Hypothesis of Rolling Bearing Performance Evolvement

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Abstract:

Poor information means that characteristic information presented in the subject investigated is incomplete and insufficient, with a small sample and the lack in prior knowledge of probability distributions and trends. For a long time, experiments on the rolling bearing performance concern primarily with statistical evaluation of the fatigue life. With the development of aeronautic and astronautic undertakings, new requirements for the variability of the bearing performance, such as friction, wear, vibration, and temperature rise, are driven. Because the number of characteristic data is small and prior information on probability distributions and trends is poor, statistics has difficulty in assessing the bearing performance. How can the problem be solved There is a phenomenon in Nature, i.e., genetic variations of a species are likely to result in some strange change. Inspired by this, the paper advanced a hypothesis, viz., maybe some genetic variation drive the nonlinearly dynamical evolvement of the information poor process of the bearing performance. To demonstrate this hypothesis, the paper found the variant gene, presented the concept of the poor information equivalence relation, and proposed the method for construction of the information poor space to reveal the new properties of the nonlinearly dynamical evolvement of the modern bearing performance.

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Advanced Materials Research (Volumes 488-489)

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1087-1093

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March 2012

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© 2012 Trans Tech Publications Ltd. All Rights Reserved

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[1] A. Vanhulsel, F. Velasco and R. Jacobs: Tribology International Vol. 40(2007), p.1186.

Google Scholar

[2] C. Nataraj and S. P. Harsha: Communications in Nonlinear Science and Numerical Simulation Vol. 13(2008), p.822.

Google Scholar

[3] K. G. Gan and L. M. Zaitov: Soviet Engineering Research Vol. 10(1990), p.41.

Google Scholar

[4] J. J. Sinou: Mechanism and Machine Theory Vol. 44(2009), p.1713.

Google Scholar

[5] X. T. Xia, T. M. Lv and F. N. Meng: Journal of Testing and Evaluation Vol. 38(2010), p.291.

Google Scholar

[6] S. Sochting, I. Sherrington and S. D. Lewis: Wear Vol. 260(2006), p.1190.

Google Scholar

[7] Ahmad Rafsanjani, Saeed Abbasion and Anoushiravan Farshidianfa: Journal of Sound and Vibration Vol. 319(2009), p.1150.

Google Scholar

[8] S. P. Harsha: Mechanism and Machine Theory Vol. 41(2006), p.688.

Google Scholar

[9] A. N. Lioulios and I. A. Antoniadis: International Journal of Mechanical Sciences Vol. 48(2006), p.809.

Google Scholar

[10] X. T. Xia, F. N. Meng and T. M. Lv: The Journal of Grey System Vol. 22(2010), p.105.

Google Scholar

[11] X. T. Xia and T. M. Lv: Applied Mechanics and Materials Vol. 26-28(2010), p.190.

Google Scholar

[12] Douglas W. Van Citters, Francis E. Kennedy and John P. Collier: Wear Vol. 263(2007), p.1087.

Google Scholar

[13] G. Y. Lin, S. R. Wang and L. P. Wang: Tribology Vol. 29(2009), p.526.

Google Scholar

[14] Saad Al-Dossary, R. I. Raja Hamzah and D. Mb: Applied Acoustics Vol. 70(2009), p.58.

Google Scholar

[15] S. Abbasion, A. Rafsanjania and A. Farshidianfar: Mechanical Systems and Signal Processing Vol. 21(2007), p.2933.

Google Scholar

[16] J. Antoni: Journal of Sound and Vibration Vol. 304(2007), p.497.

Google Scholar

[17] T. Ueda and N. Mitamura:Tribology International Vol. 42(2009), p.1832.

Google Scholar

[18] X. T. Xia and Z. Y. Wang: Chinese Journal of Mechanical Engineering Vol. 22(2009), p.244.

Google Scholar

[19] J. L. Deng: The Journal of Grey System Vol. 1(1989), p.1.

Google Scholar

[20] N. Maruyama and L. Dester Arthur: International Conference on Knowledge-Based Intelligent Electronic Systems, KES Vol. 2(1998), p.145.

Google Scholar

[21] X. T. Xia, J. F. Chen and L. Chen: Advanced Materials Research Vol. 97-101(2010), p.1328.

Google Scholar

[22] X. T. Xia, X. Y. Chen, Y. Z. Zhang and Z. Y. Wang: Measurement Vol. 41(2008), p.687.

Google Scholar

[23] X. T. Xia, Z. Y. Wang, L. M. Sun and L. C. Zhao: The Journal of Grey System Vol. 16(2004), p.243

Google Scholar

[24] X. T. Xia and Z. Y. Wang: The Journal of Grey System Vol. 16(2004), p.141.

Google Scholar

[25] X. T. Xia, Z. Y. Wang and Y. S. Gao: Measurement Science and Technology Vol. 11(2000), p.430.

Google Scholar

[26] X. T. Xia and J. H. Li: The Journal of Grey System Vol. 23(2011), p.327.

Google Scholar