Fault diagnosis of a machine tool rotary axis based on a motor current test and the ensemble empirical mode decomposition method

Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science

Volumn 225, Issue 5, 2011, Pages 1121-1129

  Zhao, F ^a   Mei, X ^a,b   Tao, T ^a   Jiang, G ^a   Zhou, Y ^a  

^a XI'AN JIAOTONG UNIVERSITY   (China)

^b XI'AN JIAOTONG UNIVERSITY   (China)

Author keywords

Computer numerical control machine tool; Dynamic model; Ensemble empirical mode decomposition; Fault diagnosis; Rotary feed axis; Servo motor current

Indexed keywords

COMPUTER NUMERICAL CONTROL MACHINES; ENSEMBLE EMPIRICAL MODE DECOMPOSITION; FAULT DIAGNOSIS; ROTARY FEED AXIS; SERVO MOTOR CURRENT;

COMPUTER CONTROL SYSTEMS; DYNAMIC MODELS; EQUIPMENT; LOW PASS FILTERS; MACHINE TOOLS; NUMERICAL CONTROL SYSTEMS; NUMERICAL METHODS; SIGNAL DETECTION; WORM GEARS;

ELECTRIC FAULT CURRENTS;

EID: 79956045383     PISSN: 09544062     EISSN: 20412983     Source Type: Journal    
DOI: 10.1177/09544062JMES2368     Document Type: Conference Paper

References (22)

1. Tsutsumi, M. and Saito, A. Identification and compensation of systematic deviations particular to 5-axis machining centers. Int. J. Mach. Tools Manuf., 2003, 43(8), 771-780.
2. Kahraman, A. and Singh, R. Nonlinear dynamics of a spur gear pair. J. SoundVibr., 1990, 142(1), 49-75.
3. Wojnarowski, J. and Onishchenko, V. Tooth wear effects on spur gear dynamics.Mech.Mach. Theory, 2003, 38(2), 161-178.
4. Liang, S. Y., Hecker, R.L., and Landers, R. G. Machining process monitoring and control: the state-of-the-art. J.Manuf. Sci. Engng, 2004, 126(2), 297-310. (Pubitemid 40122790)
5. Plapper, L. and Weck, M. Sensorless machine tool condition monitoring based on open NCs. In Proceedings of the 2001 IEEE International Conference on Robotic and automation, Seoul, Korea, 2001, pp. 3104-3108. (Pubitemid 32815676)
6. Jeong, Y.-H., andCho, D.-W. Estimating cutting force from rotating and stationary feed motor currents on a milling machine. Int. J. Mach. Tools Manuf., 2002, 42(14), 1559- 1566. (Pubitemid 35213997)
7. Kim, G.D. and Chu, C. N. Indirect cutting force measurement considering frictional behaviour in a machining centre using feed motor current. Int. J. Adv. Manuf. Technol., 1999, 15(7), 478-484.
8. Zhou, Y. Q., Mei, X. S., and Jiang, G. D. Sensorless evaluation for computer numerical control machine tool slide level using an empirical mode decomposition method. Proc. IMechE, Part C: J. Mechanical Engineering Science, 2010, 224(C3), 721-730. DOI: 10.1243/09544062JMES1631.
9. Staszewski, W. J., Worden, K., andTomlinson, G. R.Time- frequency analysis in gearbox fault detection using the Wigner-Ville distribution and pattern recognition.Mech. Syst. Signal Process., 1997, 11(5), 673-692. (Pubitemid 127402813)
10. Meng, Q. and Qu, L. Rotating machinery fault diagnosis usingWigner distribution.Mech. Syst. Signal Process., 1991, 5(3), 155-166.
11. Staszewski, W. J. Wavelet based compression and feature selection for vibration analysis. J. Sound Vibr., 1998, 211(5), 735-760. (Pubitemid 128379322)
12. Huang, N. E., Shen, Z., and Long, S. R. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Proc. R. Soc. Lond., A, 1998, 454, 903-995. (Pubitemid 128733183)
13. Yang, Y., Yu, D. J., and Cheng, J. S. A roller bearing fault diagnosis method based on EMD energy entropy and ANN. J. SoundVibr., 2006, 294, 269-277.
14. Zhu, Z. and Sun, Y. Application of EMD and SVD in fault identification. IPEC, 2007, 2007, 1247-1250.
15. Shulin, L., Haifeng, Z., and Hui, W. Application of improvedEMDalgorithm for the fault diagnosis of reciprocating pump valves with spring failure. In Proceedings of the 9th International Symposium on ISSPA 2007, Sharjah, 2007, pp. 1-4.
16. Wu, F., andQu, L.Diagnosis of subharmonic faults of large rotating machinery based on EMD. Mech. Syst. Signal Process., 2009, 23, 467-475.
17. Loutridis, S. J. Damage detection in gear systems using empirical mode decomposition. Eng. Struct., 2004, 26, 1833-1841. (Pubitemid 40256881)
18. Wu, Z. and Huang, N. E. Ensemble empirical mode decomposition a noise assisted data analysis method. Adv. Ada. Data Anal. (AADA), 2009, 1, 1-41.
19. Yaguo, L., Zhengjia, H., and Yanyang, Z. Application of the EEMD method to rotor fault diagnosis of rotating machinery.Mech. Syst. Signal Process., 2009, 23(4), 1327- 1338.
20. Wu, T. Y. and Chung, Y. L. Misalignment diagnosis of rotating machinery through vibration analysis via the hybrid EEMD and EMD approach. Smart Mater. Struct., 2009, 18, 095004.
21. Cao, B., Li, T.-F., and Zhang, C.-Y. Study on the affection of gear fault diagnosis bases on HHT by noises. Fuzzy Inf. Eng., 2009, 2, 87-96.
22. Flandrin, P., Rilling, G., and Gonçalvés, P. Empirical modedecomposition as a filter bank. IEEE SignalProcess. Lett., 2004, 11(2), 112-114.