Design Of Intelligent Monitoring System For Coal Chemical Gasifier Based On Data Analysis

Coal chemical industry occupies an important position in China's industry,and it is also the focus of national energy conservation and emission reduction.With the rapid development of science and technology and social economy,Production costs of coal chemical companies continue to rise,especially the increase in the price of raw coal,Coal chemical companies are constantly looking for ways to improve production economic benefits.Gasifier is the most important equipment for coal chemical production,Increasing the production efficiency of the gasifier can effectively solve the problem of coal chemical cost,Reduce the cost price of raw coal for gasifier,while ensuring that the gasifier is stable and efficient,can achieve the goals of energy saving,emission reduction and compression of gasifier.This paper establishes a data-driven monitoring system for the gasifier and performs cost analysis on the raw coal that is fed into the furnace.It is planned to increase the production efficiency of the gasifier and reduce the cost of raw coal.The monitoring of the gasifier is affected by its special high-temperature and high-pressure closed production environment.It is extremely difficult to monitor the gasifier through mechanism modeling.With the development of testing technology and computer technology,the production process data of the gasifier can be comprehensively tested and saved.These large amounts of gasifier industrial production process data imply a large amount of information and rules of gasifier operating conditions.Data-based gasifier monitoring,mainly from the gasifier raw coal into the furnace to the gasifier raw coal reaction process data and results of data monitoring.Study on Coal Preparation Based on Industrial Process Data of Raw Coal for Gasifier,The parameters of raw coal in gasifier are analyzed and simplified by the classical association rule algorithm,and the quality of raw coal is classified by the average algorithm in data mining,After classification,the range of excellent coal quality is obtained as the constraint condition in the coal blending optimization method,and then the process of coal blending is constrained to achieve the purpose of optimal coal blending.At the same time,through the gasifier data,the neuralnetwork is used as the modeling tool to establish the gas production prediction model,and the data simulation of coal combustion into the furnace achieves the purpose of predicting the gas production of raw coal.The coal blending model can optimize the ratio of raw coal in gasifier,thus saving the cost of raw material.Through the prediction model of gasifier,the production monitoring of raw coal in gasifier is achieved.The burner is the most important equipment of the gasifier.The use status and service life of the burner have a huge impact on the operation of the gasifier.Monitoring of gasifiers must monitor burners.This article uses the historical data of the burner to predict the life of the burner.Through analysis of the working environment and working principle of the burner,Find out the main parameters that affect the life and operation of the burner,The correlation analysis of these main parameter data is carried out,Find out that The linear relationship between parameters and burner life is obtained.Then the life prediction model of burner was established by using linear regression method through the history data of burner.Therefore,it provides assistance for gasifier operators to control the operating environment of the burner,prevents safety accidents caused by burner damage,and reduces the number of shutdowns of the gasifier,thereby achieving the purpose of improving the efficiency of the gasifier.Finally,the visual interface design of the monitoring system is performed through the gui of matlab.Visual interface includes coal blending monitoring system burner life monitoring system and gasifier variable monitoring system.And can query the running process data and historical data of the gasifier through the visual interface.Share the monitoring system on the server,Technicians can log in to the server through a local computer,And Access monitoring systems anywhere within the enterprise.