An adaptive and predictive architecture for parameterised PIV algorithms

Abstract

Particle image velocimetry (PIV) algorithms aim at flow visualisation and dynamic flow measurement. All existing PIV techniques are computing intensive and are mainly used in critical conditions. For a given experimental environment, several parameters must be set so that PIV algorithm must be parameterised. A dedicated architecture is therefore unsuitable unless it is adaptive. The aim of this work is to prove that our generic and adaptive FPGA-based system for real-time PIV applications previously designed can easily be modified when some parameters vary. From a unique structure and library of resources, the designer adapts the architecture according to the parameters. Time and resource prediction models help the designer to find the most suitable structure before the implementation process and ensure only one implementation without feedback. As a result, the design flow is fast and reliable