城市轨道交通车辆走行部安全评估方法研究
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摘要
当前,大力发展城市轨道交通,建立“多层次、立体化的综合交通体系”已成为我国交通发展的主要方向。从1969年10月开始,经过40多年的发展,我国已经进入大规模城市轨道交通建设阶段。目前,已有10余个城市建成城市轨道交通线路,50余个城市制定并在实施城市轨道交通规划,规划里程超过7500公里。“十二五”期间,规划建设城市快速轨道交通项目总长度将达1700公里。
但是,在城市轨道交通快速发展的同时,安全形势却不容乐观——列车安全问题不断出现、事故常有发生,这些故障不但严重的影响到城轨车辆的行车安全,一旦引发事故将会带来巨大的人员伤亡和经济损失。城市轨道交通车辆安全运行的基础在于车辆的关键部件,而走行部更是重中之重。为提高城市轨道交通运营的安全性,本文在对走行部原理及数据分析基础上,对其安全评估展开以下研究：
1.系统地分析了影响城市轨道交通车辆走行部安全的人员及组织管理因素、环境因素、线路基础设施、走行部内部原因、维护检修及构建了由评估层次、方法体系、安全等级以及评估流程等方面构成的走行部安全评估体系结构。
2.建立了城市轨道交通车辆走行部的改进概率影响图模型,该方法提高了运算针对性和效率,取得良好的效果,针对分析结果反映出的问题对城市轨道交通公司的工作尤其是运营维护工作提出了合理化建议。
3.采用改进层次分析法分析轮对轴箱装置、构架、弹簧悬挂装置、中央牵引装置、基础制动装置、驱动装置及相互之间的重要度,采用模糊综合评价方法建立城市轨道交通车辆走行部综合安全评估模型进行评估。在改进层次分析法中,提出采用聚类分析采集模糊风险评价集中的风险隶属度矩阵。针对评估结果探讨了采用风险控制措施降低风险的方法。
4.提出了基于概率统计推理理论的双向安全评估方法并建立概率安全模型,并通过相应模型算法实现安全概率计算。该方法基于可靠性分析GO法计算分析过程中的状态流概率,对系统正向进行安全评估,逆向进行故障概率判断定位,实现运行系统-部件的综合概率安全评估。利用提出的方法对城市轨道交通车辆走行部进行了安全概率计算分析。
5.针对城市轨道交通车辆走行系统的特点,提出通过采用传感器获取在城市轨道交通车辆走行部的振动信号,利用小波分析法、快速傅里叶变换和神经网络结合对振动速度、加速度等信号进行特征提取的方法,经过实际验证效果显著。
At present, it becomes the main trend of transport development to vigorously develop urban rail transit and to establish a "multi-level, three-dimensional integrated transport system ". From October 1969, through 40 years, China has stepped onto the stage of large-scale urban rail transit construction. Currently, rail transit lines have been built in more than 10 cities. Urban rail transportation planning has been developed and under implementation in more than 50 cities with the planning mileage over 7500 km. In the " Twelfth Five-Year " period, the planning and construction of urban rail transit lines will reach the total length of 1,700 kilometers.
However, with the rapid development of urban rail transit, the situation of its safety needs more attention, because safety issues and accidents often occur. These failures will not only seriously affect the safety of urban rail traffic vehicles, but also soon lead to huge accident human and economic losses. Safety of urban rail transit vehicles is on the basis of key components of vehicles with running gear as the top priority. In order to improve the safety of urban rail transit operations, through historical data and structural principle analysis, this article takes the vehicle running gear as the research and safety assessment object and carries out the following research:
1.The paper systematic analyzes the safety influence parameters of urban rail transit including staff and management, environments, infrastructures, running gear internal factors and maintenance. Meanwhile, in this paper the author constructs the safety assessment architecture of running gear which includes assessment layers, assessment methodologies, assessment flow and safety levels.
2.Improved probabilistic influence diagram is applied to construct safety assessment model of urban rail transit vehicle running gear, which improved the targeting and efficiency of operations. This paper proposes reasonable proposals to urban rail companies especially the maintenance department according to the problems reflected in the analysis results.
3.Improved analytic hierarchy process (AHP) was implemented to analyze the importance of different parts of running gear. On this basis, it establishes the urban rail transit vehicles running gear fuzzy safety assessment model and gathers risk matrix of fuzzy risk assessment through clustering analysis in AHP. Finally, risk control methods are discussed to reduce risks of the assessment results.
4.It proposes a safety assessment method based on the theory of probability statistics reasoning, establishes probability safety model and calculated safety probability through the appropriate model algorithm, which is on the basis of state flow probability in the analysis process of reliability analysis Go methodology which can help judge and locate of inverse probability for system failure and realized a comprehensive probabilistic safety assessment of operational system-parts. And it calculates the safety probability analysis of urban rail transit vehicles running gear in the proposed method.
5.Aiming at the characteristics of urban rail transit vehicle running systems, it proposes to acquire vibration signals of urban rail transit vehicles running gear through the sensors, combines wavelet analysis with Fast Fourier Transform and neural network to analyze the vibration velocity or acceleration signals for feature extraction, realizes the purpose of safety assessment of running gear, and achieves remarkable results by actual tests.
但是,在城市轨道交通快速发展的同时,安全形势却不容乐观——列车安全问题不断出现、事故常有发生,这些故障不但严重的影响到城轨车辆的行车安全,一旦引发事故将会带来巨大的人员伤亡和经济损失。城市轨道交通车辆安全运行的基础在于车辆的关键部件,而走行部更是重中之重。为提高城市轨道交通运营的安全性,本文在对走行部原理及数据分析基础上,对其安全评估展开以下研究：
1.系统地分析了影响城市轨道交通车辆走行部安全的人员及组织管理因素、环境因素、线路基础设施、走行部内部原因、维护检修及构建了由评估层次、方法体系、安全等级以及评估流程等方面构成的走行部安全评估体系结构。
2.建立了城市轨道交通车辆走行部的改进概率影响图模型,该方法提高了运算针对性和效率,取得良好的效果,针对分析结果反映出的问题对城市轨道交通公司的工作尤其是运营维护工作提出了合理化建议。
3.采用改进层次分析法分析轮对轴箱装置、构架、弹簧悬挂装置、中央牵引装置、基础制动装置、驱动装置及相互之间的重要度,采用模糊综合评价方法建立城市轨道交通车辆走行部综合安全评估模型进行评估。在改进层次分析法中,提出采用聚类分析采集模糊风险评价集中的风险隶属度矩阵。针对评估结果探讨了采用风险控制措施降低风险的方法。
4.提出了基于概率统计推理理论的双向安全评估方法并建立概率安全模型,并通过相应模型算法实现安全概率计算。该方法基于可靠性分析GO法计算分析过程中的状态流概率,对系统正向进行安全评估,逆向进行故障概率判断定位,实现运行系统-部件的综合概率安全评估。利用提出的方法对城市轨道交通车辆走行部进行了安全概率计算分析。
5.针对城市轨道交通车辆走行系统的特点,提出通过采用传感器获取在城市轨道交通车辆走行部的振动信号,利用小波分析法、快速傅里叶变换和神经网络结合对振动速度、加速度等信号进行特征提取的方法,经过实际验证效果显著。
At present, it becomes the main trend of transport development to vigorously develop urban rail transit and to establish a "multi-level, three-dimensional integrated transport system ". From October 1969, through 40 years, China has stepped onto the stage of large-scale urban rail transit construction. Currently, rail transit lines have been built in more than 10 cities. Urban rail transportation planning has been developed and under implementation in more than 50 cities with the planning mileage over 7500 km. In the " Twelfth Five-Year " period, the planning and construction of urban rail transit lines will reach the total length of 1,700 kilometers.
However, with the rapid development of urban rail transit, the situation of its safety needs more attention, because safety issues and accidents often occur. These failures will not only seriously affect the safety of urban rail traffic vehicles, but also soon lead to huge accident human and economic losses. Safety of urban rail transit vehicles is on the basis of key components of vehicles with running gear as the top priority. In order to improve the safety of urban rail transit operations, through historical data and structural principle analysis, this article takes the vehicle running gear as the research and safety assessment object and carries out the following research:
1.The paper systematic analyzes the safety influence parameters of urban rail transit including staff and management, environments, infrastructures, running gear internal factors and maintenance. Meanwhile, in this paper the author constructs the safety assessment architecture of running gear which includes assessment layers, assessment methodologies, assessment flow and safety levels.
2.Improved probabilistic influence diagram is applied to construct safety assessment model of urban rail transit vehicle running gear, which improved the targeting and efficiency of operations. This paper proposes reasonable proposals to urban rail companies especially the maintenance department according to the problems reflected in the analysis results.
3.Improved analytic hierarchy process (AHP) was implemented to analyze the importance of different parts of running gear. On this basis, it establishes the urban rail transit vehicles running gear fuzzy safety assessment model and gathers risk matrix of fuzzy risk assessment through clustering analysis in AHP. Finally, risk control methods are discussed to reduce risks of the assessment results.
4.It proposes a safety assessment method based on the theory of probability statistics reasoning, establishes probability safety model and calculated safety probability through the appropriate model algorithm, which is on the basis of state flow probability in the analysis process of reliability analysis Go methodology which can help judge and locate of inverse probability for system failure and realized a comprehensive probabilistic safety assessment of operational system-parts. And it calculates the safety probability analysis of urban rail transit vehicles running gear in the proposed method.
5.Aiming at the characteristics of urban rail transit vehicle running systems, it proposes to acquire vibration signals of urban rail transit vehicles running gear through the sensors, combines wavelet analysis with Fast Fourier Transform and neural network to analyze the vibration velocity or acceleration signals for feature extraction, realizes the purpose of safety assessment of running gear, and achieves remarkable results by actual tests.
引文
[1]中国城市轨道交通年度报告课题组.中国城市轨道交通年度报告2009[M].北京：中国铁道出版社,2010.
[2]罗云,樊运晓,马晓春.风险分析与安全评价[M].北京：化学工业出版社,2004.
[3]张振淼主编.城市轨道交通车辆[M].中国铁道出版社,1998.
[4]张曙光.高速铁路系统生命周期安全评估体系的研究[J].铁道学报,2007,2(4)：20-26.
[5]J.Braband. "A proposal for common safety methods and risk assessment in European Railways", Signal + Draht,2007, (4):34-37.
[6]CENELEC. "Railway Applications -The specification and demonstration of reliability, availability, maintainability and safety (RAMS). Guide to the application of EN 50126-1 for safety, Technical Report", European Committee fior Elect rotechnical Standardization, TR 50126-2, (2007).
[7]CENELEC. "Railway Applications Communication, signaling and processing systems Safety related electronic systems for signaling", European Committee for Electro-technical Standardization, EN 50129, (2003).
[8]CENELEC. "Railway Applications -The specification and demonstration of reliability, availability, maintainability and safety (RAMS)", European Committee for Electrotechnical Standardization, EN 50126, (2000).
[9]IEC. "Functional safety of electrical/electronic/programmable electronic safety related systems -Part 4:Definitions and abbreviations", International Electrotechnical Commission (IEC),61508-4,(1998).
[10]IEC. "Functional safety of electrical/electronic/programmable electronic safety related systems -Part 5:Examples of methods for the determination of safety integrity levels", International Electrotechnical Commission (IEC),61508-5, (1998).
[11]S-L.Kurz, B.Milius. NEGLIGIBLE RISK FOR EUROPEAN RAILWAY RISK ASSESSMENTS[J].20-25.
[12]Sock-Yong Phang. Urban rail transit PPPs:Survey and risk assessment of recent strategies[J]. Transport Policy 14 (2007) 214-231.
[13]John R, Wilson, Beverley J. Norris. Rail human factors:Past, present and future[J]. Applied Ergonomics,36(2005) 649-660.
[14]Mark Hartonga, Rajni Goelb, Duminda Wijesekerac.Security and the US rail infrastructure[J]. INTERNATIONAL JOURNAL OF CRITICAL INFRASTRUCTURE PROTECTION 1 (2008):15-28.
[15]Uwe Hoppmann, Stefan Koenig, Thorsten Tielkes, Gerd Matschke.A short-term strong wind prediction model for railway application:design and verification[J]. Journal of Wind Engineering and Industrial Aerodynamics,2002, (90):1127-1134.
[16]A. Carrarini.Reliability based analysis of the crosswind stability of railway vehicles[J]. Journal of Wind Engineering and Industrial Aerodynamics 95 (2007) 493-509.
[17]Chunsheng Wang, Airong Chen, Weizhen Chen, Jianguo Nie.Safety assessment of existing riveted railway bridges[J]. Proceedings of the Fourth International Conference on Advances in Steel Structures, (2005):1651-1656.
[18]D. Diamantidis, F. Zuccarell, A. Westha'user.Safety of long railway tunnels[J]. Reliability Engineering and System Safety,2000 (67):135-145.
[19]Theodore S. Glickman, Erhan Erkut. Assessment of hazardous material risks for rail yard safety[J], Safety Science,2007 (45):813-822.
[20]M. Luke, I. Varfolomeev, K. Lutkepohl, A. Esderts. Fracture mechanics assessment of railway axles:Experimental characterization and computation[J].Engineering Failure Analysis,2010 (17):617-623.
[21]Robin Clark. Rail flaw detection:overview and needs for future developments[J]. NDT&E International,37(2004)111-118.
[22]CENEL EC. EN50126 Railway applications 2:Specification and demonst ration of reliability, availability, maintainability and safety (RAMS) [S]. London:British Standards Institution,1999:30269.
[23]高爽.地铁车辆构造与维修管理[M].北京：中国铁道出版社,2003.
[24]赵洪伦.轨道乍辆结构与设计[M].北京：中国铁道出版社,2009.
[25]王伯铭.城市轨道交通车辆工程[M].成都：西南交通大学出版社,2007.
[26]薛立民.铁路基础设施自然灾害风险估测与对策[D].北京：北京交通大学,2003.
[27]周刘刚,王海祥.城市城市轨道交通及地下工程施工环境安全风险评估与控制[J].铁道勘察,2007(6)：91-94.
[28]陈志业.既有铁路地质灾害风险评估与对策研究[D].北京：北京交通大学,2006.
[29]张迎春.铁路泥石流灾害风险评价与防治研究[D].北京：北京交通大学,2007.
[30]董亚男.高速列车在侧风环境中会车的空气动力特性模拟研究.北京：北京交通大学,2008.
[31]邱英政.高速列车交会压力波数值模拟计算与测试研究[D].北京：北京交通大学2007.
[32]贾玉泉.基于模糊穴映射的轨道动态安全评估方法及其应用研究[D].北京：北京交通大学,2008.
[33]宋晓梅.铁路线路安全评价方法的研究与应用[D].北京：北京交通大学,2003.
[34]刘永前.大型桥梁结构健康监测技术研究与应用[D].北京：北京交通大学,2007.
[35]张勇,曾凡勤,刘建磊.某准高速铁路大桥的运营安全评估[J].铁道建筑,2009(3)：15-19.
[36]肖女娥.风险评估技术在铁路信号系统中的研究与应用[D].成都：西南交通大学,2009.
[37]干菲等.高速铁路信号系统的安全评估研究[J].中国铁路,2009(2)：22-24.
[38]唐涛,燕飞,郜春海.轨道交通信号系统安全评估与认证体系研究[J].都市快轨交通,2004,17(1)：28-32
[39]李兵.城市轨道交通车站施工风险管理研究[D].北京：北京交通大学,2007.
[40]陈神龙等.基于模糊综合评判的城市轨道交通车站施工风险评估[J].地下空间与工程学报,2006,2(1)：32-35.
[41]孙河川.城市轨道交通浅埋暗挖车站设计安全风险分析[D].北京：北京交通大学,2006.
[42]周红波,姚浩,卢剑华.上海某轨道交通深基坑工程施工风险评估[J].岩土工程学报,2006,28(11)：1902-1906.
[43]贾俊峰.城市轨道交通土建工程施工安全风险管理研究[D].北京：北京交通大学,2006.
[44]王芬.铁路工程施工现场安全评价研究[D].北京：北京交通大学,2003.
[45]滕红军.城市隧道穿越地面建筑物的安全风险控制[D].北京：北京交通大学,2007.
[46]贾永刚.北京城市轨道交通5号线下穿既有区间结构的安全评估[J].都市快轨交通.2006(10)：62-65.
[47]姚宣德,王梦恕.地下工程风险评估准则分析与研究[J].中国工程科学,2009(5)：86-90.
[48]姚宣德,王梦恕.对城市轨道交通工程风险评估体系框架的研究[J].中国安全科学学报,2005(8)：88-92.
[49]李铭辉.我国城市轨道交通运营安全评价体系研究[D].北京：北京交通大学,2007.
[50]林楠,黄宏伟.城市轨道交通结构安全评估指标体系的初步研究[J].现代隧道技术,2008(增)：82-85.
[51]张明春.铁路超限货物运输安全评价研究[D].北京：北京交通大学,2009.
[52]刘敏.铁路运输安全信息管理及辅助决策系统研究[D].北京：北京交通大学,2006.
[53]胡里根.铁路车务站段安全管理水平评价方法及应用研究[D].北京：北京交通大学,2005.
[54]刘建磊,王石磊,高岩.准高速铁路4m框架涵的运营安全评估[J].铁道建筑,2009(3)：4-7.
[55]Hiroaki ISHIDA,等(日).铁道车辆脱轨评估的安全标准[J].国外铁道车辆,2000,37(4)：37-43.
[56]付新生.城轨车辆运营技术故障风险综合评价方法的研究[D].北京：北京交通大学,2007.
[57]李静.车辆运行状态安全评估方法与应用研究[D].北京：北京交通大学,2008.
[58]张强.货车转向架零部件的故障规律分析及预测[D].北京：北京交通大学,2006.
[59]李旭伟.微型测振记录仪在高速机车车辆安全监测中的应用[D].北京：北京交通大学,2004.
[60]付月辉.列车运行设备安全评估的检测系统[D].北京：北京交通大学,2008.
[61]王令朝.中国铁路引入安全评估标准的探讨[J].铁路技术监督,2007,35(6)：4-7.
[62]Elms D. Rail safety[J]. Reliability Engineering and System Safety,2001,74:291～297.
[63]方鸣,陈建国,刘潍青.IEC 61508标准指导城市轨道交通设备安全功能指标实施[J].中国安全生产科学技术,2010,6(1)：158-161.
[64]田琦.项目融资风险及基于影响图的风险评估[D].成都：西南财经大学,2005.
[65]高继红.基于模糊影响图理论的房地产估价方法研究[D].大连：大连里理工大学,2005.
[66]龚莲花.基于模糊影响图的基础设施项目融资风险研究[D].武汉：武汉理工大学,2006.
[67]王颖.DF8B型机车走行部齿轮惯性故障的诊断[J].铁道机车车辆工人,2010：29-32.
[68]刘易平,黄采伦.基于小波变换的列车走行部故障诊断[J].湘潭师范学院学报(自然科学版),2005,27(3)：91-93.
[69]朱建明.机车走行部动态故障非接触式自动诊断系统的研究[J].机车电传,1999(10)：19-21.
[70]王连森.机车走行部运行可靠性研究[J].内燃机车.2010(1)：8-11.
[71]肖楠,谢基龙,周素霞.城市轨道交通车轮踏面制动疲劳强度评价方法及应用[J].工程力学,2007,27(9)：234-239.
[72]曾全君.地铁车辆车轮寿命分析[J].电力机车与城轨车辆.2005,28(2)：47-49.
[73]汪洋.地铁列车车轮踏面环状剥离的分析[J].电力机车与城轨车辆.2003,26(4)：67-68.
[74]邓民刚,孙纲.地铁车辆车轮异常磨耗测试分析[J].现代城市轨道交通,2009,1：19-22.
[75]吴宗之,高进东,魏利军.危险评价方法及其应用[M].北京：冶金工业出版社.2001.
[76]巴春喜.铁路机车轴箱轴承的失效分析[J].铁道机车车辆.2003,23(2)：35-36.
[77]曹永昌,马朝勇,王丽.机车走行部轴承的故障诊断分析及处理措施[J].内燃机车.2004(2)：24-27
[78]廖太平.侧架B部裂纹的形成原因及防止措施[J].机车车辆工艺.2000,(2)：35-36
[79]张涛,谢新民.侧架立柱磨耗板裂纹的原因分析及改进建议[J].铁道车辆.2007,45(1)：43.
[80]梁贤清.转8G型转向架侧架与支撑座组焊裂纹的原因与对策[J].铁道车辆.2003,41(8)：20-21.
[81]沈培德.地铁Duewag转向架裂纹分析及其改进[J].电力机车与城轨车辆.2003,26(4)：12-16.
[82]何有志.关于机车牵引齿轮可靠性的几个问题[J].机车车辆工艺.2000,(8)：1-4.
[83]靳伍银,侯运丰,龚俊.机乍用齿轮断裂失效分析[J].甘肃工业大学学报.2000,326(1)：41-44.
[84]陈立民,宋勇.DF_(4B)型机车齿轮箱故障原因分析及解决措施[J].内燃机车.2006,384(2)：44-45.
[85]董锡明.机车车辆运用可靠性工程[M].北京：中国铁道出版社,2002.
[86]E. Parent de Curzon and B. Beguet.Study into sources of wagon noise:Measurement of sound energy generated by vehicle bodies and running gear. Journal of Sound and Vibration. 1988,120(2):311-320.
[87]Ishizuka, Hiromichi. Probability of improvement in routine inspection work of Shinkansen vehicle axle. Quarterly Report of RTRI.1999,40(2):70-73.
[88]Zobory. Prediction of wheel/rail profile wear. Vehicle System Dynamics.1997,28(2-3): 221-259.
[89]孙苑,李熙.基于MVB总线的机车安全监测系统设计[J].铁路计算机应用,2007(4)：20-22.
[90]邓琼.安全系统工程[M].西安：西北工业大学出版社,2009.
[91]范维澄,孙金华,陆守香.火灾风险评估方法学[M].北京：科学出版社,2006.
[92]詹原瑞.影响图理论方法与应用[M].天津：天津大学出版社,1995.
[93]樊红,冯恩德.概率影响图在船舶综合安全评估中的应用[J].船海工程,2004,162(5)：3-5.
[94]李爱梅.影响图的数据结构研究[J].江南学院学报,2000,15(4)：3-6.
[95]钟麟,佟明安,钟卫,张圣云.基于多级影响图的空战连续机动决策[J].系统仿真学报2007,19(2)：410-411.
[96]李文生,秦翔宇.基于模糊影响图方法的库存弹药事故概率分析[J].中国安全科学学报.2009,19(11)：62-69.
[97]赵新,李群,朱一凡.动态随机影响图建模方法[J].计算机科学.2010,37(8)：182-193.
[98]Diehl M, Haimes Y Y.Influence Diagrams with Multiple Objectives and Tradeoff Analysis[J].IEEE Transactions on Systems, Man and Cybernetics-PartA:Systems and Humans(S1083-4427),2004,24(3):293-304.
[99]Charnes J, Shenoy P P. Multi-stage Monte Carlo Method for Solving Influence Diagrams Using Local Computation[J]. Management Science,2004,50(3):405-418.
[100]Cano A, Gomez M, Moral S. A Forward-backward Monte Carlo Method for Solving Influence Diagrams[J].International Journal of Approximate Reasoning,2006,42:119-135.
[101]D. E. Embrey.Incorporating management and organisational factors into probabilistic safety assessment[J]Reliability Engineering & System Safety,1992,38(1-2):199-208.
[102]肖晓春.基于模型的网络安全风险评估的研究[D].上海：复旦大学,2008.
[103]赵冬梅.信息安全风险评估量化方法研究[D].西安：西安电子科技大学,2007.
[104]周忠宝.基于贝叶斯网络的概率安全评估方法及应用研究[D].合肥：国防科学技术大学,2006.
[105]Hassan Y, Gibreel G. Evaluations of Highway Consistency and Safety:Practical Application [J]. Journal of Transportation Engineering,2000,23 (3):255-260.
[106]Stuaxt R N. Conformity assessment of safety related systems to IEC61508-the CASS initiative. Computing &Control Engineering Journal,2000(2):33-39.
[107]Rail track on behalf of the UK rail industry. Engineering safety management Issue 3 Yellow book3.2001.
[108]杜栋,庞庆华.现代综合评价方法与案例精选[M].北京：清华大学出版社,2006.
[109]张跃等.模糊数学方法及应用[M].北京：煤炭工业出版社,1992.
[110]王巨川等.多指标综合评判[J].昆明理工大学学报,1998,23(4)：69-71.
[111]关晓光,葛志杰.质量经济效益的模糊综合评价[J].管理工程学报,2000,14(4)：65-69.
[112]黄小青.模糊综合评判方法在物流中心选址中的应用[J].水运管理,2002,(12)：7-10.
[113]韩超群.企业技术创新能力的模糊综合评价模型研究[J].沈阳工业学院学报,2003,22(3)：88-90.
[114]沈祖培,黄祥瑞.GO法原理及应用—一种系统可靠性分析方法[M].北京：清华大学出版社,2004.
[115]Li Xi, Zhu Xiaoning. A Novel Fault Diagnosis Expert System Knowledge Acquisition Method of Metro Vehicle Equipments. ICCAE 2010,2010, (2):535-539.
[116]Williams RL, Gateley WY. U se of GO methodology to directly generate minimal cut set [A].Fussell IB. Nuclear System Reliability Engineering and Risk Assessment [C].Pennsylvania:Society for Industrial and Applied Mathematics,1977.
[117]沈祖培,黄祥瑞,高佳.可修系统可靠性分析中GO法的应用[J].核动力工程,2000,21(5)：456-461.
[118]沈祖培,郑涛.复杂系统可靠性的GO法精确算法[J].清华大学学报(自然科学版),2002,42(5)：569-572.
[119]SHEN Zupei, GAO Jia, HUANG Xiangrui. A new quantification algorithm for the GO methodology[J]. Reliability Engineering and System Safety,2000,67 (3):241-247.
[120]沈祖培,高佳.GO法原理和改进的定量分析方法[J].清华大学学报(自然科学版),1999,39(6)：15-19.
[121]黄采伦,樊晓平,陈特放.列车故障在线诊断技术及应用[M].北京：国防工业出版社,2006.
[122]谭富强.城市轨道功车动力系统状态随车检测平台的研究[D].南京：南京理工大学,2004.
[123]钟秉林,黄仁.机械故障诊断学[M].北京：机械工业出版社,2006.
[124]梅宏斌,滚动轴承振动监测与诊断[M].北京：机械工业出版社1996.
[125]韩捷,张瑞林.旋转机械故障机理及诊断技术[M].北京：机械工业出版社,1997.
[126]管辉.基于小波分析的滚动轴承故障诊断方法研究[D].太原：太原科技大学,2008.
[127]Vas, P:Parameter Estimation, Condition Monitoring, and Diagnosis of Electrical Machines. Clarendron Press, Oxford,1993.
[128]Masoud Haji, Hamid, A, Toliyat, Patern Recognition-A Technique for Induction Machines Rotor Fault Detection Eccentricity and Broken Bar Fault. Conference Record of the 2001 IEEE Industry Applications Conference,2001,30(3):1572-1578.
[129]Nandi, S, Toliyat, H A, Condition Monitoring and Fault Diagnosis of Electrical Machines-A Review. IEEE Industry Applications Conference,1999,1(1):197-204.
[130]Penman, J, Sedding, H.G, Lloyd, B.A, Fink, W.T, Detection and Location of Interturn Short Circuits in the Stator Windings of Operating Motors. IEEE Trans. Energy Conv,1996,4(9).
[131]Yazici, B, Kliman, G. B, An Adaptive Statistical Time-Frequency Method for Detection of Broken Bars and Bearing Faults in Motors Using Stator Current. IEEE Trans. On Industry Appl.,1999,2(35).
[132]Abbaszadeh, K, Milimonfared, J, Haji, M, Toliyat, H A, Broken Bar Detection In Induction Motor via Wavelet Transformation. IECON'01:The 27th Annual Conference of the IEEE Industrial Electronics Society 2001.
[133]Willsky, A, A Survey of Design Method for Failure Detection in Dynamic Systems. Automatica,1976,12(1).
[134]Isennann, R, Fault Diagnosis of Machines via Parameter Estimation and Knowledge Processing-Tutorial Paper. Automatica,1993,4(29).
[135]曾芸.基于小波分析的滚动轴承故障诊断方法研究[D].南昌：南昌大学,2007.
[136]Jia Ruijuan, Xu Chunxia, Mechanical Fault Diagnosis and Signal Feature Extraction Based on Fuzzy Neural Network[J]. Chinese Control Conference, (2008):234-237.
[137]唐秋杭.嵌入式轴承故障诊断算法的研究[D].浙江：浙江大学,2006.
[138]梅宏斌.滚动轴承若干故障的诊断与分析[M].电力机车与城市车辆,2005.
[139]Nikolaou N G, Antoniadis I A. Rolling Element Bearing Fault Diagnosis Using Wavelet Packets [J]. NDT & E International,2002,35 (3):197-205.
[140]Guo Qianjin, Yu Hai-bin, Xu Aidong. Modified Moret Wavelet Neural Networks for Fault Detection[J].International Conference on Control and Automation, (2005):1209-1214.
[141]Faa-Jeng Lin, Hsin-Jang Shieh, Po-Kai Huang. Adaptive Wavelet Neural Network Control With Hysteresis Estimation for Piezo-Positioning Mechanism[J]. IEEE Transactions on Neural Networks,2006,17(2):432-444.
[142]Huang N E, Shen S P, Eds. Hilbert-Huang Transform and Its Applications. Singapore: World Scientific,2005.
[143]Pang Peilin, Ding Guangbin. Wavelet-based Diagnostic Model for Rotating Machinery Subject to Vibration Monitoring. Proceedings of the 27th Chinese Control Conference, (2008):303-306.
[144]Cincotti G, Loi G, Pappalardo D. Frequency decomposition and compounding of ultrasound medical images with wavelet packet. IEEE Trans.On medical image,2001,20(8):764-771.
[145]Liu Hongmei, Wang Shaoping, Ouyang Pingchao. Fault Diagnosis Based on Improved Elman Neural Network for a Hydraulic Servo System. Northern Jiaotong University, 2009.
[146]金向阳,张莉,于广滨.基于改进小波神经网络的航空滚动轴承的故障检测[J].中国控制会议,(2007)：525-529.
[147]German Ramos, Jose J.Lopez, Basilio Pueo. Cascaded warped-FIR and FIR filter structure for loudspeaker equalization with low computational cost requirements. Digital Signal Processing,2009(19):393-409.
[148]冯象初,甘小冰,宋国乡.数值泛函与小波理论[M].西安：西安电子科技大学出版社,2003.
[149]王本永,郭仁宁,李文生.基于小波包分析和BP网络识别的齿轮故障诊断[J].辽宁工程技术大学学报,2002,21(5)：659-660.
[150]Grossman A. Wavelet transform and edge detection. Stochastic Processes in Physics and Engineering, Dodrecht Redial,1986.
[151]崔宝珍,潘宏伙.小波分析在滚动轴承故障诊断中的应用[J].科技情报开发与经济,2005,15(2)：176-178.
[152]汪庆年,黄建红,武和雷.小波变换及其在滚动轴承故障诊断中的应用[J].南昌大学学报,2005,27(1)：77-80.
[153]刘乐平,林凤涛.基于小波包特征向量与神经网络的滚动轴承故障诊断[J].轴承,2008,(4)：659-660.
[154]郭计云.基于小波分析的滚动轴承故障诊断方法研究[D].太原：中北大学,2007.
[155]唐贵基,范德功,胡爱军等.基于小波包能量特征向量神经网络的旋转机械故障诊断[J].汽轮机技术,2006,48(3)：215-217.
[156]马拉特,信号处理的小波导引[M].北京：机械工业出版社,2002.
[157]张德丰,MATLAB神经网络应用设计[M].北京：机械工业出版社,2009.
[158]骆江锋,龙江启,范进桢.小波包和BP神经网络在齿轮故障诊断中的应用[J].机械传动,2007,31(3)：84-86.
[159]李运红,张勇涛,裴未迟.基于小波包-Elman神经网络的电机轴承故障诊断[J].河北理工大学学报,2008,30(4)：81-85.
[160]朱树先,张仁杰.BP和RBF神经网络在人脸识别中的比较[J].仪器仪表学报,2007,28(2)：375-379.
[161]王琳,滕少华,伍乃骐.基于ART2-PNN神经网络的网络入侵检测方法[J].计算机应用与软件,2007,24(12)：41-43.
[162]刘力,周建中等.基于信息熵的改进模糊综合评价方法[J].计算机工程,2009,35(18)：4-6.
[163]金菊良,魏一鸣,丁晶.基于改进层次分析法的模糊综合评价模型[J].水力学报.2004(3)：65-69
[164]金龙哲,宋存义.安全科学原理[M].北京：化学工业出版社,2004.
[2]罗云,樊运晓,马晓春.风险分析与安全评价[M].北京：化学工业出版社,2004.
[3]张振淼主编.城市轨道交通车辆[M].中国铁道出版社,1998.
[4]张曙光.高速铁路系统生命周期安全评估体系的研究[J].铁道学报,2007,2(4)：20-26.
[5]J.Braband. "A proposal for common safety methods and risk assessment in European Railways", Signal + Draht,2007, (4):34-37.
[6]CENELEC. "Railway Applications -The specification and demonstration of reliability, availability, maintainability and safety (RAMS). Guide to the application of EN 50126-1 for safety, Technical Report", European Committee fior Elect rotechnical Standardization, TR 50126-2, (2007).
[7]CENELEC. "Railway Applications Communication, signaling and processing systems Safety related electronic systems for signaling", European Committee for Electro-technical Standardization, EN 50129, (2003).
[8]CENELEC. "Railway Applications -The specification and demonstration of reliability, availability, maintainability and safety (RAMS)", European Committee for Electrotechnical Standardization, EN 50126, (2000).
[9]IEC. "Functional safety of electrical/electronic/programmable electronic safety related systems -Part 4:Definitions and abbreviations", International Electrotechnical Commission (IEC),61508-4,(1998).
[10]IEC. "Functional safety of electrical/electronic/programmable electronic safety related systems -Part 5:Examples of methods for the determination of safety integrity levels", International Electrotechnical Commission (IEC),61508-5, (1998).
[11]S-L.Kurz, B.Milius. NEGLIGIBLE RISK FOR EUROPEAN RAILWAY RISK ASSESSMENTS[J].20-25.
[12]Sock-Yong Phang. Urban rail transit PPPs:Survey and risk assessment of recent strategies[J]. Transport Policy 14 (2007) 214-231.
[13]John R, Wilson, Beverley J. Norris. Rail human factors:Past, present and future[J]. Applied Ergonomics,36(2005) 649-660.
[14]Mark Hartonga, Rajni Goelb, Duminda Wijesekerac.Security and the US rail infrastructure[J]. INTERNATIONAL JOURNAL OF CRITICAL INFRASTRUCTURE PROTECTION 1 (2008):15-28.
[15]Uwe Hoppmann, Stefan Koenig, Thorsten Tielkes, Gerd Matschke.A short-term strong wind prediction model for railway application:design and verification[J]. Journal of Wind Engineering and Industrial Aerodynamics,2002, (90):1127-1134.
[16]A. Carrarini.Reliability based analysis of the crosswind stability of railway vehicles[J]. Journal of Wind Engineering and Industrial Aerodynamics 95 (2007) 493-509.
[17]Chunsheng Wang, Airong Chen, Weizhen Chen, Jianguo Nie.Safety assessment of existing riveted railway bridges[J]. Proceedings of the Fourth International Conference on Advances in Steel Structures, (2005):1651-1656.
[18]D. Diamantidis, F. Zuccarell, A. Westha'user.Safety of long railway tunnels[J]. Reliability Engineering and System Safety,2000 (67):135-145.
[19]Theodore S. Glickman, Erhan Erkut. Assessment of hazardous material risks for rail yard safety[J], Safety Science,2007 (45):813-822.
[20]M. Luke, I. Varfolomeev, K. Lutkepohl, A. Esderts. Fracture mechanics assessment of railway axles:Experimental characterization and computation[J].Engineering Failure Analysis,2010 (17):617-623.
[21]Robin Clark. Rail flaw detection:overview and needs for future developments[J]. NDT&E International,37(2004)111-118.
[22]CENEL EC. EN50126 Railway applications 2:Specification and demonst ration of reliability, availability, maintainability and safety (RAMS) [S]. London:British Standards Institution,1999:30269.
[23]高爽.地铁车辆构造与维修管理[M].北京：中国铁道出版社,2003.
[24]赵洪伦.轨道乍辆结构与设计[M].北京：中国铁道出版社,2009.
[25]王伯铭.城市轨道交通车辆工程[M].成都：西南交通大学出版社,2007.
[26]薛立民.铁路基础设施自然灾害风险估测与对策[D].北京：北京交通大学,2003.
[27]周刘刚,王海祥.城市城市轨道交通及地下工程施工环境安全风险评估与控制[J].铁道勘察,2007(6)：91-94.
[28]陈志业.既有铁路地质灾害风险评估与对策研究[D].北京：北京交通大学,2006.
[29]张迎春.铁路泥石流灾害风险评价与防治研究[D].北京：北京交通大学,2007.
[30]董亚男.高速列车在侧风环境中会车的空气动力特性模拟研究.北京：北京交通大学,2008.
[31]邱英政.高速列车交会压力波数值模拟计算与测试研究[D].北京：北京交通大学2007.
[32]贾玉泉.基于模糊穴映射的轨道动态安全评估方法及其应用研究[D].北京：北京交通大学,2008.
[33]宋晓梅.铁路线路安全评价方法的研究与应用[D].北京：北京交通大学,2003.
[34]刘永前.大型桥梁结构健康监测技术研究与应用[D].北京：北京交通大学,2007.
[35]张勇,曾凡勤,刘建磊.某准高速铁路大桥的运营安全评估[J].铁道建筑,2009(3)：15-19.
[36]肖女娥.风险评估技术在铁路信号系统中的研究与应用[D].成都：西南交通大学,2009.
[37]干菲等.高速铁路信号系统的安全评估研究[J].中国铁路,2009(2)：22-24.
[38]唐涛,燕飞,郜春海.轨道交通信号系统安全评估与认证体系研究[J].都市快轨交通,2004,17(1)：28-32
[39]李兵.城市轨道交通车站施工风险管理研究[D].北京：北京交通大学,2007.
[40]陈神龙等.基于模糊综合评判的城市轨道交通车站施工风险评估[J].地下空间与工程学报,2006,2(1)：32-35.
[41]孙河川.城市轨道交通浅埋暗挖车站设计安全风险分析[D].北京：北京交通大学,2006.
[42]周红波,姚浩,卢剑华.上海某轨道交通深基坑工程施工风险评估[J].岩土工程学报,2006,28(11)：1902-1906.
[43]贾俊峰.城市轨道交通土建工程施工安全风险管理研究[D].北京：北京交通大学,2006.
[44]王芬.铁路工程施工现场安全评价研究[D].北京：北京交通大学,2003.
[45]滕红军.城市隧道穿越地面建筑物的安全风险控制[D].北京：北京交通大学,2007.
[46]贾永刚.北京城市轨道交通5号线下穿既有区间结构的安全评估[J].都市快轨交通.2006(10)：62-65.
[47]姚宣德,王梦恕.地下工程风险评估准则分析与研究[J].中国工程科学,2009(5)：86-90.
[48]姚宣德,王梦恕.对城市轨道交通工程风险评估体系框架的研究[J].中国安全科学学报,2005(8)：88-92.
[49]李铭辉.我国城市轨道交通运营安全评价体系研究[D].北京：北京交通大学,2007.
[50]林楠,黄宏伟.城市轨道交通结构安全评估指标体系的初步研究[J].现代隧道技术,2008(增)：82-85.
[51]张明春.铁路超限货物运输安全评价研究[D].北京：北京交通大学,2009.
[52]刘敏.铁路运输安全信息管理及辅助决策系统研究[D].北京：北京交通大学,2006.
[53]胡里根.铁路车务站段安全管理水平评价方法及应用研究[D].北京：北京交通大学,2005.
[54]刘建磊,王石磊,高岩.准高速铁路4m框架涵的运营安全评估[J].铁道建筑,2009(3)：4-7.
[55]Hiroaki ISHIDA,等(日).铁道车辆脱轨评估的安全标准[J].国外铁道车辆,2000,37(4)：37-43.
[56]付新生.城轨车辆运营技术故障风险综合评价方法的研究[D].北京：北京交通大学,2007.
[57]李静.车辆运行状态安全评估方法与应用研究[D].北京：北京交通大学,2008.
[58]张强.货车转向架零部件的故障规律分析及预测[D].北京：北京交通大学,2006.
[59]李旭伟.微型测振记录仪在高速机车车辆安全监测中的应用[D].北京：北京交通大学,2004.
[60]付月辉.列车运行设备安全评估的检测系统[D].北京：北京交通大学,2008.
[61]王令朝.中国铁路引入安全评估标准的探讨[J].铁路技术监督,2007,35(6)：4-7.
[62]Elms D. Rail safety[J]. Reliability Engineering and System Safety,2001,74:291～297.
[63]方鸣,陈建国,刘潍青.IEC 61508标准指导城市轨道交通设备安全功能指标实施[J].中国安全生产科学技术,2010,6(1)：158-161.
[64]田琦.项目融资风险及基于影响图的风险评估[D].成都：西南财经大学,2005.
[65]高继红.基于模糊影响图理论的房地产估价方法研究[D].大连：大连里理工大学,2005.
[66]龚莲花.基于模糊影响图的基础设施项目融资风险研究[D].武汉：武汉理工大学,2006.
[67]王颖.DF8B型机车走行部齿轮惯性故障的诊断[J].铁道机车车辆工人,2010：29-32.
[68]刘易平,黄采伦.基于小波变换的列车走行部故障诊断[J].湘潭师范学院学报(自然科学版),2005,27(3)：91-93.
[69]朱建明.机车走行部动态故障非接触式自动诊断系统的研究[J].机车电传,1999(10)：19-21.
[70]王连森.机车走行部运行可靠性研究[J].内燃机车.2010(1)：8-11.
[71]肖楠,谢基龙,周素霞.城市轨道交通车轮踏面制动疲劳强度评价方法及应用[J].工程力学,2007,27(9)：234-239.
[72]曾全君.地铁车辆车轮寿命分析[J].电力机车与城轨车辆.2005,28(2)：47-49.
[73]汪洋.地铁列车车轮踏面环状剥离的分析[J].电力机车与城轨车辆.2003,26(4)：67-68.
[74]邓民刚,孙纲.地铁车辆车轮异常磨耗测试分析[J].现代城市轨道交通,2009,1：19-22.
[75]吴宗之,高进东,魏利军.危险评价方法及其应用[M].北京：冶金工业出版社.2001.
[76]巴春喜.铁路机车轴箱轴承的失效分析[J].铁道机车车辆.2003,23(2)：35-36.
[77]曹永昌,马朝勇,王丽.机车走行部轴承的故障诊断分析及处理措施[J].内燃机车.2004(2)：24-27
[78]廖太平.侧架B部裂纹的形成原因及防止措施[J].机车车辆工艺.2000,(2)：35-36
[79]张涛,谢新民.侧架立柱磨耗板裂纹的原因分析及改进建议[J].铁道车辆.2007,45(1)：43.
[80]梁贤清.转8G型转向架侧架与支撑座组焊裂纹的原因与对策[J].铁道车辆.2003,41(8)：20-21.
[81]沈培德.地铁Duewag转向架裂纹分析及其改进[J].电力机车与城轨车辆.2003,26(4)：12-16.
[82]何有志.关于机车牵引齿轮可靠性的几个问题[J].机车车辆工艺.2000,(8)：1-4.
[83]靳伍银,侯运丰,龚俊.机乍用齿轮断裂失效分析[J].甘肃工业大学学报.2000,326(1)：41-44.
[84]陈立民,宋勇.DF_(4B)型机车齿轮箱故障原因分析及解决措施[J].内燃机车.2006,384(2)：44-45.
[85]董锡明.机车车辆运用可靠性工程[M].北京：中国铁道出版社,2002.
[86]E. Parent de Curzon and B. Beguet.Study into sources of wagon noise:Measurement of sound energy generated by vehicle bodies and running gear. Journal of Sound and Vibration. 1988,120(2):311-320.
[87]Ishizuka, Hiromichi. Probability of improvement in routine inspection work of Shinkansen vehicle axle. Quarterly Report of RTRI.1999,40(2):70-73.
[88]Zobory. Prediction of wheel/rail profile wear. Vehicle System Dynamics.1997,28(2-3): 221-259.
[89]孙苑,李熙.基于MVB总线的机车安全监测系统设计[J].铁路计算机应用,2007(4)：20-22.
[90]邓琼.安全系统工程[M].西安：西北工业大学出版社,2009.
[91]范维澄,孙金华,陆守香.火灾风险评估方法学[M].北京：科学出版社,2006.
[92]詹原瑞.影响图理论方法与应用[M].天津：天津大学出版社,1995.
[93]樊红,冯恩德.概率影响图在船舶综合安全评估中的应用[J].船海工程,2004,162(5)：3-5.
[94]李爱梅.影响图的数据结构研究[J].江南学院学报,2000,15(4)：3-6.
[95]钟麟,佟明安,钟卫,张圣云.基于多级影响图的空战连续机动决策[J].系统仿真学报2007,19(2)：410-411.
[96]李文生,秦翔宇.基于模糊影响图方法的库存弹药事故概率分析[J].中国安全科学学报.2009,19(11)：62-69.
[97]赵新,李群,朱一凡.动态随机影响图建模方法[J].计算机科学.2010,37(8)：182-193.
[98]Diehl M, Haimes Y Y.Influence Diagrams with Multiple Objectives and Tradeoff Analysis[J].IEEE Transactions on Systems, Man and Cybernetics-PartA:Systems and Humans(S1083-4427),2004,24(3):293-304.
[99]Charnes J, Shenoy P P. Multi-stage Monte Carlo Method for Solving Influence Diagrams Using Local Computation[J]. Management Science,2004,50(3):405-418.
[100]Cano A, Gomez M, Moral S. A Forward-backward Monte Carlo Method for Solving Influence Diagrams[J].International Journal of Approximate Reasoning,2006,42:119-135.
[101]D. E. Embrey.Incorporating management and organisational factors into probabilistic safety assessment[J]Reliability Engineering & System Safety,1992,38(1-2):199-208.
[102]肖晓春.基于模型的网络安全风险评估的研究[D].上海：复旦大学,2008.
[103]赵冬梅.信息安全风险评估量化方法研究[D].西安：西安电子科技大学,2007.
[104]周忠宝.基于贝叶斯网络的概率安全评估方法及应用研究[D].合肥：国防科学技术大学,2006.
[105]Hassan Y, Gibreel G. Evaluations of Highway Consistency and Safety:Practical Application [J]. Journal of Transportation Engineering,2000,23 (3):255-260.
[106]Stuaxt R N. Conformity assessment of safety related systems to IEC61508-the CASS initiative. Computing &Control Engineering Journal,2000(2):33-39.
[107]Rail track on behalf of the UK rail industry. Engineering safety management Issue 3 Yellow book3.2001.
[108]杜栋,庞庆华.现代综合评价方法与案例精选[M].北京：清华大学出版社,2006.
[109]张跃等.模糊数学方法及应用[M].北京：煤炭工业出版社,1992.
[110]王巨川等.多指标综合评判[J].昆明理工大学学报,1998,23(4)：69-71.
[111]关晓光,葛志杰.质量经济效益的模糊综合评价[J].管理工程学报,2000,14(4)：65-69.
[112]黄小青.模糊综合评判方法在物流中心选址中的应用[J].水运管理,2002,(12)：7-10.
[113]韩超群.企业技术创新能力的模糊综合评价模型研究[J].沈阳工业学院学报,2003,22(3)：88-90.
[114]沈祖培,黄祥瑞.GO法原理及应用—一种系统可靠性分析方法[M].北京：清华大学出版社,2004.
[115]Li Xi, Zhu Xiaoning. A Novel Fault Diagnosis Expert System Knowledge Acquisition Method of Metro Vehicle Equipments. ICCAE 2010,2010, (2):535-539.
[116]Williams RL, Gateley WY. U se of GO methodology to directly generate minimal cut set [A].Fussell IB. Nuclear System Reliability Engineering and Risk Assessment [C].Pennsylvania:Society for Industrial and Applied Mathematics,1977.
[117]沈祖培,黄祥瑞,高佳.可修系统可靠性分析中GO法的应用[J].核动力工程,2000,21(5)：456-461.
[118]沈祖培,郑涛.复杂系统可靠性的GO法精确算法[J].清华大学学报(自然科学版),2002,42(5)：569-572.
[119]SHEN Zupei, GAO Jia, HUANG Xiangrui. A new quantification algorithm for the GO methodology[J]. Reliability Engineering and System Safety,2000,67 (3):241-247.
[120]沈祖培,高佳.GO法原理和改进的定量分析方法[J].清华大学学报(自然科学版),1999,39(6)：15-19.
[121]黄采伦,樊晓平,陈特放.列车故障在线诊断技术及应用[M].北京：国防工业出版社,2006.
[122]谭富强.城市轨道功车动力系统状态随车检测平台的研究[D].南京：南京理工大学,2004.
[123]钟秉林,黄仁.机械故障诊断学[M].北京：机械工业出版社,2006.
[124]梅宏斌,滚动轴承振动监测与诊断[M].北京：机械工业出版社1996.
[125]韩捷,张瑞林.旋转机械故障机理及诊断技术[M].北京：机械工业出版社,1997.
[126]管辉.基于小波分析的滚动轴承故障诊断方法研究[D].太原：太原科技大学,2008.
[127]Vas, P:Parameter Estimation, Condition Monitoring, and Diagnosis of Electrical Machines. Clarendron Press, Oxford,1993.
[128]Masoud Haji, Hamid, A, Toliyat, Patern Recognition-A Technique for Induction Machines Rotor Fault Detection Eccentricity and Broken Bar Fault. Conference Record of the 2001 IEEE Industry Applications Conference,2001,30(3):1572-1578.
[129]Nandi, S, Toliyat, H A, Condition Monitoring and Fault Diagnosis of Electrical Machines-A Review. IEEE Industry Applications Conference,1999,1(1):197-204.
[130]Penman, J, Sedding, H.G, Lloyd, B.A, Fink, W.T, Detection and Location of Interturn Short Circuits in the Stator Windings of Operating Motors. IEEE Trans. Energy Conv,1996,4(9).
[131]Yazici, B, Kliman, G. B, An Adaptive Statistical Time-Frequency Method for Detection of Broken Bars and Bearing Faults in Motors Using Stator Current. IEEE Trans. On Industry Appl.,1999,2(35).
[132]Abbaszadeh, K, Milimonfared, J, Haji, M, Toliyat, H A, Broken Bar Detection In Induction Motor via Wavelet Transformation. IECON'01:The 27th Annual Conference of the IEEE Industrial Electronics Society 2001.
[133]Willsky, A, A Survey of Design Method for Failure Detection in Dynamic Systems. Automatica,1976,12(1).
[134]Isennann, R, Fault Diagnosis of Machines via Parameter Estimation and Knowledge Processing-Tutorial Paper. Automatica,1993,4(29).
[135]曾芸.基于小波分析的滚动轴承故障诊断方法研究[D].南昌：南昌大学,2007.
[136]Jia Ruijuan, Xu Chunxia, Mechanical Fault Diagnosis and Signal Feature Extraction Based on Fuzzy Neural Network[J]. Chinese Control Conference, (2008):234-237.
[137]唐秋杭.嵌入式轴承故障诊断算法的研究[D].浙江：浙江大学,2006.
[138]梅宏斌.滚动轴承若干故障的诊断与分析[M].电力机车与城市车辆,2005.
[139]Nikolaou N G, Antoniadis I A. Rolling Element Bearing Fault Diagnosis Using Wavelet Packets [J]. NDT & E International,2002,35 (3):197-205.
[140]Guo Qianjin, Yu Hai-bin, Xu Aidong. Modified Moret Wavelet Neural Networks for Fault Detection[J].International Conference on Control and Automation, (2005):1209-1214.
[141]Faa-Jeng Lin, Hsin-Jang Shieh, Po-Kai Huang. Adaptive Wavelet Neural Network Control With Hysteresis Estimation for Piezo-Positioning Mechanism[J]. IEEE Transactions on Neural Networks,2006,17(2):432-444.
[142]Huang N E, Shen S P, Eds. Hilbert-Huang Transform and Its Applications. Singapore: World Scientific,2005.
[143]Pang Peilin, Ding Guangbin. Wavelet-based Diagnostic Model for Rotating Machinery Subject to Vibration Monitoring. Proceedings of the 27th Chinese Control Conference, (2008):303-306.
[144]Cincotti G, Loi G, Pappalardo D. Frequency decomposition and compounding of ultrasound medical images with wavelet packet. IEEE Trans.On medical image,2001,20(8):764-771.
[145]Liu Hongmei, Wang Shaoping, Ouyang Pingchao. Fault Diagnosis Based on Improved Elman Neural Network for a Hydraulic Servo System. Northern Jiaotong University, 2009.
[146]金向阳,张莉,于广滨.基于改进小波神经网络的航空滚动轴承的故障检测[J].中国控制会议,(2007)：525-529.
[147]German Ramos, Jose J.Lopez, Basilio Pueo. Cascaded warped-FIR and FIR filter structure for loudspeaker equalization with low computational cost requirements. Digital Signal Processing,2009(19):393-409.
[148]冯象初,甘小冰,宋国乡.数值泛函与小波理论[M].西安：西安电子科技大学出版社,2003.
[149]王本永,郭仁宁,李文生.基于小波包分析和BP网络识别的齿轮故障诊断[J].辽宁工程技术大学学报,2002,21(5)：659-660.
[150]Grossman A. Wavelet transform and edge detection. Stochastic Processes in Physics and Engineering, Dodrecht Redial,1986.
[151]崔宝珍,潘宏伙.小波分析在滚动轴承故障诊断中的应用[J].科技情报开发与经济,2005,15(2)：176-178.
[152]汪庆年,黄建红,武和雷.小波变换及其在滚动轴承故障诊断中的应用[J].南昌大学学报,2005,27(1)：77-80.
[153]刘乐平,林凤涛.基于小波包特征向量与神经网络的滚动轴承故障诊断[J].轴承,2008,(4)：659-660.
[154]郭计云.基于小波分析的滚动轴承故障诊断方法研究[D].太原：中北大学,2007.
[155]唐贵基,范德功,胡爱军等.基于小波包能量特征向量神经网络的旋转机械故障诊断[J].汽轮机技术,2006,48(3)：215-217.
[156]马拉特,信号处理的小波导引[M].北京：机械工业出版社,2002.
[157]张德丰,MATLAB神经网络应用设计[M].北京：机械工业出版社,2009.
[158]骆江锋,龙江启,范进桢.小波包和BP神经网络在齿轮故障诊断中的应用[J].机械传动,2007,31(3)：84-86.
[159]李运红,张勇涛,裴未迟.基于小波包-Elman神经网络的电机轴承故障诊断[J].河北理工大学学报,2008,30(4)：81-85.
[160]朱树先,张仁杰.BP和RBF神经网络在人脸识别中的比较[J].仪器仪表学报,2007,28(2)：375-379.
[161]王琳,滕少华,伍乃骐.基于ART2-PNN神经网络的网络入侵检测方法[J].计算机应用与软件,2007,24(12)：41-43.
[162]刘力,周建中等.基于信息熵的改进模糊综合评价方法[J].计算机工程,2009,35(18)：4-6.
[163]金菊良,魏一鸣,丁晶.基于改进层次分析法的模糊综合评价模型[J].水力学报.2004(3)：65-69
[164]金龙哲,宋存义.安全科学原理[M].北京：化学工业出版社,2004.