Journal of Robotics Spectrum

Deep Learning and Machine Learning Algorithms for Enhanced Aircraft Maintenance and Flight Data Analysis

Journal of Robotics Spectrum

Received On : 05 March 2023

Revised On : 20 April 2023

Accepted On : 12 May 2023

Published On : 15 May 2023

Volume 01, 2023

Pages : 090-099


This paper examines the use of machine learning and deep learning algorithms in the aviation industry, with a specific emphasis on aircraft diagnosis/prognosis, predictive maintenance, feature selection, and flight data monitoring (FDM). This study highlights the potential use of these algorithms in enhancing the efficacy and effectiveness of various aircraft operations. In the field of aviation prognosis and diagnosis, many designs have been acknowledged as efficient for defect identification, calculation of remaining usable life, and prediction of excessive vibration in aero-engines. The architectural models discussed in this paper include deep autoencoders, deep belief networks, long short-term memory networks, and convolutional neural networks. The use of feature selection and scalar feature selection methodologies has been seen to augment the efficacy of FDM (Feature Detection and Matching) algorithms by means of identifying noteworthy features and detecting highly linked features. The application of machine learning algorithms in the domain of predictive maintenance enables real-time assessment of equipment health, hence reducing possible hazards and improving overall equipment performance. The research results emphasize the importance of flight data monitoring in improving safety and operational efficiency in the field of civil aviation. The application of machine learning approaches, namely classification algorithms, facilitates the analysis of flight data for the aim of identifying unsafe behaviors or violations from established operational standards.


Artificial Intelligence, Machine Learning, Deep Learning, Aircraft Prognosis Diagnosis, Feature Selection, Predictive Maintenance, Flight Data Monitoring.

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Cite this article

Malene Helgo, “Deep Learning and Machine Learning Algorithms for Enhanced Aircraft Maintenance and Flight Data Analysis”, Journal of Robotics Spectrum, vol.1, pp. 090-099, 2023. doi: 10.53759/9852/JRS202301009.


© 2023 Malene Helgo. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.