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    Please use this identifier to cite or link to this item: http://ir.lib.ksu.edu.tw/handle/987654321/9670

    Title: Tool Wear Monitoring: an Automated System Based on Multiple Cutting Force Parameters and Machine Vision Technique
    Authors: Yu-Teng Liang
    Yih-Chih Chiou
    Contributor: 圖書資訊館
    Keywords: Multiple parameters
    automatic monitoring system
    cutting force
    machine vision
    dry cutting
    Date: 2008-11-08
    Issue Date: 2010-04-14 10:42:47 (UTC+8)
    Abstract: This study proposes a tool wear monitoring system
    based on multiple parameters analysis of cutting force
    and machine vision technique. A drilling model of
    cutting parameters (cutting force, coating layer, spindle
    speed and feed rate) and tool condition (focusing on
    tool flank wear measurement and analysis) was
    developed. The experimental design methods developed
    in this study can be used to optimize cutting parameters
    efficiently and reliably. The drilling model based on
    cutting force was built with regression algorithms. This
    method enabled evaluation of wear status based on the
    actual force obtained from a dynamometer. The
    relationship between cutting force and tool wear was
    then formulated. The derived relation is useful for
    in-process wear monitoring, in this study, a drilling
    model based on machine vision technique was used to
    establish a direct relation between cutting parameters
    and tool wear. The object of the experiments was to
    compare the flank wear of cutting tools with different
    protective coatings. In drills operated at a spindle speed
    of 764rpm and feed rate of 0.12 mm/rev, the
    TiAlN-coated drills generated the lowest thrust and
    torque. The experimental results show that
    TiA1N-coated tools generate the least wear followed by
    TiN- and TiCN-coated tools.
    Appears in Collections:[機械工程系所] SME 2008第六屆全國精密製造研討會-國際製造工程學會中華民國分會

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