Abstract
The paper copes with the task of estimation of turbulent spectra of fluctuating velocities sensed with LDA (laser Doppler anemometer) in three set-ups of hard flow conditions. The flows of the three set-ups differ in terms of turbulence level, flow type, free flowing, etc. Datasets of the fluctuating velocities of each flow type present a specific configuration for data rate, velocity bias and noise level. An estimator combining a local normalising slotting technique with a cubic spline smoothing is used. Firstly, the estimator is validated on simulated data and then applied to real ones. The estimator results in a drastic reduction of scattering on the autocorrelation coefficient function (ACF) and allowing the evaluation of the spike, due to noise at zero time lags, for its removal afterwards. The estimator performance is discussed considering the velocity bias and the noise, and making comparisons with the results of classical estimators like standard, improved slotting techniques and classical techniques.
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