DocumentCode :
691024
Title :
The Analysis and Application of the Monitor Model of Gasifier Temperature Based on the PSO Neural Network
Author :
Qun Jia ; Yongxin Li
Author_Institution :
Sch. of Mech. Eng., Nanjing Univ. of Sci. & Technol.(NUST), Nanjing, China
fYear :
2013
fDate :
21-23 Sept. 2013
Firstpage :
335
Lastpage :
338
Abstract :
The coal gasification technology is widely used in industrial production, but in its production process, there exists a tough problem that the gasified temperature is not easy to detect and monitor. This paper proposes the approach of pso neural network, the neural network optimized by the particle swarm optimization(pso), and it adopts soft-sensing technique for real time detection and monitoring. Therefore, the goal of improving the efficiency of production and providing the control decision can be realized.
Keywords :
coal gasification; neural nets; particle swarm optimisation; production engineering computing; PSO neural network; coal gasification technology; control decision; gasifier temperature; industrial production; monitor model; particle swarm optimization; soft-sensing technique; Mathematical model; Monitoring; Neural networks; Particle swarm optimization; Production; Temperature measurement; Temperature sensors; gasifier temperature; neural network; particle swarm optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Instrumentation, Measurement, Computer, Communication and Control (IMCCC), 2013 Third International Conference on
Conference_Location :
Shenyang
Type :
conf
DOI :
10.1109/IMCCC.2013.77
Filename :
6840466
Link To Document :
بازگشت