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Acta Aeronautica et Astronautica Sinica ›› 2025, Vol. 46 ›› Issue (17): 131617.doi: 10.7527/S1000-6893.2025.31617

• Fluid Mechanics and Flight Mechanics • Previous Articles     Next Articles

Binocular speckle-based 3D-PSP technique and its applications in compressor cascade

Limin GAO(), Jun ZHANG, Bo OUYANG, Lei WANG   

  1. School of Power and Energy,Northwestern Polytechnical University,Xi’an 710072,China
  • Received:2024-12-05 Revised:2024-12-24 Accepted:2025-02-10 Online:2025-02-19 Published:2025-02-18
  • Contact: Limin GAO E-mail:gaolm@nwpu.edu.cn
  • Supported by:
    National Natural Science Foundation of China(92152301);National Science and Technology Major Project of China (J2019-Ⅱ-0016-0037)

Abstract:

Reconstruction of 3D pressure is crucial for Pressure-Sensitive Paint (PSP) measurements. We propose a method for three-dimensional pressure reconstruction combining binocular digital image correlation technology. The PSP measurement results are mapped to the reconstructed three-dimensional point cloud pixel by pixel to realize the three-dimensional pressure reconstruction without relying on the geometric parameters of the measured model. The method involves creating random speckle patterns on the PSP coating surface and using two cameras to synchronously capture PSP images. By integrating cross-correlation analysis and the principles of binocular stereo vision in PSP data processing, we achieve precise reconstruction of the 3D pressure on the measured surface. This method has been successfully applied to the 3D pressure measurement on the surface of a compressor cascade, and a comparative analysis with pressure tap data has shown that the relative deviation of the PSP data is within 1.2%. Furthermore, the accuracy of the measurement results has been verified by comparing the reconstructed 3D point cloud with a CAD model, with an average deviation of 0.17 mm.

Key words: pressure-sensitive paint, digital image correlation, binocular stereo vision, speckle, three-dimensional pressure reconstruction

CLC Number: