The Calculation of the Tube Wall Temperature of Superheater in Boiler Based on the Resilient Back Propagation Artificial Neural Network

Author

Liu, Tong ; Wang, Yuelei ; Cai, Peng

Author_Institution

Dept. of Thermal & Power Eng., North China Electr. Power Univ., Baoding

Volume

2

fYear

2008

fDate

18-20 Oct. 2008

Firstpage

589

Lastpage

593

Abstract

Superheater is one of the most important parts in boiler and it is significant to monitor its tube wall temperature to avoid over-temperature and explosion. In this paper, the traditional calculation method of superheater tube wall temperature is firstly analysed, and then a new calculation method which is based on resilient back propagation (RPROP) network is proposed. From the result we can see that the error of the calculation which is based on RPROP is very small, so the problem that it is hard to monitor tube wall temperature of superheater is solved.

Keywords

backpropagation; boilers; computerised monitoring; heat transfer; power engineering computing; boiler; resilient back propagation artificial neural network; superheater; temperature monitoring; tube wall temperature; Artificial neural networks; Boilers; Furnaces; Heat transfer; Power engineering; Temperature measurement; Temperature sensors; Thermal conductivity; Thermal engineering; Thermal loading; RPROP neural network; superheater; tube wall temperature;

fLanguage

English

Publisher

ieee

Conference_Titel

Natural Computation, 2008. ICNC '08. Fourth International Conference on

Conference_Location

Jinan

Print_ISBN

978-0-7695-3304-9

Type

conf

DOI

10.1109/ICNC.2008.294

Filename

4667063