| Issue |
E3S Web Conf.
Volume 360, 2022
2022 8th International Symposium on Vehicle Emission Supervision and Environment Protection (VESEP2022)
|
|
|---|---|---|
| Article Number | 01003 | |
| Number of page(s) | 14 | |
| DOI | https://doi.org/10.1051/e3sconf/202236001003 | |
| Published online | 23 November 2022 | |
The microscopic characteristics of particle matter and image algorithm based on fractal theory
School of Automotive Studies, Tongji University, Shanghai 201804, PR China
* Corresponding author: tpq2000@163.com
The effects of ash and sulfur content on the morphology of particulate matter (PM) in diesel particle filter (DPF) were investigated with five different components of lubricants. The aggregate morphology of primary particles in diesel were analyzed using transmission electron microscopy (TEM). The fractal dimensions of carbon particles were calculated by box-counting method (BCM), differential box-counting method (DBC), relative differential box-counting method (RDBC) and MAD-based box counting method (MAD-DBC), and the results were compared. The results showed that the microstructure of PM developed from chain-like structure to agglomerate structure with the increase of sulfur and ash content in lubricating oil. The fractal dimension of carbon particles increased with the increase of sulfur and ash content. The SSE of RDBC fitting results was smaller, and the R-square is larger. MAD-DBC fitting results had stronger anti-noise interference performance.
Key words: Diesel engine / Particulate matter / Microstructure / Fractal dimension / Box-counting method
© The Authors, published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0/).
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