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<dc:title>3509 遺伝的プログラミングを用いた工具状態の推定(S65 加工計測・評価システム,S65 加工計測・評価システム)</dc:title>
<dc:creator>宋,東烈</dc:creator>
<dc:creator>大谷,信男</dc:creator>
<dc:creator>大高,政祥</dc:creator>
<dc:publisher>社団法人日本機械学会</dc:publisher>
<prism:publicationName>年次大会講演論文集 : JSME annual meeting</prism:publicationName>
<prism:volume>2007</prism:volume>
<prism:number>4</prism:number>
<prism:startingPage>235</prism:startingPage>
<prism:endingPage>236</prism:endingPage>
<prism:publicationDate>2007-09-07</prism:publicationDate>
<dc:date>2007-09-07</dc:date>
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<dc:title>3509 Estimation of Cutting Tool Condition Using Genetic Programming</dc:title>
<dc:creator>SONG,Dong-Yeul</dc:creator>
<dc:creator>OTANI,Nobuo</dc:creator>
<dc:creator>OTAKA,Masayoshi</dc:creator>
<dc:publisher>The Japan Society of Mechanical Engineers</dc:publisher>
<dc:description>For the purpose of improving the detecting ability of tool condition change during cutting operation, the time series model parameter obtained from the measured vibration signal and the residual error, which is a difference between the estimated and the measured signals, using genetic programming (GP) are investigated and discussed in relation to wear condition of cutting edge. As a result, it is revealed that the early wear of cutting edge, where the stiffness parameter of the machining part of a cutting model increases linearly with the progress of cutting, can be detected by monitoring of AR parameter of time series model. Moreover, subsequent wear, edge chipping and/or fracture, lead to the increasing of nonlinearity in the measured vibration wave, can be detected by monitoring of residual error. It is therefore concluded that the overall wear behavior in cutting edge can be fully identified by the residual error of the time series vibration signal determined using GP.</dc:description>
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<foaf:name>宋,東烈</foaf:name>
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<foaf:name>群馬産技センター</foaf:name>
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