참고문헌
- 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.
- Lee, T. H., "A Study on the Failure and Life Assessment of High Speed Spindle" Journal of the Korean Society for Precision Engineering, Vol. 31, No. 1, pp. 67-73, 2014. https://doi.org/10.7736/KSPE.2014.31.1.67
- Shin H. R. and Hong W. P., "Reliability Prodiction for Machining Center Spindle", Proceeding of KSME 2010 Spring Conference, pp. 25-26, 2010.
- Hyundai WIA Corp. Performance Evaluation Standards for Machining Center Ver.4.0, 2006.
- NSK Ltd, Rolling Bearings, Motion & Control, pp. A29-A30. 2005.
- Weibull Database, Barringer & Associates, Inc., http://www.barringer1.com/ (accessed 1 Aug. 2016)
- Zhou, W., Habetler, T. G., and Harley, R. G., "Bearing condition monitoring methods for electric machines: A general review." Diagnostics for Electric Machines, Power Electronics and Drives, 2007. SDEMPED 2007. IEEE International Symposium on. IEEE, 2007.
- 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
- Hyundai WIA-Seoul National University-Industry Cooperation Agency "Diagnosis and Prognosis Machine-tool Spindle Unit", University-Industry Report, 2014
- 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
- 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
- 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
- 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