Vision based algorithm for automated determination of smoke point of diesel blends. (1st January 2019)

• Record Type: Journal Article
• Authors: Rubio-Gomez, Guilllermo; Corral-Gomez, Lis; Soriano, Jose Antonio; Gomez, Arantzazu; Castillo-Garcia, Fernando J.
• Is Part Of: Fuel. Volume 235(2019)
• Page Start: 595
• Page End: 602
• Publication Date: 2019-01-01
• Subjects: Smoke point -- Threshold sooting index -- Sooting tendency -- Automated method -- Image processing; Fuel -- Periodicals; Coal -- Periodicals; Coal; Fuel; Periodicals; 662.6
• DOI: 10.1016/j.fuel.2018.08.032
• Languages: English
• ISSNs: 0016-2361

Abstract

Abstract: Current regulations restrict NOx and particulate emissions (PM) produced by new vehicles. One solution for reducing these emissions, mainly PM, is focused on the use of cleaner fuels. In this sense, the smoke point test (SP) has been proved to be a fast tool when comparing the sooting tendency of fuels. As manual SP determination can imply an error owing to the inherent uncertainty of visual flame observation, the updated ASTM D1322-18 has stated that the new commercial equipment SP10 Automated Smoke Point Analyser is the reference for SP determination. However, its high cost has motivated this work where a vision based algorithm for automated determination of SP without wick-fed modifications is proposed. Experimental results demonstrate the accuracy and repeatability of the proposed method.