Based On Principal Component Analysis Of The Furnace Pressure Feature Extraction And Combustion Model Judge

With DCS(Distribution Control System) and EIS(Enterprise information System) in thermal boiler process on a wide range of applications,lots of spot monitoring data was gathered by the monitoring system.To discover the tiny fault information of system in advance for fault detection and diagnosis has been one of the urgent problems to be solved.First,A new detection method based on dynamic multi-principal comment models is being proposed for this purpose. Then,the PCA method is mainly used to research on fault detection while PCA contribution plans to fault isolationand identification.The two methods interact and make up a complete fault diagnosis system.The main work of the paper includes following aspects.Take the actual movement data of the power station boiler as foundation in the research process,Take the furnace pressure as an object of study,to thesis the introductive contents method made use of a calculator to write procedure to carry on a great deal of contrast analysis experiment,and the result show PCA model can more accurate detect the boiler process fault.