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Volumn 147, Issue 1, 2004, Pages 65-71

Neural network approach for diagnosis of grinding operation by acoustic emission and power signals

Author keywords

Acoustic emission signals; Diagnosis of grinding operation; Neural network; Power signals

Indexed keywords

ACOUSTIC EMISSIONS; ANALOG TO DIGITAL CONVERSION; NEURAL NETWORKS; SENSOR DATA FUSION; SIGNAL PROCESSING; SURFACE ROUGHNESS; VIBRATIONS (MECHANICAL);

EID: 1842639334     PISSN: 09240136     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jmatprotec.2003.11.016     Document Type: Article
Times cited : (83)

References (9)
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  • 2
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    • Studies on the fundamental of grinding burn (3rd report) - Oxidation rate law of workpiece
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  • 5
    • 0000898625 scopus 로고    scopus 로고
    • A grinding power model for selection of dressing and grinding conditions
    • Chen X., Rowe W., Allanson D., Mills B. A grinding power model for selection of dressing and grinding conditions. Trans. ASME. 121:1999;632-637.
    • (1999) Trans. ASME , vol.121 , pp. 632-637
    • Chen, X.1    Rowe, W.2    Allanson, D.3    Mills, B.4
  • 6
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    • Sensor fusion for monitoring and controlling grinding processes
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    • (1999) Int. J. Adv. Manuf. Technol. , vol.15 , Issue.10 , pp. 730-736
    • Inasaki, I.1
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    • Monitoring manufacturing processes by utilizing empirical modeling
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    • Govekar, I.1    Grabek, E.2    Susic, E.3    Antolovic, B.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.