An application of digital image processing techniques to the characterization of liquid petroleum gas (LPG) spray

Studying the vaporizing characteristics of diesel spray could greatly help to reduce engine emission and improve performance. The high-speed schlieren imaging method is an important optical technique for investigating the macroscopic vaporizing morphological evolution of liquid fuel, and pre-combustion constant volume combustion bombs are often used to simulate the high pressure and high temperature conditions occurring in diesel engines. Complicated background schlieren noises make it difficult to segment the spray region in schlieren spray images. To tackle this problem, this paper develops a vaporizing spray boundary segmentation methodology based on an automatic threshold determination algorithm. The methodology was also used to quantify the macroscopic characteristics of vaporizing sprays including tip penetration, near-field and far-field angles, and projected spray area and spray volume. The spray boundary segmentation methodology was realized in a MATLAB-based program. Comparisons were made between the spray characteristics obtained using the program method and those acquired using a manual method and the Hiroyasu prediction model. It is demonstrated that the methodology can segment and measure vaporizing sprays precisely and efficiently. Furthermore, the experimental results show that the spray angles were slightly affected by the injection pressure at high temperature and high pressure and under inert conditions. A higher injection pressure leads to longer spray tip penetration and a larger projected area and volume, while elevating the temperature of the environment can significantly promote the evaporation of cold fuel.

Section: Verification Of the Image Processing Methodology And Repeata...supporting

confidence: 69%

Section: Definitions Of the Spray Macroscopic Characteristicsmentioning

confidence: 99%

The development and application of an automatic boundary segmentation methodology to evaluate the vaporizing characteristics of diesel spray under engine-like conditions

Ma¹,

Huang²,

Deng³

et al. 2015

“…Significant insight into spatial and temporal features of ignition and combustion processes have been gained by imaging in constant volume chambers (e.g. [9,[12][13][14]), rapid compression/expansion machines (RCEMs, e.g. [11,15]), and optically-accessible engines (e.g.…”

Section: Introductionmentioning

confidence: 99%

“…For COI analysis of in-cylinder imaging data, the general approach is to segment each raw image into a binary image containing only the region of interest to be measured (e.g. fuel-jet spread angle and penetration [14,27] or reaction zone lift-off length [19,28]), evaluate the metric of interest, and then evaluate the mean value for the metric of interest. This approach has generally been limited to SI applications (e.g.…”

Section: Introductionmentioning

confidence: 99%

Robust image segmentation for feature extraction from internal combustion engine in-cylinder images

Rochussen¹,

Kirchen²

2020

In-cylinder imaging diagnostics for internal combustion engines provide rich information on the structure and evolution of reaction zone features, which affect both engine out emissions and efficiency. However, the most common analysis of in-cylinder combustion luminosity imaging considers ensemble averaged images, which are not suitable for characterizing processes that vary significantly between cycles, such as ignition and soot formation and oxidation. Here, a robust image segmentation algorithm is presented for feature extraction from single-cycle in-cylinder combustion images and is used with a ‘combination of interpretations’ (COI) approach to analyze OH*-chemiluminescence imaging of premixed and non-premixed natural gas combustion modes in an optically-accessible reciprocating engine. Dynamic thresholding and region size filtering are combined with watershed segmentation to create a parameterized adaptive watershed (PAW) segmentation algorithm. The fusion of these segmentation methods is novel to combustion imaging and is demonstrated to provide quantified improvement relative to the current state of the art segmentation methods; PAW segmentation provides increased sensitivity for early ignition processes, and more robustly identifies the reaction zones at later stages of combustion. The PAW algorithm requires no adjustment between the two considered combustion modes or for any stage of the combustion process. The reliability of the PAW output enables feature extraction of individual reaction zone location and area from the combustion images using a polar-sector coordinate system for COI analysis. This approach characterizes the cyclic variability of individual fuel jets, identifies coupling of auto-ignition behavior between adjacent reaction zones, and demonstrates systematic errors arising from measurement of auto-ignition in ensemble averaged images. Application of PAW segmentation and the analysis approach presented here can provide more complete characterization of other spatially-resolved internal combustion diagnostics, particularly where there is high process variability, overlapping image regions, or wide signal intensity ranges.

“…A variety of measurement methods have been used to study fuel spray behavior, including Mie scattering, schlieren photography, laser-induced exciplex fluorescence (LIEF) and x-ray radiography. Mie scattering and schlieren photography are widely used to measure the liquid and vapor penetration lengths of a fuel spray, respectively [9][10][11][12]. Although schlieren photography captures both the liquid and vapor phases of a fuel spray, it is difficult to distinguish between them.…”

Section: Introductionmentioning

confidence: 99%

Measurement of spray characteristics using the background-oriented schlieren technique

Liu¹,

Kim²,

Min³

2012

The background-oriented schlieren (BOS) technique has not yet been used in the visualization of fuel spray in automotive research despite its great promise. To investigate the potential of this technique, the density distribution of a cross section of the spray was obtained by applying a filtered back projection (FBP) to the BOS results. Using the density distribution, the penetration lengths of the liquid and vapor phases of the fuel were measured and compared with the results of Mie scattering and shadowgraph images. The results show that the BOS technique is applicable for measuring the liquid and vapor penetration lengths simultaneously. Furthermore, the analysis of the back-projected density distribution revealed that the BOS technique is capable of visualizing the difference in the transient change in the density distribution due to changes in the injection pressure and the fuel volatility.