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EN
The purpose of this article is to present the results of the investigation regarding the differences of the load spectra of two unmanned fixed-wing aircraft performing photogrammetry missions: X-8 (flying wing) and PW-ZOOM (conventional configuration). The focus was on the analysis of a number of load cycles for various load increments within the range of the operational loads. The load spectra were determined using the acceleration signal recorded in the autopilot logs as an input. This signal was transferred to the chain of local extreme values scaled in the form of discrete load levels, and then the transfer arrays were derived with use of the rainflow counting algorithm. On this basis, the incremental load spectra were determined for each flight. These load spectra were subjected to statistical analyses to determine the load spectra representative of the flight sessions in a few ways between non-conservative (i.e., focused on average load histories) and conservative (i.e., focused on the worst load histories observed during the flight session). Finally, the fatigue life was calculated by having the structural element of the assumed fatigue properties subjected to the load spectra of both airplanes. A large (exceeding one order of magnitude) difference in the number of load cycles for larger load increments in the analyzed load spectra was shown. This difference is related to the different dynamic characteristics of the two aircraft, in particular the gust response. As a result, there is a several-fold difference in fatigue life.
EN
The article presents the analyses of the flights carried out the by the Unmanned Aerial Vehicle (UAV) named PW-ZOOM used to perform a photogrammetric mission and monitoring of fauna in Antarctic areas. The analyses focus on the deviations of the optical axis of the photo-camera which occurred during photogrammetric flights carried out on the same route but during several Antarctic expeditions performed in subsequent years (2014 and 2015). The results were subjected to correlation tests with weather conditions (wind speed and variability). The basis for these analyses are the data from the onboard signal recorder integrated with an autopilot.
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