dc.contributor.advisor | Keyvan, Shahla | eng |
dc.contributor.advisor | Palaniappan, K. (Kannappan) | eng |
dc.contributor.author | Cokrojoyo, Handi, 1976- | eng |
dc.date.issued | 2007 | eng |
dc.date.submitted | 2007 Summer | eng |
dc.description | The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. | eng |
dc.description | Title from title screen of research.pdf file (viewed on March 19, 2009) | eng |
dc.description | Vita. | eng |
dc.description | Thesis (Ph.D.) University of Missouri-Columbia 2007. | eng |
dc.description.abstract | A promising architecture is proposed in this research work for evaluating gasfired furnace flame combustion quality. The quality assessment is based on information on its fuel and oxidizer flow rate level which are the main ingredient for the combustion reaction. The relative composition of the two determines the overall quality of the combustion and a proper balance is needed for optimum combustion in order to avoid wasting expensive fuel or producing hazardous emissions. The proposed system utilizes a combination of image processing and machine learning techniques integrated with artificial intelligence techniques in providing combustion status that is derived directly from the captured color images of the furnace flame. The proposed system performs all of its functional capabilities on both fuel and oxidizer automatically and provides results in seconds or near real-time. | eng |
dc.description.bibref | Includes bibliographical references. | eng |
dc.identifier.merlin | b66659346 | eng |
dc.identifier.oclc | 316329328 | eng |
dc.identifier.uri | https://doi.org/10.32469/10355/4759 | eng |
dc.identifier.uri | https://hdl.handle.net/10355/4759 | |
dc.language | English | eng |
dc.publisher | University of Missouri--Columbia | eng |
dc.relation.ispartofcommunity | University of Missouri--Columbia. Graduate School. Theses and Dissertations | eng |
dc.rights | OpenAccess. | eng |
dc.rights.license | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License. | |
dc.subject.lcsh | Gas furnaces | eng |
dc.subject.lcsh | Machine learning | eng |
dc.subject.lcsh | Image processing | eng |
dc.subject.lcsh | Flame | eng |
dc.subject.lcsh | Fuel -- Analysis | eng |
dc.subject.lcsh | Oxidizing agents | eng |
dc.title | Analysis of flame images in gas-fired furnaces | eng |
dc.type | Thesis | eng |
thesis.degree.discipline | Computer engineering (MU) | eng |
thesis.degree.grantor | University of Missouri--Columbia | eng |
thesis.degree.level | Doctoral | eng |
thesis.degree.name | Ph. D. | eng |