A Novel Approach for Fault Diagnosis of Steam Turbine Unit Based on Fuzzy Rough Set Data Mining Theory
Ling Zheng · Proceedings of the CSEE · 2007
A novel approach for fault diagnosis of steam turbine unit based on fuzzy rough set(RS) data mining theory is brought forward,aimed at overcoming shortages of some current attaining methods.The historical fault data of steam turbine unit is processed with fuzzy and scatter method.The processed data is used to structure the fault diagnosis decision-making table which is treated as knowledge database.This paper introduced rough sets data mining method to take potential diagnosis rule from the fault diagnosis decision-making table of steam turbine unit.These rules can offer effective fault diagnosis service for steam turbine unit.The algorithm for classified rule learning and reducing is brought forward,and an experimental system for fault diagnosis of steam turbine unit based on fuzzy rough set data mining theory is implemented.Their diagnosising precision is above 88%.And experiments do prove that it is feasible to use the method to develop a system for fault diagnosis of steam turbine unit,which is valuable for further study in more depth.