Fault Diagnosis Of Fan And Operation Optimization In Power Plant Based On Rough Set Theory

With automation implementation of plant, troubleshooting and optimization target which can improve the economics of the plant are issues that plant power faced. In today ’s large-scale mechanical background, how to determine the type of fault quickly and accurately is the focus of attention, and with the development of market economy, the economy of power plant operation has become a primary target. As a new discipline in the industry, data mining technology has a good performance. The efficient data processing technique can extract useful information for people to use from various statistics of the plant. For guiding plant operation, data mining techniques is enormous.New as a data processing technique, only by observation and classification capabilities will rough set theory be able to identify potential relationships in the data with no prior knowledge. Analysis of principal component and attribute reduction based on rough set data pre-processing can greatly reduce the tedious work, which is very beneficial for improving the efficiency of mining.Applying rough set theory in this paper, I studied fault diagnosis of the fan and optimal operation target. Some of these algorithms have been improved to provide reference for the operation of the plant staff.