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This paper proposes a new method to diagnose the system fault of the process industry based on the monitor data set of distributed control system (DCS). Firstly, it defines a homeomorphism product space named color phase space which is a Cartesian product of two-dimensional Euclidean space and three-dimensional color phase space. Secondly, it maps the DCS data to the color phase space in order to...
Fault diagnosis and abnormal event management are key issues in process industry. For decades of research, many approaches have been proposed and put into practice. The Signed Digraph (SDG) model based diagnosis approach seems to be more effective in tracing the root causes of abnormality in large scale process system like petrochemical industry, especially when system becomes more complex nowadays...
Modern process system can be regarded as multi-medium interacted heterogeneous networks comprised of material transportation, power supply and control information exchange, in which substance like material, energy and information coexist and interact. Thus fault diagnosis and safety analysis for complex process system based on homogeneous network theory should be improved to hold multi-medium interacted...
The spreading of faults and serious failures in many large-scale engineering systems is today one of the issues of the highest concern. This paper presents a novel method for modeling the fault propagation behaviors from the perspective of complex network theory. By focusing essentially on the topological structure properties of the underlying system network, several principles that are capable of...
Bayesian network is one of the most effective theoretical models applied in the fault diagnostic decision. In order to realize the computer-aided construction of the Bayesian network for diagnostics, this paper proposes a simple, yet comprehensive failure knowledge representation model combined with the structure decomposition of the complex system. Using the polychromatic sets theory, the rock-bottom...
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