Design of Pipeline leak Detection System using Neural Network on Scada Platform of National Iranian Oil Company

Document Type : Research Paper

Authors

1 Department of Electrical Engineering, Marvdasht Branch, Islamic Azad University, Marvdasht, Iran

2 Instrumentation Design Department, Engineering Division, Faculty of Research and Development in Downstream Petroleum Industry, Research Institute of Petroleum Industry (RIPI), Tehran, Iran

Abstract

Leaks in oil and gas pipelines could cause serious problems such as explosions, environmental pollution, and the loss of energy and financial resources. Early detection of leaks in pipelines is critical to prevent or reduce the occurrence of these losses. For this purpose, a leak detection module located on the infrastructure of a Scada system can be used. In this paper, first, Olga simulates leaks of different sizes and distances on oil pipeline. The output of the Olga, which includes the pressure and flow of different parts of the pipeline, was prepared for analysis using Power Query and Dax Studio tools. The data was entered into MATLAB and the artificial neural network was designed and trained to identify the size and location of the leak. Eventually, this module will be placed on the Scada system as a digital twin of that pipeline and will receive the necessary online data to monitor the condition of the pipeline using the industrial protocols.
 

Keywords


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