Post Processing

SNR and correlation are reported in the data file because they are extremely useful when judging data quality. It is important to assess overall data quality by looking at velocity, SNR, and correlation time series and histograms before attempting to interpret the data.

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Symptoms

When looking at correlation and SNR, we recommend looking at each beam individually rather than an average across two or more beams. Problems can occur in only one beam and averaging the data across beams may obscure potential problems.

Correlation & SNR

1. Correlation looked good during data collection, but there are several range cells with poor correlation.

Low correlation in only a few range cells is symptomatic of weak spots. Unfortunately, there isn't a way to correct this data in post processing except by eliminating it. Please see the Configuration Guide for how to eliminate weak spots before recording data.

2. SNR looked good during data collection, but there are several range cells with much different SNR (higher or lower).

This is also symptomatic of weak spots or an obstruction (e.g. an object) within the beam. Weak spots will generally see higher SNR because the strong boundary echo is causing problems, but may be associated with lower SNR depending on the nature of interference.

A beam obstruction will typically produce a strong echo and high SNR. It may create an acoustic shadow resulting in low amplitude and SNR in bins behind the object as well.

Weak spots can not be corrected in post processing. Removing biased velocities associated with an object in the beam is possible by determining which range cells are affected and discarding them from analysis.

Velocity

1. Mean velocity profiles don't look good even though correlation and SNR are high.

It is important to assess data quality and perform some basic quality control on a dataset before attempting to interpret the results. The left plot above was made by averaging the unscreened velocity data. The right plot above is the same velocity profile after some basic quality control, showing a smoother shape with the sharp peaks near 0.525 and 0.625 m removed.

At minimum, discarding very low correlation measurements (<40%, adjusted as needed based on data quality) and very low SNR values (<15 dB, again adjusted as needed based on data quality). An outlier filter to remove data which is statistically different than expectations will also help improve the quality of a dataset. Histograms can be quite helpful in determining the effectiveness of any quality control procedures implemented. The figure below shows the raw velocity data from a bin above before (black) and after (red) outlier screening.

2. Velocity time series are really spiky.

Note the spikey and unphysical nature of the velocities. The mean appears to be around 0.50 m/s while there are spikes with magnitudes near 1.5 m/s. This can be caused by many problems, e.g. weak spots, a too small Velocity Range, low SNR.

The velocity spikes can be removed in post processing using an outlier filter. In this case, a simple hard threshold discarding velocities > 1 m/s and < 0 m/s will probably work.

3. Velocity changes sign when it shouldn't.

This is caused by aliasing in beam velocities when the maximum measurable velocity is exceeded. In the above plot, the solid lines indicate the ambiguity velocity for this instrument setup. Velocities larger than the ambiguity velocity wrap around to the opposite sign.

To avoid this during data collection, the Velocity Range needs to be set larger than the expected velocities (see Configuration Issues). To aid users in selecting an appropriate Velocity Range, the Vectrino II Configuration dialog reports the horizontal and vertical velocity ranges.

Correcting phase wraps is possible. It involves identification of wrapped velocities and correcting the measured velocity using the reported ambiguity velocity. For details on how to unwrap velocities please read the Pulse Coherent Primer and the following Nortek Forum threads:

• ambiguity errors
• ambiguity jumps in the Aquadopp HR data
• ambiguity velocity calculation

4. Velocity spectra show a very large spike at one or more frequencies.

This is typically caused by a vibration in the stem for fixed stem probe heads or the mount a cabled probe head is attached to. Wave impact, high flow rates, loose mountings, or vibrations from nearby equipment will generate vibrations in the probe head.

Typical vibrations from instrument mountings will have a very sharp peak and occur for a very narrow frequency band. Fixed stem probes will often see a peak around 20 Hz. The impact on measurements will depend on what flow parameters are of interest.

The Vectrino II software provides real time velocity spectra which can help diagnose and correct vibrations. The real time spectra are accessed through the Display time series data toolbar icon . Note real time spectra and imaging can not be used at the same time.