Precision of FLEET Velocimetry using High-Speed CMOS Camera Systems

Autor: Brett F. Bathel, Paul M. Danehy, Nathan D. Calvert, Christopher J. Peters, Richard B. Miles, Naibo Jiang
Rok vydání: 2015
Předmět:
Zdroj: 31st AIAA Aerodynamic Measurement Technology and Ground Testing Conference.
Popis: Femtosecond laser electronic excitation tagging (FLEET) is an optical measurement technique that permits quantitative velocimetry of unseeded air or nitrogen using a single laser and a single camera. In this paper, we seek to determine the fundamental precision of the FLEET technique using high-speed complementary metal-oxide semiconductor (CMOS) cameras. Also, we compare the performance of several different high-speed CMOS camera systems for acquiring FLEET velocimetry data in air and nitrogen free-jet flows. The precision was defined as the standard deviation of a set of several hundred single-shot velocity measurements. Methods of enhancing the precision of the measurement were explored such as digital binning (similar in concept to on-sensor binning, but done in post-processing), row-wise digital binning of the signal in adjacent pixels and increasing the time delay between successive exposures. These techniques generally improved precision; however, binning provided the greatest improvement to the un-intensified camera systems which had low signal-to-noise ratio. When binning row-wise by 8 pixels (about the thickness of the tagged region) and using an inter-frame delay of 65 microseconds, precisions of 0.5 meters per second in air and 0.2 meters per second in nitrogen were achieved. The camera comparison included a pco.dimax HD, a LaVision Imager scientific CMOS (sCMOS) and a Photron FASTCAM SA-X2, along with a two-stage LaVision HighSpeed IRO intensifier. Excluding the LaVision Imager sCMOS, the cameras were tested with and without intensification and with both short and long inter-frame delays. Use of intensification and longer inter-frame delay generally improved precision. Overall, the Photron FASTCAM SA-X2 exhibited the best performance in terms of greatest precision and highest signal-to-noise ratio primarily because it had the largest pixels.
Databáze: OpenAIRE