Theoretical description of PIV measurement errors

• Autorzy: Cameron Stuart Murray

Identyfikatory

DOI

10.1007/s11600-022-00901-9

• Języki publikacji: EN

Abstrakty

EN

Expressions for particle image velocimetry (PIV) mean error and error variance are derived for iterative deformation method algorithms. The analytical expressions explicitly account for the role of in- and out-of-plane displacements, displacement gradients, particle image diameter, fill factor of the imaging sensor, image noise, light sheet intensity distribution, seeding particle concentration, the interpolation function used to deform PIV images, and the interrogation window size and weighting window. The newly derived analytical expressions show good agreement with errors estimated using synthetic image sets.

Słowa kluczowe

EN

particle image velocimetry; measurement error; open channel flow; velocity measurement

PL

anemometria obrazowa; błąd pomiaru; przepływ w kanale otwartym; pomiar prędkości

• Wydawca: Instytut Geofizyki PAN ; Springer
• Czasopismo: Acta Geophysica
• Rocznik: 2022
• Tom: Vol. 70, no 5
• Strony: 2379--2387
• Opis fizyczny: Bibliogr. 16 poz.

Twórcy

autor

Cameron Stuart Murray

• School of Engineering, University of Aberdeen, Aberdeen, UK

• https://orcid.org/0000-0002-2333-5271

Bibliografia

• 1. Alexander BF, Ng KC (1991) Elimination of systematic error in subpixel accuracy centroid estimation. Opt Eng 30(9):1320–1331
• 2. Astarita T (2007) Analysis of weighting windows for image deformation methods in PIV. Exp Fluids 43(6):859–872
• 3. Astarita T, Cardone G (2005) Analysis of interpolation schemes for image deformation methods in PIV. Exp Fluids 38(2):233–243
• 4. Bendat J, Piersol A (2000) Random data analysis and measurement procedures. IOP Publishing
• 5. Cameron SM (2011) PIV algorithms for open-channel turbulence research: accuracy, resolution and limitations. J Hydro Environ Res 5(4):247–262
• 6. Eckstein A, Vlachos PP (2009) Assessment of advanced windowing techniques for digital particle image velocimetry (DPIV). Meas Sci Technol 20(7):075402
• 7. Foucaut J, Miliat B, Perenne N, Stanislas M (2004) Characterization of different PIV algorithms using the EUROPIV synthetic image generator and real images from a turbulent boundary layer, Particle Image Velocimetry: Recent Improvements, 163–185. Springer
• 8. Kim BJ, Sung HJ (2006) A further assessment of interpolation schemes for window deformation in PIV. Exp Fluids 41(3):499–511
• 9. Nobach H, Bodenschatz E (2009) Limitations of accuracy in PIV due to individual variations of particle image intensities. Exp Fluids 47(1):27–38
• 10. Nogueira J, Lecuona A, Rodriguez P (1999) Local field correction PIV: on the increase of accuracy of digital PIV systems. Exp Fluids 27(2):107–116
• 11. Nogueira J, Lecuona A, Rodriguez P (2001) Identification of a new source of peak locking, analysis and its removal in conventional and super-resolution PIV techniques. Exp Fluids 30(3):309–316
• 12. Raffel M, Willert CE, Wereley S, Kompenhans J (2013) Particle image velocimetry: a practical guide. Springer
• 13. Scarano F, Riethmuller ML (2000) Advances in iterative multigrid PIV image processing. Exp Fluids 29(1):S051–S060
• 14. Smith S (2013) Digital signal processing: a practical guide for engineers and scientists. Elsevier
• 15. Timmins BH, Wilson BW, Smith BL, Vlachos PP (2012) A method for automatic estimation of instantaneous local uncertainty in particle image velocimetry measurements. Exp Fluids 53(4):1133–1147
• 16. Westerweel J (2000) Theoretical analysis of the measurement precision in particle image velocimetry. Exp Fluids 29(1):S003-S012

Uwagi

PL

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).