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Processing of digital experimental data has become a key part of virtually every research project. As sensors get both more diverse and cheaper, the amount of information to be handled greatly increases as well. Especially fatigue failure modelling requires by its nature large numbers of samples to be processed, and visualised. The presented paper is based on analysis of load data gathered in flight on an unmanned aircraft. A few versions of an analysis program were developed and considered for the use case. Each implementation included ingesting the data files, creating transfer arrays and the “rain flow counting” algorithm. For the sake of the ease of use and functionality, the version based on Python programming language was selected for presentation. Short development iteration time of this approach allowed gaining new insights by tweaking parameters to better represent actual acquired data. Both the results and the software itself can be easily viewed in a web browser and run with modifications without the need to install any software locally. The developed software is meant as a demonstration of capabilities of open source computation tools dedicated to aerospace and mechanical engineering research, where they remain relatively unpopular.
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