期刊文献+

基于功率信息的航空发动机叶片铣削刀具监测试验研究 被引量:4

Research on Monitoring Test of Milling Tool for Aero-Engine Blade Based onPower Information
下载PDF
导出
摘要 针对航空发动机叶片铣削加工过程中刀具加工状态不易实时监控、更换刀具依赖加工经验等问题,利用基于功率信息的刀具状态监测方法,开发了刀具状态监测系统。通过三相功率传感器实时采集加工过程中机床主轴的功率信号,并对信号数据进行数据筛选、数据分析、离线学习,计算出功率阈值区间,以功率阈值区间为监测标准,实现了对刀具加工过程的监测以及对刀具寿命的预测。以航空发动机压气机叶片的铣削加工过程为研究对象,进行了刀具状态监测试验。结果表明,基于功率信息的刀具状态监测方法可以实现对航空发动机叶片铣刀加工状态的实时监测及对刀具剩余寿命的预测。 In view of the problems in the milling process of aero-engine blade,such as tool status is not easy to be observed and tool change depends on experience,a tool condition monitoring system is developed by using the tool status monitoring method based on power information.In the process of machining,the power signal of machine tool spindle is collected by three-phase power sensor in real time,and the signal data is filtered,analyzed and learned off-line,and the power threshold interval is calculated.The power threshold interval is used as the monitoring standard to realize the monitoring of tool machining process and the prediction of tool life.The milling process of aero-engine compressor blade is taken as the research object,and the tool condition monitoring test is carried out.The results show that through the tool condition monitoring method based on power information,the real-time monitoring of the machining condition for aeroengine blade milling tool and the prediction of the remaining life of the tool can be realized.
作者 乔石 刘阔 都书博 王鹏飞 王永青 QIAO Shi;LIU Kuo;DU Shubo;WANG Pengfei;WANG Yongqing(Dalian University of Technology,Dalian 116024,China;AECC Guizhou Liyang Aviation Power Co.,Ltd.,Guiyang 550000,China)
出处 《航空制造技术》 CSCD 北大核心 2021年第16期87-92,110,共7页 Aeronautical Manufacturing Technology
基金 辽宁省“兴辽英才计划”项目(XLYC1807081) 辽宁省科技重大专项(2020JH1/10100016)。
关键词 航空发动机叶片 主轴功率 离线学习 刀具状态监测 刀具寿命预测 Aero-engine blade Spindle power Off-line learning Tool condition monitoring Tool life prediction
  • 相关文献

参考文献7

二级参考文献66

  • 1许国康.自动钻铆技术及其在数字化装配中的应用[J].航空制造技术,2005,48(6):45-49. 被引量:27
  • 2王增强,孟晓娴,任军学,胡创国.复杂薄壁零件数控加工变形误差控制补偿技术研究[J].机床与液压,2006,34(4):61-63. 被引量:22
  • 3高宏力,许明恒,傅攀,杜全兴.基于动态树理论的刀具磨损监测技术[J].机械工程学报,2006,42(7):227-230. 被引量:24
  • 4王海丽.刀具状态多传感器监控策略的研究[M].上海:上海交通大学机械工程学院,1999..
  • 5KRAMER B M. A Comprehensive Tool Wear Model [ J ]. Annals of CIPP, 1986,35 ( 1 ) : 67 - 70.
  • 6DAN 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.
  • 7BERNHARD 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.
  • 8ERKKI Jantunen. A Summary of Methods Applied to Tool Condition Monitoring in Drilling [ J ]. International Journal of Machine Tools & Manufacture,2002,42:997 - 1010.
  • 9TETI R, JEMIELNIAK K. Advanced Monitoring of Machi- ning Operations [ J]. CIRP Annals-Manufacturing Technolo- gy,2010,59:718.
  • 10DIMLA 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.

共引文献39

同被引文献68

引证文献4

二级引证文献1

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