Extraction of a Weak Flow Field for a Multi-Rotor Unmanned Aerial Vehicle (UAV) Using High-Speed Background-Oriented Schlieren (BOS) Technology

To optically capture and analyze the structure and changes of the flow field of a weak airflow object with high accuracy, this study proposes novel weak flow field extraction methods based on background-oriented schlieren. First, a fine background pattern texture and a sensor network layout were designed to satisfy the requirement of weak flow field extraction. Second, the image displacement was extracted by calculating the correlation matrix in the frequency domain for a particle image velocimetry algorithm, and further calculations were performed for the density field using Poisson’s equation. Finally, the time series baseline stacking method was proposed to obtain the flow field changes of weak airflow structures. A combustion experiment was conducted to validate the feasibility and accuracy of the proposed method. The results of a quad-rotor unmanned aerial vehicle experiment showed that the clear, uneven, and continuous quantitative laminar flow field could be obtained directly, which overcame the interference of the weak airflow, large field of view, and asymmetrical steady flow.

Cavitation threshold pressure of focused ultrasound observed with sonochemiluminescence

Spatial distribution of sonochemiluminescence (SCL) from an argon-saturated luminol solution was measured in a focused sound field at 1 MHz in a standing-wave configuration. The SCL distribution was confined to pre-focal region at acoustic powers lower than 0.9 W, and was not located at the focus but at a few mm pre-focal side at a threshold for SCL inception. The threshold pressure amplitude for SCL inception was 3.6 atm at the focus, which value was obtained with a background-oriented schlieren method. The method is based on the broadening of multiple slits due to an optical deflection caused by ultrasound, and the broadening width measured provides an acoustic pressure amplitude. A qualitative image of the focused sound field was also obtained.

Improvement in systematic error in background-oriented schlieren results by using dynamic backgrounds

The use of electronic visual displays for background-oriented schlieren allows for the quick change of the reference images. In this study, we show that the quality of synthetic and background-oriented schlieren images can be improved by acquiring a set of images with different reference images and generating a median displacement field from it. To explore potential benefits, we studied different background changing strategies and their effect on the quality of the evaluation of the displacement field via artificial and experimental image distortions. Graphic abstract

Numerical Uncertainty in Density Estimation for Background Oriented Schlieren

Background Oriented Schlieren (BOS) is an image-based density measurement technique. BOS estimates the density gradient from the apparent distortion of a target pattern viewed through a medium with varying density using cross-correlation, tracking, or optical flow algorithms. The density gradient can then be numerically integrated to yield a spatially resolved estimate of the density [1]. A method was recently proposed to estimate the a-posteriori instantaneous and spatially resolved density uncertainty for BOS [2] and showed good agreement between the propagated uncertainties and the random error. However, the density uncertainty quantification method could not account for the systematic uncertainty in the density field due to the discretization errors introduced during the numerical integration, which could be much larger than the displacement random errors [2]. In this work, we propose a method to estimate the numerical uncertainty introduced by the density integration in BOS measurements, using a Richardson extrapolation framework. A procedure is also introduced to combine this systematic uncertainty with the random uncertainty from the previous work to provide an instantaneous, spatially-resolved total uncertainty on the density estimates. The method will be tested with synthetic fields and synthetic BOS images.