Prediction of Excess Air Factor in Automatic Feed Coal Burners by Processing of Flame Images

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dc.authoridTalu, Muhammed Fatih/0000-0003-1166-8404
dc.authoridDAŞKIN, Mahmut/0000-0001-7777-1821
dc.authoridonat, cem/0000-0002-4295-4860
dc.authorwosidTalu, Muhammed Fatih/W-2834-2017
dc.authorwosidDAŞKIN, Mahmut/AAT-4529-2021
dc.authorwosidOnat, Cem/W-7629-2018
dc.contributor.authorTalu, Muhammed Fatih
dc.contributor.authorOnat, Cem
dc.contributor.authorDaskin, Mahmut
dc.date.accessioned2024-08-04T20:43:56Z
dc.date.available2024-08-04T20:43:56Z
dc.date.issued2017
dc.departmentİnönü Üniversitesien_US
dc.description.abstractIn this study, the relationship between the visual information gathered from the flame images and the excess air factor lambda in coal burners is investigated. In conventional coal burners the excess air factor lambda. can be obtained using very expensive air measurement instruments. The proposed method to predict lambda for a specific time in the coal burners consists of three distinct and consecutive stages; a) online flame images acquisition using a CCD camera, b) extraction meaningful information (flame intensity and brightness)from flame images, and c) learning these information (image features) with ANNs and estimate lambda. Six different feature extraction methods have been used: CDF of Blue Channel, Co-Occurrence Matrix, L (a)-Frobenius Norms, Radiant Energy Signal (RES), PCA and Wavelet. When compared prediction results, it has seen that the use of co-occurrence matrix with ANNs has the best performance (RMSE = 0.07) in terms of accuracy. The results show that the proposed predicting system using flame images can be preferred instead of using expensive devices to measure excess air factor in during combustion.en_US
dc.description.sponsorshipScientific and Technological Research Council of Turkey (TUBITAK) [114M116]; MIMSAN ASen_US
dc.description.sponsorshipThis work was supported by The Scientific and Technological Research Council of Turkey (TUBITAK, Project number: 114M116) and MIMSAN AS.en_US
dc.identifier.doi10.1007/s10033-017-0095-3
dc.identifier.endpage731en_US
dc.identifier.issn1000-9345
dc.identifier.issn2192-8258
dc.identifier.issue3en_US
dc.identifier.scopus2-s2.0-85026515379en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage722en_US
dc.identifier.urihttps://doi.org/10.1007/s10033-017-0095-3
dc.identifier.urihttps://hdl.handle.net/11616/97910
dc.identifier.volume30en_US
dc.identifier.wosWOS:000400857300022en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherEditorial Office Chinese Journal Mechanical Engineeringen_US
dc.relation.ispartofChinese Journal of Mechanical Engineeringen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectExcess air factoren_US
dc.subjectFlame imagesen_US
dc.subjectCoal burneren_US
dc.titlePrediction of Excess Air Factor in Automatic Feed Coal Burners by Processing of Flame Imagesen_US
dc.typeArticleen_US

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