Title :
The application of BP neural network in Coal analysis
Author :
Yao, Wan-ye ; Su, Ling ; Yin, Shi
Author_Institution :
Dept. of Autom., North China Electr. Power Univ., Baoding, China
Abstract :
Coal analysis is of great significance to Coal power plant boiler combustion system in the diagnosis and optimization, and Calorific value of coal is an important indicator of coal quality analysis. So the research of the relation among Coal analysis data, elemental analysis data and the calorific is of great significance. Based on powerful approximating ability of neural network, the paper uses the daily common BP neural network model. The result shows that the relationship model of this method has a high precision, which makes ANN methods in coal heat power audit, Coal Quality and off-line analysis great practical significance. In addition, the paper established the relational model of coal-fired industrial analysis of data, low heat and elemental analysis data. It offers a good guide to the operation of coal-fired utility boilers.
Keywords :
backpropagation; boilers; coal; neural nets; power plants; ANN methods; BP neural network; calorific value; coal power plant boiler combustion system; coal quality analysis; coal-fired industrial analysis; coal-fired utility boilers; elemental analysis data; Analytical models; Artificial neural networks; Biological neural networks; Coal; Data models; Solid modeling; Training; Coal analysis; Neural network; On-line analysis; The calorific;
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2011 International Conference on
Conference_Location :
Guilin
Print_ISBN :
978-1-4577-0305-8
DOI :
10.1109/ICMLC.2011.6016755
