期刊文献+

刀具磨损在线监测研究现状与发展 被引量:17

Recent Development and Study of Online Monitoring of Tool-wear
下载PDF
导出
摘要 金属加工过程中,切削刀具的状态对于生产效率和表面加工质量有重要影响,因此刀具磨损在线监测具有重要意义。介绍了最近几年常用的刀具磨损在线监测方法,包括切削力、振动、声发射、温度、电流与功率信号,分析了每种信号的监测方法及其特点,并与实验结果进行了对比。提出了多传感器融合技术能有效避免单独使用一种检测手段的弊端。 In the process of metal machining,the state of the cutting tool has great influence on the efficiency of production and surface quality,therefore,tool wear online monitoring is of great significance. The commonly used online tool wear monitoring methods in recent years were introduced,including cutting forces,vibrations,acoustic emission,temperature,current and power signal. The monitoring methods of each signal and its characteristics were analyzed and compared with the experimental results. It is proposed that multi-sensor synthesis technique can effectively avoid the shortcoming of the method of using one single test.
机构地区 华中科技大学
出处 《机床与液压》 北大核心 2014年第19期174-180,共7页 Machine Tool & Hydraulics
基金 国家高技术研究发展计划(863计划)(2013AA041108)
关键词 刀具磨损在线监测 切削力 切削温度 切削振动 电流功率 声发射 Online monitoring of tool wear Cutting force Temperature signal Vibration signal Current and power signal Acoustic emission signal
  • 相关文献

参考文献48

  • 1KRAMER B M. A Comprehensive Tool Wear Model [ J ]. Annals of CIPP, 1986,35 ( 1 ) : 67 - 70.
  • 2DAN L, MATHEW J. Tool Wear and Failure Monitoring Techniques for Turning-A Review [ J ]. International Journal of Machine Tools and Manufacture, 1990,30:579 - 598.
  • 3BERNHARD Sick. On-line and Indirect Tool Wear Monito- ring in Turning with Artificial Neural Networks : A Review of More than a Decade of Research[ J]. Mechanical System and Signal Processing,2002,16 (4) :487 - 546.
  • 4ERKKI Jantunen. A Summary of Methods Applied to Tool Condition Monitoring in Drilling [ J ]. International Journal of Machine Tools & Manufacture,2002,42:997 - 1010.
  • 5TETI R, JEMIELNIAK K. Advanced Monitoring of Machi- ning Operations [ J]. CIRP Annals-Manufacturing Technolo- gy,2010,59:718.
  • 6DIMLA E, DIMLA Snr. Sensor Signals for Tool-wear Moni- toring in Metal Cutting Operations-a Review of Methods [ J ]. International Journal of Machine Tools & Manufac- ture, 2000,40 : 1073 - 1098.
  • 7CHOUDHARY S K, JAIN V K, RAMO Rao ChVV. On- line Monitoring of Tool Wear in Turning Using a Neural Network[ J ]. International Journal of Machine Tools and Manufacture, 1999,39 ( 3 ) :489 - 504.
  • 8LIN S C, LIN R J. Tool Wear Monitoring in Face Milling Using Force Signals [ J ]. Wear, 1996,198 (1/2) : 136 - 142.
  • 9DU R. Signal Understanding and Tool Condition Monito- ring [ J ]. Engineering Applications of Artificial Intelli- gence, 1999 (12) : 585 - 597.
  • 10TETI R, JEMIELNIAK K, DONNELL G O, et al. Ad- vanced Monitoring of Machining Operations [ J ]. CIRP Annals-Manufacturing Technology ,2010,59:717 - 739.

二级参考文献25

  • 1闵睿,许黎明,魏臣隽,胡德金.机械加工系统运行状态异常检测方法的研究[J].仪器仪表学报,2006,27(z3):1777-1778. 被引量:9
  • 2孙旭东,王爱玲.基于LabVIEW的数控加工虚拟在线监测系统研究[J].机械工程与自动化,2006(2):99-101. 被引量:7
  • 3吴宗凡.红外与激光技术[M].北京:国防工业出版社,1998.83-85.
  • 4[1]TRANG Y S, LEE B Y. Use of model-based cutting simulation system for tool breakage monitoring in milling [J].Int J Mach Tools Manufact, 1992, 32(5): 641-649.
  • 5[2]MATSUSHINMA K, BERTOK P, SATA T. In-process detectio of tool breakage monitoring the spindle motor current of a machine tool measurement and control for batch manufacturing[M]. Phoenix: Arizona, 1982.
  • 6[3]DAUBECHINES I. Othonormal bases of compactly supported wavelet [J]. Commentions on Pure and Applied Mathematics, 1998, 41: 909-996.
  • 7[4]RIOUL O, DUHAMEL P. Fast algorithms for discrete and continuous wavelet transforms[J]. IEEE Trains on Information Theory, 1992, 38(2): 569-686.
  • 8Hong G S,Int J Mach Tools Manuf,1996年,36卷,5期,551页
  • 9Wu Ya,Mech Syst Signal Processing,1996年,10卷,1期,29页
  • 10Ko T J,J Manufacturing Systems,1995年,14卷,2期,80页

共引文献79

同被引文献91

引证文献17

二级引证文献79

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部