SMALL UAV SYSTEMS CAPABLE OF CARRYING OUT RECONNAISSANCE MISSIONS TO DETECT LEAKS IN OIL AND GAS PIPELINES, AIMING TO LIMIT ACCIDENTAL ENVIRONMENTAL POLLUTION
The paper presents an alternative approach for detecting potential oil or gas leaks from transport and distribution pipelines. The detection of possible accidental pollution is carried out using small UAV systems with the help of photogrammetry. Currently, significant material and human resources are allocated to detect such events, and the use of UAVs can solve the problem of monitoring both small areas like oil platforms, gas extraction stations, or oil wells by implementing multirotor-type architectures, as well as long pipeline systems by using fixed-wing systems suitable for endurance flights. An essential aspect of these systems is the versatility shown in use depending on the payload. Thus, the paper considers the use of a wide range of sensors, such as optical sensors in the visible spectrum, gas sensors capable of detecting potential leaks in real time or allowing post-mission analysis of gas concentration levels in different areas of the responsibility zone, as well as LIDAR sensors, which allow mapping of the areas traversed by such transport and distribution systems. Widely studied, the presented technology represents a decisive factor in reducing environmental pollution globally, by limiting accidents involving oil and gas leaks, which are increasingly frequent in the vast existing networks. The paper begins with an overview of the system, continues with methods for mission planning and execution, simulation and actual realization of some scenarios, and concludes with the post-mission analysis of the data provided by the onboard sensors to determine the system's efficiency and the impact of its use, both economically by reducing losses and ecologically.
Authors
- Stefan-Mircea Mustata (ORCID: https://orcid.org/0009-0008-5875-8806)
- Cristian Vidan
- Ionut-Mihai Nacu
Institutions
- Military Technical Academy (RO)
Publication Details
- Journal
- International Multidisciplinary Scientific GeoConference SGEM ...
- Published
- 2024-12-15
- DOI
- https://doi.org/10.5593/sgem2024v/3.2/s06.49
- Primary Topic
- Fire Detection and Safety Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00