基于失效物理的性能可靠性技术及应用研究
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摘要
动量轮是卫星姿控系统的关键机电产品,要求在几年甚至十几年的任务时间内始终稳定可靠地工作。对这类卫星长寿命机电产品,基于大样本寿命试验的传统可靠性技术,难以解决其可靠性建模、试验设计与评估问题。本文提出基于失效物理的性能可靠性技术,从失效物理分析出发,综合基于失效物理的性能退化建模、基于性能退化的可靠性试验设计以及基于信息集成的可靠性评估技术,以动量轮为背景,解决卫星长寿命机电产品可靠性工作中的现实问题。论文主要研究内容如下:
     (1)研究基于失效物理的性能退化建模技术,解决卫星长寿命机电产品的性能可靠性建模问题。给出了一般化的由随机性模型和确定性模型构成的多项式耦合退化模型;提出了典型性能退化模型的MCMC参数估计法、两阶段参数估计法和EM迭代参数估计法;构建了基于性能退化模型的寿命分布建模方法,理顺了寿命分布和性能退化模型之间的关系,为产品寿命分布建模提供了理论支持。
     (2)研究基于性能退化的可靠性试验设计技术,解决试验费用昂贵、试验时间受限情形下,卫星长寿命机电产品可靠性试验中的关于检测频率、样本量、试验截止时间的方案设计问题。提出了一般化的基于性能退化的试验设计方法;针对威布尔寿命型和对数正态寿命型产品,分别提出了试验设计模型和实现算法;通过仿真分析证实了试验设计方法的合理性和有效性。
     (3)研究基于信息集成的可靠性评估技术,解决小子样条件下卫星长寿命机电产品的可靠性评估问题。针对实际中可能出现的各类型寿命数据、性能数据和专家判断信息等验前信息,分别提出了寿命数据的Bootstrap随机抽样挖掘方法、性能数据的EMD-AR模型随机抽样挖掘方法以及专家判断信息的参数区间随机抽样挖掘方法;给出了基于JS距离的验前信息集成模型,并构建了确定全局最优权重的模型和算法;针对威布尔寿命型和对数正态寿命型产品,分别提出了基于性能退化模型的可靠性建模方法,并结合验前信息集成方法给出了基于性能退化模型的贝叶斯可靠性评估方法。
     (4)基于上述理论方法,对xx型动量轮的可靠性展开实例研究。确定了动量轮的失效机理为轴承组件润滑系统失效,而导致其失效的主要因素是润滑剂的挥发和爬移;建立了动量轮的润滑剂动态微循环失效物理模型;得到了较高精度的动量轮可靠性评估结论,说明了本文的理论方法可以较好的解决动量轮的可靠性工程实际问题。
As one of the most important electromechanical products embedded in the attitude control system of satellite, the Momentum Wheel has the requirement of stable working within many years. For this kind of long life products of satellite, the traditional reliability technology is not suitable for the reliability modeling, design of experiments and estimation. In this dissertation, the performance reliability technology based on physics of failure is proposed. With the view of physics of failure, the performance reliability modeling method, design of experiments method and reliability estimation method based on information fusion are integrated to address the problems existing in the reliability work of long life electromechanical products of satellite. The main research production of this dissertation includes the following aspects:
     (1) Study the performance reliability modeling method based on the physics of failure, solve the reliability modeling problem of long life electromechanical products of satellite. Put forward a general degradation model with the polynomial coupling form based on stochastic model and deterministic model. Propose the MCMC method, two stages method and EM iterative method for parameter estimation based on performance degradation model. Give the life distribution modeling method based on performance degradation model, and build the bridge between the life distribution model and performance degradation model, which provide the theory support for the life distribution modeling.
     (2) Study the method for design of experiment based on performance reliability, solve the design of experiment problem of long life electromechanical products of satellite. Propose a general optimal method for design of experiment based on performance degradation. For the Weibull life product and Lognormal life product, the optimal design model and algorithm is proposed respectively. Demonstrate the rationality and validity of these method based on simulation.
     (3) Study the reliability estimation method based on information fusion, solve the small sample problem of long life electromechanical products of satellite. For different prior information derived from practice, the data mining method based on Bootstrap random sampling, the data mining method based on EMD-AR model random sampling and the data mining method based on parameter interval random sampling are proposed respectively for life data, performance data and expert judgments. Give the prior information fusion model based on Jensen-Shannon divergence, and build the global optimal weight model and algorithm based on the fusion model. For the Weibull life product and Lognormal life product, the performance reliability estimation method is proposed, and the Bayesian method is proposed for the performance reliability estimation based on prior information fusion model.
     (4) Based on above methods, study the reliability estimation for xx-type Momentum wheel. Determine that the failure mechanism of the Momentum wheel is the failure of lubrication system of bear component, and the main factor of failure is the volatilization and creep of lubrication. Build the physics of failure model in the view of microcirculation dynamic system of lubrication. Get the more high-precision estimation for the reliability of Momentum wheel, and show that the theory of this dissertation can address the practical problem for the reliability engineering of the Momentum wheel.
引文
[1] K. Sathyan, H. Y. Hsu, S. H. Lee, K. Gopinath. Long-term lubrication of momentum wheels used in spacecrafts-An overview [J]. Tribology International, 2010, 43: 259-267.
    [2] E. V. Zaretsky. Liquid lubrication in space [R]. NASA Lewis Research Centor, 1990.
    [3] W. Shapiro, F. Murray, R. Howarth, R Fusaro. Space mechanisms lessons learned study. Volume 1:Summary [R]. NASA Lewis Research Centor, 1995.
    [4] W. Shapiro, F. Murray, R. Howarth, R Fusaro. Space mechanisms lessons learned study. Volume 2:Iiterature review [R]. NASA Lewis Research Centor, 1995.
    [5]周经伦,金光,冯静,刘强.卫星长寿命机电部件(动量轮)极小子样可靠性技术[R].国防科学技术大学, 2008.
    [6] W. Q. Meeker, M. J. Luvalle. An accelerated life test model based on reliability kinetics [J]. Technometrics, 1995, 37(2): 133-146.
    [7] W. Q. Meeker, L. A. Escobar, C. J. Lu. Accelerated degradation tests: modeling and analysis [J]. Technometrics, 1998, 40(2): 89-99.
    [8] L. A. Escobar, W. Q. Meeker. A review of accelerated test models [J]. Statistical Science, 2006, 21(4): 552-577.
    [9] W. Q. Meeker, M. Hamada. Statistical tools for the rapid development & evaluation of high-reliability products [J]. IEEE Transaction on Reliability, 1995, 44(2): 187-198.
    [10] M. L. Samuels, J. A. Witmer, S. E. Jean. Statistics for the life sciences [M]. Prentice Hall Upper Saddle River, 1999.
    [11] GB2689.1-81.恒定应力寿命试验和加速寿命试验总则[S].中华人民共和国国家标准.
    [12] W. Yorkowsky, R. E. Schafter, J. M. Finkelstein. Accelerated tesing technology [R]. Rome Air Development Center, 1967.
    [13] F. Jensen. Activation energies and the Arrhenius equation [J]. Quality and Reliability Engineering International, 1985, 1(1): 13-17.
    [14] C. E. Garner, J. C. Polk, K. M. Goodfellow, L. C. Pless, J. R. Brophy. Performance evaluation and life testing of the SPT-100 [R]. Jet Propulsion Laboratory, California Institute of Technology, 1993.
    [15] C. E. Garner. A 5730-Hr cyclic endurance test of SPT-100 [R]. Jet Propulsion Laboratory, California Institute of Technology, 1995.
    [16] W Aue. Experience with start-stop operation of reacation wheel ball bearings [J]. Tribology Transactions, 1983, 26(2): 250-254.
    [17] G. Nieder. Life testing of TELDIX ball bearing reaction wheel type RSR 2-0 [R]. ESA / ESTEC, 1979.
    [18] J. H. Saleh, K. Marais. Highlights form the early (and pre-) history of reliability engineering [J]. Reliability Engineering & System Safety, 2006, 91(2): 249-256.
    [19] S. W. Lam, T. Halim, K. Muthusamy. Models with failure-free life:Applied review and extensions [J]. IEEE Transaction On Device and materials reliability, 2011, 10(2): 263-270.
    [20] W. Q. Meeker, L. A. Escobar. Statistical Methods for Reliability Data [M].John Wiley & Sons, 1998.
    [21] M. B. Carey, R. H. Koenig. Reliability Assessment Based on Accelerated Degradation: A Case Study [J]. IEEE Transaction on Reliability, 1991, 40(5): 499-506.
    [22] J. G. Ramirez, W. L. Gore, G. Johnston. New methods for modeling reliability using degradation data [J]. Statistics Data Analysis and Data Mining, 2001: 26-33.
    [23] J. C. Lu, S. G. Pantual. A repeated-measurements model for over-stressed degradation data [R]. Department of Statistic North Carolina State University, 1989.
    [24] J. D. Church, B. Harris. The estimation of reliability from stress-strength relationships [J]. Technometrics, 1970, 12(1): 49-54.
    [25] C. S. Place, J. E. Strutt, K. Allsopp, P. E. Irving, C. Trille. Reliability prediction of helicopter transmission system using stress-strength interference with underlying damage accumulation [J]. Quality and Reliability Engineering International, 1999, 15(2): 69-78.
    [26] J. G. Surles, W. J. Padgett. Inference for reliability and stress-strength for a scaled Burr Type X distribution [J]. Lifetime Data Analysis, 2001, 7(2): 187-200.
    [27] E. Takeda, N. Suzuki. An empirical model for device degradation due to hot-carrier injection [J]. IEEE Electron Device Letters, 1983, 4: 111-113.
    [28] C. K. Chan, M. Boulanger, M. Tortorella. Analysis of parameter-degradation data using life-data analysis programs [C]. Proceedings Annual Reliability and Maintainability Symposium, 1994: 288-291.
    [29] C. J. Lu, W. Q. Meeker. Using degradation measures to estimate a time to failure distribution [J]. Technometrics, 1993, 35(2): 161-167.
    [30] S. P. Wilson, D. Taylor. Reliability assessment from fatigue micro-crack data [J]. IEEE Transaction on Reliability, 1997, 46(2): 165-172.
    [31]赵建印.基于性能退化数据的可靠性建模与应用研究[D].国防科学技术大学, 2005.
    [32] H. F. Yu, C. H. Chiao. An Optimal Designed Degradation Experiment for Reliability Improvement [J]. IEEE Transaction on Reliability, 2002, 51(4).
    [33] S. J. Wu, C. T. Chang. Optimal Design of Degradation Tests in Presence of Cost Constraint [J]. Reliability Engineering & System Safety, 2002, 76: 109-115.
    [34] C. H. Chiao, M. Hamada. Analyzing experiments with degradation data for improving reliability and for achieving robust reliability [J]. 2001, 17(5): 333-344.
    [35] G. B. Yang. Reliability Enhancement through Degradation Testing [D]. Wayne State University, 2000.
    [36] H. F. Yu. Designing a screening experiment with a reciprocal Weibull degradation rate [J]. Computers & Industrial Engineering, 2007, 52: 175-191.
    [37] H. F. Yu, S. T. Tseng. Designing a degradation experiment [J]. Naval Research Logistics, 1999, 46(6): 689-706.
    [38] S. Y. Sohn, J. S. Jang. Acceptance Sampling Based on Reliability Degradation Data [J]. Reliability Engineering & System Safety, 2001, 73(1): 67-72.
    [39] S. T. Tseng, H. F. Yu. A termination rule for degradation experiments [J]. IEEE Transaction on Reliability, 1997, 46(1): 130-133.
    [40] G. B. Yang, K. Yang. Accelerated Degradation-Tests With Tightened Critical Values [J]. IEEE Transaction on Reliability, 2002, 51(4): 463-468.
    [41] M. Boulanger, L. A. Escobar. Experimental design for a class of accelerated degradation tests [J]. Technometrics, 1994, 36(3): 260-272.
    [42] H. F. Yu, S. T. Tseng. On-line procedure for terminating an accelerateddegradation test [J]. Statistics Sinica, 1998, 8: 207-220.
    [43] Q. S. Li. Accelerated degradation test planning and optimization [D]. University of Arizona, 2002.
    [44]张金槐,唐雪梅. Bayes方法(第二版) [M].国防科技大学出版社, 1992.
    [45] J. O. Berger. Statistical decision theory and Bayesian analysis [M]. Springer, 1985.
    [46] W. G. Cochran. Sampling techniques [M]. Wiley-India, 2009.
    [47] B. Efron. Bootstrap methods: another look at the jackknife [J]. The annals of statistics, 1979, 7(1): 1-26.
    [48] A. C. Davison, D. V. Hinkley. Bootstrap methods and their application [M]. Cambridge Univ Pr, 1997.
    [49] P. J. Brockwell, R. A. Davis. Time series: theory and methods [M]. Spring Verlag, 2009.
    [50] H. Jeffreys. Theory of probability (3rd edn.) [M]. Oxford University Press, 1961.
    [51] E. T. Jaynes. Papers on probability, statistics and statistical physics [M]. Springer, 1989.
    [52] L. Matyas. Generalized method of moments estimation [M]. Cambridge Univ Pr, 1999.
    [53] T. S. Ferguson. Prior distributions on spaces of probability measures [J]. The annals of statistics, 1974, 2(4): 615-629.
    [54] S. Maskell. A Bayesian approach to fusing uncertain, imprecise and conflicting information [J]. Information Fusion, 2008, 9(2): 259-277.
    [55] F. Smarandache. Unification of fusion theories [J]. International Journal of Applied Mathematics & Statistics, 2004, 2: 1-14.
    [56] F. P. Coolen. On Bayesian reliability analysis with informative priors and censoring [J]. Reliability Engineering & System Safety, 1996, 53: 91-98.
    [57] S. Lichtenstein, J. R. Newman. Empirical scaling of common verbal phrases associated with numerical probabilities [J]. Psychonometric Science, 1967, 9(10): 563-564.
    [58] M. A. Bilal. A practical guide on conducting expert-opinion elicitation of probabilities and consequences for corps facilities [R]. Institute for Water Resources of USA, 2001.
    [59] B. Heller, M. Wang. Posterior distribution for negative binomial parameter p using a group invariant prior [J]. Statistics & Probability Letters, 2007, 77(15): 1542-1548.
    [60]韩明.定时截尾指数分布先验数的适合域[J].数理统计与应用概率, 1997, 12(1): 81-85.
    [61] D. Kundu. Bayesian inference and life testing plan for the weibull distribution in presence of progressive censoring [J]. Technometrics, 2008, 50(2): 141-154.
    [62]张金槐.多种验前信息源情况下的融合验后分布[J].飞行器测控技术, 1998, 17(3): 28-35.
    [63]冯静.小子样复杂系统可靠性信息融合方法与应用研究[D].国防科学技术大学, 2004.
    [64] D. Sherman. Impact failure mechanisms in alumina tiles on finite thicknesssupport and the effect of confinement [J]. International Journal of Impact Engineering, 2000, 24(3): 313-328.
    [65] F. Padadimitrakopoulos, X. M. Zhang, D. L. Thomsen, K. A. Higginson. A chemical failure mechanism for aluminum (III) 8-hydroxyquinoline light-emitting devices [J]. Chem Mater, 1996, 8(7): 1363-1365.
    [66] K. A. Dick, K. Deppert, T. Mrtensson, B. Mandl, L. Samuelson, W. Seifert. Failure of the Vapor-Liquid-Soild mechanism in Au-assisted MOVPE growth of InAs naowires [J]. Nano Lett, 2005, 5(4): 761-764.
    [67] A. C. Garg, Y. W. Mai. Failure mechanisms in toughened epoxy resins-A review [J]. Composites Science and Technology, 1988, 31(3): 179-223.
    [68] S. Schuller, P. Schilinsky, J. Hauch, C. J. Brabec. Determination of the the degradation constant of bulk heterojunction solar cells by accelerated lifetime measurements [J]. Applied Physics A: Materials Science & Processing, 2004, 79(1): 37-40.
    [69] MIL-HDBK-217F. Reliability prediction of electronic equipment [S]. Military Specifications and Standards, USA.
    [70] S. Kotz, M. Pensky. The stress-strength model and its generalizations: Theory and applications [M]. Imperial College Pr, 2003.
    [71] W. Hwang, K. S. Han. Cumulative damage models and multi-stress fatigue life prediction [J]. Journal of Composite Materials, 1986, 20(2): 125-153.
    [72] M. Pecht, A. Dasgupta. Physics-of-failure: an approach to reliabie product development [J]. 38, 1995, 5(30-34).
    [73] J. P. Kharoufeh, S. M. Cox. Stochastic models for degradation-based reliability [J]. IIE Transactions, 2005, 37(6): 533-542.
    [74] Q. Liu, J. L. Zhou, G. Jin, M. Xi, W. Li. An adaptive protocol for pattern recongnition and estimation of time synchronization in WSNs [C]. Proceedings IEEE 2009 Asia-Pacific Conference on Computational Intelligence and Industrial Applications, 2009.
    [75] L. Lecam. Maximum Likelihood: an introduction [J]. International Statistical Review, 1990, 58(2): 153-171.
    [76]茆诗松.统计手册[M].科学出版社, 2003.
    [77] W. R. Gilk, S. Richardson, D. J Spiegelhalter. Markov chain Monte Carlo in practice [M]. Chapman & Hall / CRC, 1996.
    [78] S. Chib. Marginal likelihood from the Gibbs output [J]. Journal of the American Statistical Association, 1995, 90(432): 1313-1321.
    [79] F. S. G. Richards. A method of maximum-likelihood estimation [J]. Journal of the Royal Statistical Society Series B (Methodological), 1961, 23(2): 469-475.
    [80] L. J. Savage. The foundations of statistics [M]. Dover Pubns, 1972.
    [81] G. J. Mclachlan, T. Krishnan. The EM algorithm and extensions [M]. Wiley New York, 1997.
    [82] A. P. Dempster, N. M. Laird, D. B Rubin. Maximum likelihood from incomplete data via the EM algorithm [J]. Journal of the Royal Statistical Society Series B (Methodological), 1977, 39(1): 1-38.
    [83] P. M. Lee. Bayesian Statistics [M]. Arnold London, UK, 2004.
    [84] D. Basu. On statistics independent of a complete sufficient statistic [J]. The Indian Journal of Statistic, 1955, 15(4): 377-380.
    [85] N. E. Day. Estimating the components of a mixture of normal distributions[J]. Biometrika, 1969, 56(3): 463-474.
    [86] V. Hasselblad. Estimation of parameters for a mixture of normal distributions [J]. Technometrics, 1966, 8(3): 431-444.
    [87]常庚哲.数学分析教程[M].江苏教育出版社, 1998.
    [88] W. Q. Meeker, L. A. Escobar. A review of research and current issues in accelerated testing [J]. International Statistical Review, 1993, 61(1): 147-168.
    [89] S. D. Dubey. Some percentile estimators for Weibull parameters [J]. Technometrics, 1967, 9(1): 119-129.
    [90] J. F. Lawless. Statistical models and methods for lifetime data [M]. Wiley New York, 1982.
    [91] M. Aitkin, D. Clayton. The fittig of exponential, weibull and extreme value distributions to complex censored survival data using GLIM [J]. Applied Statistics, 1980, 29(2): 156-163.
    [92]茆诗松.寿命数据中的统计模型与方法[M].中国统计出版社, 1998.
    [93] N. L. Johnson, S. Kotz, N. Balakrishnan. Continuous Univariate Distributions [M]. Wiley New York, 1995.
    [94] N. L. Johnson, S. Kotz, N. Balakrishnan. Continuous Multivariate Univariate Distributions, volume 1, Models and Applications [M]. Wiley New York, 2002.
    [95] Z. M. Odibat, N. T. Shawagfeh. Generalized Taylor's formula [J]. Applied Mathematics and Computation, 2007, 186(1): 286-293.
    [96]盛骤,谢式千,潘承毅.概率论与数理统计[M].高等教育出版社, 1989.
    [97] A. M. Mood, F. A. Graybill, D. C. Boes. Introduction to the theory of statistics [M]. McGrawHill New York, 1976.
    [98] R. N. Kackar. Off-line quality control, parameter design, and the Taguchi method [J]. Journal of Quality Technology, 1985, 17(4): 176-188.
    [99]茆诗松,周纪芗.试验设计[M].中国统计出版社, 2004.
    [100] H. White. Maximum likelihood estimation of misspecified models [J]. Econometrica: Journal of the Econometric Society, 1982, 50(1): 1-25.
    [101] R. E. Schafter. Bayesian reliability demonstration, phase I: data for the a prior distribution [R]. Rome Air Development Center, New York, 1969.
    [102] R. E. Schafter, T. S. Sheffield. Bayesian reliability demonstration, phase II: development of a prior distribution [R]. Rome Air Development Center, New York, 1971.
    [103] Q. Liu, J. L. Zhou, G. Jin, Q. Sun, M. Xi. Bayesian sequential demonstration based on performance reliability for long life aerospace product [C]. Proceedings IEEE Second Internatinal Conference on Computer Modeling and Simulation, 2010.
    [104]刘强,周经伦,金光,厉海涛.基于可信度的动量轮Bayes可靠性评估[J].宇航学报, 2009, 30(1): 382-386.
    [105]刘强,黄秀平,周经伦,金光,孙权.基于失效物理的动量轮贝叶斯可靠性评估[J].航空学报, 2009, 30(8): 1392-1397.
    [106]周经伦,刘强,金光.卫星动量轮的污染数据的Bayes参数估计[J].航空计算技术, 2007, 37(3): 17-19.
    [107]刘强,金光,周经伦.基于EMD的卫星动量轮性能可靠性建模[J].计算机仿真, 2007, 24(11): 32-34.
    [108]金光,刘强.基于性能退化的动量轮可靠性建模与评估[J].数学的实践与认识, 2009, 39(15): 67-72.
    [109] P. J. Lenk. The logistic normal distribution for Bayesian, nonparameteric, predictive densities [J]. Journal of the American Statistical Association, 1988, 83(402): 509-516.
    [110]韩明.无失效数据的可靠性分析[M].中国统计出版社, 1999.
    [111]王伟,夏新涛.配分布曲线法在无失效数据可靠性分析中的应用[J].轴承, 2006, (3): 20-23.
    [112] N. E. Huang, Z. Shen, S. R. Long, M. C. Wu, H. H. Shi, Q. Zheng, N. C. Yen, C. C. Tung, H. H. Liu. The empirical model decomposition and the Hilbert spectrum for nolinear and non-stationary time series analysis [J]. Proceedings: Mathematical, Physical and Engineering Sciences, 1998, 454(1971): 903-995.
    [113] T. L. Saaty. How to make a decision: the analytic hierarchy process [J]. European Journal of Operational Research, 1990, 48(1): 9-26.
    [114] E. T. Jaynes. Prior probability [J]. IEEE Transaction on Systems Science and Cybernetics, 1968, 4(3): 227-241.
    [115] J. Lin. Divergence measures based on the Shannon entropy [J]. IEEE Transaction on Information theory, 1991, 37(1): 145-151.
    [116] A. P. Majtey, P. W. Lamberti, D. P. Prato. Jensen-Shannon divergence as a measure of distinguish ability between mixed quantum states [J]. Physical Review A, 2005, 72(5): 1-14.
    [117] S. Kullback, R. A. Leibler. On information and sufficiency [J]. The annals of mathematical statistics, 1951, 22(1): 79-86.
    [118] D. Henrion, J. B. Lasserre. GloptiPoly: Global optimization over polynomials with Matlab and SeDuMi [J]. ACM Transactions on Mathematical Sofeware, 2003, 29(2): 165-194.
    [119] J. Lofberg. YALMIP: A toolbox for modeling and optimization in MATLAB [C]. 2004.
    [120] A. Chao. Nonparameteric estimation of the number of classes in a population [J]. Scandinavian Journal of Statistics, 1984, 11(4): 265-270.
    [121] B. Efron. Nonparameteric standard errors and confidence intervals [J]. Canadian Journal of Statistics, 1981, 9(2): 139-158.
    [122] K. Sathyan. Long-term lubrication systems for momentum wheels used in spacecraft [D]. Indian Institute of Technology Madras, 2003.
    [123] Z. Ismail, R. Varatharajoo. A study of reaction wheel configurations for a 3-axis satellite attitude control [J]. Advances in Space Research, 2010, 45(6): 750-759.
    [124] E. E. Bisson. Lubrication and bearing problems in the vacuum of space [R]. Lewis Research Center, 1968.
    [125]樊幼温,杨晓丽,李春伟,卿涛.动量轮失效物理模型试验方案研究[J].空间科学学报, 2009, 29(1): 78-86.
    [126] E. V. Zaretsky. Lubricant effects on bearing life [R]. NASA Lewis Research Centor, 1986.
    [127] P. A. Bertrand. Oil adsorption into cotton-phenolic material [J]. J Mater Res, 1993, 8(7): 1749-1757.
    [128] W. R. Jones, M. J. Jane. Lubrication for space application [R]. NASA Glenn Research Center, 2005.
    [129]刘健海.卫星轴承微循环润滑及失效研究[D].清华大学, 1992.
    [130] P. A. Bertrand, D. J. Carre. Oil exchange between ball bearings and porous polymide ball bearing retainers [J]. Tribology Transactions, 1997, 40(2): 294-302.
    [131] M. Marchetti, W. R. Janes, S. V. Pepper, M. J. Jansen, R. E. Predmore. In-situ, on-demand lubrication system for space mechanisms [J]. Tribology Transactions, 2003, 46(3): 452-459.
    [132] L. M. Skinner, J. R. Sambles. The Kelvin equation: a review [J]. Journal of Aerosol Science, 1972, 3(3): 199-210.
    [133] W. Steckelmacher. A review of the molecular flow conductance for systems of tubes and components and the measurement of pumping speed [J]. Vacuum, 1966, 16(11): 561-584.
    [134]高本辉.真空物理[M].科学出版社, 1983.
    [135] R. J. Benzing, J. R. Strang, Ohio Air Force Material Lab Wright-Patterson Afb. Failure Mode Analysis of Lubricated Satellite Components [R]. Air Force Material Lab Wright-Patterson Afb, Ohio, 1974.
    [136] M. J. Todd. Satellite mechanism tribology at ESTL [J]. Tribology International, 1975, 8(3): 99-104.
    [137] W. R. Jones, M. J. Jane. Space Tribology [R]. NASA Glenn Research Center, 2000.
    [138]温诗铸.摩擦学原理[M].清华大学出版社, 1990.
    [139] E. V. Zaretsky. Bearing elastohydrodynamic lubrication: a complex calculation made simple [R]. NASA Lewis Research Centor, 1988.
    [140] J. L. Zhou, Q. Liu, G. Jin, Q. Sun, M. Xi. Reliability modeling for momentum wheel based on data mining of failure-physics [C]. Proceedings 3th IEEE International Conference on Knowledge Discover and Data Mining, 2010.
    [141]刘强,周经伦,金光,周忠宝.基于随机阈值的Gauss-Brown失效物理模型的动量轮可靠性评估[J].宇航学报, 2009, (5): 2109-2115.

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