Development and Application of Sintering Process Data Mining System

In order to obtain optimal process parameters for sintering process, a data mining system that mainly including the process parameters module, the data mining module, the process diagnosis module, the human-machine and data interface was developed. By integrated fuzzy cluster analysis, time series and artificial neural networks technology, the system can deduce optimal information from complex production data, and realize four kinds of analysis that include sinter chemical composition analysis, sintering process state analysis, energy consumption analysis and state diagnosis. The system was developed with Visual C++ programming language. And its application shows that the first-grade rates of sinter chemical composition are increased by 1%, the fluctuation of main state of sintering process were reduced about 20%.