한국기계가공학회지 (Journal of the Korean Society of Manufacturing Process Engineers)

  • 제15권4호
  • /
  • Pages.134-140
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  • 2016
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  • 1598-6721(pISSN)
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  • 2288-0771(eISSN)
한국기계가공학회 (The Korean Society of Manufacturing Process Engineers)
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머시닝센터 주축 고장예측에 관한 연구

A Study on Diagnosis and Prognosis for Machining Center Main Spindle Unit

  • Lee, Tae-Hong (Department of Mechanical Engineering, Osan University)
  • 투고 : 2016.05.31
  • 심사 : 2016.06.30
  • 발행 : 2016.08.31
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초록

Main Spindle System has effect on performance of machine tools and working quality as well as is required of high reliability. Especially, it takes great importance in producing automobiles which includes a large number of working processes. However, main spindle unit in Machine tools are often cases where damage occurs do not meet the design life due to driving in harsh environments. This is when excessive maintenance and repair of machine tools or for damage stability has resulted in huge economic losses. Therefore, this studying propose a method of accelerated life test for diagnosing and prognosis the state of life assessment main spindle system. Time status monitoring of diagnostic data - through the analysis of the frequency band signals were carried out inside the main spindle bearing condition monitoring and fault diagnosis.

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참고문헌

  1. Lee, S. H. and Kim, J. S., "The Failure Mode Analysis of Machine Tools using Performance Test,: Proceeding of KSPE 2002 Spring Conference, pp. 90-93, 2002.
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  8. Randall, R. B., and Antoni, J., "Rolling element bearing diagnostics-A tutorial." Mechanical Systems and Signal Processing, Vol. 25, No. 2 pp. 485-520, 2011 https://doi.org/10.1016/j.ymssp.2010.07.017
  9. Hyundai WIA-Seoul National University-Industry Cooperation Agency "Diagnosis and Prognosis Machine-tool Spindle Unit", University-Industry Report, 2014
  10. Park, D. K and Cho, Y. T et al "Optimal Design Techniques of the Ultra Precision Cutting Unit through using Optimized Bearing positioning and Latest Lubrication Systems" J. of the Korean Society of Manufacturing Process Engineers, Vol.13 No.6, pp.15-22, 2014. https://doi.org/10.14775/ksmpe.2014.13.6.015
  11. Choi, J.W. "Development of a Tool for Automation of Analysis of a Spindle System of Machine Tools", J. of the Korean Society of Manufacturing Process Engineers, Vol.14 No.2, pp.121-126, 2015. https://doi.org/10.14775/ksmpe.2015.14.2.121

피인용 문헌

  1. A Study on Fault Classification of Machining Center using Acceleration Data Based on 1D CNN Algorithm vol.18, pp.9, 2019, https://doi.org/10.14775/ksmpe.2019.18.9.029
  2. Development of Diagnosis Algorithm for Cam Wear of Paper Container Using Machine Learning vol.36, pp.10, 2016, https://doi.org/10.7736/kspe.2019.36.10.953