Towards image-based control of an industrial potato peeler

dc.contributor.advisorDubay, Rickey
dc.contributor.advisorShukla, Dhirendra
dc.contributor.authorKnopp, Zachary
dc.date.accessioned2023-03-01T16:39:26Z
dc.date.available2023-03-01T16:39:26Z
dc.date.issued2016
dc.date.updated2023-03-01T15:02:57Z
dc.description.abstractDifficult multivariate industrial control problems can be solved by combining standard control theory, adaptive computer vision algorithms and intelligent modeling into an overarching generalized control system. Creating the foundations for such a system, to be implemented on an industrial potato peeler, was the scope of this thesis. Computer vision algorithms that provided quantifiable metrics from the peeling process were developed using data gathered at a potato research center. Experiments were performed controlling the steamtime and pressure of the peeler and the size and seasonality of the potatoes. Thermal signatures and optical videos of peeled potatoes were recorded throughout testing. It was found that smaller potatoes are more difficult to peel and changes in pressure do not correlate with changes in peel efficiency. Recommendations were made for the next steps towards intelligent control of industrial potato peeling processes.
dc.description.copyright© Zachary Knopp, 2017
dc.formattext/xml
dc.format.extentxi, 87 pages
dc.format.mediumelectronic
dc.identifier.urihttps://unbscholar.lib.unb.ca/handle/1882/14280
dc.language.isoen_CA
dc.publisherUniversity of New Brunswick
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.subject.disciplineMechanical Engineering
dc.titleTowards image-based control of an industrial potato peeler
dc.typemaster thesis
thesis.degree.disciplineMechanical Engineering
thesis.degree.fullnameMaster of Science in Engineering
thesis.degree.grantorUniversity of New Brunswick
thesis.degree.levelmasters
thesis.degree.nameM.Sc.E.

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