零部件与系统动态可靠性建模理论与方法
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摘要
可靠性作为衡量机械产品质量的重要指标之一,已贯穿到产品的开发、设计、制造、试验、使用、运输、保管及维修等各个环节中。因此,发展和建立科学合理的可靠性分析理论与方法对于零部件和系统的设计制造、安全运行以及全生命周期管理都具有十分重要的意义。
传统的可靠性建模方法是在应力(或载荷)和强度概率分布已知的前提下,直接运用应力—强度干涉理论建立零部件或系统可靠性模型。然而,这些模型并不能很好地反映零部件或系统可靠度和失效率随载荷作用次数或时间的变化规律,用这些模型计算得到的可靠度实际上是随机载荷作用一次或特定次数时的可靠度,是一个“静态”的可靠度。事实上,由于零部件和系统在服役期间所受随机载荷的作用通常是反复多次的,零部件或系统的可靠度和失效率应当是随载荷作用次数或时间而变化的。同时,传统的零部件或系统失效率计算大多基于寿命分布函数,即通过对零部件或系统失效数据的统计分析获得相应的寿命分布函数,然后,得到失效率的表达式。显然,这种失效率计算方法是以大量的产品失效数据为前提,因此,并不能在新产品的研发阶段直接指导产品的设计。
对于机械系统而言,“相关”是其失效的普遍特征,忽略系统中各零部件之间以及零部件中各失效模式之间失效的相关性,简单地在失效相互独立的假设下进行零部件和系统的可靠性分析与计算,常常会导致过大的误差,甚至得出错误的结论。
本文将综合运用应力-强度干涉模型、顺序统计量理论、泊松随机过程以及概率微分方程,建立零部件和系统的动态可靠性模型。考虑共因失效这种失效相关性,在不作独立假设的前提下,直接运用应力-强度干涉模型建立了多种失效模式下的零部件可靠性模型和系统可靠性模型。在分析系统可靠性模型结构特点的基础上,提出了系统强度的概念,并建立了串联系统、并联系统以及k/n系统强度的累积分布函数和概率密度函数。指出系统可靠性模型与零部件可靠性模型具有相同的结构,零部件或单元的不同组合形成不同类型的系统,具有不同的系统强度分布,使得对于同一随机载荷,不同的系统表现出不同的可靠度。分析了随机载荷多次作用下零部件和系统失效的过程,运用顺序统计量理论建立了随机载荷多次作用时等效载荷的累积分布函数和概率密度函数。进一步,建立了随机载荷多次作用下的零部件和系统可靠性模型,研究了零部件和系统可靠度与失效率随载荷作用次数的变化规律。运用泊松随机过程描述载荷作用次数随时间的变化规律,分别建立了强度不退化和强度退化时零部件和系统的动态可靠性模型,并研究了零部件和系统可靠度与失效率随时间的变化规律。
研究表明,强度不退化或退化不明显时,零部件和系统的可靠度随时间逐渐降低,失效率随时间逐渐减小,失效率曲线具有“浴盆”曲线中“早期失效期”和“偶然失效期”的特征。强度退化时,零部件和系统的可靠度随时间逐渐降低且较为明显,零部件和系统的失效率曲线具有“浴盆”曲线的全部特征。指出零部件和系统早期失效以及其较高的失效率并不只是由其初始缺陷所引起,而是由随机载荷的作用和强度所共同决定的。
本文所建立的零部件和系统动态可靠性模型可以动态地反映零部件和系统可靠度与失效率随载荷作用次数或时间的变化规律。在强度和载荷(或应力)概率分布以及强度退化规律已知的前提下,运用本文模型可方便地计算零部件和系统在任意时刻时的可靠度与失效率。因此,本文所提出的动态可靠性建模理论与方法可应用于零部件和系统的全生命周期管理,对于指导零部件与系统的可靠性设计、科学确定零部件与系统的试运行时间和可靠寿命以及合理制定零部件与系统的维修计划都具有重要的意义。
Reliability, as one of the most important quality indices, has been embodied in all the stages of new products, such as development, manufacturing, test, operation, transportation, storage, maintenance and so on. Therefore, for the design and manufacture, safety operation and life cycle management of components and systems, it is of importance to develop the scientific and rational theory and method for the reliability analysis.
In the conventional reliability models, the load-strength interference theory is directly applied to calculate the reliability of components or systems when these probability distribution of stress (or load) and strength are known. However, these reliability models can't reflect how the reliability and the failure rate of components and systems changes with the times of load action and time. The probability calculated through these models is actually the reliability when random load acts only once or for the specified times, and it is also a static reliability. In fact, random loads which act on components or systems in service are always repetitious, and the reliability and failure rate of components and systems should vary with the times of load action or time. At the same time, the failure rate calculation of components and systems in the conventional methods is always based on the life distribution function. That is, the life distribution function is obtained through the statistical analysis of product failure data, and then the failure rate function is derived. Obviously, this method of calculating the failure rate is based on a lot of product fail data, and it can't be applied to guide the design of new products directly in the development stage.
For mechanical systems, dependent failure is their general character and it will lead to considerable errors or even misleading conclusions that neglect the failure dependence which exsits in the components of systems and the failure modes of components, and assume independent failure in the analysis and calculation of reliability of components and systems.
In this paper, we develop the time-depedent reliability models of components and systems with stress-strength interference model, order statistic theory, Poisson stochastic process and probability differential equation. Firstly, common cause failure, as one mode of dependent failure, is considered and the reliability models of components with multiple failure modes and systems are derived with the load-strength interference model and without the assumption of independent failure. Based on analyzing the reliability models of systems proposed, we develop the concept of system strength and derive the probability cumulative distribution functions and the probability density functions of strength for series system, parallel systems and k-out-of-n system. It is pointed out that the reliability models of systems have the same structure as those of components. The different kinds of systems, which have different number and different combination forms of components, have different strength distributions and can represent different reliability under the same random load. Then, the failure mechanism of components and systems under repeated random load is studied, and the probability cumulative distribution function and the probability density function of equivalent load are derived with the order statistic theory when random load acts for multiple times. Further, we develop the reliability models of components and systems under random repeated load, and for components and systems we discuss the relationship between reliability and times of load action and that between failure rate and times of random load action. The loading process is described with Poisson stochastic process, and the time-depedent reliability models of components and systems without strength degeneration and those with strength degeneration are developed respectively. Finally, for components and systems, the relationship between the reliability and time and that between the failure rate and time are discussed.
The result shows that when strength doesn't degenerate and strength degeneration can be neglected, the reliability and the failure rate of components and systems decreases with time, and the failure rate curves of components and systems both have the partial feature of the bathtub curve, namely, the early failure period and the random failure period. When strength degenerates, the reliability of components and systems decreases with time more obviously and the failure rate curves of components and systems have the whole feature of the bathtub curve. It should be noticed that the early failure and the higher failure rate of components and systems are not caused by their initial flaw only, but determined by both random load action and strength together.
The time-depedent reliability models of components and systems developed in this paper can reflect the change of the reliability and the failure rate with time time-depedentally. When the probability distribution of strength and load and the rule of strength degeneration are known, we can calculate the reliability and the failure rate of components and systems at any time. Thus, the reliability models proposed may be applied to the life cycle management of components and systems and it is very useful to guide the design, to determine the testing time and the reliable operation life and to make the rational maintenance schedule of components and systems.
传统的可靠性建模方法是在应力(或载荷)和强度概率分布已知的前提下,直接运用应力—强度干涉理论建立零部件或系统可靠性模型。然而,这些模型并不能很好地反映零部件或系统可靠度和失效率随载荷作用次数或时间的变化规律,用这些模型计算得到的可靠度实际上是随机载荷作用一次或特定次数时的可靠度,是一个“静态”的可靠度。事实上,由于零部件和系统在服役期间所受随机载荷的作用通常是反复多次的,零部件或系统的可靠度和失效率应当是随载荷作用次数或时间而变化的。同时,传统的零部件或系统失效率计算大多基于寿命分布函数,即通过对零部件或系统失效数据的统计分析获得相应的寿命分布函数,然后,得到失效率的表达式。显然,这种失效率计算方法是以大量的产品失效数据为前提,因此,并不能在新产品的研发阶段直接指导产品的设计。
对于机械系统而言,“相关”是其失效的普遍特征,忽略系统中各零部件之间以及零部件中各失效模式之间失效的相关性,简单地在失效相互独立的假设下进行零部件和系统的可靠性分析与计算,常常会导致过大的误差,甚至得出错误的结论。
本文将综合运用应力-强度干涉模型、顺序统计量理论、泊松随机过程以及概率微分方程,建立零部件和系统的动态可靠性模型。考虑共因失效这种失效相关性,在不作独立假设的前提下,直接运用应力-强度干涉模型建立了多种失效模式下的零部件可靠性模型和系统可靠性模型。在分析系统可靠性模型结构特点的基础上,提出了系统强度的概念,并建立了串联系统、并联系统以及k/n系统强度的累积分布函数和概率密度函数。指出系统可靠性模型与零部件可靠性模型具有相同的结构,零部件或单元的不同组合形成不同类型的系统,具有不同的系统强度分布,使得对于同一随机载荷,不同的系统表现出不同的可靠度。分析了随机载荷多次作用下零部件和系统失效的过程,运用顺序统计量理论建立了随机载荷多次作用时等效载荷的累积分布函数和概率密度函数。进一步,建立了随机载荷多次作用下的零部件和系统可靠性模型,研究了零部件和系统可靠度与失效率随载荷作用次数的变化规律。运用泊松随机过程描述载荷作用次数随时间的变化规律,分别建立了强度不退化和强度退化时零部件和系统的动态可靠性模型,并研究了零部件和系统可靠度与失效率随时间的变化规律。
研究表明,强度不退化或退化不明显时,零部件和系统的可靠度随时间逐渐降低,失效率随时间逐渐减小,失效率曲线具有“浴盆”曲线中“早期失效期”和“偶然失效期”的特征。强度退化时,零部件和系统的可靠度随时间逐渐降低且较为明显,零部件和系统的失效率曲线具有“浴盆”曲线的全部特征。指出零部件和系统早期失效以及其较高的失效率并不只是由其初始缺陷所引起,而是由随机载荷的作用和强度所共同决定的。
本文所建立的零部件和系统动态可靠性模型可以动态地反映零部件和系统可靠度与失效率随载荷作用次数或时间的变化规律。在强度和载荷(或应力)概率分布以及强度退化规律已知的前提下,运用本文模型可方便地计算零部件和系统在任意时刻时的可靠度与失效率。因此,本文所提出的动态可靠性建模理论与方法可应用于零部件和系统的全生命周期管理,对于指导零部件与系统的可靠性设计、科学确定零部件与系统的试运行时间和可靠寿命以及合理制定零部件与系统的维修计划都具有重要的意义。
Reliability, as one of the most important quality indices, has been embodied in all the stages of new products, such as development, manufacturing, test, operation, transportation, storage, maintenance and so on. Therefore, for the design and manufacture, safety operation and life cycle management of components and systems, it is of importance to develop the scientific and rational theory and method for the reliability analysis.
In the conventional reliability models, the load-strength interference theory is directly applied to calculate the reliability of components or systems when these probability distribution of stress (or load) and strength are known. However, these reliability models can't reflect how the reliability and the failure rate of components and systems changes with the times of load action and time. The probability calculated through these models is actually the reliability when random load acts only once or for the specified times, and it is also a static reliability. In fact, random loads which act on components or systems in service are always repetitious, and the reliability and failure rate of components and systems should vary with the times of load action or time. At the same time, the failure rate calculation of components and systems in the conventional methods is always based on the life distribution function. That is, the life distribution function is obtained through the statistical analysis of product failure data, and then the failure rate function is derived. Obviously, this method of calculating the failure rate is based on a lot of product fail data, and it can't be applied to guide the design of new products directly in the development stage.
For mechanical systems, dependent failure is their general character and it will lead to considerable errors or even misleading conclusions that neglect the failure dependence which exsits in the components of systems and the failure modes of components, and assume independent failure in the analysis and calculation of reliability of components and systems.
In this paper, we develop the time-depedent reliability models of components and systems with stress-strength interference model, order statistic theory, Poisson stochastic process and probability differential equation. Firstly, common cause failure, as one mode of dependent failure, is considered and the reliability models of components with multiple failure modes and systems are derived with the load-strength interference model and without the assumption of independent failure. Based on analyzing the reliability models of systems proposed, we develop the concept of system strength and derive the probability cumulative distribution functions and the probability density functions of strength for series system, parallel systems and k-out-of-n system. It is pointed out that the reliability models of systems have the same structure as those of components. The different kinds of systems, which have different number and different combination forms of components, have different strength distributions and can represent different reliability under the same random load. Then, the failure mechanism of components and systems under repeated random load is studied, and the probability cumulative distribution function and the probability density function of equivalent load are derived with the order statistic theory when random load acts for multiple times. Further, we develop the reliability models of components and systems under random repeated load, and for components and systems we discuss the relationship between reliability and times of load action and that between failure rate and times of random load action. The loading process is described with Poisson stochastic process, and the time-depedent reliability models of components and systems without strength degeneration and those with strength degeneration are developed respectively. Finally, for components and systems, the relationship between the reliability and time and that between the failure rate and time are discussed.
The result shows that when strength doesn't degenerate and strength degeneration can be neglected, the reliability and the failure rate of components and systems decreases with time, and the failure rate curves of components and systems both have the partial feature of the bathtub curve, namely, the early failure period and the random failure period. When strength degenerates, the reliability of components and systems decreases with time more obviously and the failure rate curves of components and systems have the whole feature of the bathtub curve. It should be noticed that the early failure and the higher failure rate of components and systems are not caused by their initial flaw only, but determined by both random load action and strength together.
The time-depedent reliability models of components and systems developed in this paper can reflect the change of the reliability and the failure rate with time time-depedentally. When the probability distribution of strength and load and the rule of strength degeneration are known, we can calculate the reliability and the failure rate of components and systems at any time. Thus, the reliability models proposed may be applied to the life cycle management of components and systems and it is very useful to guide the design, to determine the testing time and the reliable operation life and to make the rational maintenance schedule of components and systems.
引文
1.刘惟信.机械可靠性设计[M].北京：清华大学出版社,1996.
2.黄挺,朱北园.可靠性技术的最新进展[J].质量与可靠性,2002,17(5)：21-25.
3.郑骏.软件可靠性建模的发展和存在的问题[J].计算机科学,1995,(6)：74-78.
4.汪胜陆.机械产品可靠性设计方法及其发展趋势的探讨[J].机械设计,2007,24(5)：1-3.
5.谢里阳,何雪宏,李佳.机电系统可靠性与安全性设计[M].哈尔滨工业大学出版社,2006.
6. Xie Liyang, Zhou Jinyu, Hao Changzhong. System-level load-strength interference based reliability modeling of k-out-of-n system [J]. Reliability Engineering and System Safety, 2004,84:311-317.
7. Place C S, Strutt J E, Allsopp K, et al. Reliability prediction of helicopter transmission systems using stress-strength interference with underlying damage accumulation [J]. Quality and Reliability Engineering International,1999,15:69-78.
8. Levitin G. Incorporating common-cause failures into no repairable multi-state series-parallel system analysis [J]. IEEE Transactions on Reliability,2001,50 (4): 380-388.
9.谢里阳,林文强.共因失效概率预测的离散化模型[J].核科学与工程,2002,22(2)：186-192.
10.钟培道.航空发电机转动件共模失效的特征、原因与对策[J].航空科学技术,2000,4：33-35.
11.[美]E.J.亨利等著,吕应中等译.可靠性工程与风险分析[M].北京：原子能出版社,1988.
12. Werner W. Result of recent risk studies in France, Germany, Japan, Sweden and the United States [R]. NEA/CSNI/R (1994)10, Paris,1994.
13. Vaurio J K. Optimization of test and maintenance intervals based on risk and cost [J]. Reliability Engineering and System Safety,1995,49:23-26.
14. Meslin B T. Analysis and quantification on common cause failure on the basic of operating experience [J]. Nuclear Technology,1989,84:239-246.
15.喻天翔,张选生,张祖明.轴的多失效模式相关的可靠性计算[J].机械传动, 2002,3：30-34.
16. Martz H F, Kvam P H, Abramson LR. Empirical bayes estimation of the reliability of nuclear power plant emergency diesel generators [J]. Technometric,1996,38:11-24.
17. Elmer E L. A load-capacity interference model for common-mode failures in 1-out-of-2: G systems [J]. IEEE Transaction on Reliability,2001,50(1):47-51.
18. Knut O R, Gunner C L. Reliability-based design of wind-turbine rotor blades against failure in ultimate loading [J]. Engineering Structures,2000,22:565-574.
19. Li Bing, Zhu Meilin, Xu Kai. A practical engineering method for fuzzy reliability analysis of mechanical structures [J]. Reliability Engineering and System Safety,2000, 67:311-315.
20.谢里阳,李翠玲.相关系统失效概率的次序统计量模型及共因失效原因分析[J].机械强度,2005,27(1)：66-71.
21. Place C S, Strutt J E, Allsopp K, et al. Reliability prediction of helicopter transmission systems using stress-strength interference with underlying damage accumulation [J]. Quality and Reliability Engineering International,1999,15:69-78.
22.孙志礼,陈良玉,张钰,等.机械传动系统可靠性设计模型(Ⅰ)[J].东北大学学报(自然科学版),2003,24(6)：548-551.
23. Petryna Y S, Pfanner D, Stangenberg F, et al. Reliability of reinforced concrete structures under fatigue [J]. Reliability Engineering and System Safety,2002,77:253-261.
24. Murty A S R, Gupta U C, Krishna A R. A new approach to fatigue strength distribution for fatigue reliability evaluation [J]. International Journal of Fatigue,1995,17:85-89.
25. Bebbington M, Lai C D, Zitikis R. Useful periods for lifetime distribution with bathtub shaped hazard rate functions [J]. IEEE transaction on Reliability,2005,55(2):245-251.
26. Xie M, Tang Y, Goh T N. A modified Weibull extension with bathtub-shaped failure rate function [J]. Reliability Engineering and System Safety,2002,76:279-285.
27. Basu A P, Sun Kai. Multivariate exponential distributions with constant failure rates [J]. Journal of Multivariate Analysis,1997,61:159-169.
28. AGREE. Reliability of Military Electronic Equipment, report of the advisory Group on Reliability of Electronic Equipment, Washington DC:Office of the Assistant Secretary of Defense,1957.
29. Surles J G., Padgett W J, Inference for reliability and stress-strength for a scaled burr type X distribution [J]. Lifetime Data Analysis,2001,7:187-200.
30. Lynch J D. On the joint distribution of component failures for monotone load-sharing systems [J]. Journal of Statistical Planning and Inference,1999,78:13-21.
31. Zhao Y X, Gao Q, Wang J N. An approach for determining an appropriate assumed distribution of fatigue life under limited data [J]. Reliability Engineering and System Safety,2000,67:1-7.
32. Saralees Nadarajah. On the moments of the modified Weibull distribution [J]. Reliability Engineering and System Safety,2005,90:114-117.
33. Massim Y, Zeblah A, Meziane R, et al. Optimal design and reliability evaluation of multi-state series-parallel power systems [J]. Nonlinear Time-depedents,2005,40: 309-321.
34. Jong Gyun Choi, Poong Hyun Seong. Reliability assessment of embedded digital system using multi-state function [J]. Reliability Engineering and System Safety,2006,91: 261-269.
35. Jose E Ramirez-Marquez, David W Coit. A Monte-Carlo simulation approach for approximating multi-state two-terminal reliability [J]. Reliability Engineering and System Safety,2005,87:253-264.
36. Li Jing-an, Wu Yue, Lai Kin Keung, Liu Ke. Reliability estimation and prediction of multi-state components and coherent systems [J]. Reliability Engineering and System Safety,2005,88:93-98.
37. Krzysztof Kolowrocki. Asymptotic approach to reliability evaluation of large multi-state systems with application to piping transportation [J]. International Journal of Pressure Vessels and Piping,2003,80:59-73.
38. Somasundaram S, Audsin Mohana Dhas D. Reliability of a time-depedent n-unit shared load parallel system under different failure times [J]. Microelectronics Reliability,1997, 37(5):869-871.
39. Yang Kai, Younis Hisham. A semi-analytical Monte Carlo simulation method for system's reliability with load sharing and damage accumulation [J]. Reliability Engineering and System Safety,2005,87:191-200.
40. Durham S D, Lynch J D. A threshold representation for the strength distribution of a complex load sharing system [J]. Journal of Statistical Planning and Inference,200,83: 25-46.
41. Avvenuti Marco, Rizzo Luigi, Vicisano Lorenzo. Hardware support for load sharing in parallel systems [J]. Journal of Systems Architecture,1996,42:129-143.
42. Hyoungtae K, Paul H K, Reliability Estimation Based on System Data with an Unknown Load Share Rule [J], Lifetime Data Analysis,2004,10:83-94.
43. Kiyoshi Aida, Yasuyuki Owa, Kohei Suzuki, et al. Evaluation of aseismic reliability of Actual boiler structures and a study on design of seismic ties based on proof tests using a large scaled shaking table [J]. Journal of Pressure Vessel Technology,2004,126:46-52.
44. Jonnalagadda K. Reliability of via-in-pad structures in mechanical cycling fatigue [J], Microelectronics Reliability,2002,42:253-258.
45. Franchin P, Lupoi A, Pinto P E. Seismic fragility of reinforced concrete structures using a response surface approach [J]. Journal of Earthquake Engineering,2003,7:45-77.
46. Leira B J, Holma T, Herfjor K. Application of response surfaces for reliability analysis of marine structures [J]. Reliability Engineering and System Safety,2005,90:131-139.
47. Lee Hyungyil, Seo Heon, Park Gyungjin. Design enhancements for stress relaxation in automotive multi-shell-structures [J]. International Journal of Solids and Structures,2003, 40:5319-5334.
48.魏华春,张彤.一种机构可靠性的仿真分析方法[J].工程图学学报,2004,3：26-29.
49.孙志礼,陈良玉.实用机械可靠性设计理论与方法[M].北京：科学出版社,2003.210-212.
50.李良巧,顾唯明.机械可靠性设计与分析[M].北京：国防工业出版社,1998.224-245.
51. Cole G K, Ronalds B F, Fakas E. The interaction between strength and fatigue reliability for a minimum structure in shallow water [J]. Journal of Offshore Mechanics and Arctic Engineering,2003,125:282-287.
52. Jing Ling, Pan Jwo. Engineering method for reliability analyses of mechanical structures for long fatigue lives [J]. Reliability Engineering and System Safety,1997,56:135-142.
53. Kim Sang-Hyo, Lee Sang-Woo, Mha Ho-Seong. Fatigue reliability assessment of an existing steel railroad bridge [J]. Engineering Structures,2001,23:1203-1211.
54. Le Xiaobin, Peterson M L. A method for fatigue based reliability when the loading of a component is unknown [J]. International Journal of Fatigue,1999,21:603-610.
55. Zhao Y X. A methodology for strain-based fatigue reliability analysis [J]. Reliability Engineering and System Safety,2000,70:205-213.
56. Ni Kan, Zhang Shengkun. Fatigue reliability analysis under two-stage loading [J]. Reliability Engineering and System Safety,2000,68:153-158.
57. Zhao Jie, Tang Jun, Wu Han C. A Generalized Random Variable Approach for Strain-Based Fatigue Reliability Analysis [J], Transactions of the ASME,2000,122: 156-161.
58. As S K, Skallerud B, Tveiten B W, et al. Fatigue life prediction of machined components using finite element analysis of surface topography [J]. International Journal of Fatigue, 2005,27:1590-1596.
59.王正,谢里阳,李兵.考虑共因失效的机械零部件可靠性模型[J].机械设计,2007,24(1)：4-5.
60. Hagen E W. Common-mode/common-cause failure:a review [J]. Nuclear Engineering and Design,1980,59:423-431.
61. Epler E P. Common mode failure considerations in the design of system for protection and control [J]. Nuclear Safety,1969,10:38-45.
62. Fleming K N. A reliability model for common cause failures in redundant safety systems [C]. Sixth annual Pittsburgh conference on modeling and simulation, Pittsburgh,1975.
63. Hanks B J. An appreciation of common cause failures in reliability[C]. Proceeding of the Institution of Mechanical Engineers. Part E: Journal of Process Mechanical Engineering. 1998,212:31-35
64. Fleming K N, Hunnaman G W. Common cause failure considerations in predicting HTGR cooling system reliability[J]. IEEE Transaction on Reliability,1976,25:171-177.
65. Vaurio J K. Availability of redundant safety systems with common mode and undetected failures [J]. Nuclear Engineering and Design,1980,58:415-424.
66. Mankamo T, Kosonen M. Dependent failure modeling in highly redundant structures-application to BWR safety valves [J]. Reliability Engineering and System Safety,1992,35:235-244.
67. Atwood C L. The binomial failure rate common cause model [J]. Technometrics,1986, 28:139-148.
68. Fleming K N, Mosleh A, Deremer R K. A systematic procedure for the incorporation of common cause events into risk and reliability models [J]. Nuclear Engineering and Design,1986,93:245-273.
69. Johnston B D. A structured procedure for dependent failure analysis [J]. Reliability Engineering and System Safety,1987,19:125-136.
70. Harris B. Stochastic models for common cause failures [J]. Reliability and Quality Control,1986:185-200.
71. Guey C N, Heising C D. Development of a common cause failure analysis method:the inverse stress-strength interference (ISSI) technique [J]. Structural Safety,1986,4:63-77.
72. Chae K C, Clark G M. System reliability in the presence of common-cause failures [J]. IEEE Transaction on Reliability,1986,35:32-35.
73. Mosleh A. Common causes failures:an analysis methodology and examples [J]. Reliability Engineering and System Safety,1991,34:249-292.
74. Mankamo T, Kosonen M. Dependent failure modeling in highly redundant structures-application to BWR safety valves [J]. Reliability Engineering and System Safety,1992,35:235-244.
75. Mosleh A, Parry G W, Zikria A F. An approach to the analysis of common cause failure data for plant-specific application [J]. Nuclear Engineering and Design,1994,150:25-47.
76. Vaurio J K. Common cause failure models, data, quantification [J]. Reliability Engineering and System Safety,1996,53:85-96.
77. Dore P. Basic aspects of stochastic reliability analysis for redundancy systems [J]. Reliability Engineering and System Safety,1989,24:351-375.
78. Vaurio J K. Common cause failure probabilities in standby safety system fault tree analysis with testing-scheme and timing dependencies [J]. Reliability Engineering and System Safety,2003,79:43-57.
79. Vaurio J K, Availability of redundant safety systems with common mode and undetected failures [J]. Nuclear Engineering and Design,1980,58:415-424.
80. Hokstad P. A shock model for common cause failure [J]. Reliability Engineering and System Safety,1988,23:127-145.
81. Vaurio J K. An implicit method for incorporating common cause failures in system analysis [J]. IEEE Trans Raliab,1998,47(2):173-180.
82. Marshall A W, Olkin I. A multivariate exponential distribution [J]. Journal of the American Statistical Association,1967,62:30-44.
83. Hughes R P. A new approach to common cause failure [J]. Reliability Engineering and System Safety,1987,17:211-236.
84. Fleming K N, Mosleh A. Classification and analysis of reactor operating experience involving dependent failures. NP-3967. Electric Power Research Institute, June 1985.
85. Mosleh A, Siu N O. A multi-parameter event-based common-cause failure model[C]. Proceedings of the Ninth International Conference on Structural Mechanics in Reactor Technology,1987:147-152.
86. Hauptmanns U. The multi-class binomial failure rate model [J]. Reliability Engineering and System Safety,1996,53:85-90.
87. Kvam P H. A parametric mixture-model for common-cause failure data [J]. IEEE Transaction on Reliability,1998,47(1):30-34.
88. Kvam P H. The binomial failure rate mixture model for common cause failure data from the nuclear industry [J]. Application Statistics,1998,47:49-61.
89. Xie L Y. A knowledge-based multi-dimension discrete common cause failure model [J]. Nuclear Engineering and Design,1998,183:107-116.
90.黄祥瑞.可靠性工程[M].清华大学出版社,1990.
91.安伟光.系统可靠性评定方法的研究[J].应用科技,1995,4：24-29.
92.冷护基,李广安,张志胜,等.贮备冗余系统的模糊可靠性[J],机械工程学报,1998,34(3)：26-32.
93.冷护基,李广安,陈胜军,等.冷贮备系统的模糊可靠性[J].系统工程理论与实践,1997,11：113-123.
94.李铎,石铭德,马昌文.低温核供热站数字化保护系统的研究及其可靠性分析[J].核动力工程,1999,20(3)：269-273.
95.王光远,谭东耀.失效相关工程系统的可靠度[J].地震工程与工程振动,1992,12(1)：1-5.
96.王光远,张鹏.具有中介状态的工程系统的可靠性分析[J].土木工程学报.2001,34(3)：13-17.
97.何钟怡.单一随机扰动源作用下工程结构的失效相关问题[J].地震工程与工程振动,1994,14(2)：76-85.
98.张鹏,胡秀庄,孙鸿玲.失效相关下串联和并联工程系统的可靠性向量方法[J].四川大学学报(工程科学版),2004,36(1)：1-6.
99.张鹏,张庆功,胡启国.改进的哈马邱尔算子在系统可靠性分析中的应用[J].机械强度,2006,28(1)：70-78.
100.王学敏,谢里阳,周金宇.共因失效率的不确定性评估[J].航空学报,2005,26(1)：.446-449.
101.周金宇,谢里阳,王学敏.相关失效结构系统可靠度的近似求解方法[J].东北大学学报(自然科学版),2004,25(1)：74-77.
102.谢里阳,周金宇,李翠玲,等.系统共因失效分析及其概率预测的离散化建模方法[J].机械工程学报,2006,42(1)：62-68.
103.王学敏,谢里阳,周金宇,王芸.相关失效系统的可靠性模型[J].东北大学学报,2004,25(9)：887-890.
104.王学敏,谢里阳,周金宇.基于幂指数分布的共因失效新模型[J].机械制造,2004,42(9)：58-61.
105.Xie Liyang, Zhou Jinyu, Wang Yongyan, et al. Load-strength order statistics interference models for system reliability evaluation [J]. International Journal of Performance Engineering,2005,1(1):23-36.
106.Wang Zheng, Xie Liyang. Reliability Model of Component under Stochastic Ally Repeated Load [C]. The first international conference on maintenance engineering. Beijing:Science Press,2006:895-900.
107.Giinter Beckera, Leonidas Camarinopoulos, Dimitris Kabranis. Time-depedent reliability under random shocks [J]. Reliability Engineering and System Safety,2002,24:239-251.
108.Chen J J, Zeng Y G, Sun H A. Time-depedent reliability analysis of antenna reflector accuracy under wind excitation [J]. Computers & Structures,1996,59:819-822.
109.Cazuguel M, Renaud C, Cognard J Y. Time-variant reliability of nonlinear structures: application to a representative part of a plate floor [J]. Quality and Reliability Engineering International,2006,22:101-108.
110.Streicher H, Rackwitz R. Time-variant reliability-oriented structural optimization and a renewal model for life-cycle costing [J]. Probabilistic Engineering Mechanics,2004,19: 171-183.
111.Tian Liang, Noore Afzel. Time-depedent software reliability prediction:an approach based on support vector machines [J]. International Journal of Reliability, Quality and Safety Engineering,2005,12:309-321.
112.Kopustinskas V, Augutis J, Rimkevicius S. Time-depedent reliability and risk assessment of the accident localization system of the Ignalina NPP RBMK-1500 reactor [J]. Reliability Engineering and System Safety,2005,87:101-108.
113.Wang K S., Chen C S, Hung J J. Time-depedent reliability behavior of carburized steel sliding wear [J]. Reliability Engineering and System Safety,1997,58:31-41.
114.P.D.T. O'Connor. Practical Reliability Engineering [M]. Wiltshire:John Wiley & Sons, Inc.1985,105-106.
115.李艺,闫运起.现役结构时变可靠性评估[M].东北大学出版社,2004,9.
116.姚卫星,结构疲劳可靠性模型[M].国防工业出版社,2003.
117.左勇志,刘西拉.结构动态可靠性的全随机过程模型[J].清华大学学报(自然科学版),2004,44(3)：395-397,405.
118.黄飞腾,郁军,肖航.基于Markov状态转移的动态可靠性分析[J].海军工程大学学报,2002,14(6)：80-83.
119.崔利荣.马尔可夫链在可靠性计算中的一些新应用[J].系统工程与电子技 术,1999,12(12)：89-91.
120.吴志良,郭晨,赵红.基于马尔柯夫过程的可修系统可靠性建模[J].大连海事大学学报,2007,33(1)：13-16.
121.李守仁,袁海蓉.确定不同单元并联系统可靠性的马尔可夫过程[J].哈尔滨工程大学学报,2003,24(1)：90-93.
122.沈戈,苏春,许映秋.基于Petri网理论的动态系统可靠性建模方法研究[J].机械工程与自动化,2006,135(2)：1-3,10.
123.苏春,沈戈,许映秋.基于随机故障Petri网的液压系统可靠性建模与分析[J].液压与气动,2006,6：29-31.
124.Matsuoka T, Kobayashi M. The GO-FLOW reliability analysis methodology—analysis of common cause failures with uncertainty [J]. Nuclear Engineering and Design,1997, 175:205-214.
125.高振清,孙厚芳,吴琼.基于GO法的制造系统可靠性分析[J].机械科学与技术,2007,26(3)：320-323.
126.沈祖培,唐辉.有共因失效的系统可靠性的GO法分析[J].清华大学学报(自然科学版),2006,46(6)：829-832.
127.苏春,许映秋.复杂机电产品动态可靠性建模理论与方法研究[J].中国制造业信息化,2006,35(9)：24-32.
128.徐文征.GO法与故障树可靠性建模的比较研究[J].北京轻工业学院学报,17(2)：41-45.
129.袁静,胡昌华,徐瑞,等.一类改进故障树分析法的可靠性仿真及应用[J].计算机应用研究,2006,11：167-172.
130.叶俊,龙志强.基于动态故障树的中低速磁悬浮列车[J].机车电传动,2007,1：25-28.
131.Huang C Y, Chang Y R. An improved decomposition scheme for assessing the reliability of embedded systems by using time-depedent fault trees [J]. Reliability Engineering and System Safety,2007,92:1403-1412.
132.Dugan J B, Bavuso S J, Boyd M A. Time-depedent fault-tree models for fault-tolerant computer system [J]. IEEE Transaction on Reliability,1992,41(3):363-377.
133.Cepin M, Mavko B. A time-depedent fault tree [J]. Reliability Engineering and System Safety,2002,75:83-91.
134.耿江涛,刘向东,杨永田.用通用随机Petri网对硬件冗余容错计算机系统进行可靠性测评[J].计算机与数字工程,1999,27(5)：47-52.
135.王芳,侯朝桢.用蒙特卡罗和Petri网方法估计随机流网络的可靠性[J].北京理工大学学报,2004,24(7)：604-608.
136.李妍琛,朱连章.随机Petri网在软件可靠性分析中的应用[J].现代电子技术,2007,2：135-137.
137.苏春,沈戈.基于广义随机Petri网的系统可靠性建模与仿真软件开发[J].现代设计与先进制造技术,2007,36(9)：45-48.
138.Ionescu D C, Ulmeanu A P, Constantinescu A C, et al. Reliability modelling of medium voltage distribution systems of nuclear power plants using generalized stochastic Petri nets [J]. Computers and Mathematics with Applications,2006,51:285-290.
139.Volovoi V. Modeling of system reliability Petri nets with aging tokens [J]. Reliability Engineering and System Safety,2004,84:149-161.
140.Dutuit Y, Chatelet E, Signoret J P, et al. Dependability modeling and evaluation by using stochastic Petri nets: application to two test cases [J]. Reliability Engineering and System Safety,1997,55:117-124.
141.Alireza E, Seyed G M. FPGA-based Monte Carlo simulation for fault tree analysis [J]. Microelectronics Reliability,2004,44:1017-1028.
142.Marseguerra M, Zio E, Devooght J, et al. A concept paper on time-depedent reliability via Monte Carlo simulation [J]. Mathematics and Computers in Simulation,1998, 47:371-382.
143.Marseguerra M, Zio E, Cadini F. Biased Monte Carlo unavailability analysis for systems with time-dependent failure rates [J]. Reliability Engineering and System Safety,2002, 76(1):11-17.
144.苏春,王圣金,许映秋.基于蒙特卡洛仿真的液压系统动态可靠性[J].东南大学学报(自然科学版),2006,36(3)：370-373.
145.肖刚,李天柁,余梅.动态系统可靠性仿真的五种蒙特卡罗方法[J].计算物理,2001,18(2)：173-176.
146.付惠民.三参数幂函数回归分析[J].航空动力学报,1994,9(2)：186-190.
147.喻天翔,张祖明.机械系统可靠性设计新理论和零件相关系数的求解[J].北京印刷学院学报,2002,10(3)：16-27.
148.吴波,黎明发.机械零件与系统可靠性模型[M].北京：化学工业出版社,2002.217-219.
149.茆诗松,王静龙,濮晓龙.高等数理统计[M].北京：高等教育出版社；德国：施普林格出版社,1998：80-86.
150.Li JianPing, Thompson G. A method to take account of in-homogeneity in mechanical component reliability calculations [J]. IEEE Transaction on Reliability,2005,54: 159-168.
151.Ove Ditlevsen. Stochastic model for joint wave and wind loads on offshore structures [J]. Structural Safety,2002,24:139-163.
152.林元烈.应用随机过程[M].清华大学出版社,2002.
153.高镇同,熊峻江.疲劳可靠性[M].北京航空航天大学,2001.
2.黄挺,朱北园.可靠性技术的最新进展[J].质量与可靠性,2002,17(5)：21-25.
3.郑骏.软件可靠性建模的发展和存在的问题[J].计算机科学,1995,(6)：74-78.
4.汪胜陆.机械产品可靠性设计方法及其发展趋势的探讨[J].机械设计,2007,24(5)：1-3.
5.谢里阳,何雪宏,李佳.机电系统可靠性与安全性设计[M].哈尔滨工业大学出版社,2006.
6. Xie Liyang, Zhou Jinyu, Hao Changzhong. System-level load-strength interference based reliability modeling of k-out-of-n system [J]. Reliability Engineering and System Safety, 2004,84:311-317.
7. Place C S, Strutt J E, Allsopp K, et al. Reliability prediction of helicopter transmission systems using stress-strength interference with underlying damage accumulation [J]. Quality and Reliability Engineering International,1999,15:69-78.
8. Levitin G. Incorporating common-cause failures into no repairable multi-state series-parallel system analysis [J]. IEEE Transactions on Reliability,2001,50 (4): 380-388.
9.谢里阳,林文强.共因失效概率预测的离散化模型[J].核科学与工程,2002,22(2)：186-192.
10.钟培道.航空发电机转动件共模失效的特征、原因与对策[J].航空科学技术,2000,4：33-35.
11.[美]E.J.亨利等著,吕应中等译.可靠性工程与风险分析[M].北京：原子能出版社,1988.
12. Werner W. Result of recent risk studies in France, Germany, Japan, Sweden and the United States [R]. NEA/CSNI/R (1994)10, Paris,1994.
13. Vaurio J K. Optimization of test and maintenance intervals based on risk and cost [J]. Reliability Engineering and System Safety,1995,49:23-26.
14. Meslin B T. Analysis and quantification on common cause failure on the basic of operating experience [J]. Nuclear Technology,1989,84:239-246.
15.喻天翔,张选生,张祖明.轴的多失效模式相关的可靠性计算[J].机械传动, 2002,3：30-34.
16. Martz H F, Kvam P H, Abramson LR. Empirical bayes estimation of the reliability of nuclear power plant emergency diesel generators [J]. Technometric,1996,38:11-24.
17. Elmer E L. A load-capacity interference model for common-mode failures in 1-out-of-2: G systems [J]. IEEE Transaction on Reliability,2001,50(1):47-51.
18. Knut O R, Gunner C L. Reliability-based design of wind-turbine rotor blades against failure in ultimate loading [J]. Engineering Structures,2000,22:565-574.
19. Li Bing, Zhu Meilin, Xu Kai. A practical engineering method for fuzzy reliability analysis of mechanical structures [J]. Reliability Engineering and System Safety,2000, 67:311-315.
20.谢里阳,李翠玲.相关系统失效概率的次序统计量模型及共因失效原因分析[J].机械强度,2005,27(1)：66-71.
21. Place C S, Strutt J E, Allsopp K, et al. Reliability prediction of helicopter transmission systems using stress-strength interference with underlying damage accumulation [J]. Quality and Reliability Engineering International,1999,15:69-78.
22.孙志礼,陈良玉,张钰,等.机械传动系统可靠性设计模型(Ⅰ)[J].东北大学学报(自然科学版),2003,24(6)：548-551.
23. Petryna Y S, Pfanner D, Stangenberg F, et al. Reliability of reinforced concrete structures under fatigue [J]. Reliability Engineering and System Safety,2002,77:253-261.
24. Murty A S R, Gupta U C, Krishna A R. A new approach to fatigue strength distribution for fatigue reliability evaluation [J]. International Journal of Fatigue,1995,17:85-89.
25. Bebbington M, Lai C D, Zitikis R. Useful periods for lifetime distribution with bathtub shaped hazard rate functions [J]. IEEE transaction on Reliability,2005,55(2):245-251.
26. Xie M, Tang Y, Goh T N. A modified Weibull extension with bathtub-shaped failure rate function [J]. Reliability Engineering and System Safety,2002,76:279-285.
27. Basu A P, Sun Kai. Multivariate exponential distributions with constant failure rates [J]. Journal of Multivariate Analysis,1997,61:159-169.
28. AGREE. Reliability of Military Electronic Equipment, report of the advisory Group on Reliability of Electronic Equipment, Washington DC:Office of the Assistant Secretary of Defense,1957.
29. Surles J G., Padgett W J, Inference for reliability and stress-strength for a scaled burr type X distribution [J]. Lifetime Data Analysis,2001,7:187-200.
30. Lynch J D. On the joint distribution of component failures for monotone load-sharing systems [J]. Journal of Statistical Planning and Inference,1999,78:13-21.
31. Zhao Y X, Gao Q, Wang J N. An approach for determining an appropriate assumed distribution of fatigue life under limited data [J]. Reliability Engineering and System Safety,2000,67:1-7.
32. Saralees Nadarajah. On the moments of the modified Weibull distribution [J]. Reliability Engineering and System Safety,2005,90:114-117.
33. Massim Y, Zeblah A, Meziane R, et al. Optimal design and reliability evaluation of multi-state series-parallel power systems [J]. Nonlinear Time-depedents,2005,40: 309-321.
34. Jong Gyun Choi, Poong Hyun Seong. Reliability assessment of embedded digital system using multi-state function [J]. Reliability Engineering and System Safety,2006,91: 261-269.
35. Jose E Ramirez-Marquez, David W Coit. A Monte-Carlo simulation approach for approximating multi-state two-terminal reliability [J]. Reliability Engineering and System Safety,2005,87:253-264.
36. Li Jing-an, Wu Yue, Lai Kin Keung, Liu Ke. Reliability estimation and prediction of multi-state components and coherent systems [J]. Reliability Engineering and System Safety,2005,88:93-98.
37. Krzysztof Kolowrocki. Asymptotic approach to reliability evaluation of large multi-state systems with application to piping transportation [J]. International Journal of Pressure Vessels and Piping,2003,80:59-73.
38. Somasundaram S, Audsin Mohana Dhas D. Reliability of a time-depedent n-unit shared load parallel system under different failure times [J]. Microelectronics Reliability,1997, 37(5):869-871.
39. Yang Kai, Younis Hisham. A semi-analytical Monte Carlo simulation method for system's reliability with load sharing and damage accumulation [J]. Reliability Engineering and System Safety,2005,87:191-200.
40. Durham S D, Lynch J D. A threshold representation for the strength distribution of a complex load sharing system [J]. Journal of Statistical Planning and Inference,200,83: 25-46.
41. Avvenuti Marco, Rizzo Luigi, Vicisano Lorenzo. Hardware support for load sharing in parallel systems [J]. Journal of Systems Architecture,1996,42:129-143.
42. Hyoungtae K, Paul H K, Reliability Estimation Based on System Data with an Unknown Load Share Rule [J], Lifetime Data Analysis,2004,10:83-94.
43. Kiyoshi Aida, Yasuyuki Owa, Kohei Suzuki, et al. Evaluation of aseismic reliability of Actual boiler structures and a study on design of seismic ties based on proof tests using a large scaled shaking table [J]. Journal of Pressure Vessel Technology,2004,126:46-52.
44. Jonnalagadda K. Reliability of via-in-pad structures in mechanical cycling fatigue [J], Microelectronics Reliability,2002,42:253-258.
45. Franchin P, Lupoi A, Pinto P E. Seismic fragility of reinforced concrete structures using a response surface approach [J]. Journal of Earthquake Engineering,2003,7:45-77.
46. Leira B J, Holma T, Herfjor K. Application of response surfaces for reliability analysis of marine structures [J]. Reliability Engineering and System Safety,2005,90:131-139.
47. Lee Hyungyil, Seo Heon, Park Gyungjin. Design enhancements for stress relaxation in automotive multi-shell-structures [J]. International Journal of Solids and Structures,2003, 40:5319-5334.
48.魏华春,张彤.一种机构可靠性的仿真分析方法[J].工程图学学报,2004,3：26-29.
49.孙志礼,陈良玉.实用机械可靠性设计理论与方法[M].北京：科学出版社,2003.210-212.
50.李良巧,顾唯明.机械可靠性设计与分析[M].北京：国防工业出版社,1998.224-245.
51. Cole G K, Ronalds B F, Fakas E. The interaction between strength and fatigue reliability for a minimum structure in shallow water [J]. Journal of Offshore Mechanics and Arctic Engineering,2003,125:282-287.
52. Jing Ling, Pan Jwo. Engineering method for reliability analyses of mechanical structures for long fatigue lives [J]. Reliability Engineering and System Safety,1997,56:135-142.
53. Kim Sang-Hyo, Lee Sang-Woo, Mha Ho-Seong. Fatigue reliability assessment of an existing steel railroad bridge [J]. Engineering Structures,2001,23:1203-1211.
54. Le Xiaobin, Peterson M L. A method for fatigue based reliability when the loading of a component is unknown [J]. International Journal of Fatigue,1999,21:603-610.
55. Zhao Y X. A methodology for strain-based fatigue reliability analysis [J]. Reliability Engineering and System Safety,2000,70:205-213.
56. Ni Kan, Zhang Shengkun. Fatigue reliability analysis under two-stage loading [J]. Reliability Engineering and System Safety,2000,68:153-158.
57. Zhao Jie, Tang Jun, Wu Han C. A Generalized Random Variable Approach for Strain-Based Fatigue Reliability Analysis [J], Transactions of the ASME,2000,122: 156-161.
58. As S K, Skallerud B, Tveiten B W, et al. Fatigue life prediction of machined components using finite element analysis of surface topography [J]. International Journal of Fatigue, 2005,27:1590-1596.
59.王正,谢里阳,李兵.考虑共因失效的机械零部件可靠性模型[J].机械设计,2007,24(1)：4-5.
60. Hagen E W. Common-mode/common-cause failure:a review [J]. Nuclear Engineering and Design,1980,59:423-431.
61. Epler E P. Common mode failure considerations in the design of system for protection and control [J]. Nuclear Safety,1969,10:38-45.
62. Fleming K N. A reliability model for common cause failures in redundant safety systems [C]. Sixth annual Pittsburgh conference on modeling and simulation, Pittsburgh,1975.
63. Hanks B J. An appreciation of common cause failures in reliability[C]. Proceeding of the Institution of Mechanical Engineers. Part E: Journal of Process Mechanical Engineering. 1998,212:31-35
64. Fleming K N, Hunnaman G W. Common cause failure considerations in predicting HTGR cooling system reliability[J]. IEEE Transaction on Reliability,1976,25:171-177.
65. Vaurio J K. Availability of redundant safety systems with common mode and undetected failures [J]. Nuclear Engineering and Design,1980,58:415-424.
66. Mankamo T, Kosonen M. Dependent failure modeling in highly redundant structures-application to BWR safety valves [J]. Reliability Engineering and System Safety,1992,35:235-244.
67. Atwood C L. The binomial failure rate common cause model [J]. Technometrics,1986, 28:139-148.
68. Fleming K N, Mosleh A, Deremer R K. A systematic procedure for the incorporation of common cause events into risk and reliability models [J]. Nuclear Engineering and Design,1986,93:245-273.
69. Johnston B D. A structured procedure for dependent failure analysis [J]. Reliability Engineering and System Safety,1987,19:125-136.
70. Harris B. Stochastic models for common cause failures [J]. Reliability and Quality Control,1986:185-200.
71. Guey C N, Heising C D. Development of a common cause failure analysis method:the inverse stress-strength interference (ISSI) technique [J]. Structural Safety,1986,4:63-77.
72. Chae K C, Clark G M. System reliability in the presence of common-cause failures [J]. IEEE Transaction on Reliability,1986,35:32-35.
73. Mosleh A. Common causes failures:an analysis methodology and examples [J]. Reliability Engineering and System Safety,1991,34:249-292.
74. Mankamo T, Kosonen M. Dependent failure modeling in highly redundant structures-application to BWR safety valves [J]. Reliability Engineering and System Safety,1992,35:235-244.
75. Mosleh A, Parry G W, Zikria A F. An approach to the analysis of common cause failure data for plant-specific application [J]. Nuclear Engineering and Design,1994,150:25-47.
76. Vaurio J K. Common cause failure models, data, quantification [J]. Reliability Engineering and System Safety,1996,53:85-96.
77. Dore P. Basic aspects of stochastic reliability analysis for redundancy systems [J]. Reliability Engineering and System Safety,1989,24:351-375.
78. Vaurio J K. Common cause failure probabilities in standby safety system fault tree analysis with testing-scheme and timing dependencies [J]. Reliability Engineering and System Safety,2003,79:43-57.
79. Vaurio J K, Availability of redundant safety systems with common mode and undetected failures [J]. Nuclear Engineering and Design,1980,58:415-424.
80. Hokstad P. A shock model for common cause failure [J]. Reliability Engineering and System Safety,1988,23:127-145.
81. Vaurio J K. An implicit method for incorporating common cause failures in system analysis [J]. IEEE Trans Raliab,1998,47(2):173-180.
82. Marshall A W, Olkin I. A multivariate exponential distribution [J]. Journal of the American Statistical Association,1967,62:30-44.
83. Hughes R P. A new approach to common cause failure [J]. Reliability Engineering and System Safety,1987,17:211-236.
84. Fleming K N, Mosleh A. Classification and analysis of reactor operating experience involving dependent failures. NP-3967. Electric Power Research Institute, June 1985.
85. Mosleh A, Siu N O. A multi-parameter event-based common-cause failure model[C]. Proceedings of the Ninth International Conference on Structural Mechanics in Reactor Technology,1987:147-152.
86. Hauptmanns U. The multi-class binomial failure rate model [J]. Reliability Engineering and System Safety,1996,53:85-90.
87. Kvam P H. A parametric mixture-model for common-cause failure data [J]. IEEE Transaction on Reliability,1998,47(1):30-34.
88. Kvam P H. The binomial failure rate mixture model for common cause failure data from the nuclear industry [J]. Application Statistics,1998,47:49-61.
89. Xie L Y. A knowledge-based multi-dimension discrete common cause failure model [J]. Nuclear Engineering and Design,1998,183:107-116.
90.黄祥瑞.可靠性工程[M].清华大学出版社,1990.
91.安伟光.系统可靠性评定方法的研究[J].应用科技,1995,4：24-29.
92.冷护基,李广安,张志胜,等.贮备冗余系统的模糊可靠性[J],机械工程学报,1998,34(3)：26-32.
93.冷护基,李广安,陈胜军,等.冷贮备系统的模糊可靠性[J].系统工程理论与实践,1997,11：113-123.
94.李铎,石铭德,马昌文.低温核供热站数字化保护系统的研究及其可靠性分析[J].核动力工程,1999,20(3)：269-273.
95.王光远,谭东耀.失效相关工程系统的可靠度[J].地震工程与工程振动,1992,12(1)：1-5.
96.王光远,张鹏.具有中介状态的工程系统的可靠性分析[J].土木工程学报.2001,34(3)：13-17.
97.何钟怡.单一随机扰动源作用下工程结构的失效相关问题[J].地震工程与工程振动,1994,14(2)：76-85.
98.张鹏,胡秀庄,孙鸿玲.失效相关下串联和并联工程系统的可靠性向量方法[J].四川大学学报(工程科学版),2004,36(1)：1-6.
99.张鹏,张庆功,胡启国.改进的哈马邱尔算子在系统可靠性分析中的应用[J].机械强度,2006,28(1)：70-78.
100.王学敏,谢里阳,周金宇.共因失效率的不确定性评估[J].航空学报,2005,26(1)：.446-449.
101.周金宇,谢里阳,王学敏.相关失效结构系统可靠度的近似求解方法[J].东北大学学报(自然科学版),2004,25(1)：74-77.
102.谢里阳,周金宇,李翠玲,等.系统共因失效分析及其概率预测的离散化建模方法[J].机械工程学报,2006,42(1)：62-68.
103.王学敏,谢里阳,周金宇,王芸.相关失效系统的可靠性模型[J].东北大学学报,2004,25(9)：887-890.
104.王学敏,谢里阳,周金宇.基于幂指数分布的共因失效新模型[J].机械制造,2004,42(9)：58-61.
105.Xie Liyang, Zhou Jinyu, Wang Yongyan, et al. Load-strength order statistics interference models for system reliability evaluation [J]. International Journal of Performance Engineering,2005,1(1):23-36.
106.Wang Zheng, Xie Liyang. Reliability Model of Component under Stochastic Ally Repeated Load [C]. The first international conference on maintenance engineering. Beijing:Science Press,2006:895-900.
107.Giinter Beckera, Leonidas Camarinopoulos, Dimitris Kabranis. Time-depedent reliability under random shocks [J]. Reliability Engineering and System Safety,2002,24:239-251.
108.Chen J J, Zeng Y G, Sun H A. Time-depedent reliability analysis of antenna reflector accuracy under wind excitation [J]. Computers & Structures,1996,59:819-822.
109.Cazuguel M, Renaud C, Cognard J Y. Time-variant reliability of nonlinear structures: application to a representative part of a plate floor [J]. Quality and Reliability Engineering International,2006,22:101-108.
110.Streicher H, Rackwitz R. Time-variant reliability-oriented structural optimization and a renewal model for life-cycle costing [J]. Probabilistic Engineering Mechanics,2004,19: 171-183.
111.Tian Liang, Noore Afzel. Time-depedent software reliability prediction:an approach based on support vector machines [J]. International Journal of Reliability, Quality and Safety Engineering,2005,12:309-321.
112.Kopustinskas V, Augutis J, Rimkevicius S. Time-depedent reliability and risk assessment of the accident localization system of the Ignalina NPP RBMK-1500 reactor [J]. Reliability Engineering and System Safety,2005,87:101-108.
113.Wang K S., Chen C S, Hung J J. Time-depedent reliability behavior of carburized steel sliding wear [J]. Reliability Engineering and System Safety,1997,58:31-41.
114.P.D.T. O'Connor. Practical Reliability Engineering [M]. Wiltshire:John Wiley & Sons, Inc.1985,105-106.
115.李艺,闫运起.现役结构时变可靠性评估[M].东北大学出版社,2004,9.
116.姚卫星,结构疲劳可靠性模型[M].国防工业出版社,2003.
117.左勇志,刘西拉.结构动态可靠性的全随机过程模型[J].清华大学学报(自然科学版),2004,44(3)：395-397,405.
118.黄飞腾,郁军,肖航.基于Markov状态转移的动态可靠性分析[J].海军工程大学学报,2002,14(6)：80-83.
119.崔利荣.马尔可夫链在可靠性计算中的一些新应用[J].系统工程与电子技 术,1999,12(12)：89-91.
120.吴志良,郭晨,赵红.基于马尔柯夫过程的可修系统可靠性建模[J].大连海事大学学报,2007,33(1)：13-16.
121.李守仁,袁海蓉.确定不同单元并联系统可靠性的马尔可夫过程[J].哈尔滨工程大学学报,2003,24(1)：90-93.
122.沈戈,苏春,许映秋.基于Petri网理论的动态系统可靠性建模方法研究[J].机械工程与自动化,2006,135(2)：1-3,10.
123.苏春,沈戈,许映秋.基于随机故障Petri网的液压系统可靠性建模与分析[J].液压与气动,2006,6：29-31.
124.Matsuoka T, Kobayashi M. The GO-FLOW reliability analysis methodology—analysis of common cause failures with uncertainty [J]. Nuclear Engineering and Design,1997, 175:205-214.
125.高振清,孙厚芳,吴琼.基于GO法的制造系统可靠性分析[J].机械科学与技术,2007,26(3)：320-323.
126.沈祖培,唐辉.有共因失效的系统可靠性的GO法分析[J].清华大学学报(自然科学版),2006,46(6)：829-832.
127.苏春,许映秋.复杂机电产品动态可靠性建模理论与方法研究[J].中国制造业信息化,2006,35(9)：24-32.
128.徐文征.GO法与故障树可靠性建模的比较研究[J].北京轻工业学院学报,17(2)：41-45.
129.袁静,胡昌华,徐瑞,等.一类改进故障树分析法的可靠性仿真及应用[J].计算机应用研究,2006,11：167-172.
130.叶俊,龙志强.基于动态故障树的中低速磁悬浮列车[J].机车电传动,2007,1：25-28.
131.Huang C Y, Chang Y R. An improved decomposition scheme for assessing the reliability of embedded systems by using time-depedent fault trees [J]. Reliability Engineering and System Safety,2007,92:1403-1412.
132.Dugan J B, Bavuso S J, Boyd M A. Time-depedent fault-tree models for fault-tolerant computer system [J]. IEEE Transaction on Reliability,1992,41(3):363-377.
133.Cepin M, Mavko B. A time-depedent fault tree [J]. Reliability Engineering and System Safety,2002,75:83-91.
134.耿江涛,刘向东,杨永田.用通用随机Petri网对硬件冗余容错计算机系统进行可靠性测评[J].计算机与数字工程,1999,27(5)：47-52.
135.王芳,侯朝桢.用蒙特卡罗和Petri网方法估计随机流网络的可靠性[J].北京理工大学学报,2004,24(7)：604-608.
136.李妍琛,朱连章.随机Petri网在软件可靠性分析中的应用[J].现代电子技术,2007,2：135-137.
137.苏春,沈戈.基于广义随机Petri网的系统可靠性建模与仿真软件开发[J].现代设计与先进制造技术,2007,36(9)：45-48.
138.Ionescu D C, Ulmeanu A P, Constantinescu A C, et al. Reliability modelling of medium voltage distribution systems of nuclear power plants using generalized stochastic Petri nets [J]. Computers and Mathematics with Applications,2006,51:285-290.
139.Volovoi V. Modeling of system reliability Petri nets with aging tokens [J]. Reliability Engineering and System Safety,2004,84:149-161.
140.Dutuit Y, Chatelet E, Signoret J P, et al. Dependability modeling and evaluation by using stochastic Petri nets: application to two test cases [J]. Reliability Engineering and System Safety,1997,55:117-124.
141.Alireza E, Seyed G M. FPGA-based Monte Carlo simulation for fault tree analysis [J]. Microelectronics Reliability,2004,44:1017-1028.
142.Marseguerra M, Zio E, Devooght J, et al. A concept paper on time-depedent reliability via Monte Carlo simulation [J]. Mathematics and Computers in Simulation,1998, 47:371-382.
143.Marseguerra M, Zio E, Cadini F. Biased Monte Carlo unavailability analysis for systems with time-dependent failure rates [J]. Reliability Engineering and System Safety,2002, 76(1):11-17.
144.苏春,王圣金,许映秋.基于蒙特卡洛仿真的液压系统动态可靠性[J].东南大学学报(自然科学版),2006,36(3)：370-373.
145.肖刚,李天柁,余梅.动态系统可靠性仿真的五种蒙特卡罗方法[J].计算物理,2001,18(2)：173-176.
146.付惠民.三参数幂函数回归分析[J].航空动力学报,1994,9(2)：186-190.
147.喻天翔,张祖明.机械系统可靠性设计新理论和零件相关系数的求解[J].北京印刷学院学报,2002,10(3)：16-27.
148.吴波,黎明发.机械零件与系统可靠性模型[M].北京：化学工业出版社,2002.217-219.
149.茆诗松,王静龙,濮晓龙.高等数理统计[M].北京：高等教育出版社；德国：施普林格出版社,1998：80-86.
150.Li JianPing, Thompson G. A method to take account of in-homogeneity in mechanical component reliability calculations [J]. IEEE Transaction on Reliability,2005,54: 159-168.
151.Ove Ditlevsen. Stochastic model for joint wave and wind loads on offshore structures [J]. Structural Safety,2002,24:139-163.
152.林元烈.应用随机过程[M].清华大学出版社,2002.
153.高镇同,熊峻江.疲劳可靠性[M].北京航空航天大学,2001.
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