Development of a stereoscopic particle image velocimetry system for fullscale room air flow studies. Part I: algorithms and validation

摘要

One of the challenges in indoor air quality studies is to measure three-dimensional (3-D) air velocity profiles in an airspace so that the nature of airflow can be better understood and appropriate ventilation systems can be designed. There is muchdispute over a variety of computational fluid dynamics (CFD) models, primarily because there is a lack of credible data to validate those models. The objective of this study was to develop a Stereoscopic Particle Imaging Velocimetry (SPIV) system suitable for measurement of full-scale room 3-D airflow. The SPIV method is based on the principle of parallax to extract a third (z-direction), out-of-plane velocity component using two cameras. Previous research showed that a third camera is necessary to distinguish the flow direction. We have developed a new 3-D algorithm that only requires two cameras to acquire three velocity components (x, y, z) and flow directions. This paper discusses the algorithm of this new stereoscopic approach. The two-camera approach is expected to greatly simplify the image acquisition and data processing, and improve the accuracy by eliminating the error caused by the third camera image. In this new 3-D SPIV setup, two cameras are placed at different angles to view the illuminated plane and to capture particle displacement images that also contain the influence of the third velocity component. The parallax effect allows us to obtain different two-velocity component vector maps from each camera. The differences between the twoimages arise from the third, out-of-plane velocity component and the geometrical configuration of the two cameras. After image calibration, this third velocity component can be calculated. The two cameras will be set at different exposure time thus acquiring different length of streaks for the same particle path. The differences of the exposure then can used to distinguish the flow directions.