人工神经网络在石油化工中的应用研究进展
Research Progress in Application of Artificial Neural Network in Petrochemical Industry
赵晓弘 1胡西娅 2纪博睿 3段卫宇 3吴丹 3王诗语 4潘英妮 2王硕3
作者信息
- 1. 辽宁省检验检测认证中心,辽宁沈阳 110032
- 2. 沈阳药科大学 中药学院辽宁 沈阳 110016
- 3. 辽宁省检验检测认证中心,辽宁沈阳 110032;辽宁省产品质量监督检验院,辽宁沈阳 110032
- 4. 中石化(大连)石油化工研究院有限公司,辽宁大连 116045
- 折叠
摘要
石油化工行业体系庞大而复杂,其生产过程设备稳定性、安全性、节能环保等至关重要,而基于数据驱动的人工神经网络能很好地处理其生产过程中复杂的高维度、非线性数据,从而通过建模解决实际生产过程中难题.介绍了人工神经网络发展历程和基本原理,概述了人工神经网络在石油化工装置产品预测与操作优化、设备故障诊断、安全预警、节能减排等方面的应用,提出了持续优化、研发更有广度和深度的神经网络模型是未来石化工作的方向.
Abstract
The petrochemical industry system is huge and complex, and the stability, safety, energy saving and environmental protection of its production process equipment are very important. The artificial neural network based on data-driven can deal with the complex high-dimensional and nonlinear data in the production process, so as to solve the problems in the actual production process through modeling. In this paper, the development process and basic principle of artificial neural network were introduced, the application of artificial neural network in product prediction and operation optimization, equipment fault diagnosis, safety early warning, energy saving and emission reduction of petrochemical plant was summarized, and it was pointed out that continuous optimization and research and development of more in-depth neural network model should be a direction of future work.
关键词
人工神经网络/石油化工/非线性/数据预测/优化Key words
Artificial neural network/Petrochemical industry/Non-linear/Data prediction/Optimization引用本文复制引用
基金项目
辽宁省自然科学联合基金项目(2022-NLTS-12-03)
辽宁省市场局科学计划项目(2022JS003)
出版年
2024
NETL
NSTL
万方数据