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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...
An industry process includes a variety of monitoring variables, and there is a strong relevance between the variables. Time series from different monitoring points can be used to obtain the feature of system's linkage fluctuation. Using the coarse-grained method, monitoring series has been changed into a sequence of characters. The sequence which is sliding by a certain length is converted into continuous...
In this paper, we have introduced a novel method for condition diagnosis of complex systems in the chemical process industry with complex network based time series analysis. Firstly, by a computational method, the condition data from the complex system can be mapped into a network, which inherits the properties of condition data. Then, the topological properties of these complex networks are investigated,...
In this paper, we introduce a new method for safety analysis of process industry systems based on recent advances in complex networks. We model the process industry system as a large, complex network and study its topological properties, and then we investigate the cascading failures by constructing a simple model incorporating the loads on nodes and the efficiency of network. We use the Tennessee...
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