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基于相关性模型的诊断策略优化设计技术
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摘要
高新技术在武器装备中的广泛应用,一方面极大地改善了装备的性能,使装备功能越来越先进;另一方面显著地增加了装备的技术和结构复杂性,对装备的测试、诊断与维修提出严峻的挑战。主要表现在:测试与诊断能力差、准确性低,测试与诊断时间长、费用高、效率低。经过大量的研究和实践,人们认识到:要想从根本上解决上述问题,必须对装备开展可测性设计。
     诊断策略优化设计是可测性设计中的一项重要内容,对于降低测试成本,提高故障诊断能力、诊断效率和诊断精度具有十分重要的意义。基于模型的诊断策略优化设计是目前普遍采用的一种设计方法,首先对装备建立一种相关性模型,利用模型所描述的故障与测试的逻辑关系信息开展诊断策略设计与可测性评估。虽然在该技术领域已有不少的理论及应用成果,但是仍存在不少难点问题亟待解决。对此,本文在“装备可测性/机内测试分析、设计与评估技术”项目的支持下,开展理论与技术研究,重点对复杂情况(测试不可靠、存在多故障)下的诊断策略优化设计以及典型复杂结构(多模式、多回路、多层次)系统的诊断策略优化设计等难点问题开展深入研究。本文的主要研究内容与成果如下:
     1.研究了相关性建模与诊断策略优化设计的基本理论
     对相关性建模以及基于相关性模型的诊断策略优化设计的基本理论进行了系统总结;在此基础上,针对已有的诊断策略搜索算法难以在复杂情况下既快速又准确地搜索到最优解的问题,以信息启发策略为核心,将一步前向搜索和深度搜索相结合,提出了一种新的搜索算法,即准深度搜索算法,该算法可用于各种复杂情况下的诊断策略优化设计。验证结果表明:该算法可以在计算精度和计算复杂度间获得较理想的权衡,应用它可以快速找到理想的(诊断代价小、效率高)诊断策略,为后续研究奠定了基础。
     2.研究了复杂情况下的诊断策略优化设计技术
     (1)针对测试不可靠情形下的诊断策略优化设计问题,应用统计方法构造了故障-测试不确定相关性矩阵;基于该矩阵构造了一种指导诊断策略生成的启发式函数;在此基础上,结合准深度搜索算法,分别针对二值和多值不可靠测试这两种情形提出了诊断策略优化搜索算法。验证结果表明:应用该算法所得到的诊断策略不仅诊断代价小,而且诊断准确度较现有方法大大提高,有效地解决了在测试不可靠情形下的诊断策略优化设计问题。
     (2)针对多故障情形下的诊断策略优化设计问题,基于相关性模型建立了三类典型多故障的数学模型;在此基础上分析了现有方法发生误诊的机理,进而构造了一种基于布尔逻辑的多故障推理机;基于上述研究,分别针对冗余和非冗余系统这两种情形提出了多故障诊断策略优化搜索算法。验证结果表明:应用该算法所得到的诊断策略可以快速准确地隔离多故障,减少了漏诊或者误诊的发生,有效地解决了多故障情形下的诊断策略优化设计问题。
     3.研究了典型复杂结构系统的诊断策略优化设计技术
     (1)针对多模式系统的诊断策略优化设计问题,分析了在不同的系统模式下故障的传播特性,构建了各模式下的故障-测试相关性矩阵;进而提出了一种基于启发式函数的最佳模式顺序生成方法;在此基础上,结合准深度搜索算法,提出了一种多模式系统的诊断策略优化搜索算法。验证结果表明:应用该算法所得到的诊断策略通过模式的优化排序和转换,可以快速隔离出在单一模式下无法检测或隔离的故障,有效地解决了多模式系统的诊断策略优化设计问题。
     (2)针对多回路系统的诊断策略优化设计问题,根据多回路系统的结构特点,提出了一种快速搜索回路的算法以及一种基于启发式函数的最佳断点确定方法;在此基础上,结合准深度搜索算法,提出了一种多回路系统的诊断策略优化搜索算法。验证结果表明:应用该算法所得到的诊断策略可快速准确地隔离回路中的故障,且使用的断点少,有效地解决了多回路系统的诊断策略优化设计问题。
     (3)针对多层次系统的诊断策略优化设计问题,根据系统功能层次划分,对每个层级的可更换单元分别构建了故障-测试相关性矩阵;对现有的启发式函数进行改进,使之能根据不同的故障隔离级别要求生成相应的诊断策略;在此基础上,结合准深度搜索算法,提出了一种多层次系统的分层诊断策略优化搜索算法。验证结果表明:应用该算法可以优化生成任何期望故障隔离级的诊断策略,可以满足不同的维修性要求,有效地解决了多层次系统的诊断策略优化设计问题。
     4.软件开发与工程应用研究
     基于上述研究成果,设计和开发了计算机辅助可测性建模与诊断策略优化设计软件;以导弹系统为对象,应用该软件工具构建了系统相关性模型,优化设计了诊断策略,并进行了故障仿真注入试验。试验结果表明:本文所设计的诊断策略代价小、诊断准确度高、可准确隔离多故障,达到了可测性设计要求。
The performance of weapon equipments has been greatly improved with the widely application of high technology. On the other hand, the complexity of technology and structure of equipments increasing significantly raise challenges in equipment testing, diagnosis and maintenance which include poor testing and diagnosis, low accuracy, low efficiency and high consumption on time and cost. Extensive researches and practices make us recognize that Design for Testability (DFT) must be carried out concurrently with functional design of weapon equipments in order to fundamentally solve these problems.
     Diagnostic strategy design, as an important aspect in DFT, is crucial for reducing test cost and improving diagnostic accuracy and efficiency. A model-based method of diagnostic strategy design is widely used recently, in which the strategy design and testability evaluation are made following the construction of equipments dependency model.
     Although there have been numbers of theoretical findings, many complex problems still exist in this area.
     Supported by the advanced project "Equipments Testability/BIT Analysis, Design and Evaluation Technology", this dissertation makes the further studies on diagnostic strategy design methods mainly aiming at the currently existing key problems in the area, such as design in some typical complex situations (unreliable test, multiple faults) and design for systems with typical complex structure (multiple modes, multiple loops, multiple levels). The main contents and productions of the dissertation are as follows.
     1. Study on the theories of dependency modeling and optimization designs of diagnostic strategy.
     In order to accomplish the quickly optimal searching for diagnostic strategy under complex situations, a new searching algorithm, referred to as Quasi-Depth First Search (QDFS) algorithm, is presented by combining existing one-step look-ahead search algorithms with multi-step one. With information gain heuristic strategy as its core, the new algorithm and can be applied in complex situations. Experimental results show that the algorithm can reach an ideal trade-off between accuracy and computational complexity as well as produce optimal/near-optimal diagnostic strategies being of low cost and high efficiency.
     2. Study on the optimization design technologies for diagnostic strategy in typical complex situations.
     (1) In the situation of unreliable tests (two-valued and multi-valued respectively). Firstly a fault-test uncertainty dependency matrix is built using statistical method. Based on it, a new heuristic function used to guide the generation of diagnostic strategy is then presented. With the use of QDFS, an optimization algorithm is presented, as well as the construction of several prediction functions which are applied to evaluate diagnostic accuracy. Experimental results show the diagnostic strategies that follows from the proposed algorithm are lower costly and more accurate compared to the existing ones.
     (2) In the situation of multiple faults (in systems with and without redundancy respectively). First, based on the symptoms analysis of concurrent multiple faults with dependency model, three typical multiple faults mathematical models are constructed. Then a multiple fault inference engine based on Boolean logic is presented following the mechanism analysis of misdiagnosis caused by existing single fault inference engine. Based on the inference engine, an optimization algorithm is presented. Experimental results show the diagnosis of multiple faults is quick and missed or false diagnosis can be avoided.
     3. Study on the optimization design technologies for diagnostic strategy for the systems with complex structure.
     (1) In multi-mode systems. First, a series of fault-test dependency matrices for various system modes are constructed by analyzing fault propagation features of each mode. An optimization method of generating optimal mode sequences based on a heuristic function follows and then an optimization algorithm is presented. Experimental results show that the proposed algorithm carries out quick isolation of those faults that cannot be detected or isolated with any single mode.
     (2) In multi-loop systems. A loop-searching algorithm is presented firstly by the analysis of dependency model of multi-loop systems. There follows an optimization method of generating optimal feedback loop-breaking points based on a heuristic function. Then an optimization algorithm is drawn up. Experimental results show the diagnosis of multiple faults in the feedback loops is quick and with fewer breakpoints applied.
     (3) In multi-level systems. Firstly fault-test dependency matrixes of each replaceable unit at each level of system are constructed respectively according to the system hierarchy analysis. Then, existing heuristic function is improved in order to generate optimal diagnostic strategies which satisfying various fault isolation requirements. Based on QDFS and the new heuristic function, an optimization algorithm is presented finally. Experimental results show that the proposed algorithm can isolate the faults to any desired level and satisfy different maintainability requirements.
     4. Study on the software platform developing and the practical application of the methods mentioned above.
     Based on the researches mentioned above, a CAD software tool is developed for dependency modeling and diagnostic strategy optimizing.
     The application in a missile system validates the efficiency of the presented methods and software. Following the construction of dependency mode of the system, an efficient diagnostic strategy is derived with the aid of the tool. Then, the results of fault injection experiments and their evaluation show that the proposed strategies make the diagnosis of single fault or multiple faults accurate, quick and low costly, therefore satisfy the testability requirements.
引文
[1]曾天翔.电子设备测试性及诊断技术[M].北京:航空工业出版社, 1996.
    [2] Department of Defense, MIL-STD-2165A, Military Standard Testability Program for Systems and Equipments[S]. 1993.
    [3] GJB 2547-95装备测试性大纲[S].北京:国防科工委军标出版社, 1995.
    [4]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.
    [5] Department of Defense, MIL-STD-1309D, Military Standard Definitions of Terms for Testing, Measurement and Diagnostics[S], 1992.
    [6] Eric Gould. Diagnostics and Testability. http://www.dsiintl.com/Resources/Presentations/Diagnostics%20and%20Testability.pdf, 2008.9.
    [7] Kaufman M, Sheppard J W. P1522: a formal standard for testability and diagnosability measures[C]. Proceeding of the IEEE AUTOTESTCON, 1999: 411~418.
    [8] IEEE Std 1522-2004, IEEE Trial-Use Standard for Testability and Diagnosability Characteristics and Metrics[S] , Piscataway, New Jersey: IEEE Standards Press, 2004.
    [9] Simpson W R, Sheppard J W. System Test and Diagnosis[M]. Boston: Kluwer Academic Publishers, 1994.
    [10]杨廷善.设计-制造-维护纵向集成测试策略[J].测控技术, 1998, 18(9): 14~16.
    [11] Hinzmann M A. Dependency modeling of an avionics power-supply for testability analysis[C]. Proceedings of the IEEE Reliability and Maintainability Symposium, 1995: 283~289.
    [12] Azam M, Tu F, Pattipati K R, et al. A Dependency Model-based Approach for Identifying and Evaluating Power Quality Problems[J]. IEEE Transactions on Power Delivery, 2004, 19(3):1154~1166.
    [13] Dontamsetty M. Studies in Testability Optimization[D]. University of Connecticut, 1990.
    [14] Shakeri M, Advances in system fault modeling and diagnosis[D]. Univ. of Connecticut, 1996.
    [15] Simpson W R. Dependency Modelling Pitfalls[C]. Proceedings of the IEEE AUTOTESTCON, 1994: 717~720.
    [16]温熙森,徐永成,易晓山,陈循.智能机内测试理论与应用[M].北京:国防工业出版社, 2002.
    [17]曾芷德.数字系统测试与可测性[M].长沙:国防科技大学出版社, 1992.
    [18]丁瑾.可靠性与可测性分析设计[M].北京:北京邮电大学出版社, 1996.
    [19]向东,数字系统测试及可测试性设计[M].北京:科学出版社, 1997.
    [20]陈光礻禹,潘中良等,可测性设计技术[M].北京:电子工业出版社, 1997.
    [21] Miron Abrmovici等著,李华伟等译.数字系统测试与可测试设计[M],北京:机械工业出版社, 2006.
    [22]黄考利.装备测试性设计与分析[M].北京:兵器工业出版社, 2005.
    [23] SJ/T10566-1994,可测性总线.第一部分:标准测试存取口与边界扫描结构[S].北京:电子工业标准化研究所, 1994.
    [24] HB/Z301-1997,航空电子系统和设备测试性设计指南[S],北京:中国航空集团公司301所, 1997.
    [25] HB7503-1997,测试性预计程序[S],北京:中国航空集团公司301所, 1997.
    [26] GJB3385-98,测试与诊断术语[S].北京:国防科工委军标出版社, 1998.
    [27] SJ20695-1998,地面雷达测试性设计指南[S].北京:电子工业标准化研究所,1998.
    [28] QJ3050-1998,航天产品故障故障模式、影响及危害分析指南[S].北京:中国航天集团公司708所, 1998.
    [29] QJ3051-1998,航天产品测试性设计准则[S].北京:中国航天集团公司708所, 1998.
    [30] GJB 3970-2000,军用地面雷达测试性要求[S].北京:国防科工委军标出版社, 2000.
    [31] GJB4260-2001,侦察雷达测试性通用要求[S].北京:国防科工委军标出版社, 2001.
    [32]可维ARMS2.0可靠性维修性保障性工程CAD软件. http://www.kewaytech.com/, 2007.4
    [33]苏永定.机电产品测试性设辅助分析与决策相关技术研究[D].长沙:国防科技大学, 2004.
    [34] Greenspan A M. Establishing testability standards[C]. Proceeding of the IEEE AUTOTESTCON, 1978:275~281.
    [35] William L K. Service Initiative in Testability[C]. Proceedings of the IEEE Reliability and Maintainability Symposium, 1984: 158~161.
    [36] Keller T A. Mate as viewed by Westinghouse[C]. Proceedings of the IEEE AUTOTESTCON, 1978:121~123.
    [37] Kirkpatrick C L, O’Brien R R. F-15 Readiness-The Maintainability Contribution[C]. Proceedings of the IEEE Reliability and MaintainabilitySymposium, 1984:499~504.
    [38] Department of Defense, MIL-STD-470A, Military Standard Maintainability Program for Systems and Equipments[S], 1983.
    [39] Department of Defense, MIL-STD-2165, Military Standard Testability Program for Electronic Systems and Equipments[S]. 1985.
    [40] Rosenberg B. The Navy Integrated Diagnostic Support System-System Overview, Architecture and Interfaces[C]. Proceedings of the IEEE AUTOTESTCON, 1987:251~255.
    [41] Magliero, Leong R. ADS-The IDSS Adaptive Diagnostic System[C]. Proceedings of the IEEE AUTOTESTCON, 1987:61~64.
    [42] Horace A. Generic Integrated Maintenance Diagnostics (GIMADS): designing weapon systems with the maintainer in mind[C]. Proceedings of the IEEE National Aerospace and Electronics Conference, 1988, 4:23~27.
    [43] Clothier R H, Nguyen H T. GIMADS diagnostics allocation process[C]. Proceedings of the IEEE National Aerospace and Electronics Conference, 1989, 3: 1339~1344.
    [44] Department of Defense, MIL-HDBK-1814, DOD Handbook Integrated Diagnostics[S], 1997.
    [45] Department of Defense, MIL-HDBK-2165, Military Standard Testability Program for Systems and Equipments[S], 1995.
    [46] Byron J, Deight L, Stratton G. RADC Testability Notebook[R]. RADC-TR-82-189, 1982.
    [47] ARINC604, Guidance for Design & Use of Built-in Test Equipment[R], 1988.
    [48] The SMTA Testability Guidelines TP-101C, http://www.smta.org/files/smta_testability_guideline_PROMO2.pdf, 2002.
    [49] Kenneth P, Parker. The Boundary-Scan Handbook[M]. Boston: Kluwer Academic Publishers, 2003.
    [50] Parag K. Lala. Digital Circuit Testing and Testability[M]. New York: Elsevier Science and Technology Books, 1997.
    [51]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, 2000.
    [52]温熙森,邱静,刘冠军等.机电产品BIT总体设计技术[R].长沙:国防科技大学, 2005.
    [53] RASSP Design for Testability(DFT) Methodology, Version1.0[R]. http://www.eda.org/rassp/documents/atl/METHODOLOGY_DFT95.pdf, 2008.9.
    [54] Parag K. Lala. Digital Circuit Testing and Testability[M]. New York: Elsevier Science and Technology Books, 1997.
    [55] Nadeau-Dostie B. Design for At-Speed Test, Diagnosis and Measurement[M].Boston: Kluwer Academic Publishers, 2000.
    [56] Gizopoulos D. Electronic Testing Methodologies[M]. New York: Springer, 2005.
    [57]胡政.边界扫描测试理论与方法研究[D].长沙:国防科技大学, 1998.
    [58] IEEE Std 1149.1-1990. Standard Test Access Port and Boundary-Scan Architecture[S], Piscataway, New Jersey: IEEE Standards Press, 2001.
    [59]林清. TM总线技术简介[J].航空计算技术, 1997, (1):32~37.
    [60] IEEE Std 1149.5-1995. IEEE Standard for Module Test and Maintenance Bus(MTM-Bus)Protocol[S], Piscataway, New Jersey: IEEE Standards Press, 1995.
    [61]韩国泰. TM总线和模块故障检测[J].航空电子技术, 1999, (1):4~15.
    [62] IEEE Std 1149.4-1999. IEEE Standard for a Mixed-Signal Test Bus[S], Piscataway, New Jersey: IEEE Standards Press, 1999.
    [63] IEEE Std 1149.1-2001. Standard Test Access Port and Boundary-Scan Architecture[S], Piscataway, New Jersey: IEEE Standards Press, 2001.
    [64] IEEE P1149.6-2003, IEEE Standard Standard for Boundary Scan testing of Advanced Digital Networks, Draft4.1a. http://grouper.ieee.org/groups/1149/6, 2008.
    [65] Chakrabarty K. SOC (System-on-a-Chip) Testing for Plug and Play Test Automation[M]. Boston: Kluwer Academic Publishers, 2002.
    [66] Rochit Rajsuman著,于敦山等译. SoC设计与测试[M].北京:北京航空航天大学出版社, 2003.
    [67] IEEE Std 1500,IEEE Standard Testability Method for Embedded Core-based Integrated Circuits[S], Piscataway, New Jersey: IEEE Standards Press, 2005.
    [68] Basic Dependency Modeling Terminology. http://www.testability.com/Reference/Glossaries.aspx?Glossary=DependencyModeling, 2008.
    [69] Nair R, Chujen Lin, Haynes L, et al. Automatic dependency model generation using SPICE event driven simulation[C]. Proceedings of the IEEE AUTOTESTCON, 1996: 318~328.
    [70] Haynes L, Levy R, Chujen Lin, et al. Automatic generation of dependency models using autonomous intelligent agents[C]. Proceedings of the IEEE AUTOTESTCON, 1996: 303~308.
    [71] Simpson W R, Sheppard J W. System complexity and integrated diagnostics[J]. IEEE Design & Test of Computers, 1991, 8(3):16~30.
    [72] Sheppard J W, Simpson W R. A mathematical model for integrated diagnostics[J]. IEEE Design & Test of Computers, 1991, 8(4):25~38.
    [73] Sheppard J W, Simpson W R. Applying testability analysis for integrateddiagnostics[J]. IEEE Design & Test of Computers, 1992, 9(3):65~78.
    [74] Simpson W R, Sheppard J W. System testability assessment for integrated diagnostics[J]. IEEE Design & Test of Computers, 1992, 9(1):40~54.
    [75] Simpson W R, Sheppard J W. Fault isolation in an integrated diagnostic environment[J]. IEEE Design & Test of Computers, 1993, 10(1):52~66.
    [76] Sheppard J W, Simpson W R. Performing effective fault isolation in integrated diagnostics[J]. IEEE Design & Test of Computers, 1993, 10(2):78~90.
    [77] Ahmed U, Cheng Zixue, Saito S. Information flow model and estimations for services on the internet[J]. Advanced information networking and applications, 2004(1):499~505.
    [78] Sheppard J W. Maintaining diagnostic truth with information flow models[C]. Proceedings of the IEEE AUTOTESTCON, 1996:447~454.
    [79] Deb S, Pattipati K R, Raghavan V, et al. Multi-Signal Flow Graphs: A novel Approach for System Testability Analysis and Fault Diagnosis[J]. IEEE AES Magazine, 1995 (5):14~25.
    [80] Deb S, Ghoshal S, Mathur A, et al. Multisignal Modeling for Diagnosis, FMECA, and Reliability[C], Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, 1998:3026~3031.
    [81] Qualtech Systems Inc. TEAMS6.0 User’s Guide, 2002, 218pages.
    [82] Desgin for Testability and Design for Diagnosability. http://www.designfortestability.com, 2008.9.
    [83] DSI international inc. eXpress, http://www.dsiintl/WebLogic/products.aspx, 2008.9.
    [84] QSI. TEAMS, http://www.teamqsi.com/TEAMS.html, 2008.9.
    [85]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.
    [86] David M B, Brian A K, Alony M H. A System Testability"Top-Down" Apportionment Method[C]. Proceedings of the IEEE AUTOTESTCON, 1990: 451~463.
    [87] Stora M J. IEEE P1505 Receiver Fixture Interface (RFI) system standard update 6.0[C]. Proceedings of the IEEE AUTOTESTCON, 2001: 480~496.
    [88] IEEE Std 771-1998, IEEE Guide to the Use of the ATLAS Specification [S], Piscataway, New Jersey: IEEE Standards Press, 1998.
    [89] IEEE Std 776-1995, Standard Test Language for All Systems-Common/ Abbreviated Test Language for All Systems (C/ATLAS) [S], Piscataway, New Jersey: IEEE Standards Press, 1995.
    [90] IEEE Std 1232.1-1997. AI-ESTATE Data and Knowledge Specification[S], Piscataway, New Jersey: IEEE Standards Press, 1997.
    [91] 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.
    [92] IEEE P1232.2, AI-ESTATE Service Specification[S], Piscataway, New Jersey: IEEE Standards Press, 1998.
    [93] 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.
    [94] 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: International Organization for Standardization, 1994.
    [95] Sheppard J W, Kaufman M. Formal specification of testability metrics in IEEE P1522[C]. Proceedings of the IEEE AUTOTESTCON, 2001:71~82.
    [96] Sheppard J, Kaufman M. IEEE 1232 and P1522 standards[C]. Proceedings of the IEEE AUTOTESTCON, 2000: 388~397.
    [97] Mark Kaufman, Sheppard J. P1522: a formal standard for testability and diagnosability measures[C]. Proceedings of the IEEE AUTESTCON, 1999: 411~418.
    [98] Eric B, Danny C D, Lee S. The Use of Model-based Test Requirements throughout the Product Line Cycle[C]. Proceedings of the IEEE AUTOTESTCON, 1999: 53~58.
    [99] Lee S, Eric B. Test requirements model(TeRM) overview and status[C]. Proceedings of the IEEE AUTOTESTCON, 2000:380~387.
    [100] IEEE Std 1641-2004, IEEE Standard for Signal and Test Definition[S], Piscataway, New Jersey: IEEE Standards Press, 2004.
    [101] Ellis K. Signal and test definition-an IEEE standard[C]. Proceedings of the IEEE AUTOTESTCON, 2003:244~257.
    [102] Ellis K, Delaney D. Signal definition and test description-an IEEE standard[C]. Proceedings of the IEEE AUTOTESTCON, 2002:380~393.
    [103] Les Orlidge. SCC20 Annual Report for 2004, http://standards.ieee.org, 2004.
    [104] Les Orlidge. SCC20 Annual Report for 2005, http://standards.ieee.org, 2005.
    [105] William R. Simpson,Harold S. Balaban. The ARINC Research System Testability and Maintenance Program(STAMP)[C]. Proceedings of the IEEE AUTOTESTCON, 1982:88~95.
    [106] William L K. A Navy Approach to Integrated Diagnostics[C]. Proceedings of the IEEE AUTOTESTCON, 1990:443~450.
    [107] Yun Peng, James A R. Abductive Inference Model for DiagnosticProblem-Solving[M]. New York: Springer-Verlag, 1990.
    [108] Dill H H. Diagnostic Inference Model Error Source[C]. Proceedings of the IEEE AUTOTESTCON, 1994:391~397.
    [109] 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.
    [110]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, 2005.
    [111] De Paul. Logic modeling as a tool for testability[C]. Proceedings of the IEEE AUTOTESTCON, 1985:203~207.
    [112] Testability Timeline. http://www.testability.com/reference/History.aspx,2008.
    [113] Gould E, Hartop D. Thinking beyond the group size fetish: towards a new testability[C]. Proceedings of the IEEE AUTOTESTCON, 1999:673~684.
    [114]钱彦岭.测试性建模技术及其应用研究[D].长沙:国防科技大学, 2002.
    [115]黎琼炜.系统级BIT测试性设计技术及其在组合导航系统中的应用研究[D].长沙:国防科技大学, 2001.
    [116]龙兵,姜兴渭,宋政吉.基于多信号模型多故障诊断技术研究[J].宇航学报, 2004, 25(5): 591~594.
    [117]龙兵,王日新,姜兴渭.基于多信号模型航天器配电系统最优测试技术[J].哈尔滨工业大学学报, 2005, 37(4): 10~13.
    [118]杨智勇,许化龙,许爱强.基于多信号模型的故障诊断策略设计[J].计算机测量与控制, 2006, 14(2): 1616~1619.
    [119]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, (10): 13~15.
    [120]林志文,贺喆,刘松文.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.
    [121]刘海明,易晓山.多信号流图的测试性建模与分析[J].中国测试技术, 2007(1): 49~50.
    [122] Koren I, Kohavi Z. Sequential Fault Diagnosis in Combinational Networks[J]. IEEE Transactions on Computers, 1977, C-26(4):334~342.
    [123] Hakimi S L and Makajima K. On adaptive system diagnosis[J]. IEEE Transactions on Computers, 1984, C-33(3): 234~240.
    [124] Yamada T, Ohtsuka T, et al. On sequential diagnosis of multiprosessor systems[J]. Discrete applied mathematics, 2005, 146:311~342.
    [125] ?u?ec A, Biasizzo A, Novak F. Sequential diagnosis tool[J]. Microprocessors and Microsystems, 2000, 24(4):191~197.
    [126] Pattipati K R. Dontamsetty M. On a Generalized Test Sequencing Problem[J]. IEEE Transactions on Systems, Man, and Cybernetics, 1992, 22(2): 372~376.
    [127] Raghavan V, Shakeri M, Pattipati K R. Test Sequencing Problems Arising in Test Planning and Design for Testability[J]. IEEE Transactions on SMC: Part A-Systems and Humans, 1999, 29(2):153~163.
    [128] Raghavan V, Shakeri M, Pattipati K R. Optimal and Near-optimal Test Sequencing Algorithms with Realistic Test Models[J]. IEEE Transactions on SMC: Part A-Systems and Humans, 1999, 29(1):11~27.
    [129] Ruan S, Tu F, Pattipatia K R, et al. On a Multi-Mode Test Sequencing Problem, IEEE Transactions on SMC, Part B, 2003, 34(3):1490~1499.
    [130] Ruan S, Tu F, Pattipati K R. On Multi-Mode Test Sequencing Problem[C]. Proceedings of the IEEE AUTOTESTCON, 2003:194~201.
    [131] Laurent H, Ronald L R. Constructing Optimal Binary Decision Trees is NP-complete[J]. Information Processing Letters. 1976, 5(1):15~17.
    [132] VomlelováM. Decision Theoretic Troubleshooting[D]. Faculty of Informatics and Statistics of Economics, Prague, Czech Repulic, 2001.
    [133]李俭川.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, 2002.
    [134] Simpson W R, Agre J R. Adaptive Fault Isolation with Learning[C]. Proceedings of the IEEE AUTOTESTCON, 1983:331~335.
    [135] Moret B M. Decision trees and diagrams[J]. ACM Computing Surveys, 1982,14(4):593~623.
    [136] Sheppard J W, Simpson W R. Integrated Diagnosis-a Hierarchical Approach[J]. Proceedings of the IEEE AUTOTESTCON, 1990:477~483.
    [137] Johnson R A. An Information Theory Approach to Diagnosis[C]. Proceedings of the 6th Annual Conference on Reliability and Quality Control, 1960:102~109.
    [138] Hartman C P. Application of Information Theory to the Construction of Efficient Decision Trees[J]. IEEE Transaction on Information Theory. 1982, IT-28(4): 565~577.
    [139] Addis T R. Knowledge Refining for a Diagnostic Aid (An Example of Applied Epidemics)[J]. The Internationa1 Jouna1 of Man-Machine Studies, 1982, 17:151~164.
    [140] Pattpati K R,Alexandridis M.Application of heuristic search and information theory to sequential fault diagnosis[J]. IEEE Transactions on System, Man, and Cybernetics, 1990, 20(4): 872~887.
    [141] Blai B. An algorithm better than AO*?[C]. Proc. of 20th National Conf. on Artificial Intelligence(AAAI), 2005:1343~1348.
    [142] Valentina Bayer Zubek. Learning Cost-Sensitive Diagnostic Policies from Data[D]. Oregon State University, 2003.
    [143] ?mer E K. Classification via sequential testing[D]. Sabanc? University, 2004.
    [144] Raghavan V, Shakeri M, Pattipati K R. Optimal and Near-optimal Test Sequencing Algorithms with Realistic Test Models[J]. IEEE Transactions on SMC: Part A-Systems and Humans, 1999, 29(1):11~27.
    [145] Tu F, Pattipati K R. Pattipati. Rollout Strategies for Sequential Fault Diagnosis[C]. Proceedings of the IEEE AUTOTESTCON, 2002: 269~295.
    [146] Tu F, Pattipati K R. Rollout Strategies for Sequential Fault Diagnosis[J]. IEEE Transactions On SMC: Part A: Systems and Humans, 2003, 33(1):86~99.
    [147]杨叔子,丁洪.基于知识的诊断推理[M].清华大学出版社, 1993:84~86.
    [148]史铁林,杨叔子,师汉民.基于模糊理论与覆盖技术的诊断模型[J].计算机学报. 1992, (4):313~317.
    [149]石君友,田仲.故障诊断策略的优化方法[J].航空学报. 2003, 24(3):212~215.
    [150]景小宁,李全通,陈云翔,吕振中.基于信息熵的最少测试费用故障诊断策略[J].计算机应用, 2005, 25(2):417~419.
    [151]黎琼炜,易晓山,刘冠军.系统级故障隔离的间接熵法[J].系统工程与电子技术, 2001, 23(2):51~54.
    [152]连光耀,黄考利,赵常亮.复杂电子系统测试点与诊断策略的优化方法[J].系统工程与电子技术. 2004, 26(11):1739~1742.
    [153]于劲松,徐波,李行善.基于遗传算法的序贯诊断测试策略生成[J].系统仿真学报, 2004, 16(4): 833~836.
    [154]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, 2007.
    [155] Tu F. Advanced Combinational Optimization Techniques with Applications to Fault Diagnosis and Multiuser Detection[D]. Univ. of Connecticut, 2003.
    [156] Agre J R. A message-based fault diagnosis procedure[J]. Journal of the ACM, 1986, 16(3):328~337.
    [157] Ralph DePaul. Logic Modeling as a Tool for Testability[C]. Proceedings of the IEEE AUTOTESTCON, 1985:203~207.
    [158] William L K. The Assessment of LOGMOD: a Testability Design Tool[R]. http://www.testability.com/reference/Documents/JLC%201980%20Final%20Rev1.pdf, 2008.9.
    [159] Cramer M L, et al. Logic Model Analysis and Standard Maintenance Information Display System (SMIDS)[R]. http://www.testability.com/reference/Documents/LOGMOD%20Simids%20Final%201980.pdf, 2008.9.
    [160] Ralph DePaul. Design disclosure format development[R]. http://www.testability.com/reference/Documents/NMSE%20Sys%20Perform%20Final%201965.pdf, 2008.9.
    [161] Naval Ocean Systems Center. Testability Analysis Tools On A Military System[R]. http://www.testability.com/reference/Documents/Analysis%201987%20Final.pdf, 2008.9.
    [162] Franco J. Experiences Gained Using the Navy’s IDSS Weapon System Testability Analyzer[C]. Proceeding of the IEEE AUTOTESTCON, 1988: 129~132.
    [163] Franco J, Scott J. WSTA-The IDSS Weapon System Testability Analyzer[C]. Proceeding of the IEEE AUTOTESTCON, 1987: 435~440.
    [164] Pillari J, Pertowski T, Protin A, et al. Integrating testability analysis tools with automatic test systems(ATS)[C]. Proceeding of the IEEE AUTOTESTCON, 1995: 503~507.
    [165] Lockheed Martin RASSP Team. CAD System Description[R]. http://www.atl.lmco/projects/rassp/RASSP_legacy/appnotes/PDF/CAD.pdf, 2008.9.
    [166] Simpson W R. The Application of the Testability Disciplince to Full Systems Analysis[C]. Proceedings of IEEE Automatic Test Program Generation Workshop, 1983.
    [167] Simpson W R. Active Testability Analysis and Interactive Fault Isolation Using STAMP[C]. Proceeding of the IEEE AUTOTESTCON Conference Record, 1987:105~112.
    [168] Simpson W R, Sheppard J W, Unkle C R. POINTER-an intelligent maintenance aid[C]. Proceeding of the IEEE AUTOTESTCON, 1989:26~31.
    [169] Simpson W R, Sheppard J W. The application of evidential reasoning in a portable maintenance aid[C]. Proceeding of the IEEE AUTOTESTCON, 1990: 211~214.
    [170] Kelley B A, D'Urso E, Reyes R, et al. System testability analyses in the Space Station Freedom program[C]. Digital Avionics Systems Conference, IEEE/AIAA/NASA 9th, 1990:21~26.
    [171] Haynes L, Kelley B, Chujen Lin, et al. Automatic dependency model generator for mixed-signal circuits[C]. Proceeding of the IEEE AUTOTESTCON, Systems Readiness Technology Conference, 1998:91~96.
    [172] Chujen Lin, Hayes L, Malais A, et al. A new dependency model based testability analyzer[C]. Proceeding of the IEEE AUTOTESTCON, Systems Readiness Technology Conference, 1998:187~191.
    [173] Robach C, Malechaand P, Michel G. CATA: A Computer-Aided Test Analysis System[J]. IEEE Design and Test of Computers, 1984, I(5):68~79.
    [174] Pattipati K R, Deb S, Dontamsetty M, et al. START: System Testability Analysis and Research Tool[J]. IEEE Aerospace and Electronics Systems Magazine, 1991:13~20.
    [175] Pi L, de Mare G, Nolan M. DARTS: An enabling technology for concurrent engineering[C]. Proceeding of the IEEE AUTOTESTCON, 1993: 383~388.
    [176] Darty M, Li Pi Su, Bosco C. Built-in diagnostics for advanced power management[C]. Proceeding of the IEEE AUTOTESTCON, 1994: 399~407.
    [177] Ben-Bassat M, Ben-Arie D, Ben-Zvi I. Aitest: A Real Life Expert System for Electronic Troublshooting and Test Management[C]. The Sixteenth Conference of Electrical and Electronics Engineers in Israel, 1989:1-4.
    [178] Beniaminy I, Ben-Bassat M, Bodenheimer M, et al. Experience in diagnosing a remote, tele-controlled unit using the AITEST expert system[C]. Proceedings of International Test Conference, 1993:37~44.
    [179] Faure P P, Olive L X, et al. Agenda: Automatic GENeration of Diagnosis trees[C]. In: JDA '01. Toulouse (France).
    [180] Gould E. Modeling it both ways: hybrid diagnostic modeling and its application to hierarchical system designs[C]. Proceeding of the IEEE AUTOTESTCON, 2004: 576~582.
    [181] Pattipati K R, Raghavan V, Shakeri M, et al. TEAMS: Testability Engineering and Maintenance System[C]. Proceeding of the American Control Conference, 1994, 2:1989~1995.
    [182] DSI international inc. http://www.dsiintl.com/WebLogic/Users.aspx, 2008.9.
    [183] Deb S, Pattipati K R, Shrestha R. QSI’s Integrated Toolset[C]. Proceeding of the IEEE AUTOTESTCON, 1997:408-421.
    [184] Mathur A, Deb S, and Pattipati K R. Modeling and Real-time Diagnostics in TEAMS-RT[C]. Proceeding of the American Control Conference, 1998, 3: 1610~1614.
    [185] Deb S, Domagala C, Shrestha R, et al. Model-based Testability Assessment and Directed Troubleshooting of Shuttle Wiring Systems[C]. Proceedings of SPIE 2001, 4389:163~173.
    [186] Deb S, Charles D, Sudipto G, et al. Remote diagnosis of the international space station utilizing telemetry data[C]. Proceeding of the SPIE Aerosense Conference, 2001:16~20.
    [187] Sheppard J W, Kaufman M A. A Bayesian Approach to Diagnosis and Prognosis Using Built-In Test Instrumentation and Measurement[J]. IEEE Transactions on Computer, 2005, 54(3):1003~1018.
    [188] Sheppard J W, Kaufman M A. Bayesian Diagnosis and Prognosis Using Instrument Uncertainty[C]. Proceeding of the IEEE AUTOTESTCON, 2005:424~430.
    [189] Simpson W R, Sheppard J W. Multiple Failure Diagnosis[C]. Proceedings of the IEEE AUTOTESTCON, 1994:381~389.
    [190] Davis R. Retrospective on diagnostic reasoning based on structure and behavior[J]. Artificial Intelligence, 1993, 59:149~157.
    [191] Kleer J de, Williams B C. Diagnosing multiple faults[J]. Artificial Intelligence, 1987, 32: 97~130.
    [192] Shakeri M, Pattipati K R. Optimal and near-optimal algorithms for multiple fault diagnosis with unreliable tests[C]. Proceeding of the IEEE AUTOTESTCON, 1996:473~482.
    [193] Iverson D L, Patterson-Hine F A. Digraph reliability model processing advances and applications[C] Proceedings of the AIAA, 1993:1189~1199.
    [194] Shakeri M, Pattipati K R, Raghavan V, et al. Optimal and Near-Optimal Algorithms for Multiple Fault Diagnosis with Unreliable Tests[J]. IEEE trans on SMC, 1998:431~440.
    [195] Ying J, Kirubarajan T, Pattipati KR. A Hidden Markov Model-based Algorithm for Online Fault Diagnosis with Partial and Imperfect Tests[J]. IEEE Transactions on SMC: Part C, 2000, 30(4):463~473.
    [196] Tu F, Pattipati K, Deb S et al. Multiple Fault Diagnosis in Graph-Based Systems[C]. SPIE Conference on Fault Diagnosis, Prognosis and System Health Management, 2002,4733:168~179.
    [197] Tu F, Pattipati K R, Deb S, et al. Computationally Efficient Algorithms for Multiple Fault Diagnosis in Large Graph-Based Systems[J]. IEEE Transactions on Systems, Man and Cybernetics, 2003, 33(1): 73~85.
    [198] Yu F, Tu F, Tu H, et al. Multiple disease (fault) diagnosis with applications to the QMR-DT problem[C]. Proceedings of Computing Communication and Control Technology International Conference, 2003, 2:1187~1192.
    [199] Dill H H. Diagnostic Inference Model error sources[C], Proceeding of the IEEE AUTOTESTCON, 1994:391~397.
    [200] Raghavan V. Algrithms for Sequential Fault Diagnosis[D]. Dept. of Electrical and Systems Engineering, University of Connecticut, 1996.
    [201] Simpson W R, Sheppard J W. The multicriterion nature of diagnosis[C] Proceeding of the IEEE AUTOTESTCON, 1993:389~395.
    [202] Garey M R, Graham R L. Performance bounds on the splitting algorithm for binary testing[J]. Acta Information, 1974(3):347~355.
    [203] Simpson W R, Sheppard J W. Research Perspectives and Case Studies in System Test and Diagnosis[M]. Boston: Kluwer Academic Publishers, 1998:219~221.
    [204] Boumen R, et al. Test sequencing in a complex manufacturing system[J]. XOOTIC Magazine, 2005, 11(2):9~16.
    [205] Biasizzo A, ?u?ec A, Novak F. Sequential diagnosis with asymmetrical tests[J]. The computer Journal, 1998, 41(3):163~170.
    [206] Raghavan V, Shakeri M, Pattipati K R, Test sequencing algorithms with unreliable tests[J]. IEEE Transactions on SMC: Part A - Systems and Humans, 1999, 29(1):347~357.
    [207]王国玉,申绪涧等.电子系统小子样试验理论方法[M].北京:国防工业出版社, 2003.
    [208]林占江.电子测量技术[M].北京:电子工业出版社, 2003.
    [209]朱大其.电子设备故障诊断原理与实践[M].北京:电子工业出版社, 2004: 51~52.
    [210] Shakeri M, Raghavan V, Pattipati K R. Sequential Testing Algorithms for Multiple Fault Diagnosis[J] IEEE Transactions on SMC: Part A, 2000, 30(1):1~14.
    [211]张晓梅.基于模型的故障诊断技术研究及在航天领域的应用[D].哈尔滨:哈尔滨工业大学, 2001: 43~46.
    [212] Doyle S A, Dugan J B, Patterson-Hine A. A quantitative analysis of the F18 flight control system[C]. Proceedings of the AIAA, 1993:668~675.
    [213] Grunberg D B, Weiss J L, Deckert J C. Generation of optimal and suboptimal strategies for multiple fault isolation[R]. Tech. Rep. TM-248, 1987.
    [214] Reiter R. A theory of diagnosis from first principles[J]. Artificial Intelligence, 1987, 32(1):57~95.
    [215]吕克洪.基于时间应力分析的BIT降虚警与故障预测技术研究[D].长沙:国防科技大学, 2008.
    [216] James C T. An efficient search algorithm to find the elementary circuits of a graph[J]. Comunications of the ACM, 1970, 13(12): 722~726
    [217]黎琼炜,刘冠军,易晓山等.系统级BIT设计中基于模糊有向图的系统划分[J].电子测量技术, 2000, 23(2): 51~54.
    [218]李岩,杨洪柱.防空导弹测试技术与遥测系统应用研究[M].北京:宇航出版社, 1995.

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