Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/29685
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dc.coverage.spatialMonitoring of tool wear in turning and Roughness in grinding and milling Using ultrasonic technique a neuro fuzzy modeling Approachen_US
dc.date.accessioned2014-12-03T03:25:13Z-
dc.date.available2014-12-03T03:25:13Z-
dc.date.issued2014-12-03-
dc.identifier.urihttp://hdl.handle.net/10603/29685-
dc.description.abstractTool life prediction and tool change strategies are now based on newlinemost conservative estimates of tool life from past tool wear data Hence newlineusually tools are under utilized In an unmanned factory this has the effect of newlineincreased frequency of the tool changes and therefore increased cost Several newlinemonitoring methods for mass production have been developed during the last newlinefew decades by many researchers However few reliable indirect methods newlinehave been established for industrial use This is mainly due to the complexity newlineof machining process and the uncertainty in the correlation between the newlineprocess parameters and tool wear newlineAn ultrasound on line measurement of gradual wear during the newlineturning operation is presented The method relies on inducing ultrasound newlinewaves in the tool which propagates through the length of the tool and are newlinereflected by nose rake and flank surfaces The amount of reflected energy is newlinecorrelated with wear land height and crater depth Here the various ultrasonic newlineparameters like time of flight T O F amplitude pulse width and root mean newlinesquare of the signal R M S are considered to quantify the wear land height newlinecrater depth and width of wear The power spectrum analysis of received newlinesignals shows the importance of frequency components in the prediction of newlinetool wear newlineen_US
dc.format.extentxxiii, 178p.en_US
dc.languageEnglishen_US
dc.relationp168-175.en_US
dc.rightsuniversityen_US
dc.titleMonitoring of tool wear in turning and Roughness in grinding and milling Using ultrasonic technique a neuro fuzzy modeling Approachen_US
dc.title.alternativeen_US
dc.creator.researcherDinakaran Den_US
dc.subject.keywordRoot mean squareen_US
dc.subject.keywordTime of flighten_US
dc.description.noteappendix p165-167, reference p168-175.en_US
dc.contributor.guideSampathkumar Sen_US
dc.publisher.placeChennaien_US
dc.publisher.universityAnna Universityen_US
dc.publisher.institutionFaculty of Mechanical Engineeringen_US
dc.date.registeredn.d,en_US
dc.date.completed01/12/2009en_US
dc.date.awarded30/12/2009en_US
dc.format.dimensions23cm.en_US
dc.format.accompanyingmaterialNoneen_US
dc.source.universityUniversityen_US
dc.type.degreePh.D.en_US
Appears in Departments:Faculty of Mechanical Engineering

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01_title.pdfAttached File34.48 kBAdobe PDFView/Open
02_certificate.pdf5.97 kBAdobe PDFView/Open
03_abstract.pdf12.79 kBAdobe PDFView/Open
04_acknowledgement.pdf8.67 kBAdobe PDFView/Open
05_content.pdf38.22 kBAdobe PDFView/Open
06_chapter1.pdf47.97 kBAdobe PDFView/Open
07_chapter2.pdf59.32 kBAdobe PDFView/Open
08_chapter3.pdf199.25 kBAdobe PDFView/Open
09_chapter4.pdf1.26 MBAdobe PDFView/Open
10_chapter5.pdf473.86 kBAdobe PDFView/Open
11_chapter6.pdf3.05 MBAdobe PDFView/Open
12_chapter7.pdf136.54 kBAdobe PDFView/Open
13_chapter8.pdf976.54 kBAdobe PDFView/Open
14_chapter9.pdf119.8 kBAdobe PDFView/Open
15_chapter10.pdf50.85 kBAdobe PDFView/Open
16_chapter11.pdf84.95 kBAdobe PDFView/Open
17_appendix.pdf122.21 kBAdobe PDFView/Open
18_reference.pdf32.9 kBAdobe PDFView/Open
19_publication.pdf10.82 kBAdobe PDFView/Open
20_vitae.pdf6.5 kBAdobe PDFView/Open


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