论文信息 - Elman neural network in the soft sensor modelling for the unburned carbon in fly ash from utility boilers

Elman neural network in the soft sensor modelling for the unburned carbon in fly ash from utility boilers

Unburned carbon in fly ash is an important parameter affecting combustion efficiency of coal-fired boiler. In view of the deficiency of feed-forward neural network soft sensor modeling on unburned carbon in fly ash from the power plant, in this paper, we make use of recurrent Elman neural network to realize dynamic modeling of the boiler combustion process. A set of operating data from a 300MW power plant boiler is used here to train and validate the soft sensor model. Then this is compared with the results of BP network. The results after comparing show that Elman network can better achieve soft sensor modeling for unburned carbon in fly ash.

Lin Li | Xiu-Zhang Jin

[1] D. H. Rao,et al. Pseudo random number generator using Elman neural network , 2011, 2011 IEEE Recent Advances in Intelligent Computational Systems.

[2] P. Ciarlini,et al. Wavelets and Elman Neural Networks for monitoring environmental variables , 2008 .

[3] Wahyudi,et al. Development of Soft Sensor for Sensorless Automatic Gantry Crane Using RBF Neural Networks , 2006, 2006 IEEE Conference on Cybernetics and Intelligent Systems.

[4] Maohong Fan,et al. Precision and accuracy of photoacoustic measurements of unburned carbon in fly ash , 2001 .

[5] Andrew H. Sung,et al. Identifying Significant Features for Network Forensic Analysis Using Artificial Intelligence Techniques , 2003, Int. J. Digit. EVid..

[6] Sanjeev S. Tambe,et al. Soft-sensor development for fed-batch bioreactors using support vector regression , 2006 .

[7] T. Fukami,et al. The effect of using Elman-type feedback SOM for sleep stage diagnosis , 2010, IEEE/ICME International Conference on Complex Medical Engineering.

[8] C. Yoo,et al. Soft sensor and adaptive model-based dissolved oxygen control for biological wastewater treatment processes , 2004 .

[9] Shou-wei Li. Analysis of Contrasting Neural Network with Small-World Network , 2008, 2008 International Seminar on Future Information Technology and Management Engineering.