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Advanced techniques
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KIT GPUSGPU Development Kit: Complete your SITAU Phased-Array system with the power of GPU’s


SITAU GPUs package was developed for interfacing DASEL’s technology with this powerful processing hardware using PyOpenCL, the most extended multi-platform programming language. Acquired data can be easily handled and plotted using Python packages, such as, Scipy, Numpy, etc. 

GPU muelle




SITAU Python’s package also includes innovative procedures for 3D reconstruction at high frame rates. This novel 3D imaging modality combines two techniques: Phased Array (PA) and Synthetic Aperture Focusing (SAFT), to get an accurate representation and quantification of flaws. The method uses conventional linear PA probes and a mechanical scanning to inspect the whole volume of the component with high resolution in all axes.



On SITAU Python’s package you will find a complete set of example functions for ultrasonic imaging. These functions were used to obtain the 3D image of a “spring” showed on the right:


- Ultrasonic data was captured on SITAU-111-84D Full Parallel Phased Array system with 128 active channels using a Python script.

- Image reconstruction was performed on a GPU platform using PyOpenCL.

- Visualization was carried out on Mavayi embedded on Python.


You can use any Python IDE for Eclipse if you are familiarized with these tools and keep your project organized. These tools also provide many other features for authoring, modifying, compiling, deploying and debugging your software. 3D algorithms technical features



• Easy integration on your Python code

• Flexible hardware platform selection (CPU or GPU).


• 3D algorithm tested at 6 frames of 97x1860 pixels per second.


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