基于最小路径覆盖算法的化工过程重要参数的识别

Identification of important parameters in chemical process based on minimum path coverage algorithm

将复杂网络的目标控制理论应用到化工过程系统重要参数的识别中,以SDG(signed directed graph)模型和复杂网络理论为基础构建化工过程的网络模型,然后利用LeaderRank和节点相似度算法(SRank算法)对网络节点重要性进行排序并基于此对网络进行鲁棒性分析选取目标节点,通过最小路径覆盖算法对网络进行目标控制分析,确定驱动节点并对它们进行重点监控。案例分析结果表明,该方法可行,对化工过程系统中重要参数的监测和安全控制具有一定的指导意义。

This paper proposes the application of complex network target control theory in the identification of important parameters in chemical process system.The network model of chemical process is built on the basis of SDG(signed directed graph)model and complex network theory,then the importance of network nodes is sorted by LeaderRank and node similarity algorithm(SRank algorithm).Based on this,the robustness of the network is analyzed and the target node is selected.The target control analysis is carried out by the minimum path coverage algorithm and the driving nodes are confirmed and monitored.Case studies show that this method is feasible and has some guiding significance for monitoring and safety control of important parameters in chemical process system.