficient was built in the aluminum electrolysis control system, and it was used to mine the production data from the point of view of management. The best target range of attribute sets for examining could be obtained through analyzing the history data of aluminum electrolysis cells, namely attribute partition satisfied minimum support. Based on the attribute partition, the offset coefficient of single dimension attribute and the one of multidimensional attribute were mined, which gained the status excursion of current targets of the aluminum electrolysis cells, and the control parameters with obvious warp could be adjusted and modified in time to improve the efficiency of management.6. A new type of aluminum electrolysis control system was designed and developed based on the technology of network and data warehouse. The target such as remote accessing of history data and reports, remote controlling of dynamic information and remote accessing and modifying of all kinds of control parameters could be realized that a user lay in any node of the network based on his rights. The result of real application showed that thus new type of aluminum electrolysis control system strengthened the management of cells and enhanced the control level of aluminum electrolysis series.