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An approach to reliability analysis of aircraft systems for a small dataset

Okoro Onyedikachi Chioma, Zaliskyi Maksym, Serhii Dmytriiev, Abule Ibinabo

Zeszyty Naukowe. Transport / Politechnika Śląska

2023

z. 118

207--217

Data-driven predictive aircraft maintenance approach typically results in lower maintenance costs, avoiding unnecessary preventive maintenance actions and reducing unexpected failures. Information provided by a reliability analysis of aircraft components and systems can improve an existing maintenance strategy and ensure an optimal maintenance task interval. For reliability work, the exponential distribution is typically used; however, this approach requires substantial amounts of data, which often may not be generated by aviation operations. Therefore, this study proposes a method for reliability analysis given a small dataset. Real-life historical data of an aircraft operating in Nigeria validate the proposed approach and prove its applicability.

Optimal Method for Polarization Selection of Stationary Objects Against the Background of the Earth’s Surface

Volosyuk Valerii, Zhyla Simeon, Pavlikov Vladimir, Ruzhentsev Nikolay, Tserne Eduard, Popov Anatoliy, Shmatko Oleksandr, Dergachov Kostiantyn, Havrylenko Olena, Ostroumov Ivan, Kuzmenko Nataliia, Sushchenko Olga, Averyanova Yuliya, Zaliskyi Maksym, Solomentsev Oleksandr, Kuznetsov Borys, Nikitina Tatyana

International Journal of Electronics and Telecommunications

2022

Vol. 68, No. 1

83--89

Within the maximum likelihood method an optimal algorithm for polarization target selection against the background of interfering signal reflected from the earth’s surface is synthesized. The algorithm contains joint operations of spectral interference rejection and their polarization compensation by means of certain combinations of interchannel subtraction of signals of different polarizations. The physical features of the elements of the polarization scattering matrix are investigated for the technical implementation of the synthesized algorithm.