DETERMINING THE RELIABILITY OF THE INSTRUMENT SPEED PARAMETER BASED ON THE DYNAMIC CHARACTERISTICS OF THE OBJECT OBTAINED DURING FLIGHT TESTS
Abstract
The article describes about of the typical methods of air data parametric quorum control,
and an analysis of their capabilities to determine parametric failures that occur in the air data
system. To perform the calculations, the most common types of failures of the path of perception
and measurement of air pressure of the air signal system, causing catastrophic consequences,
were selected, the physical principles of their occurrence were described, the implementation of
which made it possible to build mathematical models of signal distortion. Based on the results of
modeling the operation of typical quorum control methods, and their response to failures artificially
introduced into the system, the advantages and disadvantages of the methods used are determined.
In order to eliminate the shortcomings found as a result of the analysis, an alternative
method for determining failures of the sensor group of the air data system is proposed by implementing
cross-checking of the parameters obtained from the pneumatic and vane sensor groups of
the system. For the proposed method, the results of modeling based on real flight data of a mainline
aircraft with parametric failures artificially introduced into them are presented. The possibility
of using the cross-checking algorithm in single-channel systems of air signals of small-sized
aircraft is evaluated. The statement of the research problem is formulated as follows: in order to
ensure the flight safety of an aircraft when using information in the control loop from a singlechannel
air data system, it is necessary to ensure the detection and exclusion of unreliable data
from the array of information issued by the system to consumers of information. At the same time,
the task of detecting and excluding data must be solved by the air data system itself, without using
additional data from other aircraft systems. Mathematical analysis, numerical modeling, determination
of correction factors and preparation of initial data were carried out in the MathCAD software
and mathematical complex. Analysis of the results of the studying implemented in the
MathCAD PMC cross-checking algorithm showed that the problem of determining the reliability
of information can be solved autonomously when it implemented a single-channel system of air
signals in an aircraft.
References
parametrov letatel'nykh apparatov: ucheb. posobie [Meters of aerodynamic parameters of aircraft:
textbook. manual], ed. by V.A. Mishina. Ul'yanovsk: UlGTU, 2005, 509 p.
2. Shomankov D.A. Analiz vliyaniya neispravnostey aerometricheskikh priborov i priemnikov
vozdushnykh davleniy na bezopasnost' poletov [Analysis of the impact of malfunctions of aerometric
instruments and air pressure receivers on flight safety], CredeExperto: transport, obshchestvo,
obrazovanie, yazyk [CredeExperto: transport, society, education, language], 2018, No. 4 (19). Available
at: http://ce.if-mstuca.ru/wp-content/uploads/2018/04/shomankov.pdf (accessed 10 February 2021).
3. Dobrovol'skiy D.V. Priznak nedostovernosti indikatornoy skorosti poleta [A sign of unreliability
of the flight speed indicator], Aerokosmicheskie tekhnologii [Aerospace technologies],
2017, No. 2, pp. 44-48.
4. Ivanov Yu.P., Sinyakov A.N., Filatov I.V. Kompleksirovanie informatsionno-izmeritel'nykh
ustroystv letatel'nykh apparatov: uchebnoe posobie [Integration of information and measuring
devices of aircraft: a textbook], ed. by V.A. Bodner. Leningrad: Mashinostroenie, 1984, 207 p.
5. Soldatkin V.M., Ganeev F.A., Soldatkin V.V., Nikitin A.V. Aviatsionnye pribory, izmeritel'novychislitel'nye
sistemy i kompleksy: Printsipy postroeniya, algoritmy obrabotki informatsii,
kharakteristiki i pogreshnosti: ucheb. posobie [Aviation instruments, measuring and computing
systems and complexes: Principles of construction, algorithms of information processing,
characteristics and errors: textbook], ed. by dr. of eng. sc., prof. V.M. Soldatkina. Kazan': Izdvo
Kazan. gos. tekhn. un-ta, 2014, 526 p.
6. Ledyaev V.V., Sobolev V.I. Matematicheskie aspekty teorii aerometrii VSP [Mathematical
aspects of the theory of aerometry VSP], Pribory i sistemy. Upravlenie, kontrol', diagnostika
[Instruments and systems. Management, control, diagnostics], 2000, No. 8, pp. 50-54.
7. Ivanov Yu.P., Sinyakov A.N., Filatov I.V. Kompleksirovanie informatsionno-izmeritel'nykh
ustroystv letatel'nykh apparatov: ucheb. posobie [Integration of information and measuring devices
of aircraft: a textbook], ed. by V.A. Bodner. Leningrad: Mashinostroenie, 1984, 207 p.
8. Sapogov V.A., Anisimov K.S., Novozhilov A.V. Otkazobezopasnaya vychislitel'naya sistema
dlya kompleksnykh sistem upravleniya polѐtom letatel'nykh apparatov [Fault-safe computing
system for integrated flight control systems of aircraft], Tr. MAI» [Trudy MAI], Issue No. 45.
9. Ponomarev A.I., Sorokin M.Yu. Kompleksirovanie rezul'tatov izmereniya vysotno-skorostnykh
parametrov v sisteme [Integration of the measurement results of altitude-speed parameters in
the system], Avtomatizatsiya protsessov upravleniya [Automation of control processes], 2021,
No. 2 (64), pp. 18-22.
10. Zadorozhniy A.A. Opredelenie dostovernosti parametra pribornoy skorosti na osnove
dinamicheskikh kharakteristik ob"ekta, poluchennykh v khode letnykh ispytaniy [Determination
of the reliability of the instrument speed parameter based on the dynamic characteristics of
the object obtained during flight tests], Avtomatizatsiya protsessov upravleniya [Automation of
control processes], 2020, No. 1 (59), pp. 113-120.
11. Sukhomlinov D.V., Medved' A.N. O kompleksirovanii dannykh v informatsionnoupravlyayushchey
sisteme letatel'nogo apparata [On data aggregation in the information and
control system of an aircraft], Dvigatel' [Engine], 2014, No. 5 (95), pp. 38-41.
12. Alekseev N.V., Vozhdaev E.S., Kravtsov V.G. i dr. Sistemy izmereniya vozdushnykh signalov
novogo pokoleniya [New generation air signal measurement systems], Aviakosmicheskoe
priborostroenie [Aerospace instrumentation], 2003, No. 8, pp. 31-36.
13. Aleksanin N.D., Efremenkov I.V. Modelirovanie obledeneniya priemnika vozdushnykh
davleniy s pomoshch'yu programmnogo kompleksa FENSAP-ICE [Modeling of icing of an air
pressure receiver using the FENSAP-ICE software package], Uchenye zapiski UlGU. Ser.
Matematika i informatsionnye tekhnologii [Scientific notes of UlSU. Ser. Mathematics and information
technology], 2020, No. 1, pp. 1-5.
14. Kilic U., Unal G. Aircraft air data system fault detection and reconstruction scheme design,
Aircraft Engineering and Aerospace Technology, Vol. 93, No. 6, pp. 1104-1114.
15. Fabio Balzano, Mario L. Fravolini, Marcello R. Napolitano. Stéphane d’Urso, Michele
Crispoltoni, Giuseppe del Core. Air Data Sensor Fault Detection with an Augmented Floating
Limiter, Hindawi International Journal of Aerospace Engineering, Vol. 2018, pp. 1-16.
16. Australian Government. Air data failure involving Airbus A330-243, ATSB Transport Safety Report.
2016. Available at: https://www.atsb.gov.au/media/5770344/ao2013212-final_report.pdf (accessed
10 December 2021).
17. Tyulevin S.V. Analiz otkazov elementov bortovykh radioelektronnykh sredstv [Analysis of
failures of elements of avionics]. Samarskiy natsional'nyy issledovatel'skiy universitet im.
S.P. Koroleva.
18. Veligosha A.V. Analiz problem tsifrovoy fil'tratsii i puti ikh resheniya [Analysis of digital filtering
problems and ways to solve them], Mater. konferentsii MES-2016. Rossiya, Moskva,
10.2016. IPPM RAN [Materials of the MEA-2016 conference. Russia, Moscow, 10.2016.
IPPM RAS], pp. 195-201.
19. Bardin B.V. Bystryy algoritm mediannoy fil'tratsii [Fast median filtering algorithm], Nauchnoe
priborostroenie [Scientific instrumentation], 2011, Vol. 21, No. 3, pp. 135-139.
20. Kozlov D.S., Tyumentsev Yu.V. Neyrosetevye metody obnaruzheniya otkazov datchikov i
privodov letatel'nogo apparata [Neural network methods for detecting failures of sensors and
drives of an aircraft], Tr. MAI [Trudy MAI], Issue No. 52.
