Abstract
In the present automotive scenario, along with hybridization, GDI technology is progressively spreading in order to improve the powertrain thermal efficiency. In order to properly match the fuel spray development with the combustion chamber design, using robust and accurate diagnostics is required. In particular, for the evaluation of the injection quality in terms of spray shape, vision tests are crucial for GDI injection systems. By vision tests, parameters such as spray tip penetration and cone angles can be measured, as the operating conditions in terms of mainly injection pressure, injection strategy, and chamber counter-pressure are varied. Provided that a complete experimental spray characterization requires the acquisition of several thousand spray images, an automated methodology for analyzing spray images objectively and automatically is mandatory. A decisive step in a spray image analysis procedure is binarization, i.e., the extraction of the spray structure from the background. Binarization is particularly challenging for GDI sprays, given their lower compactness with respect to diesel sprays. In the present paper, two of the most diffused automated binarization algorithms, namely the Otsu and Yen methods, are comparatively validated with an innovative approach derived from the Triangle method—the Last Minimum Criterion—for the analysis of high-pressure GDI sprays. GDI spray images acquired with three injection pressure levels (up to 600 bar) and two different optical setups (backlight and front illumination) were used to validate the considered algorithms in challenging conditions, obtaining encouraging results in terms of accuracy and robustness for the proposed approach.
Highlights
In last years, environmental issues have become the effective driving force for automotive powertrain technical evolution
For spark-ignited engines, a significant thermal efficiency improvement is allowed by the shift from homogeneous charge combustion to stratified charge combustion enabled by fuel direct injection technology (GDI engines)
The efficiency improvement potential is mainly related to the mixture quality-control approach, which is enabled by stratified charge combustion, for low and medium speed and load operating conditions
Summary
Environmental issues have become the effective driving force for automotive powertrain technical evolution. The spray image quality in terms of light contrast is influenced basically by the injection pressure and by the delay between the injection process start and the timing of image acquisition, both these parameters affecting the image signal-to-noise ratio Both the fuel and the ambient temperature can have a significant effect on the spray droplets space density. The image analysis can follow two different approaches in terms of spray boundary recognition: the spray edge detection can be based on the first or second local derivate of the light intensity function, or it can be based on a threshold level selection that is globally able to differentiate the spray from the background pixels. A diffuse illumination field is created, and so the light scattered from the spray drops is acquired by the camera, resulting in a dark background
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