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A leak detection and 3D source localization method on a plant piping system by using multiple cameras

  • Received : 2018.01.30
  • Accepted : 2018.09.21
  • Published : 2019.02.25

Abstract

To reduce the secondary damage caused by leakage accidents in plant piping systems, a constant surveillance system is necessary. To ensure leaks are promptly addressed, the surveillance system should be able to detect not only the leak itself, but also the location of the leak. Recently, research to develop new methods has been conducted using cameras to detect leakage and to estimate the location of leakage. However, existing methods solely estimate whether a leak exists or not, or only provide two-dimensional coordinates of the leakage location. In this paper, a method using multiple cameras to detect leakage and estimate the three-dimensional coordinates of the leakage location is presented. Leakage is detected by each camera using MADI(Moving Average Differential Image) and histogram analysis. The two-dimensional leakage location is estimated using the detected leakage area. The three-dimensional leakage location is subsequently estimated based on the two-dimensional leakage location. To achieve this, the coordinates (x, z) for the leakage are calculated for a horizontal section (XZ plane) in the monitoring area. Then, the y-coordinate of leakage is calculated using a vertical section from each camera. The method proposed in this paper could accurately estimate the three-dimensional location of a leak using multiple cameras.

Keywords

References

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Cited by

  1. Video-based Deep Learning for Pipe Leakage Visualization vol.31, pp.5, 2019, https://doi.org/10.5050/ksnve.2021.31.5.521