Abstract
Predictive maintenance (PM) strategies are based on real-time data for diagnosis of impending failure and prognosis of machine health. It is a proactive process, which needs predictive modeling to trigger an alarm for maintenance activities and anticipate a failure before it occurs. Various industries have adopted PM techniques because of its advantage in increasing reliability and safety. But in the aviation industry, expectations for safety are increased due to its high cost and danger to human life when an aircraft fails or becomes out of service. Flight data monitoring systems are regularly implemented in commercial operations using artificial intelligence (AI) algorithms, but there is limited work specific to safety critical systems such as engine and hydraulic system. This paper provides a survey of recent work on PM of aircraft's’ hydraulic system and engine, identifying new trends and challenges. This work also highlights the importance of PM and state-of-the-art data pre-processing techniques for large datasets.
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The authors would like to thank and acknowledge the Higher Education Commission Pakistan for funding this work through the Grant TDF 03-054. This funding (TDF 03-054) was awarded to Dr. Tanvir Ahmad (PI) and Dr. Abdul Basit (Co-PI).
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Khan, K., Sohaib, M., Rashid, A. et al. Recent trends and challenges in predictive maintenance of aircraft’s engine and hydraulic system. J Braz. Soc. Mech. Sci. Eng. 43, 403 (2021). https://doi.org/10.1007/s40430-021-03121-2
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DOI: https://doi.org/10.1007/s40430-021-03121-2