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Modeling of acoustic emission based on the experimental and theoretical methods and its application in face grinding

  • Jing Li
  • Xiaolu Wang
  • Nanyan Shen
  • Huayu Gao
  • Chen Zhao
  • Yu Wang
ORIGINAL ARTICLE
  • 36 Downloads

Abstract

Acoustic emission (AE) is widely used in the application of grinding monitoring, but few studies have been conducted on the quantitative relationship between the amplitude of AE signal and grinding parameters. In order to obtain the quantitative description and solve the problem of threshold recommendation in using AE signal to monitor grinding process, this paper proposes an amplitude model of AE signal of face grinding based on experimental and theoretical researches. The exponential relationship between grinding force and amplitude of AE signal under a certain condition of the fixed grinding wheel speed is achieved by experimental study. By establishing the theoretical model of the grinding force and cutting depth, the mathematical model between the amplitude of AE signal and the grinding parameters of face grinding is obtained indirectly. The experimental results prove the validity of the amplitude model of AE signal and its effectiveness in the automatic recommendation of the threshold for collision detection in face grinding.

Keywords

Acoustic emission Axial grinding force Face grinding Cutting depth Collision detection 

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Notes

Acknowledgments

Thanks are due to Shanghai Machine Tool Works Co., LTD for its technical support.

Funding information

The authors would like to thank the financial support from National Science and Technology Major Project of China (No. 2016X04004003).

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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2018

Authors and Affiliations

  • Jing Li
    • 1
  • Xiaolu Wang
    • 1
  • Nanyan Shen
    • 1
  • Huayu Gao
    • 1
  • Chen Zhao
    • 1
  • Yu Wang
    • 2
  1. 1.Shanghai Key Laboratory of Intelligent Manufacturing and Robotics, School of Mechatronic Engineering and AutomationShanghai UniversityShanghaiChina
  2. 2.Shanghai Machine Tool Works Co., LTDShanghaiChina

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