DC Field | Value | Language |
---|---|---|
dc.contributor.author | Cho, DW | - |
dc.contributor.author | Choi, WC | - |
dc.contributor.author | Lee, HY | - |
dc.date.accessioned | 2016-03-31T13:25:06Z | - |
dc.date.available | 2016-03-31T13:25:06Z | - |
dc.date.created | 2009-03-19 | - |
dc.date.issued | 2000-01 | - |
dc.identifier.issn | 1013-9826 | - |
dc.identifier.other | 2000-OAK-0000001646 | - |
dc.identifier.uri | https://oasis.postech.ac.kr/handle/2014.oak/19780 | - |
dc.description.abstract | This paper proposes a neural network for the decision-making system for monitoring tool wear while working materials such as Al6061, SB41, SM45C. The raw cutting forces signals are filtered and processed with adaptive AR modeling. The AR parameters and cutting conditions are used as input to the neural network along with the frequency band energy. The experimental results show that each neural network trained for each specified material can recognize tool wear with a more than 85% detection rate. When the normalized tensile strength of each material is used as additional input to the unified neural network, the network still has a success rate higher than 80%. | - |
dc.description.statementofresponsibility | X | - |
dc.language | English | - |
dc.publisher | TRANS TECH PUBLICATIONS LTD | - |
dc.relation.isPartOf | KEY ENGINEERING MATERIALS | - |
dc.subject | face milling | - |
dc.subject | neural network | - |
dc.subject | tool wear | - |
dc.subject | workpiece material | - |
dc.subject | NEURAL-NETWORK | - |
dc.title | Defecting tool wear in face milling with different workpiece materials | - |
dc.type | Article | - |
dc.contributor.college | 기계공학과 | - |
dc.identifier.doi | 10.4028/www.scientific.net/KEM.183-187.559 | - |
dc.author.google | Cho, DW | - |
dc.author.google | Choi, WC | - |
dc.author.google | Lee, H | - |
dc.relation.volume | 183-1 | - |
dc.relation.startpage | 559 | - |
dc.relation.lastpage | 564 | - |
dc.contributor.id | 10102903 | - |
dc.relation.journal | KEY ENGINEERING MATERIALS | - |
dc.relation.index | SCI급, SCOPUS 등재논문 | - |
dc.relation.sci | SCI | - |
dc.collections.name | Conference Papers | - |
dc.type.rims | ART | - |
dc.identifier.bibliographicCitation | KEY ENGINEERING MATERIALS, v.183-1, pp.559 - 564 | - |
dc.identifier.wosid | 000165527800092 | - |
dc.date.tcdate | 2019-01-01 | - |
dc.citation.endPage | 564 | - |
dc.citation.startPage | 559 | - |
dc.citation.title | KEY ENGINEERING MATERIALS | - |
dc.citation.volume | 183-1 | - |
dc.contributor.affiliatedAuthor | Cho, DW | - |
dc.description.journalClass | 1 | - |
dc.description.journalClass | 1 | - |
dc.description.wostc | 1 | - |
dc.type.docType | Article; Proceedings Paper | - |
dc.subject.keywordAuthor | face milling | - |
dc.subject.keywordAuthor | neural network | - |
dc.subject.keywordAuthor | tool wear | - |
dc.subject.keywordAuthor | workpiece material | - |
dc.relation.journalWebOfScienceCategory | Materials Science, Ceramics | - |
dc.relation.journalWebOfScienceCategory | Mechanics | - |
dc.relation.journalWebOfScienceCategory | Materials Science, Characterization & Testing | - |
dc.relation.journalWebOfScienceCategory | Materials Science, Composites | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Materials Science | - |
dc.relation.journalResearchArea | Mechanics | - |
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