Prediction of combustion states from flame image in a domestic coal burner

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dc.authoridonat, cem/0000-0002-4295-4860
dc.authoridGOLGIYAZ, SEDAT/0000-0003-0305-9713
dc.contributor.authorOnat, Cem
dc.contributor.authorDaskin, Mahmut
dc.contributor.authorToraman, Suat
dc.contributor.authorGolgiyaz, Sedat
dc.contributor.authorTalu, Muhammed Fatih
dc.date.accessioned2024-11-07T13:34:20Z
dc.date.available2024-11-07T13:34:20Z
dc.date.issued2021
dc.departmentNiğde Ömer Halisdemir Üniversitesi
dc.description.abstractCoal is still a strategic fuel for many developing countries. The environmental impact of emissions resulting from the widespread use of coal worldwide is a matter of serious debate. In this perspective, clean coal burning technologies are in demand. In this study, a measurement system that estimates emission from flame images in a domestic coal burner is proposed. The system consists of a charge-coupled device camera, image processing software (real time image acquisition, noise reduction and extracting features) and artificial intelligence elements (classification of features by neural networks). In feature extraction stage, only five flame region features (G(x), G(y) , trace, L (2) and L (infinity) norm) is extracted. G(cx) and G(cy) are the instantaneous change of the horizontal and vertical components of center mass of the flame image. These features are new concepts for emission estimation from the flame image. The proposed system makes a difference with its simpler structure and higher accuracy compared to its counterparts previously presented in the literature.
dc.description.sponsorshipScientific and Technological Research Council of Turkey (TUBITAK) [117M121]; MIMSAN AS
dc.description.sponsorshipThis work was supported by The Scientific and Technological Research Council of Turkey (TUBITAK, Project No. 117M121) and MIMSAN AS.
dc.identifier.doi10.1088/1361-6501/abe446
dc.identifier.issn0957-0233
dc.identifier.issn1361-6501
dc.identifier.issue7
dc.identifier.scopus2-s2.0-85105484607
dc.identifier.scopusqualityQ2
dc.identifier.urihttps://doi.org/10.1088/1361-6501/abe446
dc.identifier.urihttps://hdl.handle.net/11480/15930
dc.identifier.volume32
dc.identifier.wosWOS:000646859500001
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherIop Publishing Ltd
dc.relation.ispartofMeasurement Science and Technology
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241106
dc.subjectemission measurement
dc.subjectcoal
dc.subjectprediction
dc.subjectflame
dc.subjectimage processing
dc.subjectANN regression
dc.subjectcombustion control
dc.titlePrediction of combustion states from flame image in a domestic coal burner
dc.typeArticle

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