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复杂工业过程运行状态评价方法回顾与展望

Review and prospect of operation performance assessment methods for complex industrial processes
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摘要 准确感知和认知复杂工业过程的运行状态对于实现过程智能控制和优化决策至关重要,是当前实现工业人工智能需要解决的关键问题之一.传统过程监测理论系统已不能满足现代工业生产过程对过程运行状态认知的精细化及准确化的需求,因此,复杂工业过程运行状态评价技术应运而生,近几年受到学术界和工业界广泛关注并快速发展.对此,首先从复杂工业过程的主要特性以及数据提取过程中面临的问题出发,回顾基于数据驱动的相关工业过程运行状态评价方法;然后根据最优性评价结果总结导致状态非“优”的原因,并进一步给出相关非优因素追溯方法;最后对现有研究内容和这一领域中值得进一步研究的发展方向做出总结和展望. It is of great significance to accurate perception and cognition of the operating performance of complex industrial processes for the realization of process intelligent control and optimization decision.This is also one of the key issues to be solved for the current realization of industrial artificial intelligence.The traditional process monitoring theory system cannot meet the demands of the modern industrial production process for the refinement and accuracy of the process operating state cognition.Hence,the operation performance assessment technology of complex industrial processes comes into being.In recent years,it has attracted the attention of academia and industry and developed rapidly.Based on the main characteristics of complex industrial processes and the problems faced in the process of data extraction,this paper reviews the operation performance assessment methods of related industrial processes based on data-driven.Then,according to the results of non-optimal evaluation,the reasons leading to non-optimal performance are summarized,and the traceability method of relevant non-optimal factors is further given.Finally,a summary and outlook of existing research and directions of development in this area that merit further research is provided.
作者 褚菲 郝莉莉 王福利 CHU Fei;HAO Li-li;WANG Fu-li(School of Information and Control Engineering,China University of Mining and Technology,Xuzhou 221116,China;Research Center of Underground Space Intelligent Control Engineering of the Ministry of Education,China University of Mining and Technology,Xuzhou 221116,China;Artificial Intelligence Research Institute,China University of Mining and Technology,Xuzhou 221116,China;College of Information Science and Engineering,Northeastern University,Shenyang 110819,China)
出处 《控制与决策》 EI CSCD 北大核心 2024年第3期705-718,共14页 Control and Decision
基金 国家自然科学基金项目(61973304,61873049,62073060) 江苏省六大人才高峰项目(DZXX-045)。
关键词 复杂工业过程 运行状态评价 数据驱动 非优因素 complex industrial process operation performance assessment data-driven non-optimal factors
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