Development of a Method for Automatic Extraction of Know -How from Historical Information on Operation

点击翻译按钮获取中文摘要

We have developed a method for automatic extraction of operational know -how from historical information concerning plant operations. In this method, an operational know-how is extracted as an if-then rule by using C4.5, which is a one of tools for data mining. Then, special preprocessing should be necessary to deal with such a time series data as historical information concerning plant operations because events or records treated by C4.5 are naturally independent each other and the 'order of records is meaningless. In this study, we pay attention that operators watch not only present values of variables but also trends of variables and make a decision about their operations by judging whether trends are qualitatively increased or decreased. So, we have proposed to use qualitative values of differences of variables between sampling periods. As a result, it has been definitely that operational know-how can be extracted from historical information concerning plant operations if adequate selection and preprocessing of variables may be performed. However, C4.5 sometimes extracted wrong rules that were explained by inverse relations between cause and effect. In future work, we will combine C4.5 with a concept that can explain cause and effect relationship such as correlation coefficients.