ВИКОРИСТАННЯ ГІБРИДНИХ РОБОТИЗОВАНИХ КОМПЛЕКСІВ ДЛЯ ІНСПЕКЦІЇ МОРСЬКИХ НАФТОГАЗОВИХ ОБ'ЄКТІВ

Abstract

The aim of this paper is to analyse the current state and prospects of using hybrid robotic systems for the inspection of offshore oil and gas facilities. This goal is achieved during inspections in the offshore industry through the use of hybrid robotic systems, which include autonomous underwater vehicles, remotely operated underwater vehicles, unmanned aerial vehicles and autonomous surface vehicles, acting according to a single plan to minimise the risk to humans while providing accurate and reliable information about the condition of equipment in any difficult conditions. Remotely operated underwater vehicles and autonomous underwater vehicles are key links in the system for monitoring the condition and safety of offshore industry facilities. With access to hard-to-reach areas on floating structures, modern imaging technology and excellent manoeuvrability, UAVs provide detailed high-resolution images to monitor the condition of structures above the waterline, allow for prompt detection of corrosion or mechanical damage to structures and promptly propose urgent measures to eliminate them. Increased safety during regular inspections by unmanned aerial vehicles in various areas of the platform to identify potential risks that could endanger personnel, assets and the environment is achieved by excluding inspectors from working at high altitude or depth and/or in hazardous conditions. The most significant results are the allocation of several inspection zones depending on the availability of equipment and the procedure for conducting inspections on fixed and floating offshore structures. The significance of the obtained results lies in the development of proposals for the use of unmanned aerial vehicles, surface vehicles and underwater vehicles for the inspection of offshore structures, which is considered an effective alternative to the use of underwater divers and workers working at high altitudes, providing enhanced control, maintenance and repair capabilities in hard-to-reach places and faster acquisition of large amounts of data. Thus, the main direction for further work is to investigate the possibility of integrating advanced sensor technologies with existing unmanned systems to achieve more efficient inspections and using artificial intelligence and machine learning to analyse the data obtained from these inspections to improve automated detection of defects and anomalies and reduce possible risks.