融合分层分块信息的轧制过程运行状态评估方法及应用  

An operating performance assessment method for tolling processes viaintegrating hierarchical and block information

作　　者：张永博 张凯[1,2] 彭开香[1,2] 杨朋澄[1] ZHANG Yong-bo;ZHANG Kai;PENG Kai-xiang;YANG Peng-cheng(School of Automation,University of Science and Technology Beijing,Beijing 100083,China;Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education,Beijing 100083,China)

机构地区：[1]北京科技大学自动化学院,北京100083 [2]工业过程知识自动化教育部重点实验室,北京100083

出　　处：《控制与决策》2024年第8期2694-2702,共9页Control and Decision

基　　金：国家自然科学基金面上项目(62073032);国家自然科学基金区域联合重点项目(U21A20483).

摘　　要：工业过程运行状态评估方法是对过程当前运行状态进行合理的评价,为工业过程的安全、高效运行提供有益的指导.带钢轧制过程具有流程长且系统层级多等特点,而传统的运行状态评估往往采用集中式的评估方法,难以对轧制过程全流程的运行状态进行合理的评估.针对此问题,提出一种融合分层分块信息的轧制过程运行状态评估方法.采用一种多层级分块的评估策略,将全流程分为若干个层级和子块,提高评估结果的可解释性.提出一种联合核主成分分析(kernel principal component analysis,KPCA)和t-分布随机邻域嵌入算法(t-distributed stochastic neighbor embedding,t-SNE)的特征提取方法,并行地提取全局和局部的特征信息.进而,针对传统支持向量机(support vector machine,SVM)输出结果为硬判型输出,将SVM的输出结果映射为后验概率,并通过D-S证据理论融合多个层级的运行状态评估结果,从而实现决策层面的信息融合,提高评估结果的准确性.最后,将所提出方法应用于实际带钢轧制过程,与各类传统的方法相比评估准确率提高近18%.Operating performance assessment methods are performed to evaluate the operating performance of industrial processes so as to provide helpful guidance for safe and high-efficient operations.The rolling processes are always featured with plant-wide characteristics and equipped with hierarchical information systems,while traditional assessment methods are centralized,which,thus,are less efficient.To solve this problem,this paper proposes a method that integrates hierarchical and block information.Firstly,a hierarchical strategy is adopted,and the entire process are partitioned into several levels and sub-blocks such that the interpretability of the assessment results can be improved.Then,in order to extract comprehensive operating state features,a combination of kernel principal component analysis and t-distributed stochastic neighbor embedding-based method is proposed,which can capture both global and local features in a parallel manner.In addition,to overcome the hard decision-making results caused by support vector machines(SVMs),this paper transfers the results of the SVM to calculate the posterior probability,and makes use of the D-S evidence theory to fuse the decision-making process.Finally,the proposed method is applied to a real hot rolling mill process,the results show that it improves at least 18%assessment rate compared with several traditional methods.

关 键 词：流程工业 运行状态评估 特征提取 D-S证据理论 热连轧过程 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]