Author(s): J. P. Giovannettone
Linked Author(s):
Keywords: Coustic Doppler Velocimeter; Bubble column; Outliers; Water velocity; Z-score; Linear interpolation; Auto-regression; Auto-correlation; Turbulence
Abstract: Acoustic Doppler Velocimeters (ADVs) provide an efficient and economical way to measure water velocities. However, it has been shown in various studies that in the presence of air bubbles, measurements from the ADV may not be accurate. It has also been shown that much noise can occur in the velocity measurements due to bubbles. This study focuses on finding a way to deal with this noise. A method is developed to identify the inaccurate measurements, or outliers, using a z-score test. Each velocity value undergoes six statistical tests to determine whether it is an outlier. Once identified, each outlier needs to be eliminated and replaced by a value that fits the overall pattern of the velocity time series. This is accomplished through the combination of a linear interpolation model and an autoregressive model based on nearby velocity values. It is shown that this method does well at replacing the data to form a smooth time series with little or no noise. Several velocity time series measured at the Waterways Experiment Station (WES) in Vicksburg, MS, were analyzed. The method is demonstrated using measurements that were taken in and near a bubble plume in a cylindrical tank at a depth of 3 feet. This location was chosen because it contained more noise than all except two of the other measuring locations. Original and edited data are shown for this location, along with the autocorrelation functions of each for comparison.
Year: 2003