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Machine Learning Approach to Distributed Acoustic Sensors (DAS) for Securing Pipelines in Urban Areas

Third party interference is one of the leading causes of pipeline failures and accidents that create great risk for safety and environment, as well as revenue loss for the operators. Especially in urban areas unauthorized and uncoordinated infrastructure and construction works pose serious threat to liquid and gas pipelines. Effective detection of intrusive activities and a timely preventative course of action is crucial. Fiber optic Distributed Acoustic Sensors (DAS) are useful and proven tools for third party interference detection. Distributed Acoustic Sensing (DAS) is a sensing technology that uses standard telecommunications fiber optic cable that is buried parallel to the pipeline as an array of acoustic sensors….[Aselsan] propose a three-stage interference detection algorithm….Proposed algorithm is deployed in highly populated urban areas for securing natural gas pipeline in Istanbul, Turkey. The system has successfully detected multiple instances of third-party interferences with a very low nuisance alarm rate.
Machine Learning Approach to Distributed Acoustic Sensors (DAS) for Securing Pipelines in Urban Areas
Pipeline Technology Journal Issue 4 2020 p. 38 October 2, 2020
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Machine Learning Approach to Distributed Acoustic Sensors (DAS) for Securing Pipelines in Urban Areas