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Research on Key Technologies for Failure Prediction and Health Management of Unmanned Aerial Vehicles
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Abstract
Unmanned Aerial Vehicles (UAVs) are playing an increasingly important role in the modern national economy, with a wide range of applications covering a variety of fields such as agriculture, industry, transport, environmental monitoring, medical rescue, and so on, and have become a new driving force for economic development. The significance of fault prediction and health management can improve the reliability of equipment, and fault diagnosis technology can accurately find out the cause and location of equipment failure, so as to repair and restore the original function of the equipment in time. This helps to ensure the stable operation of the equipment and improve its reliability of the equipment. At the same time, it provides customized maintenance recommendations and the best time to repair the equipment, minimizing unnecessary maintenance costs. Plan maintenance ahead of time: Health prediction technology can assess the health of your equipment and predict performance degradation trends and remaining useful life. How to quickly diagnose the cause of UAV failure, accurately determine the health status, combined with the current UAV maintenance guarantee capacity, put forward rationalised maintenance countermeasure suggestions, to ensure that the UAV warranty service not only meets the economic demand of cost control, but also can efficiently support the mission requirements of its execution, so the research has a very realistic economic value and practical significance.
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How to cite this paper
Research on Key Technologies for Failure Prediction and Health Management of Unmanned Aerial Vehicles
How to cite this paper: Shengzhi Xu, Yunbin Yan, Lu Wang, Kai Han. (2025). Research on Key Technologies for Failure Prediction and Health Management of Unmanned Aerial Vehicles. Engineering Advances, 5(2), 60-63.
DOI: http://dx.doi.org/10.26855/ea.2025.04.003
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