A multi-sensor integration method of signals in a metal cutting opera tion via application of multi-layer perceptron neural networks
Identifieur interne : 002A27 ( Main/Exploration ); précédent : 002A26; suivant : 002A28A multi-sensor integration method of signals in a metal cutting opera tion via application of multi-layer perceptron neural networks
Auteurs : D. E. Jr Dimla [Royaume-Uni] ; P. M. Lister [Royaume-Uni] ; N. J. Leighton [Royaume-Uni]Source :
- IEE conference publication [ 0537-9989 ] ; 1997.
Descripteurs français
- Pascal (Inist)
- Wicri :
- topic : Métrologie, Intelligence artificielle.
English descriptors
- KwdEn :
Abstract
The potential application of neural networks in manufacturing scenarios is increasingly becoming feasible. Typical of such a manufacturing scenario is the integration of metal cutting sensor signals in pursuance of reliable Tool Condition Monitoring (TCM) system. Successful application of this method of sensor integration could save downtime and costs, that would otherwise not have been realised through traditional tool changing philosophies. Unfortunately, the neural network algorithms used have been complicated, requiring detailed sensor signal pre-processing. Partly as a consequence, developed systems have found very limited applications to-date. In this paper, the authors present a simple sensor fusion method via the neural networks approach to the TCM problem. Turning tests were conducted from which the static cutting force, dynamic cutting force and the vibration signature were recorded. The obtained data was used to investigate the classification capability of simple Multi-layer Perceptron (MLP) neural network architectures to the detection of tool wear. Obtained results showed classification accuracy of well over 90% was attainable.
Affiliations:
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Lister</name><affiliation wicri:level="1"><inist:fA14 i1="01"><s1>Engineering Research Group, SEBE, University of Wolverhampton</s1><s3>GBR</s3><sZ>1 aut.</sZ><sZ>2 aut.</sZ><sZ>3 aut.</sZ></inist:fA14><country>Royaume-Uni</country><wicri:noRegion>Engineering Research Group, SEBE, University of Wolverhampton</wicri:noRegion></affiliation></author><author><name sortKey="Leighton, N J" sort="Leighton, N J" uniqKey="Leighton N" first="N. J." last="Leighton">N. J. 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E. Jr" last="Dimla">D. E. Jr Dimla</name><affiliation wicri:level="1"><inist:fA14 i1="01"><s1>Engineering Research Group, SEBE, University of Wolverhampton</s1><s3>GBR</s3><sZ>1 aut.</sZ><sZ>2 aut.</sZ><sZ>3 aut.</sZ></inist:fA14><country>Royaume-Uni</country><wicri:noRegion>Engineering Research Group, SEBE, University of Wolverhampton</wicri:noRegion></affiliation></author><author><name sortKey="Lister, P M" sort="Lister, P M" uniqKey="Lister P" first="P. M." last="Lister">P. M. Lister</name><affiliation wicri:level="1"><inist:fA14 i1="01"><s1>Engineering Research Group, SEBE, University of Wolverhampton</s1><s3>GBR</s3><sZ>1 aut.</sZ><sZ>2 aut.</sZ><sZ>3 aut.</sZ></inist:fA14><country>Royaume-Uni</country><wicri:noRegion>Engineering Research Group, SEBE, University of Wolverhampton</wicri:noRegion></affiliation></author><author><name sortKey="Leighton, N J" sort="Leighton, N J" uniqKey="Leighton N" first="N. J." last="Leighton">N. J. Leighton</name><affiliation wicri:level="1"><inist:fA14 i1="01"><s1>Engineering Research Group, SEBE, University of Wolverhampton</s1><s3>GBR</s3><sZ>1 aut.</sZ><sZ>2 aut.</sZ><sZ>3 aut.</sZ></inist:fA14><country>Royaume-Uni</country><wicri:noRegion>Engineering Research Group, SEBE, University of Wolverhampton</wicri:noRegion></affiliation></author></analytic><series><title level="j" type="main">IEE conference publication</title><idno type="ISSN">0537-9989</idno><imprint><date when="1997">1997</date></imprint></series></biblStruct></sourceDesc><seriesStmt><title level="j" type="main">IEE conference publication</title><idno type="ISSN">0537-9989</idno></seriesStmt></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Artificial intelligence</term><term>Cutting force</term><term>Cutting tool</term><term>Data fusion</term><term>Machining</term><term>Metrology</term><term>Monitoring</term><term>Multilayer network</term><term>Neural network</term><term>Perceptron</term><term>Vibration</term></keywords><keywords scheme="Pascal" xml:lang="fr"><term>Métrologie</term><term>Monitorage</term><term>Usinage</term><term>Fusion donnée</term><term>Outil coupe</term><term>Force coupe</term><term>Vibration</term><term>Intelligence artificielle</term><term>Perceptron</term><term>Réseau neuronal</term><term>Réseau multicouche</term></keywords><keywords scheme="Wicri" type="topic" xml:lang="fr"><term>Métrologie</term><term>Intelligence artificielle</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">The potential application of neural networks in manufacturing scenarios is increasingly becoming feasible. Typical of such a manufacturing scenario is the integration of metal cutting sensor signals in pursuance of reliable Tool Condition Monitoring (TCM) system. Successful application of this method of sensor integration could save downtime and costs, that would otherwise not have been realised through traditional tool changing philosophies. Unfortunately, the neural network algorithms used have been complicated, requiring detailed sensor signal pre-processing. Partly as a consequence, developed systems have found very limited applications to-date. In this paper, the authors present a simple sensor fusion method via the neural networks approach to the TCM problem. Turning tests were conducted from which the static cutting force, dynamic cutting force and the vibration signature were recorded. The obtained data was used to investigate the classification capability of simple Multi-layer Perceptron (MLP) neural network architectures to the detection of tool wear. Obtained results showed classification accuracy of well over 90% was attainable.</div></front></TEI><affiliations><list><country><li>Royaume-Uni</li></country></list><tree><country name="Royaume-Uni"><noRegion><name sortKey="Dimla, D E Jr" sort="Dimla, D E Jr" uniqKey="Dimla D" first="D. E. Jr" last="Dimla">D. E. Jr Dimla</name></noRegion><name sortKey="Leighton, N J" sort="Leighton, N J" uniqKey="Leighton N" first="N. J." last="Leighton">N. J. Leighton</name><name sortKey="Lister, P M" sort="Lister, P M" uniqKey="Lister P" first="P. M." last="Lister">P. M. Lister</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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