Complex network theory-based condition recognition of electromechanical system in process industry

Abstract

In order to recognize the different operating conditions of a distributed and complex electromechanical system in the process industry, this work proposed a novel method of condition recognition by combining complex network theory with phase space reconstruction. First, a condition-space with complete information was reconstructed based on phase space reconstruction, and each condition in the space was transformed into a node of a complex network. Second, the limited penetrable visibility graph method was applied to establish an undirected and un-weighted complex network for the reconstructed condition-space. Finally, the statistical properties of this network were calculated to recognize the different operating conditions. A case study of a real chemical plant was conducted to illustrate the analysis and application processes of the proposed method. The results showed that the method could effectively recognize the different conditions of electromechanical systems. A complex electromechanical system can be studied from the systematic and cyber perspectives, and the relationship between the network structure property and the system condition can also be analyzed by utilizing the proposed method.