PIVlab - Digital Particle Image Velocimetry Tool for MATLAB

Soon, PIVlab will be more than just a PIV post-processing tool! I am currently implementing some additional features, so that PIVlab can control our laser and the camera directly. I am doing this, because we are using PIVlab for commercial services, and I want to have a PIV setup that is really handy in practice. I also developed a small synchronizer (see picture) that controls our Quantel Evergreen 200 PIV laser and synchronizes it with the ILA5150 PIV.Nano double-image camera. And this synchronizer (which is wireless by the way) is also controlled directly from PIVlab. Everything is as simple as it can get: Press a single button to start camera and laser, images will be saved to your hard disk and directly loaded into PIVlab. Awesome! If you want to have this too for your research, you'll need the PIVlab-SimpleSync ( Optolution.com ), the ILA5150 PIV.Nano camera, and a double-puls laser (e.g. Quantel EVG00070). The PIVlab-SimpleSync wireless synchronizer controls Lamp 1&2, Q...

PIVlab v2.30 features 'multipass window deformation ensemble correlation'. This type of correlation has been introduced by Santiago et al.  in 1998. It is especially helpful in micron-resolution particle image velocimetry (micro-PIV, µPIV), as it can deal with very low seeding densities (see below). Ensemble correlation PIV should be used if you want to analyze a steady flow that has a low seeding density. You need to record a large number of images to have the full benefit of ensemble correlation in PIVlab. The yellow lines show the interrogation areas (IAs). The white dots are particles, and you can see that there are hardly any particles in the IAs. The general rule of thumb for PIV is that there should be 5 - 15 particles per IA. This is clearly not the case here. Standard PIV algorithms will fail. In order to get a better result, you would have to increase the size of the IAs dramatically. With ensemble correlation, PIVlab analyzes a series of sparsely seed...

New features: The user can now load time-resolved masks instead of single masks The user can now select the color of the color legend label The PIV settings are now checked automatically, and a warning is given if unusual parameters were selected  Bug fixes: Loading session files from older PIVlab versions is now possible ( forum post ) Fixed bug where the tools panel showed slightly incorrect data sometimes ( forum post ) Fixed bug where a warning message was displayed too often ( forum post )

The new PIVlab release supports an advanced correlation technique (I want to thank Kyle Lynch for the discussion about this). Using a multipass window deformation technique, significantly reduces noise in the data. The maximal vector resolution can also be increased and peak-locking is reduced a lot. PIV images that have a low quality can now be processed with higher precision (see the video at the bottom). Additionally, it is possible to draw some streamlines and streamline rakes, this is useful for adding some qualitative information to the analyses. The image export procedure has also been improved, it is possible to export the displayed result at any desired resolution (only limited by the RAM on your computer). Standard direct cross-correlation (DCC) analysis using a 14*14px interrogation area with 50% overlap: Multipass, window-deformation using a 6*6px interrogation area with 50% overlap in the final pass: Streamlines: Processing low quality images: The new...

PIVlab is now available for download (see right hand side of this blog for the link). Here is a recent video showing a standard PIV analysis:

Here are some images that were analyzed with PIVlab. Click for higher resolution.

Particle Image Velocimetry (PIV) is a method to measure space- and time-resolved flow velocities in fluids. I will work a lot with this method during my PhD. In the past, I got to know some commercial PIV software systems (e.g. " Flowmanager " and " VidPIV "), but I was never totally happy with these. I also had a look at several free PIV systems (mostly based on MATLAB ), but these were not suitable for my demands. Since I am going to spend a lot of time with PIV calculations, E.J. Stamhuis and me recently developed a PIV software (called PIVlab) that takes advantage of numerous MATLAB features. I also created an extensive GUI for the software which makes it easy to get results with ease.