| DOI | Resolve DOI: https://doi.org/10.1504/IJMR.2009.022743 |
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| Author | Search for: Banerjee, Avisekh; Search for: Bordatchev, Evgueni V.1; Search for: Choudhury, Sounak Kumar |
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| Affiliation | - National Research Council of Canada. NRC Industrial Materials Institute
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| Format | Text, Article |
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| Subject | on-line monitoring; turning operation; surface roughness; bifurcated opto-electrical transducer; regression models; neural network models; pattern recognition |
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| Abstract | This work studies the feasibility of on-line monitoring of surface roughness in turning operations using a developed opto-electrical transducer. Regression and Neural Network (NN) models are exploited to predict surface roughness and compared to actual and on-line measurements. The comparative study suggests feasibility of using the transducer within 15% tolerance. Pattern recognition analysis of on-line roughness and vibration displacements is used for reliable (>93%) classification of actual roughness. The results provide important information for the future development of on-line diagnostics and control of surface roughness in turning operation. |
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| Publication date | 2009 |
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| In | |
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| Language | English |
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| Peer reviewed | Yes |
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| NPARC number | 21274329 |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | 1863da16-3912-45d6-8904-52a062cc6bd1 |
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| Record created | 2015-03-10 |
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| Record modified | 2020-04-16 |
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