期刊文献+

工业机器人故障诊断方法发展现状及发展方向 被引量:4

Development Status and Development Direction of Fault Diagnosis Methods for Industrial Robots
下载PDF
导出
摘要 由于工业机器人运行环境恶劣,因此,其极易发生故障,而加强工业机器人故障诊断是实现工业机器人安全运行的重要手段。基于此,本文总结了当前工业机器人常用的故障诊断方法,分析了各个方法的优缺点,最后对工业机器人故障诊断方法的发展前景进行了展望。 Because of the bad running environment of industrial robot,it is easy to break down.Strengthening the fault diagnosis of industrial robot is an important means to realize the safe operation of industrial robot.Based on this,this paper summarized the current industrial robot fault diagnosis methods,analyzed the advantages and disadvantag⁃es of each method,and finally prospected the development prospects of industrial robot fault diagnosis methods.
作者 赵亮 ZHAO Liang(Zhengzhou Railway Vocational&Technical College,Zhengzhou Henan 451460)
出处 《河南科技》 2020年第28期37-39,共3页 Henan Science and Technology
关键词 工业机器人 故障诊断方法 发展方向 industrial robots fault diagnosis method development direction
  • 相关文献

参考文献5

二级参考文献24

  • 1毕果,陈进,周福昌,何俊,李富才.调幅信号谱相关密度分析中白噪声影响的研究[J].振动与冲击,2006,25(2):75-78. 被引量:13
  • 2SMC(中国)有限公司.现代实用气动技术[M].北京:机械工业出版社,2003.10.
  • 3MESSINA A,GIANNOCCARO N,GENTILE A.Experimenting and modelling PWM-based pneumatic actuators[J].Mechatronics,2005,15(7):859-881.
  • 4SHEN Xiangrong,ZHANG Jianlong,MICHAEL goldfarb.Nonlinear averaging applied to the control of pulse Width modulated (PWM) pneumatic systems[C]//Proceeding of the 2004 Amerlcan Control Conference Boston.Massachusetts:AACC,2004:4444-4448.
  • 5CHATTERJEE A,SIARRY P.Nonlinear inertia weight variation for dynamic adaptation in Particle swarm optimization[J].Computers & Operations Research,2006,33:859-871.
  • 6N DalaUB Triggs. Computer vision and pattern rec-ognition [Cj.IEEE Conference on Computer Visionand Pattern Recognition,San Diego,CA,USA,2005.
  • 7F Suard, A Rakotomamonjy,A Bensrhair,et al. In-telligent vehicles symposium [Cj.IEEE Conferenceon Intelligent Vehicles Symposium, Tokyo, 2006.
  • 8Y F'reund,R Schapire.八 decision-theoretic general-ization of on-line learning and an application toboosting [J].Journal of Computer and System Sci-ences, 1997,55( 1) : 119-139.
  • 9H Bay, T Tuytelaars, L Van Gool. SURF: SpeededUp Robust Features [J].Computer Vision and ImageUnderstanding, 2008,110(3): 404-417.
  • 10Alexander Kuranov,Rainer Lienhart,Vadim Pisarevsky.Pattern recognition[C].In DAGM 25th Pattern Rec-ognition Symposium, Berlin, 2003.

共引文献47

同被引文献10

引证文献4

二级引证文献2

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