Abstract
Estimations indicate that up to a third of the power consumption of compressed air leaks is lost due to undetected leaks. The current methods of detection and localization of these leaks require intensive manual labor, making use of handheld devices. In addition, the added energy cost caused by these air leaks is concealed in the total cost of energy. These factors can explain why there is a limited commitment to detect and repair air leaks. To address this issue, we propose a solution which does not require manual labor in the process of detecting and locating pressurized air leaks. By equipping existing factory vehicles with a multi-modal sensing device containing a LIDAR, an ultrasonic microphone array and a camera, we are able to locate leaks in large industrial environments with high precision in 3D. With this proposed solution we aim to encourage the industry to proactively search for pressurized air leaks and therefore reduce energy losses costing a fraction of currently employed methods.
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Schenck, A., Daems, W., Steckel, J. (2020). AirLeakSlam: Automated Air Leak Detection. In: Barolli, L., Hellinckx, P., Natwichai, J. (eds) Advances on P2P, Parallel, Grid, Cloud and Internet Computing. 3PGCIC 2019. Lecture Notes in Networks and Systems, vol 96. Springer, Cham. https://doi.org/10.1007/978-3-030-33509-0_70
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DOI: https://doi.org/10.1007/978-3-030-33509-0_70
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