摘要
合理的民航发动机运营、维修与保障是提高其安全性、可靠性及经济性的重要手段,健康管理就是减少维修保障费用的一种重要方法,现在正受到越来越多的关注。本文针对民航发动机的运营与维修的特点,阐述了民航发动机健康管理的概念,对涉及的若干关键方法进行了深入研究,并开发了相应的集成维修管理系统,主要研究内容如下:
(1)整体上,充分研究了国外几大典型的健康管理系统,在此基础上,从民航发动机运营与维修的角度出发,形成民航发动机健康管理的概念,设计了民航发动机健康管理系统的主要功能,阐述了民航发动机健康管理适用的关键方法,再基于开放式系统架构标准建立了应用技术体系。从方法到技术,再到应用,全面地构建了民航发动机健康管理方法与技术体系。
(2)研究了民航发动机健康管理的关键方法之一:民航发动机在翼寿命预测与控制方法。首先阐述了故障强度概念和两种乘积型强度模型:比例危险模型和比例瞬时平均强度模型,研究了维修次数影响下的发动机使用可靠性建模方法。然后详细研究了两种在翼寿命预测方法:无状态监测参数时的寿命预测和有状态监测参数时的寿命预测。前者是先基于可靠性统计方法,由历史拆换记录进行威布尔建模,然后根据当前运行时间预测条件平均剩余寿命,进而得到在翼寿命的预测值,这是一种基于经验的预测;后者是一种混合模型,研究状态与发动机性能劣化衰退之间的联系,由比例危险模型建立状态与可靠性之间的关系,先得到发动机拆换控制限,结合状态变化趋势,预测发动机由于性能衰退引起的在翼寿命。再结合一些制造商、适航方面的时间限制,综合实现在翼寿命的控制。
(3)研究了民航发动机健康管理的关键方法之二:民航发动机基于状态的维修决策方法。首先在现有各种概念基础上统一了视情维修与基于状态的维修,研究了视情维修决策要素与建模理论。深入研究了两种维修决策方法,一种是基于条件剩余寿命和维修前的条件概率,动态地调整传统的定时维修策略。另外一种决策方法是基于比例危险模型,可以根据发动机当前状态,以故障强度为维修阈值决策发动机的拆换和送修时机,或以单位时间期望总维修费用最小标准下决策最优的预防性维修间隔等。
(4)针对目前监测软件与维修管理软件相互孤立的问题,并考虑航空公司的实际需求,基于民航发动机健康管理的技术体系,设计了民航发动机集成维修管理系统的业务流程与主要功能模块,使用Oracle数据库构建了系统的后台数据库,采用Java进行系统的应用程序开发,目的是实现民航发动机状态监测、寿命控制、维修决策与资源调度。此系统也是上述健康管理方法与技术的验证,正逐步应用于航空公司的发动机日常工程管理中,应用效果非常显著,提高了工作效率,降低了维修成本。
The appropriate civil aeroengine operation, maintenance and support are important for high safety, reliability and economics. Engine health management is an important method to decrease maintenance and support costs. And researchers are paying much attention to this method gradually. In this thesis, according to the features of civil aeroengine operation and maintenance, the concept of civil aeroengine health management is introduced, some involved key methods are studied in detail, and an integrated aeroengine maintenance management system is developed. The main research content is as following.
(1) Holisticly, based on some famous overseas health management systems, the concept of civil aeroengine health management is introduced for engine operaton and maintenance, and main functions of this health management system are designed. After studying the involved key technologies and application system architecture based on the standards of open system architechture. So the general civil aeroengine health management method and system are established, from method to technologies, and to applications.
(2) One key method of civil aeroengine health management is life on wing (LOW) prediction and control. Firstly the concept of failure intensity and two multiplative intensity models, which are proportional hazards model and proportion mean intensity model, are introduced. A specified engine operation reliability model with effect of repair numbers is studied. Then two kinds of LOWprediction models are studied detailedly. The first model is LOW prediction only using time data without condition monitoring data. This model is also called experience-based prognostics, which is a kind of statistics reliability model. Based on the failure time historyical data, the Weibull model is established and the conditional mean residual life is calculated at present time. So the LOW can be predicted. The second LOW prediction model is a kind of hybrid model which study the connection between engine conditions and performance deterioration. Using proportional hazards model (PH model) which combine the condition and reliability data, the LOW due to performance deterioration can be predicted with the engine removal control limit and condition trend. Then LOW control can be completed with the time constrains from engine manufacturer and airworthiness directives.
(3) In this dissertation the other key method of civil aeroengine health management is condition based maintenance (CBM) decision-making. The relationship beween CBM and on condition maintenance is consolidated. The factors and theory of CBM decision-making model are explained. Two models are studied deeply. The first one is a dynamicly adjusted model according to the conditional residual life and conditional probability. Also based on the PH model, according to the present status, civil aeroengine removal and shopvisit can be decided with the threshold of failure intensity. And the optimal engine preventive maintenance interval is offered in term of minimal expected total maintenance cost per unit time.
(4) Considering the practical demands of airlines and the fact of isolation between engine condition monitoring softwares and maintenance management softwares, based on the civial aeroengine health management system architecture, an integrated aeroengine maintenance management system is designed including the work flows, main modular functions and database. This system can implement engine condition monitoring, LOW control, maintenance decision-making and optimal engine schedule. The system is developed using Java programs and Oracle database software. And this integerated sytem is being applied to the aeroengine engineering management in airlines effectively. The work efficiency is increased and the maintenance cost is decreased.
引文
[1] Mercer C R, Simon D L, Hunter G W, et al. Fundamental Technology Development for Gas-Turbine Engine Health Management [R]. NASA-20070022364, 2007. 1-14.
[2] Alford L D. The problem with aviation COTS [J]. Aerospace and Electronic Systems Magazine, IEEE, 2001, 16(2):33-37.
[3] Alford L D. The problem with aviation COTS [J]. Defense acquisition review journal, 1999, 6(2):297-304.
[4] Mtu. Engine maintenance cost [J]. Engine yearbook, 2005:20-25.
[5]曾声奎, Pecht M G,吴际.故障预测与健康管理(PHM)技术的现状与发展[J].航空学报, 2005, 26(5):626-632.
[6] Hess A. The joint strike fighter (JSF) prognostics and health management [A]. Proceeding of 4th Annual System Engineering Conference [C]. JSF Program Office, 2001.
[7] Larder B, Azzam H, Trammel C, et al. Smith Industries HUMS: changing the M from monitoring to management [A]. Proceeding of Aerospace Conference, 2000 IEEE [C]. Big Sky, MT, USA. US: IEEE, 2000:449-455.
[8] Nasa. Integrated Vehicle Health Management - Technical Plan, Version 2.0 [R]. 2008.
[9]李爱军,章卫国,谭键.飞行器健康管理技术综述[J].电光与控制, 2007, 14(3):79-83.
[10] Zuniga F A, Maclise D C, Romano D J, et al. Integrated Systems Health Management for Exploration Systems [A]. Proceeding of 1st Space Exploration Conference: Continuing the Voyage of Discovery [C]. Orlando, FL, USA. AIAA, 2005:1-16.
[11] Figueroa F, Holland R, Schmalzel J, et al. ISHM Implementation for Constellation Systems [A]. Proceeding of 42nd AIAA/ASME/SAE/ASEE Joint Propulsion Conference & Exhibit [C]. AIAA, 2006:1-13.
[12] Hess A. JOINT STRIKE FIGHTER - Diagnostic, Prognostic and Health Management– a Thirty Year Retrospective. [EB/OL]. http://ti.arc.nasa.gov/projects/ishem/Presentations/ Hess Keynote.ppt. /2008-5-2.
[13] Maggiore J B. Remote Management of Real-Time Airplane Data. [EB/OL]. http://www.boeing.com/commercial/aeromagazine/articles/qtr_3_07/AERO_Q307_article4.pdf. 2007-9-1/2008-5-2.
[14]崔建国,李忠海,吕瑞,等.现代大型飞机的关键技术——健康管理技术研究[A]. Proceeding of大型飞机关键技术高层论坛暨中国航空学会2007年学术年会[C].深圳. 2007:1-5.
[15] Tatem. [EB/OL]. http://www.tatemproject.com.
[16] Holtz C, Smith G, Friend R. Modernizing systems through data integration - A vision for EHM in the United States Air Force [A]. Proceeding of AIAA/ASME/SAE/ASEE 40th Joint Propulsion Conference and Exhibit [C]. Fort Lauderdale, FL. AIAA, Inc, 2004:1-12.
[17]黄春峰.航空智能发动机的研究发展[A]. Proceeding of大型飞机关键技术高层论坛暨中国航空学会2007年学术年会[C].深圳. 2007:1-14.
[18] Bickford R L. Health management and controls for Earth-to-orbit propulsion systems [J]. Acta Astronautica, 1995, 35(6):411-419.
[19] ISHEM. [EB/OL]. ti.arc.nasa.gov/projects/ishem/. 2006-6-30/2008-5-7.
[20] Scheuren W J, Caldwell K A, Goodman G A, et al. Safety & The Military Aircraft Joint Strike Fighter Prognostics and Health Management [A]. Proceeding of AIAA/ASME/SAE/ASEE 34th Joint Propulsion Conference & Exhibit [C]. Cleveland, OH. AIAA, 1998:1-7.
[21] Butcher S W. Assessment of Condition-Based Maintenance in the Department of Defense [R]. LG903B1, McLean, Virginia, USA: Logistic Management Institute, DoD, 2000. 1-70.
[22] Azzam H, Beaven F, Smith A, et al. FUMS Technologies for Advanced Structural PHM [A]. Proceeding of Aerospace Conference, 2007 IEEE [C]. 2007:1-12.
[23] Byington C S, Kalgren P W, Donovan B P, et al. Streamlined avionics PHM utilizing portable information and reasoning [A]. Proceeding of Aerospace Conference, 2005 IEEE [C]. IEEE, 2005:3547-3554.
[24] Millar R C. A Systems Engineering Approach to PHM for Military Aircraft Propulsion Systems [A]. Proceeding of Aerospace Conference, 2007 IEEE [C]. IEEE, 2007:1-9.
[25] Roemer M J. Engine Health Monitoring System for Advanced Diagnostic Monitoring for Gas Turbine Engines [R]. AFRL-PR-WPTR-1998-2120, 1998. 1-91.
[26] Larkin J A, Moawad E G, Pieluszczak D P. Functional Aspects of, and Trade Considerations for, an "In-Space" Application-Optimized Engine Health Management System (EHMS) [A]. Proceeding of AIAA/ASME/SAE/ASEE 41st Joint Propulsion Conference & Exhibit [C]. Tucson, AZ, USA. AIAA, Inc, 2005:1-8.
[27] Nickerson B, Lally R. Development of a smart wireless networkable sensor for aircraft engine health management [A]. Proceeding of Aerospace Conference, 2001, IEEE [C].2001:3255-3262.
[28] Sandborn P, Pecht M. Introduction to special section on electronic systems prognostics and health management [J]. Microelectronics Reliability, 2007, 47(12):1847-1848.
[29] Sandborn P A, Wilkinson C. A maintenance planning and business case development model for the application of prognostics and health management (PHM) to electronic systems [J]. Microelectronics Reliability, 2007, 47(12):1889-1901.
[30] Yu L J, Cleary D J, Cuddihy P E. A novel approach to aircraft engine anomaly detection and diagnostics [A]. Proceeding of Aerospace Conference, 2004 IEEE [C]. IEEE, 2004:3468-3475.
[31] Roemer M J, Dzakowic J, Orsagh R F, et al. Validation and verification of prognostic and health management technologies [A]. Proceeding of Aerospace Conference, 2005 IEEE [C]. IEEE, 2005:3941-3947.
[32] Xu R, Zhang G, Zhang X, et al. Sensor Validation Using Nonlinear Minor Component Analysis [R]. AFRL-PR-WPTP-2006-275, 2006. 1-10.
[33] Litt J S, Simon D L, Garg S, et al. A Survey of Intelligent Control and Health Management Technologies for Aircraft Propulsion Systems [J]. Journal of Aerospace Computing, Information, and Communication, 2004, 1(12):543-563.
[34] Luppold R, Brotherton T, Volponi A. Adaptive On-Wing Gas Turbine Engine Performance Estimation [A]. Proceeding of Aerospace Conference, 2007 IEEE [C]. 2007:1-12.
[35] Volponi A, Brotherton T. A bootstrap data methodology for sequential hybrid engine model building [A]. Proceeding of Aerospace Conference, 2005 IEEE [C]. 2005:3463-3471.
[36] Litt J, Simon D L, Meyer C, et al. NASA aviation safety program Aircraft Engine Health Management Data Mining Tools roadmap [A]. SPIE (ed), Proceeding of the 14th Annual International Symposium on Aerospace/Defense Sensing, Simulation and Controls Aerosense [C]. Orlando, FL, USA. Bellingham, WA, USA: Society of Photo-Optical Instrumentation Engineers (SPIE), 2000:292-298.
[37] Semega K. Embedded Sensors for Measurement of Material Properties - Needs Direction, and Technology [A]. Proceeding of AIAA/ASME/SAE/ASEE 41st Joint Propulsion Conference & Exhibit [C]. Tucson, AZ,USA. AIAA, Inc, 2005:1-12.
[38] Kobayashi T, Simon D L. Integration of On-Line and Off-Line Diagnostic Algorithms for Aircraft Engine Health Management [J]. Journal of Engineering for Gas Turbines & Power, 2007, 129(4):986-993.
[39] Leader S, Friend R. A probabilistic, diagnostic and prognostic system for engine health and usage management [A]. Proceeding of Aerospace Conference, 2000 IEEE [C]. 2000:185-192.
[40] Guralnik V, Mylaraswamy D, Voges H. On handling dependent evidence and multiple faults in knowledge fusion for engine health management [A]. Proceeding of Aerospace Conference, 2006 IEEE [C]. 2006:1-9.
[41] Curry T, Behbahani A. Propulsion directorate/control and engine health management (CEHM): real-time turbofan engine simulation [A]. Proceeding of Aerospace Conference, 2004 IEEE [C]. 2004:3414-3423.
[42] Fisher C E. Gas path debris monitoring-a 21st century PHM tool [A]. Proceeding of Aerospace Conference, 2000 IEEE [C]. 2000:441-448.
[43] Jaw L C. ICEMS: a platform for advanced condition-based health management, [A]. Proceeding of Aerospace Conference, IEEE [C]. 2001:2909-2914.
[44] Jaw L C. Recent Advancements in Aircraft Engine Health Management (EHM) Technologies and Recommendations for the Next Step [A]. Proceeding of Turbo Expo 2005: 50th ASME International Gas Turbine & Aeroengine Technical Congress [C]. Nevada. 2005:1-13.
[45] Wade R A. A Need-focused Approach to Air Force Engine Health Management Research [A]. Proceeding of Aerospace Conference, 2005 IEEE [C]. 2005:1-13.
[46]王克昌.液体火箭发动机的健康管理系统[J].上海航天, 1992(1):27-35.
[47]木志高,胡海峰,胡茑庆.武器装备故障预测及健康管理系统设计[J].兵工自动化, 2006, 25(3):20-21.
[48]郑哲敏,赵亚溥. PHM——机械失效的预测和安全管理系统[J].力学进展, 1999, 29(2):268, 243.
[49]张宝珍,曾天翔.先进的故障预测与状态管理技术[J].测控技术, 2003, 22(11):4-6.
[50]张宝珍. 21世纪的保障方案——JSF的自主式后勤[J].航空维修与工程, 2003(1):27-29.
[51]王萍.先进传感器技术在飞机故障诊断中的应用[J].测控技术, 2007, 26(3):27-29.
[52]张叔农,谢劲松,康锐.电子产品健康监控和故障预测技术框架[J].测控技术, 2007, 26(2):12-16,18.
[53]徐萍,康锐.预测与状态管理系统(PHM)技术研究[J].测控技术, 2004, 23(12):58-60.
[54]孙博,康锐,谢劲松.故障预测与健康管理系统研究和应用现状综述[J].系统工程与电子技术, 2007, 29(10):1762-1767.
[55]孙博,康锐,谢劲松. PHM系统中的传感器应用与数据传输技术[J].测控技术, 2007, 26(7):12-14.
[56]高占宝,梁旭,李行善.复杂系统综合健康管理[J].测控技术, 2005, 24(8):1-5.
[57]朱睿,刘槟.飞机健康管理数据挖掘方法研究[J].中国民航学院学报, 2004, 22(S1):150-153.
[58]姜永军.简论设备安全运行与维护维修智能管理系统[J].冶金设备, 2005(5):54-56.
[59]潘全文,李天,李行善.预测与健康管理系统体系结构研究[A]. Proceeding of第十七届全国测控计量仪器仪表学术年会(MCMI'2007)论文集(上册) [C].中国福建厦门. 2007:32-37.
[60]彭云. RLV健康管理方案及关键系统监控原理[D]. [硕士论文],西安:西北工业大学, 2005.
[61] Li C, Lei Y. Fault Diagnosis for an Aircraft Engine Based on Information Fusion [A]. Proceeding of Mechatronics, 2006 IEEE International Conference on [C]. IEEE, 2006:199-202.
[62]龙兵,孙振明,姜兴渭.航天器集成健康管理系统研究[J].航天控制, 2003(2):56-61.
[63]黄伟斌.发动机健康管理的自适应机载实时模型[D]. [硕士论文],南京:南京航空航天大学, 2007.
[64] Steed J. Life Management of Electrical Plant [A]. Proceeding of High Voltage Engineering and Testing, 2007 14th Institution of Engineering and Technology International School on [C]. IEEE, 2007:509-528.
[65] Taiariol F, Papuzza C, Cerioni S, et al. Environmental impact and end of life management of telephone exchange equipment [A]. Proceeding of the 1999 IEEE International Symposium on Electronics and the Environment, ISEE [C]. IEEE, 1999:64-69.
[66] Scott N D. A single integrated circuit approach to real capacity estimation and life management of VRLA batteries [A]. Proceeding of Twenty-Third International Telecommunications Energy Conference, 2001 INTELEC [C]. IEEE, 2001:307-312.
[67] Ito H, Sekito S, Miyaike K, et al. Turbo-generator life management and service technology [A]. Proceeding of IEEE International Electric Machines and Drives Conference, 2003 [C]. IEEE, 2003:403-410.
[68] Silva H a P, Bassi W, Diogo a C T. Noninvasive ageing assessment by means of polarization and depolarization currents analysis and its correlation with moisture content for power transformer life management [A]. Proceeding of Transmission and Distribution Conference and Exposition: Latin America, 2004 IEEE/PES [C]. IEEE, 2004:611-616.
[69] Picard H, Verstraten J, Hakkens M, et al. Decision model for End of Life management ofswitchgears [A]. Proceeding of 4th European Conference on Electrical and Instrumentation Applications in the Petroleum & Chemical Industry, 2007 PCIC Europe [C]. 2007:1-10.
[70] Paquet M, Gatlin P, Cote S M. Usage monitoring - A milestone in engine life management [A]. Proceeding of AIAA, SAE, ASME, and ASEE, Joint Propulsion Conference, 21st [C]. Monterey, CA; United States. AIAA, 1985:1-7.
[71] Hurry M F, Oconnor C M. United Kingdom military engine usage, condition and maintenance systems experience [A]. Proceeding of AIAA, SAE, and ASME 19th Joint Propulsion Conference [C]. Seattle, WA; United States. AIAA, 1983:1-9.
[72] Fraser K F. An Overview of Health and Usage Monitoring Systems (HUMS) for Military Helicopters [R]. ADA289903, 1994. 1-42.
[73] Pipe K. Measuring the Performance of a HUM System - the Features that Count [A]. Proceeding of Third International Conference on Health and Usage Monitoring - HUMS2003 [C]. DSTO Platforms Sciences Laboratory, Australia, 2003:5-15.
[74] Nozhnitsky Y A, Doulnev R A, Egorov I V, et al. Evolution of aviation engine life management in CIS [R]. Moscow, Russia: Central Institute of Aviation Motors, 2000. 1-25.
[75] NATO Research And Technology Orgnization. Recommended Practices for Monitoring Gas Turbine Engine Life Consumption (Practiques Recommandees pour le Controle du Vieillisement des Turbomoteurs) [R]. ADA380949, 2000.
[76] Vittal S, Hajela P, Joshi A. Review of Approaches to gas turbine life management [A]. Proceeding of 10th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference [C]. New York. 2004:1-11.
[77] Suarez E, Hansen J, Duffy M, et al. New Approach to Tracking Engine Life [A]. Proceeding of 33d AIAA/ASME/SAE/ASEE. Joint Propulsion Conference & Exhibition [C]. Seattle, WA. 1997:1-6.
[78] Davenport O B. Extending Aircraft Engine Lives [A]. Proceeding of Aging Mechanisms and Control. Symposium Part A -Developments in Computational Aero- and Hydro-Acoustics. Symposium Part B - Monitoring and Management of Gas Turbine Fleets for Extended Life and Reduced Costs [C]. Manchester, UK. 2001:1-6.
[79] Torre M. New ASME Turbine Conference Focuses on Aero Engine Life Management. [EB/OL]. http://www.asme.org/NewsPublicPolicy/PressReleases/New_Turbine_Conference.cfm. 2004-1-5/2008-5-8.
[80] Enright M P, Huyse L, Mcclung R C, et al. Probabilistic Methodology for Life Prediction ofAircraft Turbine Rotors [A]. Proceeding of Engineering, Construction, and Operations in Challenging Environments: Earth & Space 2004 [C]. Houston, TX. 2004:453-460.
[81] Jardine a K S, Anderson P M, Mann D S. Applications of the Weibull proportional hazards Model to Aircraft and Marine Engine Failure Data [J]. Quality & Reliability Engineering International, 1987, 3:77-82.
[82] Suarez E L, Duffy M I, Gamache R N, et al. Jet engine life prediction systems integrated with prognostics health management [A]. Proceeding of IEEE Aerospace Conference [C]. 2004:3596- 3602.
[83]王通北,陈美英.军用航空发动机的可靠性和寿命[J].航空发动机, 1994(1):36-47.
[84]张连祥.提高航空发动机可靠性的途径[J].航空发动机, 2002(2):17-21.
[85]张宝诚,刘孝安.航空发动机可靠性和经济性[M].北京:国防工业出版社, 1998.
[86]张逸民.航空涡轮发动机翻修寿命与可靠性分析[J].航空学报, 1981, 2(4):44-51.
[87]吴学亮,叶新农.军用航空发动机寿命控制方法[J].航空科学技术, 1996(5):19-22.
[88]洪杰,张大钧,韩继斌.航空发动机关键件使用寿命监视系统设计[J].北京航空航天大学学报, 2000, 26(1):45-48.
[89]赵福星.以耐久性与损伤容限为中心的现役发动机寿命控制方法[J].航空动力学报, 2001, 16(4):305-308.
[90]余建航,贺美云.直升机关键构件疲劳寿命监控中的核心技术[J].直升机技术, 2006(4):15-18.
[91]刘进成,冯金富,崔功.军用飞机机载设备日历时限控制[J].空军工程大学学报(自然科学版), 2002(1):22-25.
[92]李建国,叶新农,徐可君.涡扇发动机寿命管理研究[J].海军航空工程学院学报, 2005, 20(4):468-472.
[93]宋迎东,孙志刚.操作相关的发动机载荷谱模型与仿真研究[J].航空动力学报, 2003, 18(6):727-731.
[94]郝英.基于智能技术的民航发动机故障诊断和寿命预测研究[D]. [博士thesis],南京:南京航空航天大学, 2006.
[95]徐可君,江龙平.军用航空发动机可靠性和寿命管理[J].中国工程科学, 2003, 5(1):82-88.
[96]徐可君.基于单元体的军用航空发动机寿命控制和管理[J].海军航空工程学院学报, 2007, 22(5):541-547.
[97]莫布雷J.以可靠性为中心的维修[M].北京:机械工业出版社, 1995.
[98] Bengtsson M. Standardization Issues in Condition Based Maintenance [A]. Proceeding of the16th International Congress of Condition Monitoring and Diagnostic Engineering Management [C]. V?xj?, Sweden. 2003:1-10.
[99] Waeyenbergh G, Pintelon L. Maintenance concept development: A case study [J]. International Journal of Production Economics, 2004, 89(3):395-405.
[100] Barlow R, Hunter L. Optimum preventive maintenance policies [J]. Operations Research, 1960, 8(1):90-100.
[101] Ahlborg K, Crabbe S. On Condition maintenance programs [A]. Proceeding of the 1970 annual symposium on reliability [C]. Los Angeles, CA, USA. IEEE, 1970:300-307.
[102]诺兰F S,希普H F.以可靠性为中心的维修[M]. (刘云,王立群,等),北京:中国人民解放军空军第一研究所, 1982.
[103] Lapierre L R. TEMS/CEMS IV - An advanced on-condition maintenance concept undergoing evaluation on the A-10/GE TF34-100 [A]. Proceeding of AIAA, SAE, and ASME, 20th Joint Propulsion Conference [C]. Cincinnati, OH, Engl. New York, NY, USA: AIAA, 1984:1-14.
[104] Tomita N, Beldica C. On-condition maintenance of machinery based on vibration measurement and frequency analysis [J]. Buletinul Institutului Politehnic Bucuresti, Seria Mecanica, 1988, 50:97-100.
[105] Conroy G V, Black W J, O'hare G M P. Fault diagnosis and on condition maintenance of a combined heat and power unit [A]. Proceeding of IEE Colloquium on `Expert Systems for Fault Diagnosis in Engineering Applications' (Digest No.64) [C]. London, UK. IEE, 1989:1-5.
[106] Pellegrin C. Choice of a periodic on-condition maintenance policy [J]. International Journal of Production Research, 1992, 30(5):1153-1173.
[107] Finch D V. Management of 'on condition' aircraft maintenance [A]. Proceeding of International Air Safety Seminar [C]. Lisbon, Portug. Flight Safety Foundation Inc, Arlington, VA, USA, 1994:235.
[108] Williams G B, Hirani R S. Delay time multi-level on-condition preventive maintenance inspection model based on constant base interval risk - when inspection detects pending failure [J]. International Journal of Machine Tools & Manufacture, 1997, 37(6):823-836.
[109] Catelani M, Fort A, Grande V, et al. Automatic Fault Diagnosis System for a Gas Turbine using a Simulation before Test Approach [A]. Proceeding of Instrumentation and Measurement Technology Conference, 2006. IMTC 2006. Proceedings of the IEEE [C]. 2006:86-89.
[110] Baldin a E. Condition based maintenance: A powerful tool for modern plant management [J]. Terotechnica, 1979, 1(2):119-129.
[111] Baldin a E. Condition-based maintenance [J]. Chemical Engineering, 1981, 10(16):89-95.
[112] Jardine a K S, Lin D, Banjevic D. A review on machinery diagnostics and prognostics implementing condition-based maintenance [J]. Mechanical Systems and Signal Processing, 2006, 20(7):1483-1510.
[113] Mitchell J S. From Vibration Measurements to Condition Based Maintenance: Seventy Years of Continuous Progress [J]. Sound and Vibration, 2007, 41(1):62-78.
[114] Christer a H, Wang W, Sharp J M. A state space condition monitoring model for furnace erosion prediction and replacement [J]. European Journal of Operational Research, 1997, 101(1):1-14.
[115] Wang W. Subjective estimation of the delay time distribution in maintenance modeling [J]. European Journal of Operational Research, 1997, 99:516-529.
[116] Aven T. Condition based replacement policies-a counting process approach [J]. Reliability Engineering & System Safety, 1996, 51(3):275-281.
[117] Lam Y, Zhang Y L. A shock model for the maintenance problem of a repairable system [J]. Computers & Operations Research, 2004, 31(11):1807-1820.
[118] Ghasemi A, Yacout S, Ouali M S. Optimal condition based maintenance with imperfect information and the proportional hazards model [J]. International Journal of Production Research, 2007, 45(4):989-1012.
[119] Amari S V, Mclaughlin L, Hoang P. Cost-effective condition-based maintenance using markov decision processes [A]. Proceeding of Reliability and Maintainability Symposium, 2006 RAMS. Annual [C]. 2006:464-469.
[120] Lee K, Gao R X, Schneeman R. Sensor network and information interoperability integrating IEEE 1451 with MIMOSA and OSA-CBM [A]. Proceeding of Instrumentation and Measurement Technology Conference, 2002. IMTC/2002. Proceedings of the 19th IEEE [C]. 2002:1301-1305.
[121] Dod. Condition based maintenance Plus DoD Guidebook (Draft). [EB/OL]. http://www.acq.osd.mil/log/mrmp/cbm+/. 2007-10-19/2008-1-16.
[122]夏良胜,贾希胜. CBM应用现状分析. [EB/OL]. http://www.defence.org.cn/aspnet/ vip-usa/uploadfiles/2006-8/200681612505453.pdf. 2006-8-31/2007-12-4.
[123] Tsang a H C, Yeung W K, Jardine a K S, et al. Data management for CBM optimization [J]. Journal of Quality Maintenance Engineering, 2006, 12(1):37-51.
[124] Fan X F, Zuo M J. Gearbox fault detection using Hilbert and wavelet-packet transforms [J]. Mechanical Systems and Signal Processing, 2006, 20:966-982.
[125] Liu J, Djurdjanovic D, Ni J, et al. Similarity based method for manufacturing process performance prediction and diagnosis [J]. Computers in Industry, 2007, 58(6):558-566.
[126] Lee J, Ni J, Djurdjanovic D, et al. Intelligent prognostics tools and e-maintenance [J]. Computers in Industry, 2006, 57(6):476-489.
[127]贾希胜.以可靠性为中心的维修决策模型[M].北京:国防工业出版社, 2007.
[128]甘茂治,康建设,高崎.军用装备维修工程学[M].北京:国防工业出版社, 2005.
[129]陈学楚.现代维修理论[M].北京:国防工业出版社, 2003.
[130]于永利,郝建平,杜晓明,等.维修性工程理论与方法[M].北京:国防工业出版社, 2007.
[131]何光里.视情修理和汽车维修制度的改革[J].汽车技术, 1986(5):53-59.
[132]刘家声.汽车维修与使用管理手册[M].北京:中国林业出版社, 1990.
[133]江彦桥.船舶机械可靠性技术[M].上海:上海海运学院教材, 1990.
[134]武汉水利电力学院.电力生产现代技术水电厂近代技术[M].南京:河海大学出版社, 1990.
[135]谭中富,曾鸣,张福伟.关于设备视情维修最优策略的探讨[J].现代电力, 1997, 14(3):38-42.
[136]陈学楚.维修基础理论[M].北京:科学出版社, 1998.
[137]沈加元.以可靠性为中心的飞机维修理论[J].民航经济与技术, 1995(5):61-63.
[138]黄昭毅.从美国维修体制的变迁论我国加强预测维修工作的重要性[J].中国设备工程, 1994(11):41-43.
[139]范世东,余慧芳.关于船舶机械视情维修制度的认识[J].船海工程, 2001(5):37-39.
[140]梁工谦,陈翔宇.视情维修中的设备维修模式权衡分析[J].西北工业大学学报, 2005, 23(4):504-507.
[141]张秀斌,王广伟,郭波.应用比例故障率模型进行基于状态的视情维修决策[J].电子产品可靠性与环境试验, 2002(4):19-22.
[142]张秀斌,郭波,谭跃进.马尔可夫决策过程在视情维修中的应用[J].工业工程, 2002, 5(6):53-55.
[143]程志君,郭波.连续劣化系统的最佳检测与维修策略分析[J].系统工程与电子技术, 2008, 30(1):193-196.
[144]王政,朱晓军,杨铁军,等.视情维修检测间隔模糊预测研究[J].中国修船, 2006, 19(6):46-48.
[145]袁希昌.船舶机舱视情维修系统的技术基础与应用设计[D]. [硕士论文],大连:大连海事大学, 2006.
[146]左洪福,张海军,戎翔.基于比例风险模型的航空发动机视情维修决策[J].航空动力学报, 2006, 21(4):716-721.
[147]白芳,左洪福,文振华, et al.基于视情维修策略的航空发动机调度方法[J].交通运输工程学报, 2007, 7(3):29-33.
[148]王凌.维修决策模型和方法的理论与应用研究[D]. [博士论文],杭州:浙江大学, 2007.
[149]梁旭,李行善,张磊,等.支持视情维修的故障预测技术研究[J].测控技术, 2007, 26(6):5-9.
[150]曾昭翔,董世珩.机车柴油机工况的铁谱监测与状态维修[J].铁道学报, 1992, 14(1):111-113.
[151]严志军.机械设备状态维修最佳检测周期的仿真分析方法(续) [J].中国设备管理, 2001(3):9-10.
[152]严志军.机械设备状态维修最佳检测周期的仿真分析方法[J].中国设备管理, 2001(2):11-12.
[153]严立,朱新河,严志军, et al.面向21世纪的交通运输机械设备维修现状与展望[J].交通运输工程学报, 2001, 1(2):47-51.
[154]袁志坚.电力变压器状态维修决策方法的研究[D]. [博士论文],重庆:重庆大学, 2004.
[155]康建设,尹健,王希星. CBM系统与设备状态监测[J].仪器仪表学报, 2006, 27(S):1748-1751.
[156]胡静涛,徐皑冬,于海斌. CBM标准化研究现状及发展趋势[J].仪器仪表学报, 2007, 28(3):569-576.
[157]郭前进,于海斌,徐皑冬.基于状态维修的开放系统研究与实现[J].计算机集成制造系统, 2005, 11(3):416-421.
[158]代科学,李国辉,万歆睿.状态维修理论、技术与实施[J].航空制造技术, 2005(1):101-103, 105.
[159]张伟,康建设,温亮, et al.基于信息神经网络的状态维修[J].仪器仪表学报, 2005, 26(S):617-619.
[160]贾云献.基于多状态信息的CBM建模研究及原型软件开发[A].面向信息化的维修——中国兵工学会首届维修专业学术年会论文集[C].北京:解放军出版社, 2003:100-107.
[161]陈旭华,贾云献,殷苏东.基于状态的维修及其决策模型研究[J].军械工程学院学报, 2007, 19 (3):13-18.
[162]吕文元,朱清香,方淑芬.利用故障数据和估计的检查数据建立维修优化模型[J].数学的实践与认识, 2007, 37(10):83-89.
[163]方淑芬,吕文元.设备维修管理智能决策支持系统的研究[J].系统工程理论与实践, 2001(12):53-59.
[164]王英,王文彬,方淑芬, et al.状态维修两阶段预知模型研究[J].哈尔滨工程大学学报, 2007, 28(11):1278-1281.
[165]朱清香,于立华,方淑芬,等.预防维修优化模型及其在数控设备维修中的应用[J].机床与液压, 2008, 36(1):161-163.
[166]刘宝友,方攸同,魏金祥,等.状态维修机械设备的可靠性和检测更换策略[J].机械工程学报, 2006, 42(3):30-35.
[167]巨博,奚立峰.基于约束理论的智能维护模型及策略[J].上海交通大学学报, 2007, 41(9):1526-1528, 1532.
[168] Zhou X, Xi L, Lee J. Reliability-centered predictive maintenance scheduling for a continuously monitored system subject to degradation [J]. Reliability Engineering & System Safety, 2007, 92(4):530-534.
[169]曾鸣.状态维修技术在火电厂设备维修工作中的应用[J].中国电力, 1998, 31(5):66-68.
[170]江伟.电气设备状态维修策略研究[D]. [硕士论文],武汉:华中科技大学, 2006.
[171]尹茂峰.浅谈设备状态维修[J].设备管理与维修, 2005(3):8-9.
[172]周志敏.浅析状态维修与在线监测(下) [J].中国设备工程, 2002(5):42-43.
[173]周志敏.浅析状态维修与在线监测(上) [J].中国设备工程, 2002(4):37-38.
[174]柏林,秦树人,宝平.基于虚拟仪器的预测维修系统的研发[J].中国机械工程, 2003, 14(16):1400-1402.
[175] Liu B Y, Fang Y T, Wei J X, et al. Inspection-replacement policy of system under predictive maintenance [J]. Journal of Zhejiang University(Science A), 2007, 8(3):495-500.
[176]常士基.现代民用航空维修工程管理[M].太原:山西科学技术出版社, 2002.
[177]陈光.航空发动机设计手册第3册:可靠性与维修性[M].北京:航空工业出版社, 2000.
[178]孙春林,范作民.发动机故障诊断的主成分算法[J].航空学报, 1998, 19(3):342-245.
[179]尉询楷,陆波,汪诚,等.支持向量机在航空发动机故障诊断中的应用[J].航空动力学报, 2004, 19(6):844-848.
[180] Li Y G. Performance-analysis-based gas turbine diagnostics: a review [J]. Proceedings of the Institution of Mechanical Engineers - Part A: Journal Power and Energy, 2002, 216(5):363-377.
[181] Kennet D M. A Structural Model of Aircraft Engine Maintenance [J]. Journal of Applied Econometrics, 1994, 9(4):351-368.
[182] Hopp W J, Kuo Y L. Heuristics for multicomponent joint replacement: Applications to aircraftengine maintenance [J]. Naval Research Logistics, 1998, 45:435-458.
[183] Kumar U D, Crocker J, Knezevic J. Evolutionary maintenance for aircraft engines [A]. Proceeding of Annual Reliability and Maintainability Symposium [C]. Washington, DC, USA. 1999:62-68.
[184] Crocker J, Kumar U D. Age-related maintenance versus reliability centred maintenance: a case study on aero-engines [J]. Reliability Engineering & System Safety, 2000, 67(2):113-118.
[185]梁剑.基于成本优化的航空发动机视情维修决策研究[D]. [博士论文],南京:南京航空航天大学, 2005.
[186] Yan J, Lv M, Wang P, et al. Kalman Filter Based Neural Network Methodology for Predictive Maintenance: A Case Study on Steam Turbine Blade Performance Prognostics [A]. Proceeding of ASME Conference Proceedings [C]. ASME, 2006:271-276.
[187] Zhao Y J, Volovoi V, Waters M, et al. A Sequential Approach for Gas Turbine Power Plant Preventative Maintenance Scheduling [J]. Journal of Engineering for Gas Turbines and Power, 2006, 128(4):796-805.
[188] Rao P N S, Naikan V N A. An Optimal Maintenance Policy for Compressor of a Gas Turbine Power Plant [J]. Journal of Engineering for Gas Turbines and Power, 2008, 130(2):1-5.
[189] Turner K Y, Bajwa A. A survey of aircraft engine health monitoring systems, [A]. Proceeding of AIAA/ASME/SAE/ASEE Joint Propulsion Conference and Exhibit [C]. Los Angeles, California. 1999:1-9.
[190] Powrie H E, Fisher C E. Engine health monitoring: Towards total prognostics [A]. Proceeding of IEEE Aerospace Conference [C]. 1999:11-20.
[191]郝英,孙健国,白杰.航空燃气涡轮发动机气路故障诊断现状与展望[J].航空动力学报, 2003, 18(6):753-760.
[192]钟诗胜,栾圣罡.面向航空发动机全寿命周期管理的航线数据处理系统[J].计算机集成制造系统, 2006, 12(8):1273-1278.
[193] Byington C S, Roemer M J, Kacprzynski G J, et al. Prognostic enhancements to diagnostic systems for improved condition-based maintenance [A]. Proceeding of Aerospace Conference, 2002 IEEE [C]. IEEE, 2002:2815-2824.
[194] Swearingen K, Majkowski W, Bruggeman B, et al. An Open System Architecture for Condition Based Maintenance Overview [A]. Proceeding of Aerospace Conference, 2007 IEEE [C]. 2007:1-8.
[195] Engel S J, Gilmartin B J, Bongort K, et al. Prognostics, the real issues involved with predictingliferemaining [A]. Proceeding of Aerospace Conference Proceedings, 2000 IEEE [C]. Big Sky, MT, USA. IEEE, 2000:457-469.
[196] Wang H Z, Pham H. Reliability and Optimal Maintenance [M]. London: Springer, 2006.
[197] Moubray J.以可靠性为中心的维修[M]. (石磊,谷宁昌译),北京:机械工业出版社, 1995.
[198] Wang H. A survey of maintenance policies of deteriorating systems [J]. European Journal of Operational Research, 2002, 139(3):469-489.
[199] Aven T, Jensen U. Stochastic Models in Reliability [M]. Springer, 1998.
[200]王文义,张洪芬.维修策略的概念、方法和模型(I) [J].运筹与管理, 1997, 6(2):95-99.
[201]王文义,张洪芬.维修策略的概念、方法和模型(II) [J].运筹与管理, 1997, 6(2):100-103.
[202] Naeem M, Singh R, Probert D. Consequences of aero-engine deteriorations for military aircraft [J]. Applied Energy, 2001, 70(2):103-133.
[203] Weckman G R, Shell R L, Marvel J H. Modeling the reliability of repairable systems in the aviation industry [J]. Computers & Industrial Engineering, 2001, 40(1-2):51-63.
[204] Vlok P J. Dynamic residual life estimation of industrial equipment based on failure intensity proportions [D]. [PhD thesis], Pretoria, South Africa: University of Pretoria, 2001.
[205] Hokstad P. The failure intensity process and the formulation of reliability and maintenance models [J]. Reliability Engineering & System Safety, 1997, 58(1):69-82.
[206] Jiang S-T. Assessment of semi-parametric proportional intensity model applied to recurrent failure data with multiple failure types for repairable-system reliability [D]. [Ph.D thesis], Fayetteville, Arkansas, US: University of Arkansas, 2004.
[207] Jiang S-T, Landers T L, Rhoads T R. Assessment of repairable-system reliability using proportional intensity models: a review [J]. IEEE Transactions on Reliability, 2006, 55(2):328-336.
[208] Vlok P J, Wnek M, Zygmunt M. Utilising statistical residual life estimates of bearings to quantify the influence of preventive maintenance actions [J]. Mechanical Systems and Signal Processing, 2004, 18(4):833-847.
[209] Percy D F, Kobbacy K a H, Ascher H E. Using proportional-intensities models to schedule preventive-maintenance intervals [J]. IMA Journal of Mathematics Applied in Business and Industry, 1998, 9(3):289-302.
[210] Qureshi W M. Assessment of a proportional intensity model for repairable-system reliability [D]. [Ph.D thesis], Fayetteville, Arkansas, US: University of Arkansas, 1991.
[211] Kijima M. Some results for repairable systems with general repair [J]. Journal of Applied Probability, 1989, 26(1):89-102.
[212] Krivtsov V V. Recent advances in theory and applications of stochastic point process models in reliability engineering [J]. Reliability Engineering & System Safety, 2007, 92(5):549-551.
[213] Guo H, Liao H, Zhao W, et al. A New Stochastic Model for Systems Under General Repairs [J]. Reliability, IEEE Transactions on, 2007, 56(1):40-49.
[214] Zhang L, Li X S, Yu J S. A review of fault prognostics in condition based maintenance [A]. Fang J C, Wang Z Y (eds), Proceeding of Sixth International Symposium on Instrumentation and Control Technology: Signal Analysis, Measurement Theory, Photo-Electronic Technology, and Artificial Intelligence [C]. SPIE, 2006:1-6.
[215] Roemer M J, Byington C S, Kacprzynski G J, et al. An Overview of Selected Prognostic Technologies with Reference to an Integrated PHM Architecture [A]. Proceeding of the First International Forum on Integrated System Health Engineering and Management in Aerospace [C]. NASA, 2005:1-15.
[216]程侃.寿命分布类与可靠性数学理论[M].北京:科学出版社, 1999.
[217] Liao H T, Zhao W B, Guo H R. Predicting Remaining Useful Life of an Individual Unit Using Proportional Hazards Model and Logistic Regression Model [A]. Proceeding of RAMS '06. Annual Reliability and Maintainability Symposium [C]. IEEE, 2006:127-132.