Identification Of Key Variables Of Chemical SDG Based On Complex Network Target Control Theory

With the continuous expansion of chemical production scale,its complexity and integration are increasing.At the same time,higher requirements are put forward for the safe operation of chemical production process.Identifying and effectively monitoring the key variables of chemical process can reduce the operational risk,which is of great significance to the safe and stable operation of chemical production process.Therefore,this paper proposes a robust analysis of chemical process network based on complex network theory and applies the target control theory of complex network to identify key variables in chemical production process.Firstly,the SDG(Signed Directed Graph)model of the system was built according to the chemical process,the adjacency matrix of the network is established and transformed into a directed network model.Leader Rank algorithm and node similarity algorithm are used to evaluate the importance of each node in the network.Then the maximum connectivity,characteristic path length and network efficiency are selected as evaluation indicators,the robustness of chemical process network is analyzed by random attack and deliberate attack,and the conclusion is drawn.Secondly,considering the importance of the driving nodes in the network,the key nodes in the network are identified based on the complex network target control theory.Target nodes are selected based on the robustness evaluation of the network when intentional attack occurs.The target control analysis of the network is carried out through the minimum path coverage algorithm to determine the set of driving nodes of the network,and then the key nodes that need to be monitored in the network are obtained.Finally,the key paths in chemical process network are identified based on the ideal solution method of combined weighting approximation.From the perspective of complex network,the edge-to-edge number,endpoint-to-edge support and the mean importance of nodes at both ends are selected as evaluation indexes.The weight of each index is determined by the combined weight method,and the importance value of each edge is calculated by the ranking method of TOPSIS.The key edges are selected according to the ranking of edge importance.Key paths in the network are obtained according to the network topology.The case analysis results show that the method is feasible.It has certain guiding significance for monitoring and controlling important parameters in chemical production process.