Open AccessPrediction study of temperature deviations on left and right sides of power plant boiler reheaters based on regression algorithm learning machine and expert experience
Author(s) -
Yujia Cui,
Ying Huang,
Xiaochun Ma,
Guo-hang Ma
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/892/1/012087
Subject(s) - boiler (water heating) , power station , regression , regression analysis , machine learning , artificial intelligence , engineering , algorithm , computer science , mathematics , statistics , waste management , electrical engineering
Based on regression algorithm learning machine and expert experience, the temperature deviation prediction of the left and right sides of the power plant boiler reheater is based on real-time or off-line data collected by the power plant boiler. The data is divided by expert experience and algorithm processing data. Based on the machine learning regression algorithm, a regression algorithm learning machine is established. Through this learning machine and expert experience, the temperature deviation of the left and right sides of the power plant boiler reheater is predicted. The results show that the model can accurately predict the temperature deviation of, the left and right sides of the power plant boiler reheater, thus providing reference guidance for the operation of the power plant boiler.