Oil Pipeline Leak Detection and Control using Optimal Filtering and LSTM

There are many refinery industries in Beaumont,Texas, and gas pipeline leak detection is the great business challenge.In the world, every 2 minutes there is a leak in the pipelineand more than 40 billion dollars have been unutilized for thisimpeding task. Therefore, oil pipeline leak detection and controlis a critical business issue to prevent environmental hazards,economic losses, and public concerns. This paper presents an oilpipeline leak detection and control framework that incorporatesoptimal filtering and LSTM networks. The proposed techniqueleverages sensor data from SCADA/IoT platforms to properlyestimate pipeline states, and provide real-time control commands.Moreover, the online learning framework is introduced to adaptthe model to evolving pipeline conditions. Numerical Simulationresults show the effectiveness of the developed approach. Hopefully,this framework and analysis will be significantly helpful tothe education and industries. The spatial and temporal featureswith the hurricane and tornado will be considered in this modeland analysis the impacts.Index Terms—Kalman Filter, Leak Detection, LSTM Networks,Hybrid Fault Diagnosis, Pipeline.