A laser sheet self-calibration method for scanning PIV

Abstract

Knowledge of laser sheet position, orientation, and thickness is a fundamental requirement of scanning PIV and other laser-scanning methods. This paper describes the development and evaluation of a new laser sheet self-calibration method for stereoscopic scanning PIV, which allows the measurement of these properties from particle images themselves. The approach is to fit a laser sheet model by treating particles as randomly distributed probes of the laser sheet profile, whose position is obtained via a triangulation procedure enhanced by matching particle images according to their variation in brightness over a scan. Numerical simulations and tests with experimental data were used to quantify the sensitivity of the method to typical experimental error sources and validate its performance in practice. The numerical simulations demonstrate the accurate recovery of the laser sheet parameters over range of different seeding densities and sheet thicknesses. Furthermore, they show that the method is robust to significant image noise and camera misalignment. Tests with experimental data confirm that the laser sheet model can be accurately reconstructed with no impairment to PIV measurement accuracy. The new method is more efficient and robust in comparison with the standard (self-) calibration approach, which requires an involved, separate calibration step that is sensitive to experimental misalignments. The method significantly improves the practicality of making accurate scanning PIV measurements and broadens its potential applicability to scanning systems with significant vibrations.