Remaining useful life estimation based on nonlinear feature reduction and support vector regression
Tóm tắt
Từ khóa
Tài liệu tham khảo
AFNOR, 2005. Condition monitoring and diagnostics of machines—prognostics—part 1: general guidelines. NF ISO 13381-1.
Collobert, 2001, SVMTorch, J. Mach. Learn. Res., 1, 143
Demiriz, 2001, Support vector machine regression in chemometrics, Comput. Sci. Stat
Gebraeel, 2004, Residual life predictions from vibration-based degradation signals, IEEE Trans. Ind. Electron., 51, 694, 10.1109/TIE.2004.824875
Haitao, L., Wenbiao, Z., Huairui, 2006. Predicting remaining useful life of an individual unit using proportional hazards model and logistic regression model, in: Reliability and Maintainability Symposium, RAMS’06, pp. 127–132.
Heng, 2009, Rotating machinery prognostics, Mech. Syst. Signal Process., 23, 724, 10.1016/j.ymssp.2008.06.009
Huang, 2007, Residual life predictions for ball bearings based on self-organizing map and back propagation neural network methods, Mech. Syst. Signal Process., 21, 193, 10.1016/j.ymssp.2005.11.008
Jackson, 1991
Jardine, 2006, A review on machinery diagnostics and prognostics implementing condition-based maintenance, Mech. Syst. Signal Process., 20, 1483, 10.1016/j.ymssp.2005.09.012
Lebold, M., Thurston, M., 2001. Open standards for condition-based maintenance and prognostic systems, in: Proceedings of the 5th Maintenance and Reliability Conference (MARCON).
Liao, 2009, A novel method for machine performance degradation assessment based on fixed cycle features test, J. Sound Vib., 326, 894, 10.1016/j.jsv.2009.05.005
Lingjun, 2005, Condition evaluation for mechanical equipment by means of support vector data description, Chin. J. Mech. Sci. Technol., 24, 1426
Maaten, L.J.P.V.D., Postma, E.O., Herik, H.J.V.D., 2009. Dimensionality Reduction: A Comparative Review, Tilburg University Technical Report, tiCC-TR 2009-005.
Malhi, 2004, PCA-based feature selection scheme for machine defect classification, IEEE Trans. Instrum. Meas., 53, 1517, 10.1109/TIM.2004.834070
Medjaher, 2012, Remaining useful life estimation of critical components with application to bearings, IEEE Trans. Reliab., 61, 292, 10.1109/TR.2012.2194175
Samko, 2006, Selection of the optimal parameter value for the ISOMAP algorithm, Pattern Recognition Lett., 27, 968, 10.1016/j.patrec.2005.11.017
Schölkopf, 2002
Shao, 2000, Prognosis of remaining bearing life using neural networks, J. Syst. Control Eng. Part I, 214, 217
Tenenbaum, 2000, A global geometric framework for nonlinear dimensionality reduction, Science, 290, 2319, 10.1126/science.290.5500.2319
Tobon-Mejia, 2012, CNC machine tool's wear diagnostic and prognostic by using dynamic Bayesian networks, Mech. Syst. Signal Process., 28, 167, 10.1016/j.ymssp.2011.10.018
Vapnik, 1995
Vapnik, 1997, Support vector method for function approximation, regression estimation, and signal processing, Adv. Neural Inf. Process. Syst., 9, 281
Xi, 2000, Bearing diagnostics based on pattern recognition of statistical parameters, J. Vib. Control, 6, 75