Soft sensor for ammonia concentration at the ammonia converter outlet based on an improved particle swarm optimization and BP neural network

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• 作者：Wei  ; Xu ; Lingbo  ; Zhang ; Xingsheng  ; Gu  ; ;   ; ^{xsgu@ecust.edu.cn} ;   ; ^{xuwei@mail.ecust.edu.cn}
• 关键词：Soft sensor ; Ammonia synthesis ; Ammonia concentration ; Particle swarm optimization
• 刊名：Chemical Engineering Research and Design
• 出版年：2011
• 出版时间：October 2011
• 年：2011
• 卷：89
• 期：10
• 页码：2102-2109
• 全文大小：299 K

文摘

Ammonia synthesis production is a critical chemical industry around the world. As the key process variable, the ammonia concentration at the ammonia converter outlet reflects the production status and provides good advices for the operators. However, it cannot be easily measured because of high expenditure and deficient reliability of online sensors in a real-world ammonia synthesis process. Due to this, a soft sensor, which is used to predict the outlet ammonia concentration, is developed using BP neural network (BPNN). An improved particle swarm optimization with expansion and constriction operation (PSOEC) is proposed to optimize the weights and thresholds of BPNN. The PSOEC and BPNN based soft-sensing model (PSOEC-NN) is applied to inferring the outlet ammonia concentration in a fertilizer plant. Results using other modeling methods (BPNN and PSO-NN) are presented for comparison purpose. The proposed PSOEC-NN based soft sensor shows high precision and good generalization capability. PSOEC-NN model would offer great help for further work like advanced control and operational optimization in the ammonia synthesis process.