1343. Online milling tool condition monitoring with a single continuous hidden Markov models approach

被引:0
作者
机构
[1] [1,Chen, Lu
[2] 1,Tieying, Li
[3] Hongmei, Liu
来源
Hongmei, Liu (liuhongmei@buaa.edu.cn) | 1600年 / Vibromechanika卷 / 16期
关键词
D O I
暂无
中图分类号
学科分类号
摘要
引用
收藏
相关论文
共 50 条
  • [31] Multimodal Hidden Markov Model-Based Approach for Tool Wear Monitoring
    Geramifard, Omid
    Xu, Jian-Xin
    Zhou, Jun-Hong
    Li, Xiang
    IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2014, 61 (06) : 2900 - 2911
  • [32] A multi-sensor based online tool condition monitoring system for milling process
    Zhang, X. Y.
    Lu, X.
    Wang, S.
    Wang, W.
    Li, W. D.
    51ST CIRP CONFERENCE ON MANUFACTURING SYSTEMS, 2018, 72 : 1136 - 1141
  • [33] ONLINE CONDITION MONITORING OF TOOL WEAR IN END MILLING USING ACOUSTIC-EMISSION
    OSURI, RH
    CHATTERJEE, S
    CHANDRASHEKHAR, S
    INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 1991, 29 (07) : 1339 - 1353
  • [34] Markov Transition Field Enhanced Deep Domain Adaptation Network for Milling Tool Condition Monitoring
    Sun, Wei
    Zhou, Jie
    Sun, Bintao
    Zhou, Yuqing
    Jiang, Yongying
    MICROMACHINES, 2022, 13 (06)
  • [35] A novel online tool condition monitoring method for milling titanium alloy with consideration of tool wear law
    Qin, Bo
    Wang, Yongqing
    Liu, Kuo
    Jiang, Shaowei
    Luo, Qi
    MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2023, 199
  • [36] A decision fusion algorithm for tool condition monitoring in drilling using Hidden Markov Model (HMM)
    Natarajan, U
    Arun, P
    Periasamy, VM
    INDIAN JOURNAL OF ENGINEERING AND MATERIALS SCIENCES, 2006, 13 (02) : 103 - 109
  • [37] Network anomaly detection by continuous hidden markov models: An evolutionary programming approach
    Flores, Juan J.
    Calderon, Felix
    Antolino, Anastacio
    Garcia, Juan M.
    INTELLIGENT DATA ANALYSIS, 2015, 19 (02) : 391 - 412
  • [38] A tool wear condition monitoring approach for end milling based on numerical simulation
    Zhu Q.
    Sun W.
    Zhou Y.
    Gao C.
    Eksploatacja i Niezawodnosc, 2021, 23 (02): : 371 - 380
  • [39] A comparative evaluation of neural networks and hidden Markov models for monitoring turning tool wear
    Scheffer, C
    Engelbrecht, H
    Heyns, PS
    NEURAL COMPUTING & APPLICATIONS, 2005, 14 (04) : 325 - 336
  • [40] Online Tool Wear Monitoring Via Hidden Semi-Markov Model With Dependent Durations
    Zhu, Kunpeng
    Liu, Tongshun
    IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2018, 14 (01) : 69 - 78