An automated algorithm approbated for the analysis of telemetric parameters of the state of spacecraft onboard systems
Authors: Abanin O.I.
Published in issue: #1(121)/2022
DOI: 10.18698/2308-6033-2022-1-2149
Category: Aviation and Rocket-Space Engineering | Chapter: Aircraft Dynamics, Ballistics, Motion Control
The paper focuses on the problem of analyzing spacecraft telemetric information solved by wavelet transform, reveals the prerequisites for automating the analysis process, and indicates the possible results of implementing algorithms for analyzing the state of spacecraft onboard systems according to the proposed method. To detect abnormal changes in telemetric parameters, we propose an algorithm for automated processing of their values; to analyze reliable data on the state of spacecraft onboard systems, we describe the step-by-step process of wavelet filtering of telemetric parameters time series. The study also introduces the ways to identify and eliminate faulty values in telemetric information. The method for automating the analysis process is based on the developed special mathematical apparatus; the paper briefly describes the mathematical transformations used in the study. We tested the method by analyzing the archival spacecraft telemetric information. The test results are given, as well as the results of the wavelet analysis of the telemetric parameters of the air conditioning system and the power supply system of the ISS Russian Segment.
References
[1] Donskov A.V., Mishurova N.V., Solovev S.V. Vestnik Moskovskogo aviatsionnogo instituta — Aerospace MAI Journal, 2018, vol. 25, no. 3, pp. 151–160.
[2] Abanin O.I., Soloviev S.V. Inzhenerny zhurnal: nauka i innovatsii — Engineering Journal: Science and Innovation, 2018, iss. 7. http://dx.doi.org/10.18698/2308-6033-2018-7-1788
[3] Sakrutina E.A., Bakhtadze N.N. Identifikatsiya sistem na osnove veyvlet-analiza [System identification based on wavelet analysis]. In: XII Vserossiyskoe soveschanie po problemam upravleniya VSPU-2014 [XII All-Russian Meeting on Management Problems 2014]. Moscow, Institute of Control Sciences RAS Publ., 2014, pp. 2868–2889.
[4] Astafeva N.M. Uspekhi fizicheskikh nauk — Physics-Uspekhi (Advances in Physical Sciences), 1996, vol. 166, no. 11, pp. 1145–1170.
[5] Kozinov I.A. Informatsionno-upravlyayuschie sistemy — Information and Control Systems, 2015, no. 1, p. 4.
[6] Dyakonov V.P. Veyvlety. Ot teorii k praktike [Wavelets. From theory to practice]. Moscow, Solon-R Publ., 2002, 448 p.
[7] Barsegyan A.A., Kupriyanov M.S., Kholod I.I. Analiz dannykh i protsessov [Analysis of data and processes]. 3rd ed. St. Petersburg, BKhV-Peterburg Publ., 2009.
[8] Vorobiev V.I., Gribunin V.G. Teoriya i praktika veyvlet-preobrazovaniya [Theory and practice of wavelet transform]. St. Petersburg, VUS Publ., 1999, pp. 1–204.
[9] Konysheva V.Yu., Maksimov N.A., Sharonov A.V. Trudy MAI (Proceedings of MAI), 2018, no. 97. Available at: http://trudymai.ru/upload/iblock/911/Konysheva_Maksimov_SHaronov_ru.pdf
[10] Dremin I.M., Ivanov O.V., Nechitaylo V.A. Uspekhi fizicheskikh nauk — Physics-Uspekhi (Advances in Physical Sciences), 2001, vol. 171, no. 5, pp. 465–501.
[11] Dyakonov V., Abramenkova I. MATLAB. Obrabotka signalov i izobrazheniy. Spetsialny spravochnik [MATLAB. Signal and image processing. Special reference book]. St. Petersburg, Piter Publ., 2002, 608 p.
[12] Petukhov A.P. Vvedenie v teoriyu bazisov vspleskov [Introduction to the theory of wavelet bases]. St. Petersburg, SPSIT Publ., 1999, 132 p.
[13] Pereberin A.V. Vychislitelnye metody i programmirovanie — Numerical Methods and Programming, 2001, vol. 2, pp. 15–40.