Multi-Sensory Tool Holder for Process Force Monitoring and Chatter Detection in Milling

被引:0
|
作者
Schuster, Alexander [1 ]
Otto, Andreas [1 ]
Rentzsch, Hendrik [1 ]
Ihlenfeldt, Steffen [1 ]
机构
[1] Fraunhofer Inst Machine Tools & Forming Technol IW, D-09126 Chemnitz, Germany
关键词
smart tool holder; sensor integrated; process monitoring; chatter; cutting force; vibration; DYNAMOMETER;
D O I
10.3390/s24175542
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Sensor-based monitoring of process and tool condition in milling is a key technology for improving productivity and workpiece quality, as well as enabling automation of machine tools. However, industrial implementation of such monitoring systems remains a difficult task, since they require high sensitivity and minimal impact on CNC machines and cutting conditions. This paper presents a novel multi-sensory tool holder for measurement of process forces and vibrations in direct proximity to the cutting tool. In particular, the sensor system has an integrated temperature sensor, a triaxial accelerometer and strain gauges for measurement of axial force and bending moment. It is equipped with a self-sufficient electric generator and wireless data transmission, allowing for a tool holder design without interfering contours. Milling and drilling experiments with varying cutting parameters are conducted. The measurement data are analyzed, pre-processed and verified with reference signals. Furthermore, the suitability of all integrated sensors for detection of dynamic instabilities (chatter) is investigated, showing that bending moment and tangential acceleration signals are the most sensitive regarding this monitoring task.
引用
收藏
页数:23
相关论文
共 50 条
  • [31] Detection of tool deflection in milling by a sensory axis slide for machine tools
    Denkena, Berend
    Litwinski, Kai Martin
    Boujnah, Haythem
    MECHATRONICS, 2016, 34 : 95 - 99
  • [32] Early chatter detection in thin-walled workpiece milling process based on multi-synchrosqueezing transform and feature selection
    Yan, Shichao
    Sun, Yuwen
    MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2022, 169
  • [33] Analysis and implementation of chatter frequency dependent constrained layer damping tool holder for stability improvement in turning process
    Liu, Yang
    Liu, Zhanqiang
    Song, Qinghua
    Wang, Bing
    JOURNAL OF MATERIALS PROCESSING TECHNOLOGY, 2019, 266 : 687 - 695
  • [34] Diamond tool wear monitoring by sensory analysis in milling of absolute black granite
    Turchetta, Sandro
    Sorrentino, Luca
    Parodo, Gianluca
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE, 2022, 236 (05) : 625 - 635
  • [35] A novel chatter detection method in micro-milling process using wavelet packet entropy
    Jing, Xiubing
    Yang, He
    Song, Xiaofei
    Chen, Yun
    Li, Huaizhong
    INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2024, 131 (9-10): : 5289 - 5303
  • [36] Early chatter detection in end milling based on multi-feature fusion and 3σ criterion
    Cao, Hongrui
    Zhou, Kai
    Chen, Xuefeng
    Zhang, Xingwu
    INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2017, 92 (9-12): : 4387 - 4397
  • [37] Detection process approach of tool wear in high speed milling
    Kious, M.
    Ouahabi, A.
    Boudraa, M.
    Serra, R.
    Cheknane, A.
    MEASUREMENT, 2010, 43 (10) : 1439 - 1446
  • [38] Virtual milling force monitoring method based on in-process milling force prediction model to eliminate predetermination of cutting coefficients
    Kaneko, Kazuki
    Nishida, Isamu
    Sato, Ryuta
    Shirase, Keiichi
    8TH CIRP CONFERENCE ON HIGH PERFORMANCE CUTTING (HPC 2018), 2018, 77 : 22 - 25
  • [39] A novel online chatter detection method in milling process based on multiscale entropy and gradient tree boosting
    Li, Kai
    He, Songping
    Li, Bin
    Liu, Hongqi
    Mao, Xinyong
    Shi, Chengming
    MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2020, 135
  • [40] Micro-Milling Tool Wear Monitoring via Nonlinear Cutting Force Model
    Liu, Tongshun
    Wang, Qian
    Wang, Weisu
    MICROMACHINES, 2022, 13 (06)