石化智能工厂建设关键场景与技术

doi:10.16085/j.issn.1000-6613.2023-1206

化工进展 ›› 2024, Vol. 43 ›› Issue (2): 894-902.DOI: 10.16085/j.issn.1000-6613.2023-1206

石化智能工厂建设关键场景与技术

赵学良¹(), 贾梦达²(), 王显鹏³, 苏丽杰⁴, 刘东庆²

^1.中国石油化工集团有限公司，北京 100728
^2.石化盈科信息技术有限责任公司，北京 100007
^3.东北大学工业智能与系统优化国家级前沿科学中心，辽宁沈阳 110819
^4.东北大学智能工业数据解析与优化教育部重点实验室，辽宁沈阳 110819

收稿日期:2023-07-16 修回日期:2023-09-12 出版日期:2024-02-25 发布日期:2024-03-07
通讯作者: 贾梦达
作者简介:赵学良（1981—），男，教授级高级工程师，研究方向为石油化工、信息化管理。E-mail: zhaoxl@sinopec.com。
基金资助:
国家自然科学基金重大项目(72192830);国家自然科学基金面上项目(72072029);111项目(B16009)

Key scenarios and technologies for smart plant construction in petrochemical industry

ZHAO Xueliang¹(), JIA Mengda²(), WANG Xianpeng³, SU Lijie⁴, LIU Dongqing²

^1.China Petrochemical Corporation, Beijing 100728, China
^2.Petro-Cyber Works Information Technology Co. , Ltd. , Beijing 100007, China
^3.National Frontiers Science Center for Industrial Intelligence and Systems Optimization, Northeastern University, Shenyang 110819, Liaoning, China
^4.Key Laboratory of Data Analytics and Optimization for Smart Industry (Northeastern University), Ministry of Education, Shenyang 110819, Liaoning, China

Received:2023-07-16 Revised:2023-09-12 Online:2024-02-25 Published:2024-03-07
Contact: JIA Mengda

摘要/Abstract

摘要：

智能工厂是石化工业发展智能制造、实现绿色可持续转型的重要途径。本文从业务和技术两个方面出发，重点探讨了未来石化智能工厂建设中边缘云平台规划和需要构建的关键业务场景，并结合数据解析与人工智能提出了各场景的关键技术方法，主要包括基于数据与机理融合建模的石化生产计划与调度优化、石化生产过程多目标进化学习建模与操作优化和石化生产设备智能运行监测与故障诊断。本文的研究成果对于推动石化智能工厂建设，实现石化生产管控智能化、质量管控智能化、设备管控智能化的核心能力提升具有重要意义。

关键词: 石化智能工厂, 生产管控, 操作管控, 设备管控

Abstract:

Smart plant is an important way to develop smart manufacturing and achieve green and sustainable transformation in petrochemical industry. This paper proposed the planning of edge cloud platform and the key business scenarios to be built in the future construction of petrochemical smart plant from both business and technical aspects, and designed the technical methods for each scenario by combining data analysis and artificial intelligence, mainly including production planning and scheduling based on data and mechanism integration modeling, multi-objective evolutionary learning for modeling production process and operation optimization, smart operation monitoring and fault diagnosis for production equipment. The research results of this paper were of great significance to promote the construction of petrochemical smart plant and to realize the improvement of core capabilities such as intelligent petrochemical production control, intelligent quality control and intelligent equipment control.

Key words: petrochemical smart plant, production control, operation control, equipment control

中图分类号:

赵学良, 贾梦达, 王显鹏, 苏丽杰, 刘东庆. 石化智能工厂建设关键场景与技术[J]. 化工进展, 2024, 43(2): 894-902.

ZHAO Xueliang, JIA Mengda, WANG Xianpeng, SU Lijie, LIU Dongqing. Key scenarios and technologies for smart plant construction in petrochemical industry[J]. Chemical Industry and Engineering Progress, 2024, 43(2): 894-902.

图/表 8

图1 石化智能工厂关键场景的总体规划

图2 石化边缘云平台协议识别模型

图3 石化边缘云平台智能入侵检测

图4 基于数据与机理融合建模的石化生产计划与调度优化方法流程

图5 石化智能工厂生产过程进化学习建模与操作优化方法流程

图6 石化智能工厂基于多目标进化学习的建模方法

图7 石化智能工厂设备运行智能监测与诊断模型构建

图8 石化智能工厂设备运行融合特征构建方法

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石化智能工厂建设关键场景与技术

Key scenarios and technologies for smart plant construction in petrochemical industry

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