Health Monitoring of Pressure Regulating Stations in Gas Distribution Networks Using Mathematical Models

Article Automation & Control Systems

A State Monitoring Method of Gas Regulator Station Based on Evidence Theory Driven by Time-Domain Information

Bo Wang et al.

Summary: This article proposes an improved method of evidence theory for the state monitoring of a gas regulator station. By using a back-propagation neural network to judge evidence conflicts, introducing a relative conflict factor to modify evidence, and calculating an adaptive time attenuation factor to reduce accumulated error, the dynamic fusion of time-domain information is achieved. The feasibility and effectiveness of the method are verified through experiments.

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2022)

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Article Computer Science, Information Systems

State Monitoring of Gas Regulator Station Based on Feature Selection of Improved Grey Relational Analysis

Jingyuan Jia et al.

Summary: This paper proposes a feature selection method based on gray relational analysis to optimize the state monitoring of gas regulator stations. By transforming the distance between the comparison matrix and the reference matrix into geometric probability distribution, the problem of data initial transformation is solved. Furthermore, a weight coefficient is constructed by combining redundancy and correlation to improve the application of gray relational degree in nonsequential systems. Simulation analysis and experimental results demonstrate that the proposed method achieves higher maximum classification accuracy and smaller selected feature set. When combined with multiple classifiers, the method shows good comprehensive performance, enabling the quick identification of the subset containing the most identifiable features and improving monitoring efficiency.

IEEE INTERNET OF THINGS JOURNAL (2022)

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Article Computer Science, Interdisciplinary Applications