Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/26266
Title: Study of tool wear using acoustic emission and intelligent techniques
Researcher: Kulandaivelu P
Guide(s): Senthilkumar P
Keywords: Acoustic emission
Acoustic emission technique
Artificial neural network
Manufacturing industry
Mechanical engineering
Tool wear
Upload Date: 1-Oct-2014
University: Anna University
Completed Date: 01/03/2012
Abstract: One of the challenges in the manufacturing industries is the ability of the machines to change the tools automatically during its wear or damage In general tool failure contributes about 7 to the down time of the machining centers Therefore on line monitoring of tool wear is an important phenomenon in producing quality products at reasonable cost This also increases the production rate in the industries Tool condition monitoring using Acoustic Emission Technique is one of the best methods identified by researchers for on line quality assessment of machine tools Artificial Neural Network is an information processing system that has certain performance characteristics in common with biological neural networks The artificial neural network have been developed as generalisation of mathematical models of human neural biology The network is trained by initially selecting random weights and internal threshold and then presenting all training data Weights and thresholds are adjusted after every training until required output is obtained This technique is utilized to predict the expected tool wear during its operation
Pagination: xviii,127p.
URI: http://hdl.handle.net/10603/26266
Appears in Departments:Faculty of Mechanical Engineering

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01_title.pdfAttached File16.15 kBAdobe PDFView/Open
02_certificates.pdf2.36 MBAdobe PDFView/Open
03_abstract.pdf8.6 kBAdobe PDFView/Open
04_acknowledgement.pdf6.65 kBAdobe PDFView/Open
05_contents.pdf24.13 kBAdobe PDFView/Open
06_chapter1.pdf189.64 kBAdobe PDFView/Open
07_chapter2.pdf51.33 kBAdobe PDFView/Open
08_chapter3.pdf5.64 MBAdobe PDFView/Open
09_chapter4.pdf4.01 MBAdobe PDFView/Open
10_chapter5.pdf14.01 kBAdobe PDFView/Open
11_references.pdf23.36 kBAdobe PDFView/Open
12_publications.pdf7.87 kBAdobe PDFView/Open
13_vitae.pdf6 kBAdobe PDFView/Open


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