Abstract
This work has the goal of experimentally determining the rotational moment of inertia of a wind turbine rotor blade and quantifying the uncertainty of this inertia measurement. Rotational inertia is an important parameter for modeling wind turbine power capacity due to its great influence on powertrain performance. There is a directly proportional relationship between the inertia and rotational power machines. Among commonly used experimental methods, the acceleration–deceleration method was conducted for rotational moment of inertia measurement of a commercial HAWT (Horizontal-Axis Wind Turbines) iSTA Breeze® i-500 model. As recommended by GUM Supplement 1, the Monte Carlo method was used to estimate the measurement uncertainty related to wind turbine rotational inertia. Experimental acceleration–deceleration tests were performed using the motion capture software Tracker to collect angular position data by video capturing the rotational motion of a wind turbine attached to a falling mass, which is rolled to the rotor axis. After appropriate data processing, the experimental uncertainty measure was obtained by the Monte Carlo method. A statistical analysis was implemented to validate the measurement model via comparisons with other methods. The main finding of the present article is the experimental validation, according to ISO-GUM, of the experimental acceleration–deceleration methodology to determine the rotational inertia of equipment, with low uncertainty, without the need to dismantle it, using simple low-cost sensors. The rotational moment of inertia obtained was compared to trifilar pendulum method with a discrepancy between the results of less than \(0.7\%\) and a confidence interval of \(95.1\%\).
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The authors would like to thank CNPq and MCTI, process number 406895/2013-9, and FAPDF, process number 0193. 001359/2016, for the financial support.
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Santana, R.U., Reis, S.F.S., Morais, M.V.G. et al. GUM-S1 to Evaluate Rotational Inertia Uncertainty Obtained by Acceleration–Deceleration Tests. Iran J Sci Technol Trans Civ Eng (2024). https://doi.org/10.1007/s40996-023-01336-y
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DOI: https://doi.org/10.1007/s40996-023-01336-y