The General Motors Research Laboratories has developed an image processing system that automatically analyzes the size distributions in fuel spray video images. Images are generated by using pulsed laser light to freeze droplet motion in the spray sample volume under study. This coherent illumina-tion source produces images that contain droplet diffraction patterns representing the droplet's degree of focus. Thousands of images are recorded per sample volume to get an ensemble average of the distribution at that spray location. After image acquisition the recorded video frames are replayed and analyzed under computer control. The analysis is performed by extracting feature data describing droplet diffraction patterns in the images. This allows the system to select droplets from image anomalies and measure only those droplets con-sidered in focus. The system was designed to analyze sprays from a variety of environments. Currently these are an ambient spray chamber, a high pressure, high temperature spray facility, and a running engine. Unique features of the system are the totally automated analysis and droplet feature measurement from the gray scale image. Also, it can distinguish nonspherical anomalies from droplets, which allows sizing of droplets near the spray nozzle. This paper describes the feature extraction and image restoration algorithms used in the system. Preliminary performance data are also given for two experiments. One experiment gives a comparison between manual and automatic measurements of a synthesized distribution. The second experiment compares measurements of a real spray distribution using current methods and using the automatic system.
Gary P. Bertollini,
Larry M. Oberdier,
Yong H. Lee,
"Image Processing System To Analyze Droplet Distributions In Sprays," Optical Engineering 24(3), 243464 (1 June 1985). https://doi.org/10.1117/12.7973508