Intelligent Optimization of Circulating Fluidized Bed Boiler

2014 ◽  
Vol 614 ◽  
pp. 580-583
Author(s):  
De Gong Chang ◽  
Yun Peng Ju
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Fluidized Bed ◽  
Bp Neural Network ◽  
Circulating Fluidized Bed ◽  
Optimization Method ◽  
Intelligent Optimization ◽  
Search Function ◽  
Boiler Efficiency ◽  
Boiler Operation

BP neural network can predict and establish a relationship between the parameters of boiler operation. Because this method has certain errors, so this paper presents a optimization method based on genetic algorithm. The method uses the genetic algorithm to optimize the key parameters of boiler operation and search out the maximum boiler efficiency taking advantages of genetic algorithm's global search function. According to optimization results obtained, the staff can adjust the parameters of the boiler and achieve the purpose of optimizing.

Discuss on Post Combustion Characteristics of the 116MW Circulating Fluidized Bed Hot Water Boiler

2013 ◽  
Vol 291-294 ◽  
pp. 1714-1718
Author(s):  
Guo Li Qi ◽  
Jian Guan ◽  
Hao Leng
Keyword(s):  
Fluidized Bed ◽  
Temperature Rise ◽  
Flue Gas ◽  
Circulating Fluidized Bed ◽  
Performance Testing ◽  
Hot Water ◽  
Outlet Temperature ◽  
Boiler Efficiency ◽  
Boiler Operation ◽  
Boiler Design

116MW circulating fluidized bed hot water boiler performance testing was carried out that found that burning high volatile lignite had post combustion phenomenon of separator yet. The phenomenon of post-combustion research results show that flue gas outlet temperature rise of the separation can be significantly reduced by adjusting the twelve wind ratio; Increasing coal-fired granularity which was able to reduce the separator post combustion phenomenon; Moderate post combustion of separation was able to improve boiler efficiency and reduce N2O. These results can provide guidance for improving boiler operation technology and improving the boiler design standard.

scholarly journals Application of Multidirectional Mutation Genetic Algorithm and Its Optimization Neural Network in Intelligent Optimization of English Teaching Courses

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Zi Yang
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Bp Neural Network ◽  
Optimization Problems ◽  
Local Optimization ◽  
Bp Algorithm ◽  
Control Group ◽  
Intelligent Optimization ◽  
English Teaching ◽  
Optimization System

Aiming at the problems existing in the traditional teaching mode, this paper intelligently optimizes English teaching courses by using multidirectional mutation genetic algorithm and its optimization neural network method. Firstly, this paper gives the framework of intelligent English course optimization system based on multidirectional mutation genetic BP neural network and analyses the local optimization problems existing in the traditional BP algorithm. A BP neural network optimization algorithm based on multidirectional mutation genetic algorithm (MMGA-BP) is presented. Then, the multidirectional mutation genetic BPNN algorithm is applied to the intelligent optimization of English teaching courses. The simulation shows that the multidirectional mutation genetic BP neural network algorithm can solve the local optimization problem of traditional BP neural network. Finally, a control group and an experimental group are set up to verify the role of multidirectional mutation genetic algorithm and its optimization neural network in the intelligent optimization system of English teaching courses through the combination of summative and formative teaching evaluations. The data show that MMGA-BP algorithm can significantly improve the scores of academic students in English courses and has better teaching performance. The effect of vocabulary teaching under the guidance of MMGA-BP optimization theory is very significant, which plays a certain role in the intelligent curriculum optimization of the experimental class.

Accurate prediction of the extrusion forming bonding reliability for heterogeneous welded sheets based on GA-BP neural network

2021 ◽  
Author(s):  
Lei Gao ◽  
Feng Li ◽  
Peng Da Huo ◽  
Chao Li ◽  
Jie Xu
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Process Parameters ◽  
Bp Neural Network ◽  
Bonding Strength ◽  
Prediction Accuracy ◽  
High Performance ◽  
Orthogonal Experiment ◽  
Optimization Method ◽  
Factors Affecting

Abstract As a widely recognized optimization method, BP neural network can provide scientific guidance for the formulation of reasonable process parameters. However, due to the randomness of its own weights and thresholds, the prediction accuracy remains to be further improved. The forming and manufacturing of heterogeneous welded sheet is a new extrusion connection method. There are many factors affecting the bonding quality, which brings trouble to the evaluation of bonding strength and quality. In this paper, orthogonal experiment, finite element simulation and process experiment were used to design and verify the key process parameters that affected the bonding strength of heterogeneous sheets. BP neural network and genetic algorithm neural network were used to predict the bonding strength. The results showed that the genetic algorithm neural network model has higher reliability, and the prediction accuracy was 99.5 %. Compared with the traditional BP neural network, the prediction accuracy was improved by 5.78 %, and the error was reduced to 0.5 %. It has good generalization ability, and provides a new way for intelligent reliability evaluation of high performance heterogeneous sheets extrusion manufacturing.

scholarly journals The Analysis of Influence of the Gangue in the Coal as Fired on the Coal Conveying System and the Boiler Operation of the Circulating Fluidized Bed Unit

2019 ◽  
Vol 118 ◽  
pp. 02011
Author(s):  
Su Pan ◽  
Yu Pengfeng ◽  
Linbo Liu ◽  
Han Jing ◽  
Xiao Shen
Keyword(s):  
Fluidized Bed ◽  
Circulating Fluidized Bed ◽  
Storage Conditions ◽  
Coal Gangue ◽  
Quality Data ◽  
Stable Operation ◽  
Coal Quality ◽  
Boiler Operation ◽  
Conveying System

The coal as fired, with unidentified characteristics of the coal gangue, was burned on a 300MW circulating fluidized bed unit. The equipment of the coal conveying system was damaged and the boiler operation was unstable. In response to the problems, the coal quality data and storage conditions of the coal were examined and the site was spot-checked to evaluate the coal quality characteristics. At the same time, the typical representative parameters of the coal handling system and boiler operation were selected. According to the analysis of coal quality and coal storage, the coal quality fluctuates greatly and the uniformity of particle size distribution is poor. There is actually the coal gangue with hard texture and hard to grind in the coal pile. The coal gangue will have adverse effects on the fine screening machine, fine crusher and other equipment. After burned this type of coal, the fluidized quality of the boiler bed is degraded to make an impact on the safe and stable operation of the boiler. It is recommended that the coal should be screened and then burned into the furnace to ensure safe and stable operation of the boiler.

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