TSK fuzzy modeling for tool wear condition in turning processes: An experimental study

被引：31
|
作者：
Ren, Qun [1 ]
Balazinski, Marek [1 ]
Baron, Luc [1 ]
Jemielniak, Krzysztof [2 ]
机构：
[1] Ecole Polytech, Dept Mech Engn, Montreal, PQ H3C 3A7, Canada
[2] Warsaw Univ Technol, Fac Prod Engn, PL-02524 Warsaw, Poland
来源：
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE | 2011年 / 24卷 / 02期
关键词：
TSK fuzzy modeling; Tool wear condition; Subtractive clustering; IDENTIFICATION; SYSTEMS; RULES;
D O I：
10.1016/j.engappai.2010.10.016
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper presents an experimental study for turning process in machining by using Takagi-Sugeno-Kang (TSK) fuzzy modeling to accomplish the integration of multi-sensor information and tool wear information. It generates fuzzy rules directly from the input-output data acquired from sensors, and provides high accuracy and high reliability of the tool wear prediction over a wide range of cutting conditions. The experimental results show its effectiveness and satisfactory comparisons relative to other artificial intelligence methods. (C) 2010 Elsevier Ltd. All rights reserved.
引用
收藏
页码：260 / 265
页数：6
相关论文
共 50 条
  • [1] Uncertainty Prediction for Tool Wear Condition Using Type-2 TSK Fuzzy Approach
    Ren, Qun
    Balazinski, Marek
    Baron, Luc
    2009 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS (SMC 2009), VOLS 1-9, 2009, : 660 - 665
  • [2] Tool wear condition monitoring in drilling processes using fuzzy logic
    Yumak, Onder
    Ertunc, H. Metin
    NEURAL INFORMATION PROCESSING, PT 3, PROCEEDINGS, 2006, 4234 : 508 - 517
  • [3] Experimental Investigation to Predict Tool Wear and Vibration Displacement in Turning - A Base for Tool Condition Monitoring
    Babu, M. Prakash
    Prasad, Balla Srinivasa
    JOURNAL FOR MANUFACTURING SCIENCE AND PRODUCTION, 2016, 16 (02) : 103 - 114
  • [4] Experimental Study of Turning Temperature and Turning Vibration for the Tool of Different Wear State
    Li, Shuncai
    Yu, Qiu
    Yuan, Guanlei
    Liang, Li
    2017 INTERNATIONAL SYMPOSIUM ON APPLICATION OF MATERIALS SCIENCE AND ENERGY MATERIALS (SAMSE 2017), 2018, 322
  • [5] Hybrid Incremental Modeling Based on Least Squares and Fuzzy K-NN for Monitoring Tool Wear in Turning Processes
    Penedo, Francisco
    Haber, Rodolfo E.
    Gajate, Agustin
    del Toro, Raul M.
    IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2012, 8 (04) : 811 - 818
  • [6] An experimental study on the effect of tool geometry on tool wear and surface roughness in hard turning
    Pham Minh Duc
    Le Hieu Giang
    Mai Duc Dai
    Do Tien Sy
    ADVANCES IN MECHANICAL ENGINEERING, 2020, 12 (09)
  • [7] Study on the tool wear in turning fluorophlogopite
    Qinhuangdao Institute of Technology, Qinhuangdao 066100, China
    不详
    不详
    Zhongguo Jixie Gongcheng, 2007, 17 (2098-2101):
  • [8] Real-time tool wear condition monitoring in turning
    Li, XL
    INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2001, 39 (05) : 981 - 992
  • [9] Feature selection for tool condition monitoring in turning processes
    Rodriguez-Salgado, D.
    Cambero-Rivero, I.
    Alonso-Sanchez, F. J.
    ADVANCES IN MATERIALS PROCESSING TECHNOLOGIE, 2006, 526 : 97 - 102
  • [10] MODELING OF TOOL WEAR BASED ON CUTTING FORCES IN TURNING
    RAVINDRA, HV
    SRINIVASA, YG
    KRISHNAMURTHY, R
    WEAR, 1993, 169 (01) : 25 - 32
12345