Parametric Study to Improve Subpixel Accuracy of Nitric Oxide Tagging Velocimetry with Image Preprocessing

Ravi Teja Vedula, Mayank Mittal, Harold Schock

Research output: Contribution to journalArticle

Abstract

Biacetyl phosphorescence has been the commonly used molecular tagging velocimetry (MTV) technique to investigate in-cylinder flow evolution and cycle-to-cycle variations in an optical engine. As the phosphorescence of biacetyl tracer deteriorates in the presence of oxygen, nitrogen was adopted as the working medium in the past. Recently, nitrous oxide MTV technique was employed to measure the velocity profile of an air jet. The authors here plan to investigate the potential application of this technique for engine flow studies. A possible experimental setup for this task indicated different permutations of image signal-to-noise ratio (SNR) and laser line width. In the current work, a numerical analysis is performed to study the effect of these two factors on displacement error in MTV image processing. Also, several image filtering techniques were evaluated and the performance of selected filters was analyzed in terms of enhancing the image quality and minimizing displacement errors. The flow displacement error without image preprocessing was observed to be inversely proportional to SNR and directly proportional to laser line width. The mean filter resulted in the smallest errors for line widths smaller than 9 pixels. The effect of filter size on subpixel accuracy showed that error levels increased as the filter size increased.

Original languageEnglish (US)
Article number6159802
JournalJournal of Combustion
Volume2017
DOIs
StatePublished - 2017

Profile

marking
filters
Velocity measurement
Health Physics
Linewidth
Halogens
preprocessing
phosphorescence
engines
signal to noise ratios
cycles
Phosphorescence
Signal to noise ratio
Engines
Lasers
Guanosine
Cytotoxins
Alkylation
air jets
nitrous oxides

ASJC Scopus subject areas

  • Chemical Engineering(all)
  • Fuel Technology
  • Condensed Matter Physics
  • Energy Engineering and Power Technology

Cite this

Parametric Study to Improve Subpixel Accuracy of Nitric Oxide Tagging Velocimetry with Image Preprocessing. / Vedula, Ravi Teja; Mittal, Mayank; Schock, Harold.

In: Journal of Combustion, Vol. 2017, 6159802, 2017.

Research output: Contribution to journalArticle

Vedula, Ravi Teja; Mittal, Mayank; Schock, Harold / Parametric Study to Improve Subpixel Accuracy of Nitric Oxide Tagging Velocimetry with Image Preprocessing.

In: Journal of Combustion, Vol. 2017, 6159802, 2017.

Research output: Contribution to journalArticle

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