boiler efficiency prediction based on type of coal using artificial neural network

Boiler name: boiler efficiency prediction based on type of coal using artificial neural network
Boiler description: High efficiency, low back pressure, ultra-low NOx emissions
Location:: WUXI China

Molten salt heaters use molten potassium nitrate and sodium nitrite as heating media. Molten salt heater will heat the powder salt over the melting point until the viscosity of the molten salt allows circulating pump works, after the whole system is under circulating condition, then feed then into the thermal fluid heater for further circulating rising temperature to make it to be recycling used. Normal media working temperature is 400-550℃, top working temperature could reach 600℃.

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Review on Combustion Optimization Methods in Pulverise

boiler efficiency. Ji Zheng Chu et. al. [6] proposed their study on new constrained procedure using artificial neural network as models for target processes. Information analysis based on random search, fuzzy c-mean clustering and minimization of information energy is performed iteratively in proposed procedure.

Application of artificial neural network to exerg

‘Application of artificial neural network to exergy performance analysis of coal plant was used to model the efficiency prediction with ANN model, which has back-propagation learning LM

The Artificial Neural Network On-Line Monitoring Model o

At last,based on a 600MW boiler,the borler efficiency was predicted in this paper.we can easily know from the prediction result that the artificial neural network on-line monitoring model of boiler efficiency can predict the boiler efficiency accurately and constantly at a wide range condition.

Performance prediction of a RPF-fired boiler using artificial neural networ

Performance prediction of a RPF-fired boiler using artificial neural networks This study was aimed at assessing and optimizing the performance of a refuse plastic fuel-fired boiler using artificial neural networks. Sanjeev S. Tambe, B. D. Kulkarni, Artificial Intelligence-based Modeling of High Ash Coal Gasification in a Pilot Plant

Prediction Model of Coal-Fired Power Plant Boiler'

Y. Chen et al., "Prediction Model of Coal-Fired Power Plant Boiler's Nitrogen Oxide Emissions Based on Elman Neural Network", Advanced Materials Research, Vols. 807-809, pp. 227-231, 2013 Online since:

Application of Back Propagation Neural Network to Dru

neural network based drum level controller for sub-critical steam within the Boiler drum, thus reducing boiler efficiency and carrying moisture into the process or is to develop such a new controller using artificial neural networks. Particularly, the focus is on dealing with the

Development of artificial neural network model for a coa

Development of artificial neural network (ANN) models using real plant data for the prediction of fresh steam properties from a brown coal-fired boiler of a Slovenian power plant is reported.

Fault Diagnostics on Steam Boilers and Forecasting Syste

The slagging/fouling due to the accession of fireside deposits on the steam boilers decreases boiler efficiency and availability which leads to unexpected shut-downs. The research develops a generic slagging/fouling prediction tool based on hybrid fuzzy clustering and Artificial Neural Networks (FCANN). Díez, L.I. and Arauzo, I. (2005


But determination of boiler efficiency using conventional method is time linear and non-linear regression models are used along with kinetic models [7]. Artificial Neural Network (ANN) modeling is considered for prediction of the oxide deposition rate on the The research work carried out on multiple regression analysis for prediction of


artificial neural network, based on experimental data col An interesting and important feature of a Neural Network trained using back knowledge of the process it is being trained to is required [11, 12]. Also, they learn from experience by coal, oil, or gas is used within a boiler to convert water to high-pressure steam. The steam

Heat value identification of coal in utility boilers wit

The caloric value of coal is important to adjust the combustion performance in the boiler for operators. Based on the principles of coal combustion a neural network model is constructed to identify