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Performance Degradation Assessment of Rolling Element Bearings using Improved Fuzzy Entropy

rolling element bearings. Tribology International , 32 (8), 469-480. [4] Gebraeel, N., Lawley, M., Liu, R., Parmeshwaran, V. (2004). Residual life predictions from vibration-based degradation signals: A Neural Network approach. IEEE Transactions on Industrial Electronics , 51 (3), 694-700. [5] Qiu, H., Lee, J., Lin, J., Yu, G. (2003). Robust performance degradation assessment methods for enhanced rolling element bearing prognostics. Advanced Engineering Informatics , 17 (3), 127-140. [6] Huang, R.Q., Xi, L.F., Li, X.L., Liu, C.R., Qiu, H., Lee, J

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Estimation of rolling bearing life with damage curve approach

References Qui H., Lee J., Yu G.: Robust performance degradation assessment methods for enhanced rolling element bearing prognostics , Advanced Engineering Informatics, Vol. 17 No. (3-4), pp.127-140, 2003 Zhao Y., Zhang G., Du J., Wang G., Vachsevanos G.: Development of distributed bearing health monitoring and assessing system , 8 th International conference on control, Automation, Robotics and Vision, pp. 474-478, 2004 Mba D., Al-Ghamd A. M.: A comparative experimental study

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A Feature Extraction Method for Vibration Signal of Bearing Incipient Degradation

] Wang, D., Shen, C. (2014). An equivalent cyclic energy indicator for bearing performance degradation assessment. Journal of Vibration and Control , doi 10.1177/1077546314547224. [7] Fatima, S., Guduri, B., Mohanty, A.R., Naikan, V.N.A. (2014). Transducer invariant multi-class fault classification in a rotor-bearing system using support vector machines. Measurement , 58, 363-374. [8] Shen, C., Cai, G., He, Z., Huang, W., Zhu, Z. (2015). A parameterized Doppler distorted matching model for periodic fault identification in locomotive bearing. Proceedings

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