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Spatio-Temporal Decision Fusion for Quickest Fault Detection Within Industrial Plants: The Oil and Gas Scenario

Abstract

In this work, we present a spatio-temporal decision fusion approach aimed at performing quickest detection of faults within an Oil and Gas subsea production system. Specifically, a sensor network collectively monitors the state of different pieces of equipment and reports the collected decisions to a fusion center. Therein, a spatial aggregation is performed and a global decision is taken. Such decisions are then aggregated in time by a post-processing center, which performs quickest detection of system fault according to a Bayesian criterion which exploits change-time statistical distributions originated by system components’ datasheets. The performance of our approach is analyzed in terms of both detection- and reliability-focused metrics, with a focus on (fast & inspection-cost-limited) leak detection in a real-world oil platform located in the Barents Sea.
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Category

Academic chapter

Language

English

Author(s)

Affiliation

  • SINTEF Energy Research / Gassteknologi
  • University of Naples 'Federico II'
  • Norwegian University of Science and Technology

Year

2021

Publisher

IEEE (Institute of Electrical and Electronics Engineers)

Book

24th International Conference on Information Fusion (FUSION)

ISBN

9781737749714

View this publication at Norwegian Research Information Repository