EXPERIMENTAL STUDY OF SOUND SIGNAL FOR TOOL CONDITION MONITORING IN MICRO MILLING PROCESSES

被引：0
|
作者：
Yen, Chia-Liang [1 ]
Lin, Ching-Yuan
Lu, Ming-Chyuan [1 ]
Chen, Tin-Hong [1 ]
机构：
[1] Natl Chung Hsing Univ, Dept Mech Engn, Taichung 402, Taiwan
来源：
MSEC 2008: PROCEEDINGS OF THE ASME INTERNATIONAL MANUFACTURING SCIENCE AND ENGINEERING CONFERENCE 2008, VOL 2 | 2009年
关键词：
FLANK WEAR;
D O I：
暂无
中图分类号：
Q81 [生物工程学（生物技术）]; Q93 [微生物学];
学科分类号：
071005 ; 0836 ; 090102 ; 100705 ;
摘要：
The audible sound signals obtained in micro-milling processes are analyzed in the time and frequency domain for the tool wear and breakage monitoring. Micro end-mills of phi 700 mu m are implemented in the tool wear test, along with a high speed spindle with speed up to 60000 rpm. The audible sound signals and vibration signals for different tool conditions were collected simultaneously in the cutting. After transferring data from time domain to the frequency domain, as well as the Wavelet coefficients, the capability of audible sound signals in detecting the tool condition for the micro milling process was evaluated.
引用
收藏
页码：257 / 264
页数：8
相关论文
共 50 条
  • [1] Study of Sound Signal for Tool Wear Monitoring System in Micro-milling Processes
    Chen, Tin-Hong
    Lu, Ming-Chyuan
    Chiou, Shean-Juinn
    Lin, Ching-Yuan
    Lee, Ming-Hsing
    [J]. PROCEEDINGS OF THE ASME INTERNATIONAL MANUFACTURING SCIENCE AND ENGINEERING CONFERENCE, VOL 2, 2009, : 57 - 65
  • [2] Face milling tool condition monitoring using sound signal
    Madhusudana C.K.
    Kumar H.
    Narendranath S.
    [J]. International Journal of System Assurance Engineering and Management, 2017, 8 (Suppl 2) : 1643 - 1653
  • [3] Tool condition monitoring in micro milling of brittle materials
    Gong, Zheng
    Huo, Dehong
    [J]. PRECISION ENGINEERING-JOURNAL OF THE INTERNATIONAL SOCIETIES FOR PRECISION ENGINEERING AND NANOTECHNOLOGY, 2024, 87 : 11 - 22
  • [4] Review of tool condition monitoring methods in milling processes
    Yuqing Zhou
    Wei Xue
    [J]. The International Journal of Advanced Manufacturing Technology, 2018, 96 : 2509 - 2523
  • [5] Review of tool condition monitoring methods in milling processes
    Zhou, Yuqing
    Xue, Wei
    [J]. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2018, 96 (5-8): : 2509 - 2523
  • [6] Study of AE signal for Tool Wear Monitoring in Micro Milling Based on LVQ Algorithm
    Yen, Chia-Liang
    Lu, Ming-Chyuan
    Chen, Jau-Liang
    [J]. ADVANCES IN ABRASIVE TECHNOLOGY XIII, 2010, 126-128 : 719 - 725
  • [7] A machine vision system for micro-milling tool condition monitoring
    Dai, Yiquan
    Zhu, Kunpeng
    [J]. PRECISION ENGINEERING-JOURNAL OF THE INTERNATIONAL SOCIETIES FOR PRECISION ENGINEERING AND NANOTECHNOLOGY, 2018, 52 : 183 - 191
  • [8] Cutting force denoising in micro-milling tool condition monitoring
    Zhu, K.
    Hong, G. S.
    Wong, Y. S.
    Wang, W.
    [J]. INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2008, 46 (16) : 4391 - 4408
  • [9] Tool Condition Monitoring in Micro-End Milling using wavelets
    Dubey, N. K.
    Roushan, A.
    Rao, U. S.
    Sandeep, K.
    Patra, K.
    [J]. INTERNATIONAL CONFERENCE ON RECENT ADVANCES IN MATERIALS & MANUFACTURING TECHNOLOGIES, 2018, 346
  • [10] Sound singularity analysis for milling tool condition monitoring towards sustainable manufacturing
    Zhou, Chang'an
    Guo, Kai
    Sun, Jie
    [J]. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2021, 157
12345