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Research on Fault Diagnosis Technology of CNC Machine Tool Based on Machining Surface Roughness Cover

Research on Fault Diagnosis Technology of CNC Machine Tool Based on Machining Surface Roughness

Open Access
|Apr 2018

References

  1. [1] Zhang Jian, based on the image of the workpiece surface roughness detection system research [D], Nanjing University of Aeronautics and Astronautics, 2011.
  2. [2] Xu Xiao Mei, Hu Hong. Development of non-contact surface roughness measurement in last decades [J]. ICMTMA 2009, 1:210-213.
  3. [3] MAO Chun-yu, ZHOU Guang-Wen, XU Yu-kun,Research of Pre-Rotating Machinery Fault Diagnosis Based on Fuzzy Neural Network And Information Fusion, International Symposium on Computer, Consumer and Control, Taiwan, 2014.06.10-12.
  4. [4] Wang Jiahai, Huang Jiangtao, Shen Bin, and so on. Research Status and Prospect of CNC machine tools Intelligent Fault Diagnosis [J]. Machinery manufacturing, 2014 (5): 30 – 32.
  5. [5] FERREIRO S, SIERRA B, IRIGOIEN I, et al. A bayesiannetwork for burr detection in the drilling process [J]. Journalof Intelligent Manufacturing, 2012, 23 (5): 1463-1475.
  6. [6] JOSéVICENTE ABELLáN NEBOT, FERNANDO ROMEROSUBIRON. A review of machining monitoring systems basedon artificial intelligence process models [J]. International Journal of Advanced Manufacturing Technology, 2010, 47 (1/2/3/4): 237-258.
  7. [7] Wang Jianguo, WU Qing, Qin Bo, and so on. Prediction with oxygen [J] PSO support vector machine BOF. Foundry Technology, 2014 (8): 1806-1809.
  8. [8] Wang Jiahai, Huang Jiangtao, Shen Bin, and so on. Research Status and Prospect of CNC machine tools Intelligent Fault Diagnosis [J]. Machinery manufacturing, 2014 (5): 30 – 32.
  9. [9] SUN Yan-jie, AI Chang-sheng.Study on tool wear state monitoring based on fusion of cutting and cutting force parameters [J]. Combined Machine Tool and Automation Processing Technology ,2011 (05).
  10. [10] XIAO Hong-jun.Fuzzy Control and Experiment of Inverted Pendulum Based on Sugeno Model [J]. Journal of Xi’an Engineering University, 2011 (05).
  11. [11] MAO Chun-yu, ZHOU Guang-Wen, TIAN Mei, esearch Early Mechanical Failure of CNC Motorized Spindle Prediction Method Base on D-S Evidence Theory Information Fusion, IMEICI 2016, Shengyang, china, 2016.09.24-26.
Language: English
Page range: 98 - 102
Published on: Apr 12, 2018
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2018 Zhou Guang-wen, Mao Chun-yu, Tian Mei, Sun Yan-hong, published by Xi’an Technological University
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.