首页|Predictive analytics for fault reasoning in gas flow control facility: A hybrid fuzzy theory and expert system approach
Predictive analytics for fault reasoning in gas flow control facility: A hybrid fuzzy theory and expert system approach
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NSTL
Elsevier
Gas pressure reduction stations are essential in energy distribution networks because even a minor failure of these systems causes disruptive consumer problems. This study aims to introduce and implement a new knowledge-based platform that uses the synthesized expert's opinions to improve gas pressure control facilities. Given the record of failure of gas transmission system components and the data's uncertain nature, a new fuzzy expert system is developed that takes advantage of the object-oriented programming paradigm to analyze failure modes and conditions. The artificial intelligent model is designed in C# programming language, and a user-friendly interface is developed for ease of implementation. The knowledge-based model's validity has been tested by implementing real-world case studies adapted from the Iranian gas industry. Implementing the designed expert system shows that it can minimize the probability of a breakdown and improve safety conditions.
Decision treeFailure diagnosis and analysisFuzzy inductive reasoningGas stationsObject-oriented programmingPredictive analytics
Hassannayebi E.、Nourian R.、Mousavi S.M.、Seyed Alizadeh S.M.、Memarpour M.
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Industrial Engineering Department Sharif University of Technology
Department of Industrial Engineering South Tehran Branch Islamic Azad University
Department of Industrial Engineering Shahed University
Petroleum Engineering Department Australian College of Kuwait
Industrial Engineering Department Tarbiat Modares University
NSTL
Elsevier
