Research On State Early Warning Of Induced Draft Fan In Coal Fired Power Station Based On Big Data Analysis

The induced draft fan is an important auxiliary equipment of coal-fired power stations.The function of the induced draft fan is to extract the flue gas generated by the combustion of thermal coal in the furnace and maintain the negative pressure of the boiler furnace within a certain range.High-power coal-fired power stations often arrange three induction Fans,if the induced draft fan fails,the load of the unit will also be reduced,which will affect the economy.After the environmental protection transformation,the induced draft fan is usually arranged between the electric dust removal system and the desulfurization system,the dust content in the flue gas is reduced,and the working environment of the induced draft fan has been improved to a certain extent,but the complex flue gas system stabilizes the working state of the induced draft fan Sex has a higher requirement.Therefore,the early warning of the state of the induced draft fan of the coal-fired power station has very important engineering value.Nowadays,big data analysis methods have been widely used,and the combination of big data analysis methods provides new technical ideas for improving the intelligence level of coal-fired power plant units.In this paper,the induced draft fan is the research object,combined with the on-site operation characteristics of coal-fired power stations and the big data analysis method to carry out the research and design of the induced draft fan state early warning system.Firstly,it introduces the neural network algorithm and data preprocessing method used in the establishment of the induced draft fan status warning system.Then,combined with the structure and working characteristics of the induced draft fan and the monitoring points of the coal-fired power station monitoring system,the induced draft fan characteristic information set is established and used The moving average denoising method and the normalized processing method preprocess the historical operating data of the characteristic information set to obtain the training set and the validation set of the condition warning model,and use the neural network algorithm to train and verify the condition warning model of the induced draft fan.Finally,the overall design of the function of the early warning system and the monitoring screen for the state of the induced draft fan of the coal-fired power station is carried out.The verification results show that the average relative error of the state warning model for the induced draft fan of coal-fired power stations based on big data analysis is low,which meets the engineering requirements and can improve the safety and economy of coal-fired power stations.