The combustion properties of blended fuel combinations can be characterized by performing single droplet fuel combustion experiments. These combustion experiments are visualized using high speed image acquisition. Once the high speed images are obtained, the burn rate and other characteristics of combustion, such as the occurrence of microexplosions, can be characterized. Currently these quantities are either measured manually or are measured using automated software. However, the current software packages used for this task are limited in that they can only measure droplets that are elliptical in shape and manual corrections often have to be made to avoid significant errors in the measurement. An automated droplet tracking algorithm is presented that can automatically track droplet size without manual intervention due to its robustness to the presence of missing or extra edges in the images. In addition, the proposed method can track shapes more general than ellipses, which is required in order to track the droplet during microexplosions. The proposed algorithm starts by fitting ellipses to numerous five point subsets from the droplet edge data. The closed contour is parameterized by determining the median perimeter of the set of ellipses. The resulting curve is not an ellipse, allowing arbitrary closed contours to be parameterized. The performance of the proposed algorithm and the performance of existing algorithms are compared to a ground truth segmentation of the fuel droplet images. This comparison demonstrates that the median ellipse parameterization algorithm has improved performance for both area quantification and edge deviation.
|Original language||English (US)|
|Journal||Measurement Science and Technology|
|State||Published - Dec 31 2015|
Bibliographical notePublisher Copyright:
© 2016 IOP Publishing Ltd.
- contour fitting
- droplet size measurement
- image processing
- robust ellipse fitting