Soft Sensor for Ammonia Concentration at the Ammonia Converter Outlet Based on an Improved Group Search Optimization and BP Neural Network<sup>*</sup>

阎兴頔; 杨文; 马贺贺; 侍洪波

Your Location：

Home >

Browse articles >

Soft Sensor for Ammonia Concentration at the Ammonia Converter Outlet Based on an Improved Group Search Optimization and BP Neural Network^*

Updated：2026-01-06

- Soft Sensor for Ammonia Concentration at the Ammonia Converter Outlet Based on an Improved Group Search Optimization and BP Neural Network^*
- Chinese Journal of Chemical Engineering Vol. 20, Issue 6, Pages: 1184-1190(2012)
- Affiliations：
  
  Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education, East China University of Science and Technology,Shanghai,China,200237
- Author bio：
- Funds：
- DOI：
  CLC：
- Published：2012
- Accepted：
Scan QR Code
[J]. Chinese Journal of Chemical Engineering, 2012, 20(6): 1184-1190.
DOI：

[J]. Chinese Journal of Chemical Engineering, 2012, 20(6): 1184-1190. DOI：

摘要

Abstract

The ammonia synthesis reactor is the core unit in the whole ammonia synthesis production.The ammonia concentration at the ammonia converter outlet is a significant process variable

which reflects directly the production efficiency.However

it is hard to be measured reliably online in real applications.In this paper

a soft sensor based on BP neural network (BPNN) is applied to estimate the ammonia concentration.A modified group search optimization with nearest neighborhood (GSO-NH) is proposed to optimize the weights and thresholds of BPNN.GSO-NH is integrated with BPNN to build a soft sensor model.Finally

the soft sensor model based on BPNN and GSO-NH (GSO-NH-NN) is used to infer the outlet ammonia concentration in a real-world application.Three other modeling methods are applied for comparison with GSO-NH-NN.The results show that the soft sensor based on GSO-NH-NN has a good prediction performance with high accuracy.Moreover

the GSO-NH-NN also provides good generalization ability to other modeling problems in ammonia synthesis production.

关键词

Keywords

references

Views

1011

Downloads

CSCD

Alert me when the article has been cited

Submit

Tools

Publicity Resources

Attention-enhanced multi-time scale LSTM for soft sensor modeling of corn starch liquefaction

Stability investigation and techno-economic assessment of gliding arc plasma coupled electrocatalytic ammonia synthesis system

High-performance red mud as an electrocatalyst for nitrate reduction toward ammonia synthesis

Highly efficient subnanometer Ru-based catalyst for ammonia synthesis via an associative mechanism

Active training sample selection and updating strategy for near-infrared model with an industrial application

Related Author

Du Jian

Zhang Lei

Wang Yu

Li Fan

Li Yi

Tao Jin

Zhang Zhongyi

Zhuang Yu

Related Institution

COFCO Biotechnology Co., Ltd.

Institute of Chemical Process Systems Engineering, School of Chemical Engineering, Dalian University of Technology

State Key Laboratory of Fluorine & Nitrogen Chemicals, School of Chemical Engineering and Technology, Xi'an Jiaotong University

College of Chemistry and Chemical Engineering, Anhui University

School of Energy Science and Engineering, University of Science and Technology of China

⁰