装备测试性验证试验优化设计与综合评估方法研究
|
摘要
测试性是装备研制和采办中一个非常重要的技术指标。测试性验证与评估是检验和评估由设计和制造所赋予装备的测试性,是装备采办管理和科学决策的基础。在试验费用和试验周期的约束下,如何开展测试性验证试验设计与综合评估,对装备测试性水平给出低风险的验证结论和高置信度的评估结论,是理论和工程实践中亟待解决的问题,因而具有重要的理论和工程应用价值。
论文针对开展测试性验证试验与评估存在的费用高、周期长,验证与评估结论风险高,精度、置信度低等问题,以故障检测率(Fault Detection Rate,FDR)和故障隔离率(Fault Isolation Rate,FIR)为具体的验证与评估指标,提出了基于全寿命周期数据的测试性验证试验优化设计与综合评估技术解决方案,系统深入地研究了测试性验证试验设计中的故障样本优化选取方法、故障有效注入方法和测试性综合评估方法,并通过案例应用,验证方法的有效性。
论文的主要研究内容与结论包括:
1.在深入分析影响测试性验证试验风险与评估精度、置信度的因素基础上,建立了以二项分布为基础的标准抽样方案与FDR/FIR验证结论风险、置信度的关系模型,给出了抽样样本集大小和样本结构对验证结论风险、置信度的影响规律;建立了故障检测/隔离数据量与FDR/FIR评估结论精度、置信度的关系模型,给出了故障检测/隔离数据量对评估结论精度、置信度的影响规律。上述模型以及所描述的本质关系和规律为后续有针对性的开展测试性验证试验优化设计与综合评估方法研究提供了技术指导并奠定了理论基础。
2.为解决由于标准抽样方案确定的故障样本量太大导致试验无法展开;故障样本结构不合理导致测试性验证结论置信度低以及在相同的故障样本量下,由于随机抽样导致故障样本集对被测对象(Unit Under Test,UUT)故障模式集的代表性无法评判等问题,分别从确定优化故障样本量、构建合理的故障样本结构和故障样本集评估优选三个方面,研究并提出了测试性验证试验设计中的故障样本优化选取方法,为装备测试性验证试验设计提供了新的故障样本优化选取思路和方法。
(1)针对如何确定优化抽样方案问题,在有效分析研制阶段测试性先验数据基础上,提出了一种利用研制阶段先验数据的优化抽样方案确定方法。研究表明优化抽样方案在承制方、使用方风险基本不变的情况下,能有效减少故障样本量;或在故障样本量保持不变的情况下,将有效降低承制方、使用方风险。
(2)针对先验故障率数据不准确导致现有的基于故障率的分层故障样本量分配带来的随机抽样误差过大问题,在分析基于故障率和装备复杂度分层故障样本量分配模型随机抽样误差影响因素基础上,提出了基于专家经验数据的故障率Gamma估计方法和基于定时截尾“小子样”试验数据的故障率Bootstrap极大似然估计方法,据此故障率估计值完成分层故障样本量分配。研究表明本文给出的故障样本量分配得到的故障样本结构更合理,可有效减小随机抽样误差。
(3)针对如何对传播型故障模式描述与抽取问题,引入模糊概率Petri网来描述故障的传播扩散过程,并在模糊概率Petri网推理算法基础上求得故障扩散强度。以此为基础,提出了基于故障扩散强度的故障模式随机重要抽样算法。研究表明对故障扩散强度高的故障模式做重要抽样,将能有效降低使用方风险。
(4)为解决在相同故障样本量下如何对随机抽取的多个故障样本集进行评估优选,建立了衡量故障样本集对故障模式集代表性好坏的评价指标体系及其量化方法,给出了具体的故障样本集优选模型和方法。研究表明采用本文的优选算法,其优选后的故障样本集能更好地代表被测对象的故障模式集。
3.为解决位置不可访问故障的有效注入问题,在深入分析影响故障注入有效性主要因素基础上,建立了故障—状态、故障—故障之间传递特性分析模型,并以故障传递特性为依据,建立了基于故障传递特性的故障模型和位置不可访问故障注入方法以及故障注入策略优化设计方法。研究表明基于故障传递特性的故障注入方法能在保证较高的故障样本注入率,有效节省试验费用的情况下,较好地解决装备位置不可访问故障的注入问题,具有重要的理论意义和工程指导作用。
4.针对小样本情况下FDR/FIR评估结论置信度低的问题,研究并提出了基于Bayes变动统计理论的FDR/FIR综合评估模型和方法。首先以多元Dirichlet分布为先验分布,提出了由可更换单元测试性信息、专家经验信息确定先验分布参数的方法,将先验信息转化为先验分布。在此基础上,融合“小子样、异总体”研制阶段增长试验数据和“小子样”外场使用数据,研究并提出了FDR/FIR的Bayes综合评估模型。同时针对FDR/FIR的Bayes综合评估模型的复杂高维后验积分求解问题,分别给出了解析计算方法和马尔科夫链蒙特卡罗法(Markov Chain Monte Carlo,MCMC)抽样计算方法,并仿真分析了模型的稳健性。研究表明利用该模型进行FDR/FIR综合评估,能在较短的外场使用周期内或小样本数据情况下,给出较高置信度的评估结论,为装备测试性综合评估研究提供了重要的理论依据和方法。
5.研制开发了装备测试性验证试验优化设计与综合评估系统,并以某型导弹控制系统为对象开展了演示验证应用。该系统能为装备测试性验证试验优化设计与综合评估提供有力的工具,具有很好的工程应用和推广价值。
Testability is a critical technical index of the equipment development and purchase. The testability verification test and evaluation are mainly intend to test and evaluate the equipment testability resulting from the design and manufacturing and are the foundation to the equipment purchase management and scientific decision making. How to implement a study on the optimization for the testability verification test and integrated evaluation method considering the limitation of test cost and period and make a low-risk verification conclusion and a high confidence evaluation conclusion is a pending problem in the theory and engineering. It relates to many physical interest and practical applications.
This paper is aiming to solve the problems of high cost, long period, high-risk verification/evaluation conclusion and low accuracy/confidence level in the testability verification test and evaluation , which takes the fault detection rate (FDR) and fault isolation rate (FIR) as the specific verification and evaluation index. The systematic scheme for design of testability verification test and integrated evaluation is put forward, which is based on data in whole life period.Then, the failure sampling optimization, failure injection efficiency in the design of testability verification test and testability integrated evaluation methods are studied systematically, and the cases are analyzed to verify the effectiveness of all the methods.
The major contents and conclusions of the dissertation are as follows.
1. The model of relationship between the plan of sampling and the risk/confidence level of FDR/FIR verification conclusion is established, the relationship between the failure sampling structure and the risk/confidence level is analyzed , the model of relationship between the failure detection/isolation data number and the accuracy/confidence level of FDR/FIR integrated evaluation conclusion is built up by deeply analyzing of the factors which affect the risk, accuracy and confidence level of the testability verification test and evaluation. The models and the natural relationship described can provide guidance for the further pertinent study of testability verification test optimization design and integrated evaluation.
2.To settle the problems such as testability verification test unable to perform due to the oversized failure sampling determined by typical plan of sampling, the low confidence level of the testability verification test conclusion resulting from the irrational failure sampling structure and the preferred failure sampling set’s represention for the failure mode set of UUT based on random sampling can not be judged, the failure sample optimization selection method for the design of testability verification test is researched by determining the optimized failure sampling size , building the rational failure sampling structure and failure sampling sets evaluation and optimization. What has been investigated can offer us a new idea and method for the failure sample optimization selection of testability verification test.
(1)For the determination of optimized plan of sampling, An optimized plan of sampling which is put forward based on the prior equivalent binomial data during the development stage. The study shows the failure sampling size can be efficiently reduced providing the little risk change of the producer/user and the risk of the producer/user efficiently reduced providing no change of failure sampling size.
(2)For the gross error of random sampling of the failure rate-based failure sampling size resulting from the inaccurate prior failure rate, The influencing factors to error of random sampling of the failure rate-based failure sampling size allocation model are analyzed. On such basis, a Gamma distribution-based failure rate estimation method and a Bootstrap maximum likelihood failure rate estimation method are researched, so as to make a failure sampling size allocation distribution on failure rate and equipment complexity basis.The study says a more rational failure sampling structure can be obtained by the failure sampling size allocation on such basis and the error of random sampling can be decreased effectively.
(3)For the description and sampling of propagation failure, a fuzzy probability Petri net is built to descript the propagation of failure and the fuzzy probability Petri net inference algorithm is added on the fuzzy probability Petri net to get the failure propagation intensity.On such basis, a random selective sampling algorithm is put forward based on the failure propagation intensity. The study indicates the random selective sampling algorithm can play a key role for the reduction of the final risk of the user.
(4)Considering the problems such as evaluate the various failure sampling sets randomly sampled, a evaluation index system is founded and quantified weighing the representation of the failure sampling set to the failure mode set, on such basis the model and method for failure sample set evaluation are put forward. The study indicates the preferred failure sampling set can accurately represent the failure mode set of the subject to be tested.
3.For the incapability of effective injection of failure resulting from the inaccessible location, by deepening the analysis on the major factors affecting the effectiveness of the failure injection, the failure propagation characteristic-based failure model and such model-based injection method of failure resulting from the inaccessible location are researched in light of the failure propagation characteristic. The study clarifies the failure propagation characteristic-based failure injection method effectively works out the injection incapability of failure resulting from the inaccessible location. At the same time, the fault injection cost can be considerably cut down. What has been researched can relate to many theory interest and practical applications.
4.For problems in the FDR/FIR evaluation occurred when the field usage data for testability of equipment with high reliability is small sample, the Bayes Inference on Dynamic Population-based FDR/FIR integrated evaluation model and method are considered and launched. To comprehensively utilize the plentiful module test information and expert information in the equipment development stage, the pertinent information fusion method is advanced according to various information types. With the multivariate Dirichlet distribution as the prior distribution and the complete fusion of growth test data in development stage and field usage data, the FDR/FIR integrated evaluation model based Bayes inference on dynamic population is set up. An analytical method and Markov Chain Monte Carlo method are adopted to solve the complex posterior distribution inference problem. The model robustness is investigated. The study shows the FDR/FIR integrated evaluation by means of such model can produce the evaluation conclusion with high confidence level in a short field usage period or under“small sample”condition. What has been investigated can offer us an important theory base and method for testability integrated evaluation of equipments.
5.A system for optimization of testability verification test and integrated evaluation is developed and take a missile control system as the subject of application. The system furnishes a useful tool for the optimization of testability verification test and integrated evaluation of large scale and complicated equipment.
论文针对开展测试性验证试验与评估存在的费用高、周期长,验证与评估结论风险高,精度、置信度低等问题,以故障检测率(Fault Detection Rate,FDR)和故障隔离率(Fault Isolation Rate,FIR)为具体的验证与评估指标,提出了基于全寿命周期数据的测试性验证试验优化设计与综合评估技术解决方案,系统深入地研究了测试性验证试验设计中的故障样本优化选取方法、故障有效注入方法和测试性综合评估方法,并通过案例应用,验证方法的有效性。
论文的主要研究内容与结论包括:
1.在深入分析影响测试性验证试验风险与评估精度、置信度的因素基础上,建立了以二项分布为基础的标准抽样方案与FDR/FIR验证结论风险、置信度的关系模型,给出了抽样样本集大小和样本结构对验证结论风险、置信度的影响规律;建立了故障检测/隔离数据量与FDR/FIR评估结论精度、置信度的关系模型,给出了故障检测/隔离数据量对评估结论精度、置信度的影响规律。上述模型以及所描述的本质关系和规律为后续有针对性的开展测试性验证试验优化设计与综合评估方法研究提供了技术指导并奠定了理论基础。
2.为解决由于标准抽样方案确定的故障样本量太大导致试验无法展开;故障样本结构不合理导致测试性验证结论置信度低以及在相同的故障样本量下,由于随机抽样导致故障样本集对被测对象(Unit Under Test,UUT)故障模式集的代表性无法评判等问题,分别从确定优化故障样本量、构建合理的故障样本结构和故障样本集评估优选三个方面,研究并提出了测试性验证试验设计中的故障样本优化选取方法,为装备测试性验证试验设计提供了新的故障样本优化选取思路和方法。
(1)针对如何确定优化抽样方案问题,在有效分析研制阶段测试性先验数据基础上,提出了一种利用研制阶段先验数据的优化抽样方案确定方法。研究表明优化抽样方案在承制方、使用方风险基本不变的情况下,能有效减少故障样本量;或在故障样本量保持不变的情况下,将有效降低承制方、使用方风险。
(2)针对先验故障率数据不准确导致现有的基于故障率的分层故障样本量分配带来的随机抽样误差过大问题,在分析基于故障率和装备复杂度分层故障样本量分配模型随机抽样误差影响因素基础上,提出了基于专家经验数据的故障率Gamma估计方法和基于定时截尾“小子样”试验数据的故障率Bootstrap极大似然估计方法,据此故障率估计值完成分层故障样本量分配。研究表明本文给出的故障样本量分配得到的故障样本结构更合理,可有效减小随机抽样误差。
(3)针对如何对传播型故障模式描述与抽取问题,引入模糊概率Petri网来描述故障的传播扩散过程,并在模糊概率Petri网推理算法基础上求得故障扩散强度。以此为基础,提出了基于故障扩散强度的故障模式随机重要抽样算法。研究表明对故障扩散强度高的故障模式做重要抽样,将能有效降低使用方风险。
(4)为解决在相同故障样本量下如何对随机抽取的多个故障样本集进行评估优选,建立了衡量故障样本集对故障模式集代表性好坏的评价指标体系及其量化方法,给出了具体的故障样本集优选模型和方法。研究表明采用本文的优选算法,其优选后的故障样本集能更好地代表被测对象的故障模式集。
3.为解决位置不可访问故障的有效注入问题,在深入分析影响故障注入有效性主要因素基础上,建立了故障—状态、故障—故障之间传递特性分析模型,并以故障传递特性为依据,建立了基于故障传递特性的故障模型和位置不可访问故障注入方法以及故障注入策略优化设计方法。研究表明基于故障传递特性的故障注入方法能在保证较高的故障样本注入率,有效节省试验费用的情况下,较好地解决装备位置不可访问故障的注入问题,具有重要的理论意义和工程指导作用。
4.针对小样本情况下FDR/FIR评估结论置信度低的问题,研究并提出了基于Bayes变动统计理论的FDR/FIR综合评估模型和方法。首先以多元Dirichlet分布为先验分布,提出了由可更换单元测试性信息、专家经验信息确定先验分布参数的方法,将先验信息转化为先验分布。在此基础上,融合“小子样、异总体”研制阶段增长试验数据和“小子样”外场使用数据,研究并提出了FDR/FIR的Bayes综合评估模型。同时针对FDR/FIR的Bayes综合评估模型的复杂高维后验积分求解问题,分别给出了解析计算方法和马尔科夫链蒙特卡罗法(Markov Chain Monte Carlo,MCMC)抽样计算方法,并仿真分析了模型的稳健性。研究表明利用该模型进行FDR/FIR综合评估,能在较短的外场使用周期内或小样本数据情况下,给出较高置信度的评估结论,为装备测试性综合评估研究提供了重要的理论依据和方法。
5.研制开发了装备测试性验证试验优化设计与综合评估系统,并以某型导弹控制系统为对象开展了演示验证应用。该系统能为装备测试性验证试验优化设计与综合评估提供有力的工具,具有很好的工程应用和推广价值。
Testability is a critical technical index of the equipment development and purchase. The testability verification test and evaluation are mainly intend to test and evaluate the equipment testability resulting from the design and manufacturing and are the foundation to the equipment purchase management and scientific decision making. How to implement a study on the optimization for the testability verification test and integrated evaluation method considering the limitation of test cost and period and make a low-risk verification conclusion and a high confidence evaluation conclusion is a pending problem in the theory and engineering. It relates to many physical interest and practical applications.
This paper is aiming to solve the problems of high cost, long period, high-risk verification/evaluation conclusion and low accuracy/confidence level in the testability verification test and evaluation , which takes the fault detection rate (FDR) and fault isolation rate (FIR) as the specific verification and evaluation index. The systematic scheme for design of testability verification test and integrated evaluation is put forward, which is based on data in whole life period.Then, the failure sampling optimization, failure injection efficiency in the design of testability verification test and testability integrated evaluation methods are studied systematically, and the cases are analyzed to verify the effectiveness of all the methods.
The major contents and conclusions of the dissertation are as follows.
1. The model of relationship between the plan of sampling and the risk/confidence level of FDR/FIR verification conclusion is established, the relationship between the failure sampling structure and the risk/confidence level is analyzed , the model of relationship between the failure detection/isolation data number and the accuracy/confidence level of FDR/FIR integrated evaluation conclusion is built up by deeply analyzing of the factors which affect the risk, accuracy and confidence level of the testability verification test and evaluation. The models and the natural relationship described can provide guidance for the further pertinent study of testability verification test optimization design and integrated evaluation.
2.To settle the problems such as testability verification test unable to perform due to the oversized failure sampling determined by typical plan of sampling, the low confidence level of the testability verification test conclusion resulting from the irrational failure sampling structure and the preferred failure sampling set’s represention for the failure mode set of UUT based on random sampling can not be judged, the failure sample optimization selection method for the design of testability verification test is researched by determining the optimized failure sampling size , building the rational failure sampling structure and failure sampling sets evaluation and optimization. What has been investigated can offer us a new idea and method for the failure sample optimization selection of testability verification test.
(1)For the determination of optimized plan of sampling, An optimized plan of sampling which is put forward based on the prior equivalent binomial data during the development stage. The study shows the failure sampling size can be efficiently reduced providing the little risk change of the producer/user and the risk of the producer/user efficiently reduced providing no change of failure sampling size.
(2)For the gross error of random sampling of the failure rate-based failure sampling size resulting from the inaccurate prior failure rate, The influencing factors to error of random sampling of the failure rate-based failure sampling size allocation model are analyzed. On such basis, a Gamma distribution-based failure rate estimation method and a Bootstrap maximum likelihood failure rate estimation method are researched, so as to make a failure sampling size allocation distribution on failure rate and equipment complexity basis.The study says a more rational failure sampling structure can be obtained by the failure sampling size allocation on such basis and the error of random sampling can be decreased effectively.
(3)For the description and sampling of propagation failure, a fuzzy probability Petri net is built to descript the propagation of failure and the fuzzy probability Petri net inference algorithm is added on the fuzzy probability Petri net to get the failure propagation intensity.On such basis, a random selective sampling algorithm is put forward based on the failure propagation intensity. The study indicates the random selective sampling algorithm can play a key role for the reduction of the final risk of the user.
(4)Considering the problems such as evaluate the various failure sampling sets randomly sampled, a evaluation index system is founded and quantified weighing the representation of the failure sampling set to the failure mode set, on such basis the model and method for failure sample set evaluation are put forward. The study indicates the preferred failure sampling set can accurately represent the failure mode set of the subject to be tested.
3.For the incapability of effective injection of failure resulting from the inaccessible location, by deepening the analysis on the major factors affecting the effectiveness of the failure injection, the failure propagation characteristic-based failure model and such model-based injection method of failure resulting from the inaccessible location are researched in light of the failure propagation characteristic. The study clarifies the failure propagation characteristic-based failure injection method effectively works out the injection incapability of failure resulting from the inaccessible location. At the same time, the fault injection cost can be considerably cut down. What has been researched can relate to many theory interest and practical applications.
4.For problems in the FDR/FIR evaluation occurred when the field usage data for testability of equipment with high reliability is small sample, the Bayes Inference on Dynamic Population-based FDR/FIR integrated evaluation model and method are considered and launched. To comprehensively utilize the plentiful module test information and expert information in the equipment development stage, the pertinent information fusion method is advanced according to various information types. With the multivariate Dirichlet distribution as the prior distribution and the complete fusion of growth test data in development stage and field usage data, the FDR/FIR integrated evaluation model based Bayes inference on dynamic population is set up. An analytical method and Markov Chain Monte Carlo method are adopted to solve the complex posterior distribution inference problem. The model robustness is investigated. The study shows the FDR/FIR integrated evaluation by means of such model can produce the evaluation conclusion with high confidence level in a short field usage period or under“small sample”condition. What has been investigated can offer us an important theory base and method for testability integrated evaluation of equipments.
5.A system for optimization of testability verification test and integrated evaluation is developed and take a missile control system as the subject of application. The system furnishes a useful tool for the optimization of testability verification test and integrated evaluation of large scale and complicated equipment.
引文
[1] Department of Defense.MIL-STD-2165A,Military Standard Testability Program for Systems and Equipments[S].1993.
[2] GJB2547-1995.装备测试性大纲[S].
[3]田仲,石君友.系统测试性设计分析与验证[M].北京:北京航空航天大学出版社,2003.
[4] Department of Defense.MIL-STD-1309D,Military Standard Definitions of Terms for Testing, Measurement and Diagnostics[S].1992.
[5]杨廷善.设计—制造—维护纵向集成测试策略[J].测控技术,1998,8(9):14-16.
[6]徐滨士.发展装备再制造工程,提升装备维修保障能力[C].长沙:国防科技大学出版社,2008:129-133.
[7]江妙富.装备可靠性维修性保障性要求总体方案技术研究[D].北京:北京航空航天大学硕士学位论文,2004.
[8]邹国晨,赵澄谋,邱衡.武器装备采办管理[M].北京:国防工业出版社,2003.
[9] Department of Defense.MIL-STD-471A,Maintainbility Verification/Demonstra- tion /Evaluation[S].1973.
[10] Department of Defense.MIL-STD-471A Interim Notice 2, Demonstration and Evaluation of Equipments / System Built-in Test / External Test / Fault Isolation /Testability Attributes and Requirements[S].1978.
[11] Department of Defense.MIL-STD-470A, Military Standard Maintainability Pro- gram for Systems and Equipments[S].1983.
[12] Department of Defense.MIL-STD-2165, Military Standard Testability Program for Electronic Systems and Equipments[S].1985.
[13] GJB/Z299B-1998.电子设备可靠性预计手册[S].
[14] Def Std 00-43(Part 2)/Issue 1, Reliability and Maintainability Assurance Activity Part 2: Maintainability Demonstrations[S].1995.
[15] GB/T5080.5-1985.设备可靠性试验—成功率的验证试验方案[S].
[16] GJB1135.3-1991.地空导弹武器系统维修性评审、试验与评定[S].
[17] GJB1298-1991.通用雷达、指挥仪维修性评审与试验方法[S].
[18] GJB1770.3-1993.对空情报雷达维修性试验与评定[S].
[19] GJB2072-1994.维修性试验与评定[S].
[20] GJB4810-1997(GJBz 20455-1997).地面无线电引信对抗设备试验场试验方法[S].
[21] ARINC No.604-1.Guidance for Design and Use of Built in Test Equipment[S].1998.
[22] HB7177-1995.军用飞机可靠性维修性外场验证[S].
[23] AD-A142075.F-16 APG-66 Fore Control Radar Case Study Report [R].1983,8.
[24] AD-A142103.F/A-18 NA/APG-65 Radar Case Study Report.[R].1983,8.
[25] AD-A081128.BIT/External Test Figures of Merit and Demonstration Techniqu- es[R].1979.
[26] AD-A101130.Design Guide Built-in Test (BIT) and Built-in Test Equipment (BITE) for Army Missile Systems[R].1981.
[27] AD-A118881.RADC Testability Notebook[R].1982.
[28] AD-A137526.Testing Technology Working Group Report (IDA/OSD R&M STUDY)[R].1983.
[29] AD-A142072.AN/APN-128 Lightweight Doppler Navigation System (LDNS) Case Study Report[R].1983.
[30] AD-A137329.Artifical Intelligence Applications to Maintenance Technology Working Group Report(IDA/OSD R&M STUDY)[R]. 1983.
[31] AD-A241621.Analysis and Demonstration of Diagnostic Performance in Modern Electronic Systems[R].1991.
[32] Department of the Army Pamphlet 750-43. Army Test Program Set Procedures [R].1992.
[33] ARINC No. 604-1. Guidance for Design and Use of Built in Test Equipment[R]. 1998.
[34] N000140-00-BAA3339. Integrated Product/Process Development in Update and Modification Programs[R].2003.
[35] Fred Liguori. Built-in-test Capability Evaluation for Weapon Systems Using Computer Modeling[C]. Reliability and Maintainability Symposium, 1993. Proceedings, Annual, pages:484-489.
[36] Dario R, Beniquez. Built-in-test Adequacy-Evaluation Methodology for An Air-Vehicle System[C]. Reliability and Maintainability Symposium, 1995. Proceedings, Annual, pages:290-295.
[37] Sudolaky M D. C-17 O-Level Fault Detection and Isolation BIT Improvement Concepts[C]. AUTOTESTCON’96,‘Test Technology and Commercialization’. Conference Record, 16-19 Sept,1996, Page(s):361-368.
[38] Cotton R, Lopez J. Establishment of the B-2 Avionics Organic Depot[C]. AUTOTESTCON’97. 1997 IEEE Autotestcon Proceedings, 22-25 Sept. 1997, Page(s):212-217.
[39] Sudolsky M D. Enhanced C-17 O-level QAR Data Processing and Reporting[C]. AUTOTESTCON’97. 1997 IEEE Autotestcon Proceedings, 22-25 Sept. 1997, Page(s):44-51.
[40] Smeulers M, Zeelen R, Bos A. PROMIS-A Generic PHM Methodology Applied to Aircraft Subsystems[C]. 2002 Aerospace Conference, 2002 IEEE Proceedings:Page(s):3153-3159.
[41] Anderson J L, Figurerres Z E, Hovakemian A. Using ATE Simulation to Develop Test Procedures and Verify Testability for the Standard Missile[C]. AUTOTESTCON’98. IEEE Systems Readiness Technology Conference, 1998 IEEE, 24-27 Aug. 1998,Page(s):28-34.
[42] Moore F, Dickson R, Kobata R. C-17 TPS Development Strategy [C]. AUTOTESTCON '95. 'Systems Readiness: Test Technology for the 21st Century .Conference Record, Aug,1995,Page(s): 410– 419.
[43]何钟武.军用飞机可靠性维修性外场验证方法的研究[D].北京:北京航空航天大学硕士学位论文,2003.
[44]石君友,田仲.机内测试定量要求的现场试验验证方法研究[J].航空学报,2006,27(5):883-887.
[45]石君友,田仲.测试性研制阶段数据评估验证方法[J].航空学报,2009,30(5):901-905.
[46]王旭,刘发金.空空导弹测试性验证方法探讨[J].国防技术基础,2007.4.
[47]王海波,王旭,侯同刚.空空导弹测试性验证应用研究[J].航空兵器,2005,(3):40-43.
[48]卞春江.航空发动机电子控制器BIT设计及验证技术研究[D].南京:南京航空航天大学硕士学位论文,2005.
[49]韩国泰.改进目前测试性设计的若干建议[J].测控技术,2007,22(11):7-10.
[50]俞纯权,王曰人.论样本的代表性[J].统计与信息论坛,2003,18(2):12-15.
[51]杜子芳.抽样技术及其应用[M].北京:清华大学出版社,2005.
[52] GJB451A-2005.可靠性维修性保障性术语[S].
[53]徐萍,刘松林,李勇.测试性试验概念及模型研究[J].计算机测量与控制,2006,14(9):1149-1152.
[54]徐萍.测试性试验方法与试验平台研究[D].北京:北京航空航天大学博士学位论文,2006.
[55]朱万年.智能化机内测试验证系统的设计与实现[J].航空电子技术,1998,4:35-40.
[56]连光耀.基于信息模型的装备测试性设计与分析方法研究[D].石家庄:军械工程学院博士学位论文,2007.
[57]杨鹏.基于相关性模型的诊断策略优化设计技术[D].长沙:国防科技大学博士学位论文,2008.
[58] Shakeri M. Advances in System Fault Modeling and Diagnosis [D]. Univ. of Connecticut, 1996.
[59]沈亲沐.装备系统级测试性分配技术研究及应用[D].长沙:国防科技大学硕士学位论文,2007.
[60]邱静,刘冠军,李天梅.基于虚拟样机的可测性虚拟试验验证技术研究及发展[C].第二届国防科技工业试验与测试技术发展战略高层论坛论文集,2008.10.
[61]刘冠军.基于边界扫描的智能板级BIT技术研究[D].长沙:国防科技大学博士学位论文,2000.
[62] Angus J E, Schafer R E. Statistical Demonstration of Fault Isolation Requirements [J].IEEE T-R, 1980, R-29(2): 28-35.
[63] Jerome Klion. Testability Demonstration [C]. AUTOTESTCON, 1982: 118-123.
[64] Weiss J L, Deckert J C , Kelly K B. Analysis and Demonstration of Diagnostics Performance in Modern Electronic Systems [J].RL-TR-91-180,1991, 5: 149-155.
[65] Def Stan 00-13/Issue 3. Requirements for the Achievement of Testability in Electronic and Allied Equipment [R]. 1994.
[66] Karen T, Bain, David G. Orwig. F/A-18E/F Built-in-test (BIT) Maturation Process[A]. National Defense Industrial Association System Engineering Committee 3rdAnnual Systems Engineering & Supportability Conference [C]. 2000: 178-185.
[67] Santos, Marcelino Bicho, Goncalves. RTL Design Validation, DFT and Test Pattern Generation for High Defects Coverage [J]. Journal of Electronic Testing: Theory and Applications (JETTA), 2002, 18( 2): 179-187.
[68] Karri R. Guest Editor's Introduction to Special Section on High-level Design Validation and Test [J]. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2001, 20(3): 353-354.
[69] Zhang Qiu shuang, Harris, Ian G..Domain Coverage Metric for the Validation of Behavioral VHDL Descriptions [A]. IEEE International Test Conference, 2000:302-308.
[70] Baril, Barry. Future of Functional IC Validation [J]. European Semiconductor Design Production Assembly, 2000,22(4): 77-78.
[71] Cavalli, Ana, Ionescu, et al. Validation of the GSM-MAP Protocol [A]. Annales des Telecommunications/Annals of Telecommunications [C], 2000,5: 58-69.
[72] Thaker, Pradip A, Vishwani D,et al. Validation Vector Grade (VVG): A New Coverage Metric for Validation and Test [C]. Proceedings of the IEEE VLSI Test Symposium [C], 1999:182-187.
[73] Tapan J Chakrabory,Chen-Huan Chiang.A Novel Fault Injection Method for System Verification Based on FPGA Boundary Scan Arichitecture[C].IEEE ITCInternational Test Conference,pp:923-929.
[74]沈岭,周鸣岐.航天装备测试性试验验证方法[J].质量与可靠性,2006,7:16-18.
[75] Current K,Wayne. Demonstration of An Analog IC Function Maintenance Strategy, Including Direct Calibration, Built-in self-test and Commutation of Redundant Functional Blocks [J]. Analog Integrated Circuits and Signal Processing, 2001,26(2): 129-140.
[76] Jeffrey H, Albert, Mike J,et al. Built-in-Test Verification Techniques [R], RADC-TR-86-241, 1987.
[77] Tasar V, Ohlef H. A Method for Determining the Statistically Weighted Percent Fault Detection Coverage of a Self-test Program [A]. Reliability and Maintainability Symposium Proceedings [C]. 1979: 39-43.
[78] Kreuze F J. BIT Analysis and Design Reliability [A], Reliability and Maintainability Symposium Proceedings [C]. 1983: 328-333.
[79] Collett R E, Bachant P W. Integration of BIT Effectiveness with FMECA[C], Reliability and Maintainability Symposium Proceedings. 1984: 300-305.
[80] Benowitz N, Calhoun D, Lee G..Fault Detection/Isolation Results from AAFIS Hardware Built-In Test [C]. NAECON Record,1976: 215-222.
[81] Bastian J, Hochwald W, Suzuki F. Figure of Merit for BIT Testability for VLSI [C], Autotestcon. 1979: 90-95.
[82] Malcolm J G. Practical Application of Bayes Formulas[C]. Proceedings of Relia- bility and Maintainability Symposium. 1983: 180-186.
[83] Malcolm J G, Foreman G L. The Need: Improved Diagnostics–Rather than Improved[C].Proceedings of the Reliability and Maintainability Symposium.1984: 315-322.
[84] Gleason D. Analysis of Built-In-Test Accuracy[C]. Proceedings of the Reliability and Maintainability Symposium. 1982: 370-372.
[85]徐萍,康锐.测试性试验验证中的故障注入系统框架研究[J].测控技术,2004,23(8):12-14.
[86]张晓杰,王晓峰,金曼.基于机内测试的故障注入系统设计[J].北京航空航天大学学报,2006,32(4):430-434.
[87]张晓杰,虞臣杰,张艺琼等.基于机内测试的一个故障注入系统[J].测控技术,2006,25(2):9-12.
[88]秦海波,张天宏,孙健国.面向FADEC系统BIT验证的综合故障注入器研究[J].航空动力学报,2006,21(3):581-587.
[89]张艳红,易志虎.导弹故障诊断系统中的故障注入方法研究[J].导弹与制导学报,2007,27(3):292-294.
[90]王成刚,周晓东,阎松涛等.电路板TPS验证与评估方法研究[J].中国测试技术,2007,33(1):34-36.
[91]徐应诗,刘斌,阮镰.基于故障注入的仿真测试方法过程框架[J].测控技术,2007,26(10):50-52.
[92]常庆,陈建辉,邱鹏等.基于机内测试的某型装备故障注入系统设计[J].仪表技术,2007,10:12-14.
[93]石君友,李郑,刘骝.自动控制故障注入设备的设计与实现[J].航空学报,2007,28(3):556-560.
[94]黄永飞,彭欣洁.常用电路的故障注入方法[J].航空兵器,2007,2:59-61.
[95] Pecht M, Dube M, Natishan M, et al. Evaluation of Built-in Test[J].Aerospace and Electronic Systems, IEEE Transactions on, 2001, 37(1):266-271.
[96] Barnett N. In-service Reliability, Maintainability and Testability Demonstrations-15years of Experimence[C].Proceedings Annual Reliability and Maintainability Symposium. 2003,pp587-592.
[97]常文兵.高可靠性在高科技战争中的地位[J].航空科学技术,2001,4:20-25.
[98]夏建中.美国陆军装备将向超高可靠性方向发展[J].国外动态及对策,2001,3:14-15.
[99]何钟武.浅谈军用飞机可靠性维修性外场验证信息的收集[J].航空标准化和质量,2003,2:43-45.
[100]石君友.测试性试验验证中的样本选取方法研究[D].北京:北京航空航天大学博士学位论文,2004.
[101]石君友,康锐,田仲.测试性试验中样本集的测试覆盖充分性研究[J].测控技术,2004,23(12):19-21.
[102]石君友,康锐.基于通用充分性准则的测试性试验方案研究[J].航空学报,2005,26(6):691-695.
[103]石君友,康锐,田仲.基于信息模型的测试性试验样本集充分性研究[J].北京航空航天大学学报,2005,31(8):874-878.
[104]石君友,康锐,田仲.测试性试验中样本集的功能覆盖充分性研究[J].电子测量与仪器学报,2006,23(3):23-27.
[105]徐萍,康锐.考虑FDR的测试性测定试验及其相关方法[J].北京航空航天大学学报,2007,33(3):357-360.
[106] Department of Defense. MIL-HDBK-471, Maintainbility Verification/Demons- tration/Evaluation[S].1995.
[107]田松,周玉芬,高锡俊.测试性验证中正态分布法改进[J].电子测量技术,1999,3:13-15.
[108]田仲.测试性验证方法研究[J].航空学报,1995,16(8):65-70.
[109]田仲,石君友.现有测试性验证方法分析与建议[J].质量与可靠性,2006,2:47-51.
[110]周玉芬,徐松涛,高锡俊等.测试性验证的理论和方法研究[J].电子装备可靠性与环境试验,1998,2:10-15.
[111]范红军.某潜射导弹伺服系统测试性研究[J].产品开发与设计,2007,1:46-47.
[112]斯泰蒙迪斯.故障模式影响分析:FMEA从理论到实践[M].北京:国防工业出版社,2005.
[113]康锐,石荣德.FMECA技术及其应用[M].北京:国防工业出版社,2006.
[114] Jarboui T, Alart J, Crouzet Y, et al. Experimental Analysis of the Errors Induced into Linux by Three Fault Injection Technology[C]. IEEE Proceedings of the International Conference on Dependable Systems and Networks, 2002:6-11.
[115] Benso A, Prinetto P, Rebaudengo M, et al. A Fault Injection Environment for Microprocessor-based Boards[C]. IEEE International Test Conference, 2001,31(1):768-776.
[116]王胜文.基于软件的故障注入方法研究[D].哈尔滨:哈尔滨工业大学博士学位论文,2005.
[117] Alart J,Amat L,Crouzet Y,et al.Fault Injection for Dependability Validation:A Methodalogy and Some Applications[J].IEEE Transactions on Software Engineerings,1990,16(2):166-182.
[118] Fang Tu, Deb K R, Malepati S. Computationally Efficient Algorithms for Multiple Fault Diagnosis in Large Graph-Based Systems[J]. IEEE Design and Test of Computers.2003,33(1):73-85.
[119] Vaidynathan R, Venka V. Process Fault Detection and Diagnosis Using Neural Networks-2[C].Dynamic processes. AI CHE Annual Meeting, Chicago IL NOV(1990).
[120] Gros X E, Lowden D W. Approach to NDT Data Fusing[J]. Non-Destuctive Testing and Condition Monitoring. 1995,37(5):462-468.
[121] Alouani A T, Rice T R.Optimal Multi-sensor Trark Fusion[C]. SPE,1994: 327- 334.
[122] Karsson J, Gunneflo U, Liden P, et al. Two Fault Injection Techniques for Test of Fault Handling Mechanisms[C]. IEEE Inter.Conference on Test. 2001,1:140-149.
[123] Thorhuus R. Software Fault Injection Testing[C]. Master of Science Thesis.2000:5-21.
[124] Alderighi M, Angelo D S, Mancini M, et al. A fault Injection Tool for SRAM-based FPGA[C]. Proceedings of 9th IEEE International On-Line Testing Symposium (IOLTS 2003), 2003:129~133.
[125] Chakraborty T J, Chen-Huan Chiang. A Novel Fault Injection Method forSystem Verification Based on FPGA Boundary Scan Architecture[C].Proceedings of International Test Conference 2002 (Cat. No.02CH37382), 2002: 923~929.
[126] Rebaudengo M, Reorda S M, Violante M. Analysis of SEU Effects in a Pipelined Processor[C].Proceedings of the 8th IEEE International On-Line Testing Workshop (IOLTW 2002), 2002: 112~116.
[127] Benso Alfredo, Martinetto Stefano, Prinetto Paolo, et al. SEU Injection Tool to Evaluate DSP-based Architectures for Space Applications[C]. 2000 International Conference on Computer Design, Austin, TX, USA: Institute of Electrical and Electronics Engineers Inc., Piscataway, NJ, USA, Sep 17-20, 2000.
[128] Faure F, Velazco R, Peronnard P. Single-Event-Upset-Like Fault Injection: A Comprehensive Framework[J]. IEEE Transactions on Nuclear Science, 2005, 52(6-1): 2205~2209.
[129] Antoni L, Leveugle R, Feher B. Using Run-Time Reconfiguration for Fault Injection Applications[J]. IEEE Transactions on Instrumentation and Measurement, 2003, 52(5): 1468~1473.
[130]李华旺,刘海涛,杨根庆.航天单粒子事件故障注入系统研究[J].量子电子学报, 2002, 19(1): 57~60.
[131]彭俊杰,黄庆成,洪炳镕等.一种用于星载系统可靠性评测的软件故障注入工具[J].宇航学报, 2005, 26(6): 823~827.
[132]刘宏泰.基于软件实现的故障注入系统设计与仿真[D].哈尔滨:哈尔滨工业大学硕士学位论文, 2003.
[133]邢克飞.星载信号处理平台单粒子效应检测与加固技术研究[D].长沙:国防科技大学博士学位论文,2007.
[134] Stott D T, Ries G, Hsuer M C, et al. Dependability Analysis of a High-speed Network Using Software-Implemented Fault Injection and Simulated Fault Injection[J]. IEEE Transactions on Computers, 1998,47(1):108-119.
[135] Sieh V, Tschache O, Balbach F. VERIFY: Evaluation of Reliability Using VHDL-Models with Embedded Fault Descriptions[C]. Prop. 27th IEEE Int. Symp. on Fault Tolerant Computing(FTCS-27), WA, Seattle,1997:32-36.
[136] Laprie J C. Dependable Computing and Fault Tolerance: Concepts and Terminology [C].Proc.of the 15th Int’l Symp. on Fault-Tolerant Computing (FTCS-15),June 1985:2-11.
[137] Choi G S, Iyer R K. FOCUS: An Experimental Eenvironment for Fault Sensitivity Analysis[J]. IEEE Trans.Comp.1992, 41: 1515-1525.
[138]张天宏,李璇君,辛季龄.智能化BIT测试适配器研究[J].数据采集与处理,1999.12(4):462-466.
[139]孙峻朝,王建莹,杨孝宗.管脚级故障模型的分析与生成技术的研究[J].计算机学报,1999,22(8):845-851.
[140] Gaisler J. Evaluation of a 322 Bit Microprocessor with Built-in Concurrent Error-Detection [C]. Proc. 27th IEEE Int. Symp. on Fault Tolerant Computing (FTCS-27). 1997: 422-426.
[141] Gunneflo U, Karlsson J, Torin J. Evaluation of Error Detection Schemes Using Fault Injection by Heavy-ion Radiation [C]. Proc.of the 19th Int’l Symp.on Fault-Tolerant Computing (FTCS-19), 1989: 340-347.
[142] Arlat J, Crouze Y, Fabre J C. Fault Injection for Dependability Validation of Fault-tolerant Computer Systems [C]. Proc.of the 19th Int’l Symp.on Fault-Tolerant Computing (FTCS-19),1989: 348-355.
[143] Mei-Chern Hsueh, Timothy K.Tsai, Ravishankar K.Iyer. Fault Injection Techniques and Tools [J]. Computer. 1997, 30(4): 75-82.
[144] Asenek V. SEU Induced Errors Observed in Microprocessor Systems[C]. 35th International Nuclear & Space Radiation Effects, Newport Beach, CA, July 1998.
[145] Segall Z, Vrsalovic D, Siewiorek D, et al. FIAT– Fault Iinjection Based Automated Testing Environment [C]. Proc.of the 18th Int’l Symp.on Fault-Tolerant Computing (FTCS-18),1988: 102-107.
[146] Tsai T K, Iyer R K, Jewitt D. An Approach towards Benchmarking of Fault-tolerant Commercial Systems [C]. Proc. FTCS-26, 1996: 314-323.
[147] Kao W, Iyer R K, Tang D. FINE: A Fault Injection and Monitoring Environment for Tracing the UNIX System Behavior under Faults[J]. IEEE Trans.on Software Engineering.1993,19(11):1105-1118
[148] Kao W, Iyer R K. DEFINE:A Distributed Fault Injection and Monitoring Environment [C]. Proc. Workshop Fault-Tolerant Parallel and Distributed Systems ,1994:511-518.
[149] Seungjae Han, Harold A,Rosenberg, et al. DOCTOR: An Integrated Software Fault Injection Environment for Distributed Real-Time System [C]. In: IEEE Int.Computer Performance and Dependability Symposium, 1995: 204-213.
[150] Henrique Madeira, Jo?o Gabriel Silva. Xception : A Technique for the Experimental Evaluation of Dependability in Modern Computers [J]. IEEE Transactions on Software Engineering. 1998, 24(2): 77-83.
[151] Echtle K, Leu M. The EFA Fault Injector for Fault-tolerant Distributed System Testing[C]. IEEE Workshop on Fault-Tolerant Parallel and Distributed Systems . 1992:28-35.
[152] Chani A. Kanawati, Nasser A, Kanawati,et al. Abraham. FERRARI: a Tool for the Validation of System Dependability Properties[J]. In Fault-TolerantComputing FTCS-22, 1992: 336-344.
[153] Clark J A , Pradhan D K. Fault Injection: A Method for Validating Computer System Dependability [J]. IEEE Computer, 1995, 28 (6) : 47-56.
[154] Czeck E W. On the Prediction of Fault Behavior Based on Workload [D]. Camegie Mellon University, Pittsburgh, PA, Apr.1991.
[155] Stou D T, Ries G, Hsueh M.-C,et al. Dependability Analysis of A High Speed Network Using Software Implemented Fault Injection and Simulated Fault Injection [J]. IEEE Trans. Comp. Special Issue on Dependable Computing, 1998, 47: 109-119.
[156] Guthoff J, Sieh V. Combining Software-implemented and Simulation-based Injection into A Single Fault Injection Method [C]. Proc.of the 25th Int’l Symp.on Fault-Tolerant Computing (FTCS-25), 1995: 196-206.
[157] Young L, Lyer R K, Goswami K,et al. Hybrid Monitor Assisted Fault Injection Environment [C]. Proc.of the 3th IFIP Int’Working Conf. Dependable Computers for Critical Applications (DCCA-3),1993: 163-174.
[158]史铁林,陈勇辉,李巍华等.提高大型复杂机电系统故障诊断质量的几种新方法[J].机械工程学报,2003,39(9):1-10.
[159]韩暋.装备可测性设计及验证技术的发展及应用[C].国防科技工业试验与测试技术高层论坛论文集,2007.
[160]杨为民.可靠性.维修性.保障性总论[M].北京:国防工业出版社,2001.
[161]王成刚,周晓东,彭顺堂等.一种基于多信号模型的测试性评估方法[J].测控技术,2006,25(10):13-15.
[162]林志文,贺喆,刘松风.基于多信号模型的系统测试性分析与评估[J].计算机测量与控制,2006,14(2):222-224.
[163]徐赫,王宝龙,武建辉.基于贝叶斯网络的测试性预计方法[J].导弹与制导学报,2007,27(4):232-235.
[164]王成刚,周晓东,王学伟.基于贝叶斯网络的复杂装备测试性评估[J].电子测量与仪器学报,2009,23(5):17-21.
[165]石君友,刘骝,李郑.测试性验证辅助软件(TVAS)设计与实现[J].测控技术,2007,26(7):58-60.
[166] James O B. Statestic Decision Theory-Foundations[J]. Concepts and Methods, Newyork,Springverlay,1989.
[167] Gelfand A, Maillick E. Bayesian Analysis of Proportional Hazards Models Built from Monotone Functions[J]. Biometrics,1995(15):843-852.
[168] Harry F, Martz. Empirical Bayes Estimation of the Reliability of Nuclear-Power-Plant Emergency Diesel Generators[J]. Technometrics, 1996,38(1).
[169] Kurt Porn. The two-stage Bayesian Method Used for the T-Book Application[J]. Reliability Engineering and System Safety, 1996(5).
[170] Bergman B, Ringi M. System Reliability Prediction Using Data from Non-identical Environments[J]. Reliability engineering and system safety. 1997(8).
[171] [美]A.M.穆德, F.A.格雷比尔著,史定华译.统计学导论.北京:科学出版社,1992.
[172] Gelfand A E, Maillick. Bayesian Analysis of Proportional Hhazards Models Built from MonotoneFunctions[J]. Biometrics,1995(15):843-852.
[173] Watkins A J. On Maximum Likelihood Estimation for the Two Parameter Weibull Distribution[J]. Microelectronics Reliability,1996,36(5):595-603.
[174] Calabria R, Pulcini G.. An Engineering Approach to Bayes Estimation for the Weibull Distribution[J]. Microelectronics Reliability,1994,34(5):789-802.
[175] Pierce D A. Fiducial, Frequency, Bayesian Inference on Reliability for the Two Parameter Negative Exponential Distribution[J]. Technometrics, 1973, 15(2):249-253.
[176]唐雪梅,张金槐,邵凤昌等.武器装备小子样试验分析与评估[M].北京:国防工业出版社,2001.
[177]成平,陈希孺.参数估计[M].上海:上海科学技术出版社,1985.
[178]峁诗松,王静龙,濮晓龙.高等数理统计[M].北京:高等教育出版社,2007.
[179]张金槐,唐雪梅.Bayes方法[M].长沙:国防科技大学出版社,1989.
[180]唐雪梅.武器装备小子样试验分析与评估[D].长沙:国防科技大学博士学位论文,2007.
[181]李欣欣.基于Bayes变动统计的精度鉴定与可靠性增长评估研究[D].长沙:国防科技大学博士学位论文,2008.
[182]明志茂.动态分布参数的Bayes可靠性综合试验与评估方法研究[D].长沙:国防科技大学博士学位论文,2009.
[183]张玉柱,胡自伟,曹世民等.维修性验证试验与评定原理[M].北京:国防工业出版社,2006.
[184]徐忠伟,周玉芬,高锡俊.测试性验证中抽样方案的精确算法[J].空军工程大学学报(自然科学版),2000,1(1):76-78.
[185]徐忠伟,周玉芬,徐松涛.测试性验证中抽样方案的精确算法及应用[J].航空学报,2000,21(1):67-69.
[186]温旭东.关于假设检验及两种错误的思考[J].今日论坛,2008.5.
[187]袁力,盛爱辉.区间估计与假设检验的相关性及应用[J],郧阳师范高等专科学校学报,2007,27(6):30-31.
[188] Michael J C, David E M, Thomas J S,et al. Comparison of Electronics Reliability Assessment Approaches [J] . IEEE Transactions on Reliability , 1993 , 42 (4):542-546.
[189] Telcordia SR2332 ( Issue 2) . Reliability Prediction Procedure for Electronic Equipment [S] . 2006.
[190] Dylis D D. PRISM : A New Approach to Reliability Prediction[J ] . Reliability Review , 2001 , 21 (1) : 5-11 , 13-15.
[191] FIDES Guide ( Issue A) . Reliability Met Hodology for Electronic Systems[ S] . France : FIDES Group , 2004.
[192] Pecht M. Why the Traditional Reliability Prediction Model Do Not Work Is There An Alternative [J] . Electronic Cooling , 1996,2(1):10.
[193] Pecht M, Dasgupta A. Physics of Failure: An Approach to Reliable Product Development[J]. Journal of t he Institute of Environmental Sciences , 1995 , 38 (5) : 30-34.
[194] Seymour M. Reliability Prediction Methods—An Overview[J].The Journal of RAC,1999 (3):8-11.
[195]李瑞颖,康锐.基于神经网络的故障率预测方法[J].航空学报,2008.29(2):357-363.
[196]韩光臣,孙树栋,司书宾等.复杂系统故障传播与故障分析模型研究[J].计算机集成制造系统,2005,11(6):794-798.
[197]欧贵兵,刘清国.概率统计及其应用[M].北京:科学出版社,2007.
[198]周源泉.维修性增长的Bayes方法[J].质量与可靠性,2005,3:19-23.
[199] Barlow R E, Scheuer E M. Reliability Growth During a Development Testing Program [J]. Techno-metrics, 1966,31(8):53-60.
[200]田国梁.二项分布的可靠性增长模型[J].宇航学报,1992,1:55-61.
[201]赵宇,黄敏,于丹等.利用试验数据的产品可靠性综合验证方案确定方法[J].航空学报,2005,26(5):637-640.
[202]王玲玲.指数分布下可靠性Bayes验证[J].华东师范大学学报(自然科学版). 1993(3):1-10.
[203]陈文华,崔杰,潘俊等.威布尔分布下失效率的Bayes验证试验方法[J].机械工程学报,2005,41(12):118-121.
[204]甘茂治,吴真真.维修性设计与验证[M].北京:国防工业出版社,1995.
[205] Ammer W. Handbook of System and Product Safety [M] . Prentice Hall ,2000.
[206]罗佑新,张龙庭,李敏.灰色系统理论及其在机械工程中的应用[M].长沙:国防科技大学出版社,2000:30-98.
[207]何文章,郭鹏.关于灰色关联度中的几个问题的探讨[J].数据统计与管理.1999,18(3):25-29.
[208] Zeki A. A Fuzzy AHP-based Simulation Approach to Concept Evaluation in a NPD Environment [J],IIE Transavtions,2005,37(9):827-842.
[209]曲晓慧,乔新勇,陈玫等.基于灰色关联分析的柴油机状况评估[J].兵工学报,2005,26(4):557-559.
[210] Qualtech Systems Inc. TEAMS6.0 User’s Guide, 2002, 218pages.
[211] Desgin for Testability and Design for Diagnosability.http://www.design for testability.com, 2008.9.
[212] DSI Iinternational Inc. eXpress. http://www.dsiintl/WebLogic/products.aspx, 2008.9.
[213] QSI. TEAMS. http://www.teamqsi.com/TEAMS.html, 2008.9.
[214]李行善,左毅,孙杰.自动测试系统集成技术[M].北京:电子工业出版社, 2004:42-50.
[215] David M B, Brian A K, Alony M H. A System Testability"Top-Down"Apportion- ment Method[C]. Proceedings of the IEEE AUTOTESTCON, 1990:451-463.
[216] Stora M J. IEEE P1505 Receiver Fixture Interface (RFI) System Standard Update [C]. Proceedings of the IEEE AUTOTESTCON, 2001: 480-496.
[217] IEEE Std 771-1998. IEEE Guide to the Use of the ATLAS Specification [S].Piscataway, New Jersey: IEEE Standards Press, 1998.
[218] IEEE Std 776-1995. Standard Test Language for All Systems-Common/Abbrevi- ated Test Language for All Systems (C/ATLAS) [S]. Piscataway, NewJersey: IEEE Standards Press, 1995.
[219] IEEE Std 1232.1-1997. AI-ESTATE Data and Knowledge Specification[S]. Pisc- ataway, New Jersey: IEEE Standards Press, 1997.
[220] IEEE Std 1232-1995, Artificial Intelligence and Expert System Tie to Automatic Test Equipment (AI-ESTATE): Overview and Architecture[S].Piscataway, New Jersey: IEEE Standards Press, 1995.
[221] IEEE P1232.2, AI-ESTATE Service Specification[S]. Piscataway, New Jersey:IEEE Standards Press, 1998.
[222] IEEE Std 1232-2002, IEEE Standard for Artificial Intelligence Exchange and Service Tie to All Test Environments(AI-ESTATE)[S]. Piscataway, New Jersey: IEEE Standards Press, 2002.
[223] ISO 10303-11:1994. Industrial Automation Systems and Integration-Product Data Representation and Exchange-Part 11: Description Methods: The EXPRESS Language Reference Manual[S]. Geneva, Switzerland: InternationalOrganization for Standardization, 1994.
[224] Sheppard J W, Kaufman M. Formal Specification of Testability Metrics in IEEE P1522[C]. Proceedings of the IEEE AUTOTESTCON, 2001:71-82.
[225] Sheppard J, Kaufman M. IEEE 1232 and P1522 Standards[C]. Proceedings of the IEEE AUTOTESTCON, 2000: 388-397.
[226] Mark Kaufman, Sheppard J. P1522: A Formal Standard for Testability and Diagnosability Measures[C]. Proceedings of the IEEE AUTESTCON, 1999: 411-418.
[227] Eric B, Danny C D, Lee S. The Use of Model-based Test Requirements throug- hout the Product Line Cycle[C]. Proceedings of the IEEE AUTOTESTCON, 1999: 53-58.
[228] Lee S, Eric B. Test Requirements Model(TeRM) Overview and Status[C]. Proceedings of the IEEE AUTOTESTCON, 2000:380-387.
[229] IEEE Std 1641-2004. IEEE Standard for Signal and Test Definition[S]. Piscataway, New Jersey: IEEE Standards Press, 2004.
[230] Ellis K. Signal and Test Definition-an IEEE Standard[C]. Proceedings of the IEEE AUTOTESTCON, 2003:244-257.
[231] Ellis K, Delaney D. Signal Definition and Test Description-an IEEE Standard[C]. Proceedings of the IEEE AUTOTESTCON, 2002:380-393.
[232] Les Orlidge. SCC20 Annual Report for 2004, http://standards.ieee.org, 2004.
[233] Les Orlidge. SCC20 Annual Report for 2005, http://standards.ieee.org, 2005.
[234] William R, Simpson, Harold S,et al. The ARINC Research System Testability and Maintenance Program(STAMP)[C]. Proceedings of the IEEE AUTOTESTCON, 1982:88-95.
[235] William L K. A Navy Approach to Integrated Diagnostics[C]. Proceedings of the IEEE AUTOTESTCON, 1990:443-450.
[236] Yun Peng, James A R. Abductive Inference Model for Diagnostic Problem-Solving[M]. New York: Springer-Verlag, 1990.
[237] Dill H H. Diagnostic Inference Model Error Source[C]. Proceedings of the IEEE AUTOTESTCON, 1994:391-397.
[238] Bartolini A, Sheppard J W, Munns T E. An Application of Diagnostic Inference Modeling to Vehicle Health Management[C]. Proceedings of the IEEE AUTOTESTCON, 2001: 706-717.
[239]龙兵.多信号建模与故障诊断方法及其在航天器中的应用研究[D].哈尔滨:哈尔滨工业大学博士学位论文,2005.
[240] De Paul. Logic Modeling as A Tool for Testability[C]. Proceedings of the IEEE AUTOTESTCON, 1985:203-207.
[241] Testability Timeline. http://www.testability.com/reference/History.aspx,2008.
[242] Gould E, Hartop D. Thinking beyond the Group Size Fetish: towards A New Testability[C]. Proceedings of the IEEE AUTOTESTCON, 1999:673-684.
[243] Lala J H. Fault Detection, Isolation, and Reconfiguration in FTMP: Methods and Experimental Results [C].Proc.of the 5th AIAA/IEEE Digital Aviontics Systems Conf.(DASC),1983: 130-146.
[244] Laura F Burkhardt, Thomas K Masotto, Jaynarayan H Lala. Advanced Information Processing System: Fault Injection Study and Results [R]. NASA Contractor Report-189590,1992.
[245] Raymond P Kurlak, Robert J. Chobort. CPU Coverage Evaluation using Automatic Fault Injection [R]. AIAA 81-2281R,1982.
[246] Benson J W. Hardware Fault Insertion and Instrumentation System Mechanization and Validation [R]. NASA-CR-181445,1987.
[247]李璇君.航空发动机数字控制器与航空电子综合系统BIT技术研究[D].南京:南京航空航天大学硕士学位论文,2001.
[248]李璇君,辛季龄.基于后驱动技术的故障注入方法研究[J].哈尔滨工业大学学报,2001,33(6):858-862.
[249]李海军,刘霄,王永涛.Gibbs抽样的诊断贝叶斯网络模型评估方法[J].系统仿真学报,2007,19(10):2392-2394.
[250]苏羽,赵海,苏威积.基于贝叶斯网络的态势评估诊断模型[J],东北大学学报(自然科学版),2005.26(8):739-742.
[251]李剑川.贝叶斯网络故障诊断与维修决策方法及应用研究[D].长沙:国防科技大学博士学位论文,2002.
[252]王建莹.面向容错系统验证的故障注入技术研究[D].哈尔滨:哈尔滨工业大学博士学位论文,2000.
[253] [苏]H.?.舒波夫.电机的噪声与振动[M].北京:机械工业出版社,1980.
[254] Ahmed Y, Ben Sasi, Fengshou Gu,et al. A Validated Model for the Prediction of Rotor Bar Failure in Squirrel-cage Motors Using Instantaneous Angular Speed[J]. Mechanical Systems and Signal Processing,2006,20:1572-1589.
[255]峁诗松.统计手册[M].北京:科学出版社,2003.
[256]刘飞.固体火箭发动机可靠性增长试验理论及应用研究[D].长沙:国防科技大学博士学位论文,2006.
[257] Mazzuchi T A, Soyer R. A Bayes Method for Assessing Product Reliability During Development Testing[J].IEEE transactions on reliability, 1993:322-325.
[258] Mazzuchi T A, Soyer R. Reliability Assessing and Prediction During Product Development[C].Annual Reliability and maintainability Symposium, 1992:468-474.
[259] [英]B.S.艾沃日特著,刘韵源,周家丽译.列联表分析.北京:科学出版社,1980.14-15.
[260]刘宏伟,杨孝宗,曲峰等.一个基于响铃形故障检测率函数的软件可靠性增长模型[J].计算机学报,2005,28(5):908-912.
[261] GB/T15500-1995.利用电子随机数抽样器进行随机抽样的方法[S].
[262] GB10111-1988.利用随机数骰子进行随机抽样的方法[S].
[263] Kwong C K,Bai H.A Fuzzy AHP Approach to the Determination of Importance Weights of Customer Requipments in Quality Function Deployment[J].Journal of Intelligent Manufacturing,2002,13(3):367-377.
[264]古莹奎,吴陆恒.机械运动方案评价中评价因素权重确定的模糊层次分析法[J].中国机械工程,2007,18(9):1052-1056.
[265] PeterJ B,David A F. Some Asymptotic Theory the Bootstrap[J].The Annuals of Statistics, 1981, 9(6):1197-1217.
[266]屈斐,王树宗.基于Bootstrap仿真的鱼雷可靠性置信下限[J].鱼雷技术,2006,14(4):32-35.
[267]谷振宇,王胜文,洪炳熔.软件故障注入方法及其仿真应用[J].福建师范大学学报(自然科学版),2004,20(4):28-31.
[268]王莲芬,许树柏.层次分析法引论[M].北京:中国人民大学出版社,1989.
[269]张金槐,刘琦,冯静.Bayes试验分析方法[M].长沙:国防科技大学出版社,2007.
[270]曹晋华,程侃.可靠性数学引论[M].北京:高等教育出版社,2006.
[2] GJB2547-1995.装备测试性大纲[S].
[3]田仲,石君友.系统测试性设计分析与验证[M].北京:北京航空航天大学出版社,2003.
[4] Department of Defense.MIL-STD-1309D,Military Standard Definitions of Terms for Testing, Measurement and Diagnostics[S].1992.
[5]杨廷善.设计—制造—维护纵向集成测试策略[J].测控技术,1998,8(9):14-16.
[6]徐滨士.发展装备再制造工程,提升装备维修保障能力[C].长沙:国防科技大学出版社,2008:129-133.
[7]江妙富.装备可靠性维修性保障性要求总体方案技术研究[D].北京:北京航空航天大学硕士学位论文,2004.
[8]邹国晨,赵澄谋,邱衡.武器装备采办管理[M].北京:国防工业出版社,2003.
[9] Department of Defense.MIL-STD-471A,Maintainbility Verification/Demonstra- tion /Evaluation[S].1973.
[10] Department of Defense.MIL-STD-471A Interim Notice 2, Demonstration and Evaluation of Equipments / System Built-in Test / External Test / Fault Isolation /Testability Attributes and Requirements[S].1978.
[11] Department of Defense.MIL-STD-470A, Military Standard Maintainability Pro- gram for Systems and Equipments[S].1983.
[12] Department of Defense.MIL-STD-2165, Military Standard Testability Program for Electronic Systems and Equipments[S].1985.
[13] GJB/Z299B-1998.电子设备可靠性预计手册[S].
[14] Def Std 00-43(Part 2)/Issue 1, Reliability and Maintainability Assurance Activity Part 2: Maintainability Demonstrations[S].1995.
[15] GB/T5080.5-1985.设备可靠性试验—成功率的验证试验方案[S].
[16] GJB1135.3-1991.地空导弹武器系统维修性评审、试验与评定[S].
[17] GJB1298-1991.通用雷达、指挥仪维修性评审与试验方法[S].
[18] GJB1770.3-1993.对空情报雷达维修性试验与评定[S].
[19] GJB2072-1994.维修性试验与评定[S].
[20] GJB4810-1997(GJBz 20455-1997).地面无线电引信对抗设备试验场试验方法[S].
[21] ARINC No.604-1.Guidance for Design and Use of Built in Test Equipment[S].1998.
[22] HB7177-1995.军用飞机可靠性维修性外场验证[S].
[23] AD-A142075.F-16 APG-66 Fore Control Radar Case Study Report [R].1983,8.
[24] AD-A142103.F/A-18 NA/APG-65 Radar Case Study Report.[R].1983,8.
[25] AD-A081128.BIT/External Test Figures of Merit and Demonstration Techniqu- es[R].1979.
[26] AD-A101130.Design Guide Built-in Test (BIT) and Built-in Test Equipment (BITE) for Army Missile Systems[R].1981.
[27] AD-A118881.RADC Testability Notebook[R].1982.
[28] AD-A137526.Testing Technology Working Group Report (IDA/OSD R&M STUDY)[R].1983.
[29] AD-A142072.AN/APN-128 Lightweight Doppler Navigation System (LDNS) Case Study Report[R].1983.
[30] AD-A137329.Artifical Intelligence Applications to Maintenance Technology Working Group Report(IDA/OSD R&M STUDY)[R]. 1983.
[31] AD-A241621.Analysis and Demonstration of Diagnostic Performance in Modern Electronic Systems[R].1991.
[32] Department of the Army Pamphlet 750-43. Army Test Program Set Procedures [R].1992.
[33] ARINC No. 604-1. Guidance for Design and Use of Built in Test Equipment[R]. 1998.
[34] N000140-00-BAA3339. Integrated Product/Process Development in Update and Modification Programs[R].2003.
[35] Fred Liguori. Built-in-test Capability Evaluation for Weapon Systems Using Computer Modeling[C]. Reliability and Maintainability Symposium, 1993. Proceedings, Annual, pages:484-489.
[36] Dario R, Beniquez. Built-in-test Adequacy-Evaluation Methodology for An Air-Vehicle System[C]. Reliability and Maintainability Symposium, 1995. Proceedings, Annual, pages:290-295.
[37] Sudolaky M D. C-17 O-Level Fault Detection and Isolation BIT Improvement Concepts[C]. AUTOTESTCON’96,‘Test Technology and Commercialization’. Conference Record, 16-19 Sept,1996, Page(s):361-368.
[38] Cotton R, Lopez J. Establishment of the B-2 Avionics Organic Depot[C]. AUTOTESTCON’97. 1997 IEEE Autotestcon Proceedings, 22-25 Sept. 1997, Page(s):212-217.
[39] Sudolsky M D. Enhanced C-17 O-level QAR Data Processing and Reporting[C]. AUTOTESTCON’97. 1997 IEEE Autotestcon Proceedings, 22-25 Sept. 1997, Page(s):44-51.
[40] Smeulers M, Zeelen R, Bos A. PROMIS-A Generic PHM Methodology Applied to Aircraft Subsystems[C]. 2002 Aerospace Conference, 2002 IEEE Proceedings:Page(s):3153-3159.
[41] Anderson J L, Figurerres Z E, Hovakemian A. Using ATE Simulation to Develop Test Procedures and Verify Testability for the Standard Missile[C]. AUTOTESTCON’98. IEEE Systems Readiness Technology Conference, 1998 IEEE, 24-27 Aug. 1998,Page(s):28-34.
[42] Moore F, Dickson R, Kobata R. C-17 TPS Development Strategy [C]. AUTOTESTCON '95. 'Systems Readiness: Test Technology for the 21st Century .Conference Record, Aug,1995,Page(s): 410– 419.
[43]何钟武.军用飞机可靠性维修性外场验证方法的研究[D].北京:北京航空航天大学硕士学位论文,2003.
[44]石君友,田仲.机内测试定量要求的现场试验验证方法研究[J].航空学报,2006,27(5):883-887.
[45]石君友,田仲.测试性研制阶段数据评估验证方法[J].航空学报,2009,30(5):901-905.
[46]王旭,刘发金.空空导弹测试性验证方法探讨[J].国防技术基础,2007.4.
[47]王海波,王旭,侯同刚.空空导弹测试性验证应用研究[J].航空兵器,2005,(3):40-43.
[48]卞春江.航空发动机电子控制器BIT设计及验证技术研究[D].南京:南京航空航天大学硕士学位论文,2005.
[49]韩国泰.改进目前测试性设计的若干建议[J].测控技术,2007,22(11):7-10.
[50]俞纯权,王曰人.论样本的代表性[J].统计与信息论坛,2003,18(2):12-15.
[51]杜子芳.抽样技术及其应用[M].北京:清华大学出版社,2005.
[52] GJB451A-2005.可靠性维修性保障性术语[S].
[53]徐萍,刘松林,李勇.测试性试验概念及模型研究[J].计算机测量与控制,2006,14(9):1149-1152.
[54]徐萍.测试性试验方法与试验平台研究[D].北京:北京航空航天大学博士学位论文,2006.
[55]朱万年.智能化机内测试验证系统的设计与实现[J].航空电子技术,1998,4:35-40.
[56]连光耀.基于信息模型的装备测试性设计与分析方法研究[D].石家庄:军械工程学院博士学位论文,2007.
[57]杨鹏.基于相关性模型的诊断策略优化设计技术[D].长沙:国防科技大学博士学位论文,2008.
[58] Shakeri M. Advances in System Fault Modeling and Diagnosis [D]. Univ. of Connecticut, 1996.
[59]沈亲沐.装备系统级测试性分配技术研究及应用[D].长沙:国防科技大学硕士学位论文,2007.
[60]邱静,刘冠军,李天梅.基于虚拟样机的可测性虚拟试验验证技术研究及发展[C].第二届国防科技工业试验与测试技术发展战略高层论坛论文集,2008.10.
[61]刘冠军.基于边界扫描的智能板级BIT技术研究[D].长沙:国防科技大学博士学位论文,2000.
[62] Angus J E, Schafer R E. Statistical Demonstration of Fault Isolation Requirements [J].IEEE T-R, 1980, R-29(2): 28-35.
[63] Jerome Klion. Testability Demonstration [C]. AUTOTESTCON, 1982: 118-123.
[64] Weiss J L, Deckert J C , Kelly K B. Analysis and Demonstration of Diagnostics Performance in Modern Electronic Systems [J].RL-TR-91-180,1991, 5: 149-155.
[65] Def Stan 00-13/Issue 3. Requirements for the Achievement of Testability in Electronic and Allied Equipment [R]. 1994.
[66] Karen T, Bain, David G. Orwig. F/A-18E/F Built-in-test (BIT) Maturation Process[A]. National Defense Industrial Association System Engineering Committee 3rdAnnual Systems Engineering & Supportability Conference [C]. 2000: 178-185.
[67] Santos, Marcelino Bicho, Goncalves. RTL Design Validation, DFT and Test Pattern Generation for High Defects Coverage [J]. Journal of Electronic Testing: Theory and Applications (JETTA), 2002, 18( 2): 179-187.
[68] Karri R. Guest Editor's Introduction to Special Section on High-level Design Validation and Test [J]. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2001, 20(3): 353-354.
[69] Zhang Qiu shuang, Harris, Ian G..Domain Coverage Metric for the Validation of Behavioral VHDL Descriptions [A]. IEEE International Test Conference, 2000:302-308.
[70] Baril, Barry. Future of Functional IC Validation [J]. European Semiconductor Design Production Assembly, 2000,22(4): 77-78.
[71] Cavalli, Ana, Ionescu, et al. Validation of the GSM-MAP Protocol [A]. Annales des Telecommunications/Annals of Telecommunications [C], 2000,5: 58-69.
[72] Thaker, Pradip A, Vishwani D,et al. Validation Vector Grade (VVG): A New Coverage Metric for Validation and Test [C]. Proceedings of the IEEE VLSI Test Symposium [C], 1999:182-187.
[73] Tapan J Chakrabory,Chen-Huan Chiang.A Novel Fault Injection Method for System Verification Based on FPGA Boundary Scan Arichitecture[C].IEEE ITCInternational Test Conference,pp:923-929.
[74]沈岭,周鸣岐.航天装备测试性试验验证方法[J].质量与可靠性,2006,7:16-18.
[75] Current K,Wayne. Demonstration of An Analog IC Function Maintenance Strategy, Including Direct Calibration, Built-in self-test and Commutation of Redundant Functional Blocks [J]. Analog Integrated Circuits and Signal Processing, 2001,26(2): 129-140.
[76] Jeffrey H, Albert, Mike J,et al. Built-in-Test Verification Techniques [R], RADC-TR-86-241, 1987.
[77] Tasar V, Ohlef H. A Method for Determining the Statistically Weighted Percent Fault Detection Coverage of a Self-test Program [A]. Reliability and Maintainability Symposium Proceedings [C]. 1979: 39-43.
[78] Kreuze F J. BIT Analysis and Design Reliability [A], Reliability and Maintainability Symposium Proceedings [C]. 1983: 328-333.
[79] Collett R E, Bachant P W. Integration of BIT Effectiveness with FMECA[C], Reliability and Maintainability Symposium Proceedings. 1984: 300-305.
[80] Benowitz N, Calhoun D, Lee G..Fault Detection/Isolation Results from AAFIS Hardware Built-In Test [C]. NAECON Record,1976: 215-222.
[81] Bastian J, Hochwald W, Suzuki F. Figure of Merit for BIT Testability for VLSI [C], Autotestcon. 1979: 90-95.
[82] Malcolm J G. Practical Application of Bayes Formulas[C]. Proceedings of Relia- bility and Maintainability Symposium. 1983: 180-186.
[83] Malcolm J G, Foreman G L. The Need: Improved Diagnostics–Rather than Improved[C].Proceedings of the Reliability and Maintainability Symposium.1984: 315-322.
[84] Gleason D. Analysis of Built-In-Test Accuracy[C]. Proceedings of the Reliability and Maintainability Symposium. 1982: 370-372.
[85]徐萍,康锐.测试性试验验证中的故障注入系统框架研究[J].测控技术,2004,23(8):12-14.
[86]张晓杰,王晓峰,金曼.基于机内测试的故障注入系统设计[J].北京航空航天大学学报,2006,32(4):430-434.
[87]张晓杰,虞臣杰,张艺琼等.基于机内测试的一个故障注入系统[J].测控技术,2006,25(2):9-12.
[88]秦海波,张天宏,孙健国.面向FADEC系统BIT验证的综合故障注入器研究[J].航空动力学报,2006,21(3):581-587.
[89]张艳红,易志虎.导弹故障诊断系统中的故障注入方法研究[J].导弹与制导学报,2007,27(3):292-294.
[90]王成刚,周晓东,阎松涛等.电路板TPS验证与评估方法研究[J].中国测试技术,2007,33(1):34-36.
[91]徐应诗,刘斌,阮镰.基于故障注入的仿真测试方法过程框架[J].测控技术,2007,26(10):50-52.
[92]常庆,陈建辉,邱鹏等.基于机内测试的某型装备故障注入系统设计[J].仪表技术,2007,10:12-14.
[93]石君友,李郑,刘骝.自动控制故障注入设备的设计与实现[J].航空学报,2007,28(3):556-560.
[94]黄永飞,彭欣洁.常用电路的故障注入方法[J].航空兵器,2007,2:59-61.
[95] Pecht M, Dube M, Natishan M, et al. Evaluation of Built-in Test[J].Aerospace and Electronic Systems, IEEE Transactions on, 2001, 37(1):266-271.
[96] Barnett N. In-service Reliability, Maintainability and Testability Demonstrations-15years of Experimence[C].Proceedings Annual Reliability and Maintainability Symposium. 2003,pp587-592.
[97]常文兵.高可靠性在高科技战争中的地位[J].航空科学技术,2001,4:20-25.
[98]夏建中.美国陆军装备将向超高可靠性方向发展[J].国外动态及对策,2001,3:14-15.
[99]何钟武.浅谈军用飞机可靠性维修性外场验证信息的收集[J].航空标准化和质量,2003,2:43-45.
[100]石君友.测试性试验验证中的样本选取方法研究[D].北京:北京航空航天大学博士学位论文,2004.
[101]石君友,康锐,田仲.测试性试验中样本集的测试覆盖充分性研究[J].测控技术,2004,23(12):19-21.
[102]石君友,康锐.基于通用充分性准则的测试性试验方案研究[J].航空学报,2005,26(6):691-695.
[103]石君友,康锐,田仲.基于信息模型的测试性试验样本集充分性研究[J].北京航空航天大学学报,2005,31(8):874-878.
[104]石君友,康锐,田仲.测试性试验中样本集的功能覆盖充分性研究[J].电子测量与仪器学报,2006,23(3):23-27.
[105]徐萍,康锐.考虑FDR的测试性测定试验及其相关方法[J].北京航空航天大学学报,2007,33(3):357-360.
[106] Department of Defense. MIL-HDBK-471, Maintainbility Verification/Demons- tration/Evaluation[S].1995.
[107]田松,周玉芬,高锡俊.测试性验证中正态分布法改进[J].电子测量技术,1999,3:13-15.
[108]田仲.测试性验证方法研究[J].航空学报,1995,16(8):65-70.
[109]田仲,石君友.现有测试性验证方法分析与建议[J].质量与可靠性,2006,2:47-51.
[110]周玉芬,徐松涛,高锡俊等.测试性验证的理论和方法研究[J].电子装备可靠性与环境试验,1998,2:10-15.
[111]范红军.某潜射导弹伺服系统测试性研究[J].产品开发与设计,2007,1:46-47.
[112]斯泰蒙迪斯.故障模式影响分析:FMEA从理论到实践[M].北京:国防工业出版社,2005.
[113]康锐,石荣德.FMECA技术及其应用[M].北京:国防工业出版社,2006.
[114] Jarboui T, Alart J, Crouzet Y, et al. Experimental Analysis of the Errors Induced into Linux by Three Fault Injection Technology[C]. IEEE Proceedings of the International Conference on Dependable Systems and Networks, 2002:6-11.
[115] Benso A, Prinetto P, Rebaudengo M, et al. A Fault Injection Environment for Microprocessor-based Boards[C]. IEEE International Test Conference, 2001,31(1):768-776.
[116]王胜文.基于软件的故障注入方法研究[D].哈尔滨:哈尔滨工业大学博士学位论文,2005.
[117] Alart J,Amat L,Crouzet Y,et al.Fault Injection for Dependability Validation:A Methodalogy and Some Applications[J].IEEE Transactions on Software Engineerings,1990,16(2):166-182.
[118] Fang Tu, Deb K R, Malepati S. Computationally Efficient Algorithms for Multiple Fault Diagnosis in Large Graph-Based Systems[J]. IEEE Design and Test of Computers.2003,33(1):73-85.
[119] Vaidynathan R, Venka V. Process Fault Detection and Diagnosis Using Neural Networks-2[C].Dynamic processes. AI CHE Annual Meeting, Chicago IL NOV(1990).
[120] Gros X E, Lowden D W. Approach to NDT Data Fusing[J]. Non-Destuctive Testing and Condition Monitoring. 1995,37(5):462-468.
[121] Alouani A T, Rice T R.Optimal Multi-sensor Trark Fusion[C]. SPE,1994: 327- 334.
[122] Karsson J, Gunneflo U, Liden P, et al. Two Fault Injection Techniques for Test of Fault Handling Mechanisms[C]. IEEE Inter.Conference on Test. 2001,1:140-149.
[123] Thorhuus R. Software Fault Injection Testing[C]. Master of Science Thesis.2000:5-21.
[124] Alderighi M, Angelo D S, Mancini M, et al. A fault Injection Tool for SRAM-based FPGA[C]. Proceedings of 9th IEEE International On-Line Testing Symposium (IOLTS 2003), 2003:129~133.
[125] Chakraborty T J, Chen-Huan Chiang. A Novel Fault Injection Method forSystem Verification Based on FPGA Boundary Scan Architecture[C].Proceedings of International Test Conference 2002 (Cat. No.02CH37382), 2002: 923~929.
[126] Rebaudengo M, Reorda S M, Violante M. Analysis of SEU Effects in a Pipelined Processor[C].Proceedings of the 8th IEEE International On-Line Testing Workshop (IOLTW 2002), 2002: 112~116.
[127] Benso Alfredo, Martinetto Stefano, Prinetto Paolo, et al. SEU Injection Tool to Evaluate DSP-based Architectures for Space Applications[C]. 2000 International Conference on Computer Design, Austin, TX, USA: Institute of Electrical and Electronics Engineers Inc., Piscataway, NJ, USA, Sep 17-20, 2000.
[128] Faure F, Velazco R, Peronnard P. Single-Event-Upset-Like Fault Injection: A Comprehensive Framework[J]. IEEE Transactions on Nuclear Science, 2005, 52(6-1): 2205~2209.
[129] Antoni L, Leveugle R, Feher B. Using Run-Time Reconfiguration for Fault Injection Applications[J]. IEEE Transactions on Instrumentation and Measurement, 2003, 52(5): 1468~1473.
[130]李华旺,刘海涛,杨根庆.航天单粒子事件故障注入系统研究[J].量子电子学报, 2002, 19(1): 57~60.
[131]彭俊杰,黄庆成,洪炳镕等.一种用于星载系统可靠性评测的软件故障注入工具[J].宇航学报, 2005, 26(6): 823~827.
[132]刘宏泰.基于软件实现的故障注入系统设计与仿真[D].哈尔滨:哈尔滨工业大学硕士学位论文, 2003.
[133]邢克飞.星载信号处理平台单粒子效应检测与加固技术研究[D].长沙:国防科技大学博士学位论文,2007.
[134] Stott D T, Ries G, Hsuer M C, et al. Dependability Analysis of a High-speed Network Using Software-Implemented Fault Injection and Simulated Fault Injection[J]. IEEE Transactions on Computers, 1998,47(1):108-119.
[135] Sieh V, Tschache O, Balbach F. VERIFY: Evaluation of Reliability Using VHDL-Models with Embedded Fault Descriptions[C]. Prop. 27th IEEE Int. Symp. on Fault Tolerant Computing(FTCS-27), WA, Seattle,1997:32-36.
[136] Laprie J C. Dependable Computing and Fault Tolerance: Concepts and Terminology [C].Proc.of the 15th Int’l Symp. on Fault-Tolerant Computing (FTCS-15),June 1985:2-11.
[137] Choi G S, Iyer R K. FOCUS: An Experimental Eenvironment for Fault Sensitivity Analysis[J]. IEEE Trans.Comp.1992, 41: 1515-1525.
[138]张天宏,李璇君,辛季龄.智能化BIT测试适配器研究[J].数据采集与处理,1999.12(4):462-466.
[139]孙峻朝,王建莹,杨孝宗.管脚级故障模型的分析与生成技术的研究[J].计算机学报,1999,22(8):845-851.
[140] Gaisler J. Evaluation of a 322 Bit Microprocessor with Built-in Concurrent Error-Detection [C]. Proc. 27th IEEE Int. Symp. on Fault Tolerant Computing (FTCS-27). 1997: 422-426.
[141] Gunneflo U, Karlsson J, Torin J. Evaluation of Error Detection Schemes Using Fault Injection by Heavy-ion Radiation [C]. Proc.of the 19th Int’l Symp.on Fault-Tolerant Computing (FTCS-19), 1989: 340-347.
[142] Arlat J, Crouze Y, Fabre J C. Fault Injection for Dependability Validation of Fault-tolerant Computer Systems [C]. Proc.of the 19th Int’l Symp.on Fault-Tolerant Computing (FTCS-19),1989: 348-355.
[143] Mei-Chern Hsueh, Timothy K.Tsai, Ravishankar K.Iyer. Fault Injection Techniques and Tools [J]. Computer. 1997, 30(4): 75-82.
[144] Asenek V. SEU Induced Errors Observed in Microprocessor Systems[C]. 35th International Nuclear & Space Radiation Effects, Newport Beach, CA, July 1998.
[145] Segall Z, Vrsalovic D, Siewiorek D, et al. FIAT– Fault Iinjection Based Automated Testing Environment [C]. Proc.of the 18th Int’l Symp.on Fault-Tolerant Computing (FTCS-18),1988: 102-107.
[146] Tsai T K, Iyer R K, Jewitt D. An Approach towards Benchmarking of Fault-tolerant Commercial Systems [C]. Proc. FTCS-26, 1996: 314-323.
[147] Kao W, Iyer R K, Tang D. FINE: A Fault Injection and Monitoring Environment for Tracing the UNIX System Behavior under Faults[J]. IEEE Trans.on Software Engineering.1993,19(11):1105-1118
[148] Kao W, Iyer R K. DEFINE:A Distributed Fault Injection and Monitoring Environment [C]. Proc. Workshop Fault-Tolerant Parallel and Distributed Systems ,1994:511-518.
[149] Seungjae Han, Harold A,Rosenberg, et al. DOCTOR: An Integrated Software Fault Injection Environment for Distributed Real-Time System [C]. In: IEEE Int.Computer Performance and Dependability Symposium, 1995: 204-213.
[150] Henrique Madeira, Jo?o Gabriel Silva. Xception : A Technique for the Experimental Evaluation of Dependability in Modern Computers [J]. IEEE Transactions on Software Engineering. 1998, 24(2): 77-83.
[151] Echtle K, Leu M. The EFA Fault Injector for Fault-tolerant Distributed System Testing[C]. IEEE Workshop on Fault-Tolerant Parallel and Distributed Systems . 1992:28-35.
[152] Chani A. Kanawati, Nasser A, Kanawati,et al. Abraham. FERRARI: a Tool for the Validation of System Dependability Properties[J]. In Fault-TolerantComputing FTCS-22, 1992: 336-344.
[153] Clark J A , Pradhan D K. Fault Injection: A Method for Validating Computer System Dependability [J]. IEEE Computer, 1995, 28 (6) : 47-56.
[154] Czeck E W. On the Prediction of Fault Behavior Based on Workload [D]. Camegie Mellon University, Pittsburgh, PA, Apr.1991.
[155] Stou D T, Ries G, Hsueh M.-C,et al. Dependability Analysis of A High Speed Network Using Software Implemented Fault Injection and Simulated Fault Injection [J]. IEEE Trans. Comp. Special Issue on Dependable Computing, 1998, 47: 109-119.
[156] Guthoff J, Sieh V. Combining Software-implemented and Simulation-based Injection into A Single Fault Injection Method [C]. Proc.of the 25th Int’l Symp.on Fault-Tolerant Computing (FTCS-25), 1995: 196-206.
[157] Young L, Lyer R K, Goswami K,et al. Hybrid Monitor Assisted Fault Injection Environment [C]. Proc.of the 3th IFIP Int’Working Conf. Dependable Computers for Critical Applications (DCCA-3),1993: 163-174.
[158]史铁林,陈勇辉,李巍华等.提高大型复杂机电系统故障诊断质量的几种新方法[J].机械工程学报,2003,39(9):1-10.
[159]韩暋.装备可测性设计及验证技术的发展及应用[C].国防科技工业试验与测试技术高层论坛论文集,2007.
[160]杨为民.可靠性.维修性.保障性总论[M].北京:国防工业出版社,2001.
[161]王成刚,周晓东,彭顺堂等.一种基于多信号模型的测试性评估方法[J].测控技术,2006,25(10):13-15.
[162]林志文,贺喆,刘松风.基于多信号模型的系统测试性分析与评估[J].计算机测量与控制,2006,14(2):222-224.
[163]徐赫,王宝龙,武建辉.基于贝叶斯网络的测试性预计方法[J].导弹与制导学报,2007,27(4):232-235.
[164]王成刚,周晓东,王学伟.基于贝叶斯网络的复杂装备测试性评估[J].电子测量与仪器学报,2009,23(5):17-21.
[165]石君友,刘骝,李郑.测试性验证辅助软件(TVAS)设计与实现[J].测控技术,2007,26(7):58-60.
[166] James O B. Statestic Decision Theory-Foundations[J]. Concepts and Methods, Newyork,Springverlay,1989.
[167] Gelfand A, Maillick E. Bayesian Analysis of Proportional Hazards Models Built from Monotone Functions[J]. Biometrics,1995(15):843-852.
[168] Harry F, Martz. Empirical Bayes Estimation of the Reliability of Nuclear-Power-Plant Emergency Diesel Generators[J]. Technometrics, 1996,38(1).
[169] Kurt Porn. The two-stage Bayesian Method Used for the T-Book Application[J]. Reliability Engineering and System Safety, 1996(5).
[170] Bergman B, Ringi M. System Reliability Prediction Using Data from Non-identical Environments[J]. Reliability engineering and system safety. 1997(8).
[171] [美]A.M.穆德, F.A.格雷比尔著,史定华译.统计学导论.北京:科学出版社,1992.
[172] Gelfand A E, Maillick. Bayesian Analysis of Proportional Hhazards Models Built from MonotoneFunctions[J]. Biometrics,1995(15):843-852.
[173] Watkins A J. On Maximum Likelihood Estimation for the Two Parameter Weibull Distribution[J]. Microelectronics Reliability,1996,36(5):595-603.
[174] Calabria R, Pulcini G.. An Engineering Approach to Bayes Estimation for the Weibull Distribution[J]. Microelectronics Reliability,1994,34(5):789-802.
[175] Pierce D A. Fiducial, Frequency, Bayesian Inference on Reliability for the Two Parameter Negative Exponential Distribution[J]. Technometrics, 1973, 15(2):249-253.
[176]唐雪梅,张金槐,邵凤昌等.武器装备小子样试验分析与评估[M].北京:国防工业出版社,2001.
[177]成平,陈希孺.参数估计[M].上海:上海科学技术出版社,1985.
[178]峁诗松,王静龙,濮晓龙.高等数理统计[M].北京:高等教育出版社,2007.
[179]张金槐,唐雪梅.Bayes方法[M].长沙:国防科技大学出版社,1989.
[180]唐雪梅.武器装备小子样试验分析与评估[D].长沙:国防科技大学博士学位论文,2007.
[181]李欣欣.基于Bayes变动统计的精度鉴定与可靠性增长评估研究[D].长沙:国防科技大学博士学位论文,2008.
[182]明志茂.动态分布参数的Bayes可靠性综合试验与评估方法研究[D].长沙:国防科技大学博士学位论文,2009.
[183]张玉柱,胡自伟,曹世民等.维修性验证试验与评定原理[M].北京:国防工业出版社,2006.
[184]徐忠伟,周玉芬,高锡俊.测试性验证中抽样方案的精确算法[J].空军工程大学学报(自然科学版),2000,1(1):76-78.
[185]徐忠伟,周玉芬,徐松涛.测试性验证中抽样方案的精确算法及应用[J].航空学报,2000,21(1):67-69.
[186]温旭东.关于假设检验及两种错误的思考[J].今日论坛,2008.5.
[187]袁力,盛爱辉.区间估计与假设检验的相关性及应用[J],郧阳师范高等专科学校学报,2007,27(6):30-31.
[188] Michael J C, David E M, Thomas J S,et al. Comparison of Electronics Reliability Assessment Approaches [J] . IEEE Transactions on Reliability , 1993 , 42 (4):542-546.
[189] Telcordia SR2332 ( Issue 2) . Reliability Prediction Procedure for Electronic Equipment [S] . 2006.
[190] Dylis D D. PRISM : A New Approach to Reliability Prediction[J ] . Reliability Review , 2001 , 21 (1) : 5-11 , 13-15.
[191] FIDES Guide ( Issue A) . Reliability Met Hodology for Electronic Systems[ S] . France : FIDES Group , 2004.
[192] Pecht M. Why the Traditional Reliability Prediction Model Do Not Work Is There An Alternative [J] . Electronic Cooling , 1996,2(1):10.
[193] Pecht M, Dasgupta A. Physics of Failure: An Approach to Reliable Product Development[J]. Journal of t he Institute of Environmental Sciences , 1995 , 38 (5) : 30-34.
[194] Seymour M. Reliability Prediction Methods—An Overview[J].The Journal of RAC,1999 (3):8-11.
[195]李瑞颖,康锐.基于神经网络的故障率预测方法[J].航空学报,2008.29(2):357-363.
[196]韩光臣,孙树栋,司书宾等.复杂系统故障传播与故障分析模型研究[J].计算机集成制造系统,2005,11(6):794-798.
[197]欧贵兵,刘清国.概率统计及其应用[M].北京:科学出版社,2007.
[198]周源泉.维修性增长的Bayes方法[J].质量与可靠性,2005,3:19-23.
[199] Barlow R E, Scheuer E M. Reliability Growth During a Development Testing Program [J]. Techno-metrics, 1966,31(8):53-60.
[200]田国梁.二项分布的可靠性增长模型[J].宇航学报,1992,1:55-61.
[201]赵宇,黄敏,于丹等.利用试验数据的产品可靠性综合验证方案确定方法[J].航空学报,2005,26(5):637-640.
[202]王玲玲.指数分布下可靠性Bayes验证[J].华东师范大学学报(自然科学版). 1993(3):1-10.
[203]陈文华,崔杰,潘俊等.威布尔分布下失效率的Bayes验证试验方法[J].机械工程学报,2005,41(12):118-121.
[204]甘茂治,吴真真.维修性设计与验证[M].北京:国防工业出版社,1995.
[205] Ammer W. Handbook of System and Product Safety [M] . Prentice Hall ,2000.
[206]罗佑新,张龙庭,李敏.灰色系统理论及其在机械工程中的应用[M].长沙:国防科技大学出版社,2000:30-98.
[207]何文章,郭鹏.关于灰色关联度中的几个问题的探讨[J].数据统计与管理.1999,18(3):25-29.
[208] Zeki A. A Fuzzy AHP-based Simulation Approach to Concept Evaluation in a NPD Environment [J],IIE Transavtions,2005,37(9):827-842.
[209]曲晓慧,乔新勇,陈玫等.基于灰色关联分析的柴油机状况评估[J].兵工学报,2005,26(4):557-559.
[210] Qualtech Systems Inc. TEAMS6.0 User’s Guide, 2002, 218pages.
[211] Desgin for Testability and Design for Diagnosability.http://www.design for testability.com, 2008.9.
[212] DSI Iinternational Inc. eXpress. http://www.dsiintl/WebLogic/products.aspx, 2008.9.
[213] QSI. TEAMS. http://www.teamqsi.com/TEAMS.html, 2008.9.
[214]李行善,左毅,孙杰.自动测试系统集成技术[M].北京:电子工业出版社, 2004:42-50.
[215] David M B, Brian A K, Alony M H. A System Testability"Top-Down"Apportion- ment Method[C]. Proceedings of the IEEE AUTOTESTCON, 1990:451-463.
[216] Stora M J. IEEE P1505 Receiver Fixture Interface (RFI) System Standard Update [C]. Proceedings of the IEEE AUTOTESTCON, 2001: 480-496.
[217] IEEE Std 771-1998. IEEE Guide to the Use of the ATLAS Specification [S].Piscataway, New Jersey: IEEE Standards Press, 1998.
[218] IEEE Std 776-1995. Standard Test Language for All Systems-Common/Abbrevi- ated Test Language for All Systems (C/ATLAS) [S]. Piscataway, NewJersey: IEEE Standards Press, 1995.
[219] IEEE Std 1232.1-1997. AI-ESTATE Data and Knowledge Specification[S]. Pisc- ataway, New Jersey: IEEE Standards Press, 1997.
[220] IEEE Std 1232-1995, Artificial Intelligence and Expert System Tie to Automatic Test Equipment (AI-ESTATE): Overview and Architecture[S].Piscataway, New Jersey: IEEE Standards Press, 1995.
[221] IEEE P1232.2, AI-ESTATE Service Specification[S]. Piscataway, New Jersey:IEEE Standards Press, 1998.
[222] IEEE Std 1232-2002, IEEE Standard for Artificial Intelligence Exchange and Service Tie to All Test Environments(AI-ESTATE)[S]. Piscataway, New Jersey: IEEE Standards Press, 2002.
[223] ISO 10303-11:1994. Industrial Automation Systems and Integration-Product Data Representation and Exchange-Part 11: Description Methods: The EXPRESS Language Reference Manual[S]. Geneva, Switzerland: InternationalOrganization for Standardization, 1994.
[224] Sheppard J W, Kaufman M. Formal Specification of Testability Metrics in IEEE P1522[C]. Proceedings of the IEEE AUTOTESTCON, 2001:71-82.
[225] Sheppard J, Kaufman M. IEEE 1232 and P1522 Standards[C]. Proceedings of the IEEE AUTOTESTCON, 2000: 388-397.
[226] Mark Kaufman, Sheppard J. P1522: A Formal Standard for Testability and Diagnosability Measures[C]. Proceedings of the IEEE AUTESTCON, 1999: 411-418.
[227] Eric B, Danny C D, Lee S. The Use of Model-based Test Requirements throug- hout the Product Line Cycle[C]. Proceedings of the IEEE AUTOTESTCON, 1999: 53-58.
[228] Lee S, Eric B. Test Requirements Model(TeRM) Overview and Status[C]. Proceedings of the IEEE AUTOTESTCON, 2000:380-387.
[229] IEEE Std 1641-2004. IEEE Standard for Signal and Test Definition[S]. Piscataway, New Jersey: IEEE Standards Press, 2004.
[230] Ellis K. Signal and Test Definition-an IEEE Standard[C]. Proceedings of the IEEE AUTOTESTCON, 2003:244-257.
[231] Ellis K, Delaney D. Signal Definition and Test Description-an IEEE Standard[C]. Proceedings of the IEEE AUTOTESTCON, 2002:380-393.
[232] Les Orlidge. SCC20 Annual Report for 2004, http://standards.ieee.org, 2004.
[233] Les Orlidge. SCC20 Annual Report for 2005, http://standards.ieee.org, 2005.
[234] William R, Simpson, Harold S,et al. The ARINC Research System Testability and Maintenance Program(STAMP)[C]. Proceedings of the IEEE AUTOTESTCON, 1982:88-95.
[235] William L K. A Navy Approach to Integrated Diagnostics[C]. Proceedings of the IEEE AUTOTESTCON, 1990:443-450.
[236] Yun Peng, James A R. Abductive Inference Model for Diagnostic Problem-Solving[M]. New York: Springer-Verlag, 1990.
[237] Dill H H. Diagnostic Inference Model Error Source[C]. Proceedings of the IEEE AUTOTESTCON, 1994:391-397.
[238] Bartolini A, Sheppard J W, Munns T E. An Application of Diagnostic Inference Modeling to Vehicle Health Management[C]. Proceedings of the IEEE AUTOTESTCON, 2001: 706-717.
[239]龙兵.多信号建模与故障诊断方法及其在航天器中的应用研究[D].哈尔滨:哈尔滨工业大学博士学位论文,2005.
[240] De Paul. Logic Modeling as A Tool for Testability[C]. Proceedings of the IEEE AUTOTESTCON, 1985:203-207.
[241] Testability Timeline. http://www.testability.com/reference/History.aspx,2008.
[242] Gould E, Hartop D. Thinking beyond the Group Size Fetish: towards A New Testability[C]. Proceedings of the IEEE AUTOTESTCON, 1999:673-684.
[243] Lala J H. Fault Detection, Isolation, and Reconfiguration in FTMP: Methods and Experimental Results [C].Proc.of the 5th AIAA/IEEE Digital Aviontics Systems Conf.(DASC),1983: 130-146.
[244] Laura F Burkhardt, Thomas K Masotto, Jaynarayan H Lala. Advanced Information Processing System: Fault Injection Study and Results [R]. NASA Contractor Report-189590,1992.
[245] Raymond P Kurlak, Robert J. Chobort. CPU Coverage Evaluation using Automatic Fault Injection [R]. AIAA 81-2281R,1982.
[246] Benson J W. Hardware Fault Insertion and Instrumentation System Mechanization and Validation [R]. NASA-CR-181445,1987.
[247]李璇君.航空发动机数字控制器与航空电子综合系统BIT技术研究[D].南京:南京航空航天大学硕士学位论文,2001.
[248]李璇君,辛季龄.基于后驱动技术的故障注入方法研究[J].哈尔滨工业大学学报,2001,33(6):858-862.
[249]李海军,刘霄,王永涛.Gibbs抽样的诊断贝叶斯网络模型评估方法[J].系统仿真学报,2007,19(10):2392-2394.
[250]苏羽,赵海,苏威积.基于贝叶斯网络的态势评估诊断模型[J],东北大学学报(自然科学版),2005.26(8):739-742.
[251]李剑川.贝叶斯网络故障诊断与维修决策方法及应用研究[D].长沙:国防科技大学博士学位论文,2002.
[252]王建莹.面向容错系统验证的故障注入技术研究[D].哈尔滨:哈尔滨工业大学博士学位论文,2000.
[253] [苏]H.?.舒波夫.电机的噪声与振动[M].北京:机械工业出版社,1980.
[254] Ahmed Y, Ben Sasi, Fengshou Gu,et al. A Validated Model for the Prediction of Rotor Bar Failure in Squirrel-cage Motors Using Instantaneous Angular Speed[J]. Mechanical Systems and Signal Processing,2006,20:1572-1589.
[255]峁诗松.统计手册[M].北京:科学出版社,2003.
[256]刘飞.固体火箭发动机可靠性增长试验理论及应用研究[D].长沙:国防科技大学博士学位论文,2006.
[257] Mazzuchi T A, Soyer R. A Bayes Method for Assessing Product Reliability During Development Testing[J].IEEE transactions on reliability, 1993:322-325.
[258] Mazzuchi T A, Soyer R. Reliability Assessing and Prediction During Product Development[C].Annual Reliability and maintainability Symposium, 1992:468-474.
[259] [英]B.S.艾沃日特著,刘韵源,周家丽译.列联表分析.北京:科学出版社,1980.14-15.
[260]刘宏伟,杨孝宗,曲峰等.一个基于响铃形故障检测率函数的软件可靠性增长模型[J].计算机学报,2005,28(5):908-912.
[261] GB/T15500-1995.利用电子随机数抽样器进行随机抽样的方法[S].
[262] GB10111-1988.利用随机数骰子进行随机抽样的方法[S].
[263] Kwong C K,Bai H.A Fuzzy AHP Approach to the Determination of Importance Weights of Customer Requipments in Quality Function Deployment[J].Journal of Intelligent Manufacturing,2002,13(3):367-377.
[264]古莹奎,吴陆恒.机械运动方案评价中评价因素权重确定的模糊层次分析法[J].中国机械工程,2007,18(9):1052-1056.
[265] PeterJ B,David A F. Some Asymptotic Theory the Bootstrap[J].The Annuals of Statistics, 1981, 9(6):1197-1217.
[266]屈斐,王树宗.基于Bootstrap仿真的鱼雷可靠性置信下限[J].鱼雷技术,2006,14(4):32-35.
[267]谷振宇,王胜文,洪炳熔.软件故障注入方法及其仿真应用[J].福建师范大学学报(自然科学版),2004,20(4):28-31.
[268]王莲芬,许树柏.层次分析法引论[M].北京:中国人民大学出版社,1989.
[269]张金槐,刘琦,冯静.Bayes试验分析方法[M].长沙:国防科技大学出版社,2007.
[270]曹晋华,程侃.可靠性数学引论[M].北京:高等教育出版社,2006.