Quantitative methods for feature extraction in tool conditioning monitoring
143 p.
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2011
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sg-ntu-dr.10356-471892023-03-11T17:16:06Z Quantitative methods for feature extraction in tool conditioning monitoring Ye Nyi Win. Zhong Zhaowei School of Mechanical and Aerospace Engineering DRNTU::Engineering::Mechanical engineering 143 p. The tool condition monitoring and process monitoring become major development in automatic manufacturing environment. A High speed milling machine plays a major role in industrial applications. The methods to monitor the health of the milling machine cutter are discussed in this dissertation. Tool wear and tool failure are not acceptable in the milling operation because these can have great effect on product quality, production time and production cost. The aim of the dissertation is to develop the idea of the nondestructive testing in the milling process by acoustic emission signal and force signal. Among the different types of nondestructive methods, some of the methods are analyzed and discussed for their effectiveness and usefulness in industrial applications. Master of Science (Logistics) 2011-12-27T06:34:15Z 2011-12-27T06:34:15Z 2009 2009 Thesis http://hdl.handle.net/10356/47189 Nanyang Technological University application/pdf |
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DRNTU::Engineering::Mechanical engineering Ye Nyi Win. Quantitative methods for feature extraction in tool conditioning monitoring |
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143 p. |
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Zhong Zhaowei |
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Zhong Zhaowei Ye Nyi Win. |
format |
Theses and Dissertations |
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Ye Nyi Win. |
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Ye Nyi Win. |
title |
Quantitative methods for feature extraction in tool conditioning monitoring |
title_short |
Quantitative methods for feature extraction in tool conditioning monitoring |
title_full |
Quantitative methods for feature extraction in tool conditioning monitoring |
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Quantitative methods for feature extraction in tool conditioning monitoring |
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Quantitative methods for feature extraction in tool conditioning monitoring |
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quantitative methods for feature extraction in tool conditioning monitoring |
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2011 |
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http://hdl.handle.net/10356/47189 |
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1761781323739955200 |