IN-PROCESS DRILL WEAR AND BREAKAGE MONITORING FOR A MACHINING CENTER BASED ON CUTTING FORCE PARAMETERS

被引:19
作者
LI, GS
LAU, WS
ZHANG, YZ
机构
[1] Department of Mechanical Engineering, Nanjing Aeronautical Institute, Nanjing
[2] Department of Manufacturing Engineering, Hong Kong Polytechnic, Kowloon
关键词
Computer aided manufacturing - Cutting tools - Drilling - Drilling machines (machine tools) - Drills - Flexible manufacturing systems - Machine shop practice - Machining - Monitoring;
D O I
10.1016/0890-6955(92)90035-F
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
There are many physical parameters in the cutting process that could be used for the in-process monitoring of cutting tools' working conditions. Of these parameters, cutting forces are strongly recommended by the investigators to be used because of their higher sensitivity and more rapid response to the changes in cutting states. In this paper, the variation in the dynamic behaviour of drilling thrust force and torque with drill wear, breakage and other kinds of fault forms have been investigated experimentally. The results and associated theoretical investigations indicate that, to make the monitoring system more reliable and suitable for a wider range of cutting conditions, both thrust force F(z) and torque T arising from drilling operations should be taken as associated monitoring quantities, rather than choosing just one of them. The methodology of signal signature extraction and data processing techniques are discussed and a practical monitoring strategy proposed.
引用
收藏
页码:855 / 867
页数:13
相关论文
共 8 条
  • [1] Laster, Barrow, Tool condition monitoring systems, Proc. 26th Int. Conf. MTDR, (1986)
  • [2] Martin, Brandon, Grosvenor, Owen, A comparison of in-process tool wear measurement methods in turning, Proc. 26th Int. Conf. MTDR, (1986)
  • [3] Brinksmeier, Prediction of tool fracture in drilling, Ann. CIRP, 39, (1990)
  • [4] Li, Wu, Monitoring drilling wear states by a fuzzy pattern recognition technique, Journal of Engineering for Industry, 110, (1988)
  • [5] Dornfeld, Neural network sensor fusion for tool condition monitoring, Ann. CIRP, 39, (1990)
  • [6] Jiang, Zhang, Xu, In-process monitoring of tool wear stage by frequency band-energy method, Ann. CIRP, 36, (1987)
  • [7] Huang, Zhang, Mao, A study of tool life reliability and tool wear monitoring in flexible manufacturing system, J. Nanjing Inst. Technol., 18, (1988)
  • [8] Gong, Zhu, Yu, Tool wear monitoring by using time series analysis of cutting sound, Proc. 5th Int. Mfg Conf., (1991)