Open AccessAnalysis of blockage reasons of air preheater based on big data
Author(s) -
Z. J. Gai,
G. Zhang
Publication year - 2019
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/354/1/012035
Subject(s) - air preheater , boiler (water heating) , flue gas , power station , engineering , thermal power station , flue , cogeneration , process engineering , waste management , electricity generation , power (physics) , electrical engineering , physics , quantum mechanics
With the rapid development of Internet and computer technology, the era of big data has arrived. With the increasingly high degree of automation in the power industry, data mining technology and cloud computing technology are continuously developing in the power industry to deal with massive operational data. Supervisory Information System (SIS) and Distributed Control System (DCS) have been widely used in power plants, which enables massive operation data of power plants to be saved. As data mining technology rises rapidly in the power industry, many scholars begin to use data mining technology to study and solve problems encountered in power plants. Air preheater is a kind of heat exchange equipment which USES the waste heat of flue gas to heat the air needed for boiler combustion. The air preheater can recover the heat of flue gas, reduce the temperature of smoke exhaust and improve the efficiency of boiler. In recent years, the phenomenon of air-preheater clogging is increasing. Based on big data theory, this paper investigated 26 thermal power generating units - a total of 52 air preheaters with a capacity of 300∼600MW, and applied the neural network Modeling method to the air preheater clogging reasons identification system. So we can find out the clogging reasons of air preheaters timely and accurately, slow down and avoid the clogging of air preheater.