Load spectra of a light unmanned aircraft – data recording frequencies and resulting measurement variations

• Autorzy: Rodzewicz Miroslaw

Identyfikatory

DOI

10.24425/ame.2024.151335

• Języki publikacji: EN

Abstrakty

EN

The article focuses on the load spectrum of a lightweight unmanned aircraft. It examines the impact of load signal sampling frequency on the load spectrum derived from the load signal. The flight sessions followed two scenarios: a maneuvering flight causing a wide range of load factor variations and a calm photogrammetric flight. The recorded load signals from two types of sensors were initially rescaled into load factor time series, with an optional signal smoothing process. These series were then downsampled by selecting every nth term, resulting in load factor sequences recorded at a lower frequency. Next, all sequences were transformed into sequences of local extremes of the Load Levels, resulting from quantifying the operational load variability into 32 intervals. Two options were considered: without filtering or with filtering of sequential pairs of terms generating small Load Level increments. Subsequently, the Rainflow Counting algorithm was applied, producing 32×32 load half-cycle arrays. Based on these arrays, incremental load spectra were calculated. The study provides a detailed comparison of load spectra for different load signal sources and recording frequencies. Additionally, calculations of the fatigue life of a structural element subjected to various load spectra were performed, leading to the formulated conclusions.

Słowa kluczowe

EN

load spectra; unmanned aircraft; signal frequency; fatigue life

PL

bezzałogowy statek powietrzny; częstotliwość sygnału; żywotność zmęczeniowa

• Wydawca: Komitet Budowy Maszyn PAN
• Czasopismo: Archive of Mechanical Engineering
• Rocznik: 2024
• Tom: LXXI, nr 4
• Strony: 525--545
• Opis fizyczny: Bibliogr. 23 poz., fot., rys., wykr.

Twórcy

autor

Rodzewicz Miroslaw

• Warsaw University of Technology, Warsaw, Poland

• https://orcid.org/0000-0003-1424-8624

Bibliografia

• [1] S.K. Chaturvedi, R. Sekhar, S. Banerjee, and H. Kamal. Comparative review study of military and civilian unmanned aerial vehicles (UAVs). INCAS Bulletin, 11(3):181–182, 2019. doi: 10.13111/2066-8201.2019.11.3.16
• [2] P. Radoglou-Grammatikis, P. Sarigiannidis, T. Lagkas, and I. Moscholios. A compilation of UAV applications for precision agriculture. Computer Networks, 172:107148, 2020. doi: 10.1016/j.comnet.2020.107148.
• [3] S.A.H. Mohsan, N.Q.H. Othman, Li Y, M.H. Alsharif, and M.A. Khan. Unmanned aerial vehicles (UAVs): practical aspects, applications, open challenges, security issues, and future trends. Intelligent Service Robotics. 16(1):109–137, 2023. doi: 10.1007/s11370-022-00452-4.
• [4] K. AL-Dosari,Z. Hunaiti, and W. Balachandran. Systematic review on civilian drones in safety and security applications.Drones 7(3): 210, 2023. doi: 10.3390/drones7030210.
• [5] T. Goetzendorf-Grabowski, A. Tarnowski, M. Figat, J. Mieloszyk, and B. Hernik. Lightweight unmanned aerial vehicle for emergency medical service – Synthesis of the layout. Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, 235(1):5– 21, 2021. doi: 10.1177/0954410020910584.
• [6] W. Stecz and P. Kowaleczko. Designing operational safety procedures for UAV according to NATO architecture framework. In Proceedings of the 16th International Conference on Software and Data Technologies, pages 135–142, 2021.
• [7] W. Wang, X. Guo, Y. Liu, A. Tang, and Q. Yang. Factors affecting unmanned aerial vehicles’ unsafe behaviors and influence mechanism based on social network theory. Transportation Research Record, 2677(5):1030–1045, 2023. doi: 10.1177/03611981221138782.
• [8] E.S. Jahanpour, B. Berberian, J.P. Imbert, and R.N. Roy. Cognitive fatigue assessment in operational settings: a review and UAS implications. IFAC-PapersOnLine, 53(5):330–337, 2020. doi: 10.1016/j.ifacol.2021.04.188.
• [9] M. Krichen and A. Mihoub. Unmanned aerial vehicles communications security challenges: a survey. In: M. Abdelkader, A. Koubaa (eds) Unmanned Aerial Vehicles Applications: Challenges and Trends. Springer, Cham. 2023. doi: 10.1007/978-3-031-32037-8_12.
• [10] M. Noor, Z. Fang, and Y. Cao. Fatigue life estimation of fixed-wing unmanned aerial vehicle engine by grey forecasting. Measurement and Control, 54(5-6):799–810, 2021. doi: 10.1177/0020294020915215.
• [11] A. ElSaid, D. Adjekum, J. Nordlie, and F.A. El Jamiy. A test-bed for measuring UAS servo reliability. Aerospace, 6(9):96, 2019. doi: 10.3390/aerospace6090096.
• [12] A. Kurnyta, W. Zielinski, P. Reymer, K. Dragan, and M. Dziendzikowski Numerical and ex- perimental UAV structure investigation by pre-flight load test. Sensors, 20(11):3014, 2020. doi: 10.3390/s20113014.
• [13] S.N. Satish Kumar, T.L. Rakesh Babu, and M. Ramesh. Fatigue and vibrational analysis of drone by using composite and mmc alloys for military applications. International ResearchJournal of Engineering and Technology (IRJET), :7(7):5650–5665, 2020.
• [14] G.D. Jin, L.B. Lu, L.X. Gu, J. Liang, and X.F. Zhu. Fatigue life of UAV airframe based on damage coefficient. Advanced Materials Research, 709:358–362, 2013. doi: 10.4028/www.scientific.net/AMR.709.358.
• [15] J.E. Locke, H.W. Smith, E.A. Gabriel, and T. DeFlore. General Aviation Aircraft-normal Acceleration Data Analysis and Collection Project. Report No DOT/FAA/CT-91/20, University of Kansas Flight Research Laboratory, 1993.
• [16] M. Rodzewicz, D. Głowacki , and J. Hajduk. Comparative analysis of the load spectra recorded during photogrammetric missions of lightweight UAVs in tailless and conventional configurations. Fatigue of Aircraft Structures, 2022(14):114-134, 2022. doi: 10.2478/fas-2022-0009.
• [17] L.E. Clay, R.L. Dickey, M.S. Moran, K.W. Payauys, andT.P. Severyn. Statistical analysis of general aviation VG-VGH data. NASA Report No. NASA-CR-132531 prepared under Contract No. NAS1-12389 by Technology Incorporated Instruments and Control Division, Dayton, Ohio, 1974.
• [18] H. Millwater, J. Ocampo, G. Singh, H. Smith, and E. Meyer. Probabilistic Structural Risk as- sessment and risk management for small airplanes. Report No. DOT/FAA/AR-11/14, sponsored by U.S. Department of Transportation, Federal Aviation Administration, Kansas City, 2017.
• [19] M.S. Łukasiewicz. Load spectrum analysis with open source software - an application example. Fatigue of Aircraft Structures, 2021(13):17–30, 2021. doi: 10.2478/fas-2021-0003.
• [20] S. Gajek. Automation of aircraft fatigue life estimation. Fatigue of Aircraft Structures, 2022(14):83–103, 2022. doi: 10.2478/fas-2022-0007.
• [21] H. Kossira and W. Reinke. Entwicklung eines Belastungskollektivs fur leichte Motorflugzeuge aus den Beanspruchungsmessungen an einem Segelflugzeug (Development of a load spectrum for light aircraft based on stress measurements from a glider). IFL-IB 86-04, TU Braunschweig, 1986. (in German).
• [22] M. Rodzewicz. Investigation of the Glider Load Spectra. Technical Soaring, 31(1):2–12, 2007.
• [23] Engineering and Manufacturing Division, Airframe Branch. Fatigue evaluation of wing and associated structure on small airplanes. Report No. AFS-120-73-2, sponsored by Department of Transportation, Federal Aviation Administration, Washington, DC, 1973.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025)