Systematic interrogation area optimization in large-scale particle image velocimetry using information entropy
Journal
Journal of Hydro-environment Research
Journal Volume
60-61
Start Page
100665
ISSN
15706443
Date Issued
2025-06-30
Author(s)
Abstract
This study introduces an Information Entropy-based method for determining optimal Interrogation Area (IA) size in Large-Scale Particle Image Velocimetry (LSPIV), a crucial factor for enhancing non-contact surface flow measurement accuracy. By analyzing entropy in particle images across variable IA sizes, we assessed 48 synthetic and 2 experimental flow scenarios. The method demonstrated superior accuracy, achieving Vector Correlation Coefficients up to 1.916 and Root Mean Square Errors as low as 1.113 and 2.444 pixels/frame in synthetic cases, and accuracy rates of 90.89% and 97.23% in experimental cases, rivaling traditional empirical approaches. Incorporation of surrounding pixel intensity data resulted in a 48–52% improvement in particle information quantification. Expanding the range of IA sizes from 5 to 8 significantly reduced measurement errors to below 0.7 and 1.0 pixels/frame. These findings suggest that the Information Entropy method offers a robust framework for systematic optimization of IA selection in LSPIV, promising enhanced measurement accuracy through further refinement of convergence criteria and noise reduction techniques.
Subjects
Discharge Measurement
Information Entropy
Interrogation Area
Large-Scale Particle Image Velocimetry
Publisher
Elsevier B.V.
Type
journal article