The present thesis has been carried out to investigate a data processing method to obtain statistical correlations and spectra of turbulent flow field using randomly bursted data from the counter type LDV processor.
The raw signal from the LDV counter processor varies discontinuously stepwise with random duration, and only the data points at the instance of each step burst, or the starting point of each step represent the correct instantaneous velocities.
In this study, the autocorrelation function $R_{uu}(\tau)$ was numerically calculated by using such valid data set only and then the power spectrum was obtained by taking the Fourier transform of the resultant correlation. In order to verify the present method, the correlation function and spectrum were compared with those obtained by the hot-wire anemometer signals. The correlation function by the LDV signal remains positive, whereas that of the hot-wire signals becomes negative for large $\tau$. And the power spectrum based on the LDV signal shows slightly higher energy constant in high frequency range compared with that of hot-wire signals. This implies that the data rate is not large enough so that the aliasing problem arises.
In order to overcome such aliasing problem, Buchhave's weighting is required in the calculation procedure of the correlation function.
