基于光纤传感的机械设备动态监测关键技术研究与应用
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摘要
大型机械装备日益向着大型化、复杂化、高速化、高效化和自动化的方向发展,这些发展取得了巨大的社会效益和经济效益,但同时也带来了一些新的问题,特别是机械装备状态物理量的变化呈现出随机性、多维性、时变性、耦合性和非线性等特点,使其事故更具突发性、灾难性和社会性。因此,针对这些大型装备系统的运行状态深度感知、智能监测与故障诊断技术一直是机械装备状态监测领域极为关注的热点和迫切需要的技术。
目前机械设备的状态监测主要采用传统的电磁类传感器,但该类传感器具有测点参数单一、抗电磁干扰能力弱、以及信号远距离传输能力较差等局限性,从而使得其在机械设备多参数分布式动态监测中的应用受到限制。采用光纤传感技术对机械设备进行实时监测,具有防爆、抗电磁干扰、耐高温高压等电磁类传感器所无法比拟的优势,而更易于多路复用组网,适于远距离监测。利用光纤传感技术对机械设备进行状态监测已有学者进行研究,但多处于理论阶段或侧重于静态测量,且研究内容单一、不够系统。鉴于此,本文研究适于机械设备长期、动态、多参量监测的检测方法与诊断系统以及研制相应的光纤传感器,无疑具有十分重要的意义。
论文根据机械设备典型部件(轴承、转轴、叶片等)的主要特点,在分析各自工况下动态特性的基础上,系统研究并提出了基于光纤传感技术的动态监测理论与检测方法；研制了多种光纤光栅振动传感器,并将这些传感器应用到机械设备的状态检测中。
本文的主要研究内容及结论如下：
1.系统研究了机械设备动态监测理论,重点对轴承、转子和叶片等机械设备中典型部件的动力学特性及相关的耦合系统动力学进行了分析；结合机械设备动态在线检测特点以及光纤传感技术的独有特性,提出了基于光纤传感器的动态信号数据测量与后处理方法。
2.针对机械设备动态监测的不同需求,研制了两种不同类型的光纤光栅加速度传感器。第一种为“L”型悬臂梁结构,属于波长解调型的高灵敏度传感器,频率检测范围为0-60Hz,灵敏度达到60pm/m/s2,加速度测量范围大于25m/s2,适用于低速重载装备的检测；第二种属于强度解调型高频加速度传感器,采用双FBG光栅匹配解调和光强比值算法,解决了检测频率不高和光强不稳对信号干扰等问题,传感器频率检测范围大于500Hz,并在此原理基础上设计了三维一体化光纤光栅加速度传感器,可用于高转速机械设备的振动测量。
3.讨论了采用双光纤光栅对转轴扭矩和温度进行同时测量的可行性,理论表明转轴的扭矩大小对光栅的差模波长变化产生影响,而温度变化只改变共模波长的数值,因此允许对温度和扭矩进行同时测量。由此,搭建实验系统对转轴的扭矩和温度测量分别进行了静态和动态实验,在该系统中,由扭矩引起的差模波长变化率为12.88pm/Nm,对应的温度灵敏度为-1.28pm/℃；与扭矩测量相反的是,共模波长的温度灵敏度为18.5pm/℃,扭矩引起的差模波长的交叉变化率为-1.25pm/Nm。在动态在线实验中,对不同工况下的转轴扭矩进行了测试,结果表明：采用光纤传感技术可以较好的反应转轴的实时负载状态,并且对其信号进行深层次分析,甚至可分析系统不平衡、不对中等设备故障。
4.研究了旋转部件运行状态中裂纹扩展的在线检测方法,以旋转叶片为例进行了验证。采用飞秒激光微加工技术在叶片上制作了微裂纹,以期达到在叶片状态检测中模拟故障叶片的目的,并通过有限元分析和实验对模拟的真实性进行了验证。对叶片进行在线状态检测采用光纤光栅和光纤旋转连接器相结合的方法,将光纤光栅粘贴于叶片的敏感部位检测在运转过程中的应变和频率变化,光纤旋转连接器负责将旋转过程中光栅信号传输到解调系统,通过对叶片应变和频率的变化判断叶片的实时状态；最后利用已有叶片研究了裂纹对叶片疲劳断裂的影响和破坏速率。
5.以一种石化设备的状态监测实例,讨论了动态监测关键技术在工程中的应用。在石化行业中,机械设备安全运行的重要性显得尤为突出。本文将所研制的光纤光栅振动传感器和状态监测系统应用到了石化机械装备的故障检测中,以往复式氢气压缩机为监测对象,对设备的曲轴箱、十字头和缸盖的振动情况以及气阀位置的温度变化进行了长期在线测量,并取得了良好的效果。实测结果证实了光纤传感技术在大型机械设备安全运行监测中具有广阔的应用前景。
The large mechanical equipment is stepping into large-scale, complication, high speed, high efficiency and automatization, which has made great social and economic benefits, but also brings some new issues, especially the change of mechanical equipment state physical quantity showing randomness, multi-dimensional, time-varying, coupling and nonlinear features, then making accidents more abrupt, catastrophic, and social. Therefore, it has been the hot topic and urgent technology to depth perception, intelligent monitoring and fault diagnosis for machinery equipment condition monitoring.
Currently mechanical equipment condition monitoring mainly use conventional electromagnetic-type sensors, but such sensors have some limitations such as measuring parameters single, anti-electromagnetic interference capability weak, as well as long-distance signal transmission capacity poor, making application limited in the multi-parameters distributed dynamic monitoring of machinery equipment. Using optical fiber sensing technology for real-time monitoring of the mechanical equipment, there is increasing incomparable advantages than conventional sensors in explosion-proof, anti-electromagnetic interference, heat resistance and high pressure resistance, easier to multiplex network, and suitable for remote monitoring. The mechanical equipment condition monitoring has been studied by optical fiber sensing technology, but mostly in the stage of theory or focus on the static measurement, single content and not systematic. In view of this, this paper undoubtedly has a very important significance to study detection methods and diagnosis system and develop fiber optic sensor for mechanical equipment long-term, dynamic, multi-parameters monitoring.
According to the main features of typical parts (bearings, shaft, blades, etc.) in mechanical equipment, on the basis of the analysis of the dynamic characteristics of the respective conditions, this paper systematically researched and proposed dynamic monitoring theory and detection methods based on optical fiber sensing technology; developed a variety of fiber Bragg grating vibration sensors, and then these sensors are applied to the state detection of the machinery.
The main contents and conclusions of this paper are as follows:
1. Systematically studied the dynamic monitoring theory of mechanical equipment, the dynamics characteristics of the typical components (bearings, rotor and blades) of the mechanical equipment and associated coupling system dynamics are analyzed; combined with the characteristics of dynamic online detection of mechanical equipment and the unique properties of optical fiber sensing technology, proposed a dynamic signal data measuring and processing method based on optical fiber sensor.
2. According to the different needs of dynamic monitoring of machinical equipment, two different types fiber accelerometer were developed. The first one is "L" shaped cantilever beam, which belong to wavelength demodulation type high-sensitivity sensor, the frequency detection range of0-60Hz, sensitivity to60pm/m/s2, and acceleration measurement range greater than25m/s2, suitable for low speed heavy equipment; The second is intensity-demodulation high frequency acceleration sensor, which adopts double FBGs matching demodulation and light intensity ratio algorithm to solve problems about the detection frequency not high and the signal intensity instability. The frequency detection range of this sensor was greater than500Hz, so based on this principle, the three-dimensional integrated optical fiber accelerometer was designed, which can be used for vibration measurement of high speed equipment.
3. Discusses the feasibility of simultaneous measurement of temperature and torque in a rorating shaft using a dual fiber grating sensor. It shows theoretically that torsion affects the differential-mode wavelength of the gratings in the proposed configuration, whereas temperature changes only the common-mode wavelength, allowing measurement of both torsion and temperature. Thus, the experimental system was set up to carry out static and dynamic experiments of shaft torque and temperature. For the particular system investigated experimentally, the differential wavelength change due to torque was12.88pm/Nm, and the corresponding temperature sensitivity was-1.28pm/℃. In contrast to these values, the temperature sensitivity of the common-mode wavelength change was18.5pm/℃, and its torque cross-sensitivity was-1.25pm/Nm. In the dynamic experiment, shaft torque was tested in different conditions, the results showed that:optical fiber sensing technology can reflect real-time shaft load state, and in-depth analysis of its signal, even analysis some equipment failure such as system imbalance and misalignment fault.
4. Studied on-line detection method of crack propagation in the rotating components—a case study of rotating blades. The micro-cracks were processed on the blades using femtosecond laser micromachining technology in order to purpose of fault simulation of blade in the blade state detection, and validated by the finite element analysis and experiment on the authenticity of simulation. The blade-line state detection was taken by combining FBG sensor and fiber optic rorating joint (FORJ), FBG sensors pasted on sensitive parts of the blades detect strain and frequency variations, FORJ is responsible for transferring FBG signal to the demodulation system. The blade strain and frequency variations were used to judge the real time status of blades. Finally the blade crack was studied effects on fatigue fracture and failure rate.
5. Discussed the key technologies of dynamic monitoring in engineering applications—taken petrochemical equipment condition monitoring as an example. In the petrochemical industry, the importance of the safe operation of mechanical equipment is particularly prominent. In this paper, the fiber Bragg grating vibration sensor and the condition monitoring system is applied to fault detection of petrochemical machinery equipment. Reciprocating hydrogen compressor as the monitoring object was taken for a long time online measurement and achieved good results on the equipment vibration of crankcase, cross head and cylinder head and temperature variation of valve position. Experimental results confirmed that the fiber optic sensing technology had broad application prospects in monitoring the safe operation of large machinical equipment.
目前机械设备的状态监测主要采用传统的电磁类传感器,但该类传感器具有测点参数单一、抗电磁干扰能力弱、以及信号远距离传输能力较差等局限性,从而使得其在机械设备多参数分布式动态监测中的应用受到限制。采用光纤传感技术对机械设备进行实时监测,具有防爆、抗电磁干扰、耐高温高压等电磁类传感器所无法比拟的优势,而更易于多路复用组网,适于远距离监测。利用光纤传感技术对机械设备进行状态监测已有学者进行研究,但多处于理论阶段或侧重于静态测量,且研究内容单一、不够系统。鉴于此,本文研究适于机械设备长期、动态、多参量监测的检测方法与诊断系统以及研制相应的光纤传感器,无疑具有十分重要的意义。
论文根据机械设备典型部件(轴承、转轴、叶片等)的主要特点,在分析各自工况下动态特性的基础上,系统研究并提出了基于光纤传感技术的动态监测理论与检测方法；研制了多种光纤光栅振动传感器,并将这些传感器应用到机械设备的状态检测中。
本文的主要研究内容及结论如下：
1.系统研究了机械设备动态监测理论,重点对轴承、转子和叶片等机械设备中典型部件的动力学特性及相关的耦合系统动力学进行了分析；结合机械设备动态在线检测特点以及光纤传感技术的独有特性,提出了基于光纤传感器的动态信号数据测量与后处理方法。
2.针对机械设备动态监测的不同需求,研制了两种不同类型的光纤光栅加速度传感器。第一种为“L”型悬臂梁结构,属于波长解调型的高灵敏度传感器,频率检测范围为0-60Hz,灵敏度达到60pm/m/s2,加速度测量范围大于25m/s2,适用于低速重载装备的检测；第二种属于强度解调型高频加速度传感器,采用双FBG光栅匹配解调和光强比值算法,解决了检测频率不高和光强不稳对信号干扰等问题,传感器频率检测范围大于500Hz,并在此原理基础上设计了三维一体化光纤光栅加速度传感器,可用于高转速机械设备的振动测量。
3.讨论了采用双光纤光栅对转轴扭矩和温度进行同时测量的可行性,理论表明转轴的扭矩大小对光栅的差模波长变化产生影响,而温度变化只改变共模波长的数值,因此允许对温度和扭矩进行同时测量。由此,搭建实验系统对转轴的扭矩和温度测量分别进行了静态和动态实验,在该系统中,由扭矩引起的差模波长变化率为12.88pm/Nm,对应的温度灵敏度为-1.28pm/℃；与扭矩测量相反的是,共模波长的温度灵敏度为18.5pm/℃,扭矩引起的差模波长的交叉变化率为-1.25pm/Nm。在动态在线实验中,对不同工况下的转轴扭矩进行了测试,结果表明：采用光纤传感技术可以较好的反应转轴的实时负载状态,并且对其信号进行深层次分析,甚至可分析系统不平衡、不对中等设备故障。
4.研究了旋转部件运行状态中裂纹扩展的在线检测方法,以旋转叶片为例进行了验证。采用飞秒激光微加工技术在叶片上制作了微裂纹,以期达到在叶片状态检测中模拟故障叶片的目的,并通过有限元分析和实验对模拟的真实性进行了验证。对叶片进行在线状态检测采用光纤光栅和光纤旋转连接器相结合的方法,将光纤光栅粘贴于叶片的敏感部位检测在运转过程中的应变和频率变化,光纤旋转连接器负责将旋转过程中光栅信号传输到解调系统,通过对叶片应变和频率的变化判断叶片的实时状态；最后利用已有叶片研究了裂纹对叶片疲劳断裂的影响和破坏速率。
5.以一种石化设备的状态监测实例,讨论了动态监测关键技术在工程中的应用。在石化行业中,机械设备安全运行的重要性显得尤为突出。本文将所研制的光纤光栅振动传感器和状态监测系统应用到了石化机械装备的故障检测中,以往复式氢气压缩机为监测对象,对设备的曲轴箱、十字头和缸盖的振动情况以及气阀位置的温度变化进行了长期在线测量,并取得了良好的效果。实测结果证实了光纤传感技术在大型机械设备安全运行监测中具有广阔的应用前景。
The large mechanical equipment is stepping into large-scale, complication, high speed, high efficiency and automatization, which has made great social and economic benefits, but also brings some new issues, especially the change of mechanical equipment state physical quantity showing randomness, multi-dimensional, time-varying, coupling and nonlinear features, then making accidents more abrupt, catastrophic, and social. Therefore, it has been the hot topic and urgent technology to depth perception, intelligent monitoring and fault diagnosis for machinery equipment condition monitoring.
Currently mechanical equipment condition monitoring mainly use conventional electromagnetic-type sensors, but such sensors have some limitations such as measuring parameters single, anti-electromagnetic interference capability weak, as well as long-distance signal transmission capacity poor, making application limited in the multi-parameters distributed dynamic monitoring of machinery equipment. Using optical fiber sensing technology for real-time monitoring of the mechanical equipment, there is increasing incomparable advantages than conventional sensors in explosion-proof, anti-electromagnetic interference, heat resistance and high pressure resistance, easier to multiplex network, and suitable for remote monitoring. The mechanical equipment condition monitoring has been studied by optical fiber sensing technology, but mostly in the stage of theory or focus on the static measurement, single content and not systematic. In view of this, this paper undoubtedly has a very important significance to study detection methods and diagnosis system and develop fiber optic sensor for mechanical equipment long-term, dynamic, multi-parameters monitoring.
According to the main features of typical parts (bearings, shaft, blades, etc.) in mechanical equipment, on the basis of the analysis of the dynamic characteristics of the respective conditions, this paper systematically researched and proposed dynamic monitoring theory and detection methods based on optical fiber sensing technology; developed a variety of fiber Bragg grating vibration sensors, and then these sensors are applied to the state detection of the machinery.
The main contents and conclusions of this paper are as follows:
1. Systematically studied the dynamic monitoring theory of mechanical equipment, the dynamics characteristics of the typical components (bearings, rotor and blades) of the mechanical equipment and associated coupling system dynamics are analyzed; combined with the characteristics of dynamic online detection of mechanical equipment and the unique properties of optical fiber sensing technology, proposed a dynamic signal data measuring and processing method based on optical fiber sensor.
2. According to the different needs of dynamic monitoring of machinical equipment, two different types fiber accelerometer were developed. The first one is "L" shaped cantilever beam, which belong to wavelength demodulation type high-sensitivity sensor, the frequency detection range of0-60Hz, sensitivity to60pm/m/s2, and acceleration measurement range greater than25m/s2, suitable for low speed heavy equipment; The second is intensity-demodulation high frequency acceleration sensor, which adopts double FBGs matching demodulation and light intensity ratio algorithm to solve problems about the detection frequency not high and the signal intensity instability. The frequency detection range of this sensor was greater than500Hz, so based on this principle, the three-dimensional integrated optical fiber accelerometer was designed, which can be used for vibration measurement of high speed equipment.
3. Discusses the feasibility of simultaneous measurement of temperature and torque in a rorating shaft using a dual fiber grating sensor. It shows theoretically that torsion affects the differential-mode wavelength of the gratings in the proposed configuration, whereas temperature changes only the common-mode wavelength, allowing measurement of both torsion and temperature. Thus, the experimental system was set up to carry out static and dynamic experiments of shaft torque and temperature. For the particular system investigated experimentally, the differential wavelength change due to torque was12.88pm/Nm, and the corresponding temperature sensitivity was-1.28pm/℃. In contrast to these values, the temperature sensitivity of the common-mode wavelength change was18.5pm/℃, and its torque cross-sensitivity was-1.25pm/Nm. In the dynamic experiment, shaft torque was tested in different conditions, the results showed that:optical fiber sensing technology can reflect real-time shaft load state, and in-depth analysis of its signal, even analysis some equipment failure such as system imbalance and misalignment fault.
4. Studied on-line detection method of crack propagation in the rotating components—a case study of rotating blades. The micro-cracks were processed on the blades using femtosecond laser micromachining technology in order to purpose of fault simulation of blade in the blade state detection, and validated by the finite element analysis and experiment on the authenticity of simulation. The blade-line state detection was taken by combining FBG sensor and fiber optic rorating joint (FORJ), FBG sensors pasted on sensitive parts of the blades detect strain and frequency variations, FORJ is responsible for transferring FBG signal to the demodulation system. The blade strain and frequency variations were used to judge the real time status of blades. Finally the blade crack was studied effects on fatigue fracture and failure rate.
5. Discussed the key technologies of dynamic monitoring in engineering applications—taken petrochemical equipment condition monitoring as an example. In the petrochemical industry, the importance of the safe operation of mechanical equipment is particularly prominent. In this paper, the fiber Bragg grating vibration sensor and the condition monitoring system is applied to fault detection of petrochemical machinery equipment. Reciprocating hydrogen compressor as the monitoring object was taken for a long time online measurement and achieved good results on the equipment vibration of crankcase, cross head and cylinder head and temperature variation of valve position. Experimental results confirmed that the fiber optic sensing technology had broad application prospects in monitoring the safe operation of large machinical equipment.
引文
[1]B.Bajic. Multidimensional Diagnostics of Turbine Cavitation [J]. Journal of Fluids Engineering,2002,124(4):943-950.
[2]张恒良,谢诞梅,熊扬恒,等.600MW汽轮机转子高精度热应力在线监测模型研制[J].中国电机工程学报,2006,26(1)：21-25.
[3]G.C. Stone. Advancements during the Past Quarter Century in On-line Monitoring of Motor and Generator Winding insulation[J]. IEEE Trans on Dielectrics and Electrical Insulation, 2002,9(5):746-751.
[4]S.R. Campbell., G.C. Stone, H.G.Sedding, et al. Practical On-line Partial Discharge Tests for Turbine Generators and motors [J]. IEEE Trans on Energy Conversion,1994,9(2):281-287.
[5]陈雪峰,李继猛,程航,等.风力发电机状态监测和故障诊断技术的研究与进展[J].机械工程学报,2011,47(9)：45-52.
[6]冯志鹏,宋希庚,薛冬新,等.旋转机械振动故障诊断理论与技术进展综述[J].振动与冲击,2001,20(4)：36-39.
[7]Sheng S, Veers P S. Wind Turbine Drive train Condition Monitoring-An Overview[M]. National Renewable Energy Laboratory,2011.
[8]李平康,吕玲,杜秀霞,等.火电机组旋转机械振动监测与故障诊断技术现状及发展[J].中国电力,2001,11：015.
[9]姜德生,何伟.光纤光栅传感器的应用概况[J].光电子·激光,2002,13(4)：420-430.
[10]Francis, T. S., Shizhuo Yin, and Paul B. Ruffin. Fiber optic sensors[M]. CRC press,2010.
[11]Kanellos G T, Papaioannou G, Tsiokos D, et al. Two dimensional polymer-embedded quasi-distributed FBG pressure sensor for biomedical applications[J]. Opt. Express,2010, 18(1):179-186.
[12]Salo J, Korhonen I. Calculated estimate of FBG sensor's suitability for beam vibration and strain measuring[J]. Measurement,2013.
[13]王颜.基于光纤光栅的铣削力测量方法基础研究[D].武汉理工大学,2012.
[14]游磊,方方,李平勇,等.轴流泵振动加速度状态监测诊断系统的研究与设计[J].四川大学学报：工程科学版,2011,43(1)：236-239.
[15]Sun T, Zhang Z Y, Grattan K T V. Frequency-domain fluorescence based fiber optic fire alarm system[J]. Review of Scientific Instruments,2001,72(4):2191-2196.
[16]Ohno H, Naruse H, Kihara M, et al. Industrial applications of the BOTDR optical fiber strain sensor[J]. Optical fiber technology,2001,7(1):45-64.
[17]Spammer S J, Fuhr P L. Temperature insensitive fiber optic accelerometer using a chirped Bragg grating[J]. Optical Engineering,2000,39(8):2177-2181.
[18]Papadopoulos C A. The strain energy release approach for modeling cracks in rotors:A state of the art review[J]. Mechanical Systems and Signal Processing,2008,22(4):763-789.
[19]毛汉领.混流式水轮机转轮叶片裂纹监测研究[M].北京,中国水利水电出版社,2009.
[20]马玉真.旋转叶片叶尖间隙测量的关键技术研究[D].天津大学,2006.
[21]Nam S B, Yun G J, Carletta J, et al. A novel noncontact electromagnetic field-based sensor for the monitoring of resonant fatigue tests[J]. Smart Materials and Structures,2011,20(3): 035005.
[22]O'Sullivan T M, Bingham C M, Schofield N. High-performance control of dual-inertia servo-drive systems using low-cost integrated SAW torque transducers [J]. Industrial Electronics, IEEE Transactions on,2006,53(4):1226-1237.
[23]Kwun H, Kim S Y. Measurement of torsional dynamics of rotating shafts using magnetostrictive sensors:U.S. Patent 7,131,339[P].2006-11-7.
[24]Wang L, Xu X, Wu G. Reciprocating Machinery Fault Diagnose Based on Phase Detection Test[J]. Advanced Science Letters,2012,12(1):363-366.
[25]刘宝友,方攸同,魏金祥,王永亮.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.
[26]R. Keith Mobley. An Introduction to Predictive Maintenance[M]. Butterworth-Heinemann, 2002.
[27]张杰,杨明亮.一种新型机械式周向振动主轴激振驱动器的原理与结构[J].机械设计,2003,20(4)：
[28]Z. Wang, G. Liu, H. Li, "Research on Crosstalk Noise of Eddy Current Displacement Sensor for Active Magnetic Bearing," Chinese Journal of Scientific Instrument, Vol.31, No.5,2010, pp.1035-1040
[29]Y. Zhang, F. Duan, Z. Fang, T. Ouyang, S. Ye, "Analysis of Non-contact Asynchronous Vibration of Rotating Blades Based on Tip-timing," Chinese Journal of Mechanical Engineering, Vol.44, No.7,2008,147-150
[30]D. Jiang, J. Yang, "Three-dimensional vibration measurement based on magnetic levitation effect," Chinese Journal of Scientific Instrument, Vol.32, No.3,2011, pp.557-562
[31]R.F. Burchill. Resonant structure technique for bearing fault analysis[J].18th meeting of the MFPG, Gsthersburg, Maryland,1972.
[32]P.D. McPadden, M.M. Toozhy. Application of synchronous averaging to vibration monitoring of rolling element bearing[J]. Mechanical Systems and Signal processing,2000,14(6): 891-906.
[33]C.K. Mechefske, J. Mathew. Fault detection and diagnosis in low speed rolling element bearings Part_:The use of parametric spectra[J]. Mechanical Systems and Signal Processing,1992,6(4):297-307.
[34]J.P Dron, L. Rasolofondraibe, F. Bolaers. High-resolution method in vibratory analysis: application to ball bearing monitoring and production machine[J]. International Journal of Solids and Structures,2001,38:4293-4313.
[35]Y. F. Wang, P. J. Kootsookos. Modeling of low shaft speed bearing faults for condition monitoring[J]. Mechanical Systems and Signal Processing,1998,12(3):415-426.
[36]G.K. Chaturvedi, D.W. Thomas. Bearing fault detection using adaptive noise cancelling[J]. ASME, J. Mech. Des.,1982,104:280-289.
[37]D. Ho, R.B. Randall. Optimisation of bearing diagnostic techniques using simulated and actual bearing fault signals[J]. Mechanical Systems and Signal Processing,2000,14(5): 763-788.
[38]Brian T. Holm-Hansen, Robert X. Gao. Structural design and analysis for a sensor-integrated ball bearing[J]. Finite Elements in Analysis and Design,2000,34:257-270.
[39]Brian T. Holm-Hansen, Robert X. Gao. Vibration Analysis of a Sensor-Integrated Ball Bearing[J]. Transactions of the ASME,2000,122(10):384-392
[40]Yimin SHAO, Liang GE and Jieping FANG. Fault Diagnosis System Based on Smart Bearing[J]. International Conference on Control, Automation and Systems 2008, Oct.14-17, 2008 in COEX, Seoul, Korea
[41]高航,吕青,Robert X.Gao.基于微传感器的智能轴承技术[J].中国机械工程,2003,14(21)：1883-1885
[42]Corvari V, Fry W C, Seibert W L, et al. Instrumentation of a high-shear mixer:Evaluation and comparison of a new capacitive sensor, a watt meter, and a strain-gage torque sensor for wet granulation monitoring[J]. Pharmaceutical research,1992,9(12):1525-1533.
[43]喻洪麟,何安国,龙振宇,等.一种新的扭矩测量原理[J].光子学报,1997,26(9)：832-835.
[44]王登泉,杨明,叶林,等.非接触式旋转轴扭矩测量现状[J].电子测量技术,2010,33(6).
[45]Tian X, Tao X. Torsion measurement by using FBG sensors[J]. Processing of SPIE,2000, 4077:154-64.
[46]Wang L A, Lin C Y, Chern G W. A torsion sensor made of a corrugated long period fibre grating [J]. Meas. Sci. Technol.,2001,12:793-799.
[47]Lo Y-L, Chue B-R, Xu S-H. Fiber torsion sensor demodulated by a high-birefringence fiber Bragg grating[J]. Opt. Commun.,2004,230:287-295.
[48]Rao Y-J, Wang Y-P, Ran Z-L, Zhu T. Novel fiber-optic sensors based on long-period fiber gratings written by high-frequency CO2-laser pulses[J]. J. Lightwave Technol.,2003,21: 1320-1327.
[49]Zhang W, Kai G, Dong X, Yuan S, Zhao Q. Temperature-independent FBG-type torsion sensor based on combinatorial torsion beam[J]. IEEE Photon. Technol. Lett.,2002,14: 1154-1156
[50]Kruger L, Swart P L, Chtcherbakov A A, van Wyk A J. Non-contact torsion sensor using fibre Bragg gratings[J]. Measurement Science and Technology,2004,15:1448-1452.
[51]Swart P L, Chtcherbakov A A, van Wyk A J. Bragg grating sensor for torsion and temperature measurements in rotating machinery [J]. Processing of SPIE,2005,5634: 353-60.
[52]Pieter L Swart, Anatoli A Chtcherbakov, A Japie van Wyk. Dual Bragg grating sensor for concurrent torsion and temperature measurement J]. Measurement Science and Technology, 2006,17:1057-1064
[53]牛向东.超声端点反射法测量裂纹自身高度的数字处理方法[J].无损检测,2001,23(7)：298-301.
[54]段权,程光旭.在役压力容器疲劳裂纹的涡流无损检测方法研究[J].化工机械,2000,27(4)：208-210
[55]中国机械工程学会无损检测分会.磁粉检测[M].北京：机械工业出版社,2005
[56]穆琳琳.光纤声发射检测的影响因素的实验研究[D].哈尔滨工程大学,2008.
[57]曹剑绵,陈昌林.大型水轮机转轮异常振动及叶片裂纹分析[J].西南交通大学学报,2002,37(B11)：68-72.
[58]王向红,朱昌明,毛汉领,等.基于声发射技术的水轮机转轮叶片疲劳裂纹扩展速率实验研究[J].中国机械工程,2009,20(7)：847-851.
[59]Company Bently Nevada. Bently Nevada expands reciprocating compressor monitoring solutions. Bently Nevada's News Release.http://www.bently.com/news.htm.
[60]闫贺.往复式压缩机在线监测系统开发与应用[C].北京工业大学,2010.
[61]徐志刚.港口大型机械金属结构应力在线监测与诊断系统研究[D].武汉理工大学,2008.
[62]侯贵宾.基于光纤光栅传感的翻车机健康监测与诊断系统研究[D].武汉：武汉理工大学,2009.
[63]杨光,黄俊斌,顾洪灿等.光纤Bragg光栅加速度传感器研究进展[J].舰船电子工程,2011,31(7)：76-80
[64]刘钦朋,乔学光,赵建林,等.双悬梁光纤布拉格光栅低频加速度传感器[J].光电子·激光,2011,22(8)：1119-1123.
[65]Amanda fender, Willian N. MacPherson, Robert R. J. Maier, et al. Two-axis temperature-insensitive accelerometer based on multicore fiber Bragg gratings[J].IEEE Sensors Journal,2008,8(7):1292-1298
[66]曾楠.光纤加速度传感器若干关键技术研究[D].北京：清华大学,2005.
[67]王善鲤,向光华,忽满利等.一种新型光纤Bragg光栅振动传感器的设计[J].光电子·激光,2011,22(4)：515-519
[68]Basumallick, N. Chatterjee, I. Biswas et al..Fiber Bragg grating accelerometer with enhanced sensitivity [J].Sensors and Actuators, A:Physical,2012,173(1):108-115
[69]S. R. K. Morikawa, A. S. Ribeiro, R. D. Regazzi et al. Triaxial Bragg grating accelerometer[C].Optical Fiber Sensors Conference Technical Digest,2002,1:95-98
[70]N. Basumallick, I. Chatterjee, P. Biswas, et al. Fiber Bragg grating accelerometer with enhanced sensitivity [J]. Sensors and Actuators A:Physical,2012,173(1)(2012):108-115
[71]S(?)ren Andresen, Torben R. Licht, Finn K. Nielsen. Test and calibration of Bragg grating based vibration sensors[C]. Processing of SPIE,2012,8421:8421B7
[72]张东生,姚开方,罗裴等.一种新型的光纤光栅高频加速度传感器[J].仪器仪表学报,2009,30(7)：1400-1403
[73]李政颖,周祖德,童杏林等.高速大容量光纤光栅解调仪的研究[J].光学学报,2012,32(3)：0306007
[74]贾振安,刘静,乔学光等.FBG传感信号数字化可调谐F-P滤波器解调技术研究[J].光电子·激光,2011,22(5)：649-651.
[75]L. A. Ferreria, J. L. Santes, F. Farah, et al. Pseudoheterodyne demodulation technique for fiber Bragg grating sensors using two matched gratings[J]. IEEE Photon. Technology Letters, 1997,9(4):487-489
[76]陈显,余尚江,杨吉祥等.线性滤波法高速解调技术中的测量有效性研究[J].光学学报,2009,29(1)：145-150.
[77]姜明顺,孟玲,隋青美等.一种新颖的双边缘滤波光纤布拉格光栅解调技术[J].光电子·激光,2011,22(3)：355-358.
[78]Takeda N, Okabe Y,Kuwahara J, et al.Development of smart composite structure with small-diameter fiber Brag grating sensor for damage detection:quantitative evaluation of delamination length in CFRP laminates,using Lamb wave sensing.Compos Sci Technol 2005;65:2575-87
[79]Tsuda H. Ultrasound and damage detection in CFRP using fiber Bragg grating sensor.compos Sci Technol 2006:66:676-83
[80]Hiroshi Tsuda,Jung-Ryul Lee, Yisheng Guan, Junji Takatsubo. Investigation of fatigue crack in stainless steel using a mobile fiber Bragg grating ultrasonic sensor. Optical Fiber Technology 13 (2007) 209-214
[81]Graham Wild and Steven Hinckley. A Transmit Reflect Detection System for Fiber Bragg Grating Acoustic Emission and Transmission Sensors. Lecture Notes in Electrical Engineering,2008, Volume 20, Part IV,183-197
[82]Ling H, Lau K, Cheng L, et al. Viability of using an embedded FBG sensor in a composite structure for dynamic strain measurement[J]. Measurement,2006,39(4):328-334.
[83]MENG Li-jun,TAN Yue-gangl, ZHOU Zu-de. Research on Demodulation System for Fiber Bragg Grating Sensor Based on Tunable Laser Light. Advanced Materials Research Vols. 341-342 (2012) pp 838-842
[84]闻邦椿,武新华,丁千,韩清凯.故障旋转机械非线性动力学的理论与试验[M].北京：科学出版社,2004.
[85]丁镇军.裂纹叶片动态特性与疲劳试验监测系统研究[D].南京航空航天大学,2009.
[86]朱厚军,赵玫,王德洋.Jeffcott裂纹转子动力特性的研究[J].振动与冲击,2001,20(1)：1-4.
[87]Davies W G R et al. Analysis of the response of a multi-shaft-bearing system containing a transverse crack in a rotor[J].ASME Journal of Vibration and Acoustics,1984,106:139-145
[88]罗继伟,罗天宇.滚动轴承分析计算与应用[M].北京：机械工业出版社,2009
[89]T.A.Harris,M.N.Kotzalas,Rolling bearing analysis,fifthed.[M].Taylor & Francis Group,2006.
[90]钟一谔,何衍宗,王正,李方泽.转子动力学[M].北京,清华大学出版社,1987.
[91]Genta G.On the stability of rotating blade arrays[J]. Journal of sound and vibration,2004, 273(4):805-836.
[92]王立刚.叶片—转子—轴承耦合系统的非线性动力学特性研究[D].哈尔滨工业大学,2009.
[93]闻邦椿,刘树英,何勃.振动机械的理论与动态设计方法[M].北京：机械工业出版社,2001.
[94]Yuan Y., Liang L., Zhang D.. Spectra of fiber Bragg grating and long period fiber grating undergoing linear and quadratic strain[J]. Optoelectronics Letters,2009,5:182-185.
[95]Prabhugoud M, Peters K. Modified transfer matrix formulation for Bragg grating strain sensors[J]. Journal of lightwave technology,2004,22(10):2302.
[96]信思金.FBG传感技术在大坝安全监测中的应用研究[J].武汉理工大学学报,2004,26(8)：35-37.
[97]Rao Y J. In-fibre Bragg grating sensors[J]. Measurement science and technology,1997,8(4): 355.
[98]Grattan K T V, Sun T. Fiber optic sensor technology:an overview[J]. Sensors and Actuators A:Physical,2000,82(1):40-61.
[99]Kersey A D, Berkoff T A, Morey W W. Multiplexed fiber Bragg grating strain-sensor system with a fiber Fabry—Perot wavelength filter[J]. Optics letters,1993,18(16):1370-1372.
[100]周雪芳.光纤布喇格光栅振动传感技术研究[D].武汉理工大学,2003.
[101]T. Guo, QD. Zhao, H. Zhang, et al. Temperature-insensitive fiber Bragg grating force sensor via a bandwidth modulation and optical-power detection technique[J]. Journal of Lightwave Technology,2006,24(10):3797-3802.
[102]张东生,郭丹.基于匹配滤波解调的光纤光栅振动传感器研究[J].传感技术学报,2007,20(2)：311-313.
[103]Othonos A, Kalli K. Fiber Bragg gratings:fundamentals and applications in telecommunications and sensing[M]. Norwood, MA:Artech House Publishers; 1999.
[104]汪弋平,王鸣,黄晓琴.基于光纤光栅偏振特性的横向压力传感器[J].中国激光,2011.38(4)：0405004-1-6.
[105]谢作生,李伟文,林伟鹏等.利用扫频光纤激光器实现低频周期振动传感[J].中国激光,2011,38(12)：133-137.
[106]Hiroshi Tsuda, Jung-Ryul Lee, Yisheng Guan, et al. Investigation of fatigue crack in stainless steel using a mobile fiber Bragg grating ultrasonic sensor[J]. Optical Fiber Technology,2007,13(3):209-214
[107]J.S. Sakellariou, S.D. Fassois. Vibration Based Fault Detection and Identification in an Aircraft Skeleton Structure via a Stochastic Functional Model Based Method[J]. Mechanical Systems and Signal Processing,2008,22(3):557-573
[108]岳丽娜,黄俊,姜德生.光纤传感技术在长江二桥加固监测中的应用[J].武汉理工大学学报,2009,31(2)：10-12.
[109]张东生,李微,郭丹等.基于光纤光栅振动传感器的桥梁索力实时监测[J].传感技术学报,2007,20(12)：2720-2723.
[110]Kyungmok K I M, Lee J M, Hwang Y. Torsion Measurement using Fiber Bragg Grating Sensors and a Rotary Optical Coupler[J].15th International Congress on Sound and Vibration 6-10 July 2008, Daejeon, Korea:2529-2536
[111]范钦珊.材料力学[M].北京,高等教育出版社,2000.
[112]Udd E, Spillman W B. Fiber optic sensors[M]. John Wiley & Sons,1991.
[113]张玉贵.烟气轮机叶片振动的非接触式在线监测关键技术研究[D].天津大学,2008.
[114]张锦,刘晓平,叶轮机振动模态分析理论及数值方法[M].北京：国防工业出版社,2001
[115]沈达宽,航空发动机强度计算,北京：国防工业出版社,1980
[116]王宇华.高速旋转叶片振动叶端定时测量方法和系统研究[D].,2003.
[117]华东电力试验研究所,江苏省电力试验研究所,南京工学院,汽轮机振动特性和调整[M].北京：电力工业出版社,1981.
[118]Seongkuk Lee, Dongfang Yang, Suwas Nikumb. Femtosecond laser micro-milling of Si wafers[J], Applied Surface Science,2008,254 (10):2996-3005
[119]P. Moreno, C. Mendez, A. Garci, I. Arias, L. Rosoa. Femtosecond laser ablation of carbon reinforced polymers[J]. Applied Surface Science,2006,252 (12):4110-4119.
[120]R. Le Harzic, D. Breitling, M.Weikert, S. Sommer. Ablation comparison with low and high energy densities for Cu and A1 with ultra-short laser pulses[J]. Materials Science & Processing,2005,80(7):1589-1593.
[121]R. Le Harzica, D. Breitlinga, M. Weikert, S. Sommer, C.Fohl, S. Valettec, C. Donnet, E. Audouardc, F. Dausinge. Pulse width and energy influence on laser micromachining of metals in a range of 100 fs to 5 ps[J]. Applied Surface Science.2005,249(1-4):322-331.
[122]M. Hashida, A.F Semerok, O. Gobert, G. Petite, Y. Izawa, J.F. Wagner. Ablation threshold dependence on pulse duration for copper[J]. Applied surface science.2002,(197-198): 862-867.
[123]Leon R L, Scheibel J R. Current status of the EPRI acoustic Doppler blade.monitor EPRJ steam turbine blade reliability workshop[J]. Los Angeles,1986.
[124]И.E.萨勃洛斯基等著,吴士祥,郑叔琛译,涡轮机叶片振动的非接触测量[M],北京：国防工业出版社,1986
[125]Sever I A. Experimental validation of turbomachinery blade vibration predictions[D]. Imperial College London (University of London),2004.
[126]Robert L L, Keith T. Monitoring Systems for Steam Turbine Blade Faults[J]. Sound and Vibration/February,1990.
[127]S. Kuhnt, J. Wernicke, J. Shadden, R. Byars. Advanced Wind Turbine Controls Input Based on Real Time Loads Measured with Fibre Optical Sensors Embedded in Rotor Blades[J]. the European Wind Energy Conference & Exhibition,2006.
[128]Schroeder K, Ecke W, Apitz J, et al. A fibre Bragg grating sensor system monitors operational load in a wind turbine rotor blade[J]. Measurement Science and Technology, 2006,17(5):1167.
[129]Dorsey G. Fiber optic rotary joints-a review[J].Components, Hybrids, and Manufacturing Technology, IEEE Transactions on,1982,5(1):37-41.
[130]Jing W, Jia D, Tang F, et al. Design and implementation of a broadband optical rotary joint using C-lenses[J]. Optics express,2004,12(17):4088-4093.
[131]陈传尧.疲劳与断裂[M].武汉：华中科技大学出版社,2005.
[132]邓增杰,周敬恩.工程材料的断裂与疲劳[M].机械工业出版社,1995.
[133]赵俊龙.往复式压缩机振动信号特征分析及故障诊断方法研究[D].大连理工大学,2010.
[134]高金吉.机泵群实时监测网络和故障诊断专家系统[J].中国工程科学,2001,3(9)：41-47.
[135]何嘉武.樊新海,基于振动烈度的机械状态监测方法及应用[J].仪器仪表学报,2010,31(4)：37-39.
[136]陈云,江志农,高金吉.基于LabVIEW的大型往复式氢气压缩机组在线监测系统开发[J].北京化工大学学报：2003,30(2)：63-65.
[137]Ahmed M, Abdusslam S, Baqqar M, et al. Fault classification of reciprocating compressor based on Neural Networks and Support Vector Machines[C]. Automation and Computing (ICAC),2011 17th International Conference on. IEEE,2011:213-218.
[138]Yang B S, Hwang W W, Kim D J, et al. Condition classification of small reciprocating compressor for refrigerators using artificial neural networks and support vector machines[J]. Mechanical Systems and Signal Processing,2005,19(2):371-390.
[139]Prata A T, Fernandes J R S, Fagotti F. Dynamic analysis of piston secondary motion for small reciprocating compressors[J]. Journal of tribology,2000,122(4):752-760.
[140]Hanna R, Schmitt D W. Failure analysis of 7500 HP induction motors driving reciprocating compressors with three years service[C]. Petroleum and Chemical Industry Conference (PCIC),2010 Record of Conference Papers Industry Applications Society 57th Annual. IEEE,2010:1-6.
[2]张恒良,谢诞梅,熊扬恒,等.600MW汽轮机转子高精度热应力在线监测模型研制[J].中国电机工程学报,2006,26(1)：21-25.
[3]G.C. Stone. Advancements during the Past Quarter Century in On-line Monitoring of Motor and Generator Winding insulation[J]. IEEE Trans on Dielectrics and Electrical Insulation, 2002,9(5):746-751.
[4]S.R. Campbell., G.C. Stone, H.G.Sedding, et al. Practical On-line Partial Discharge Tests for Turbine Generators and motors [J]. IEEE Trans on Energy Conversion,1994,9(2):281-287.
[5]陈雪峰,李继猛,程航,等.风力发电机状态监测和故障诊断技术的研究与进展[J].机械工程学报,2011,47(9)：45-52.
[6]冯志鹏,宋希庚,薛冬新,等.旋转机械振动故障诊断理论与技术进展综述[J].振动与冲击,2001,20(4)：36-39.
[7]Sheng S, Veers P S. Wind Turbine Drive train Condition Monitoring-An Overview[M]. National Renewable Energy Laboratory,2011.
[8]李平康,吕玲,杜秀霞,等.火电机组旋转机械振动监测与故障诊断技术现状及发展[J].中国电力,2001,11：015.
[9]姜德生,何伟.光纤光栅传感器的应用概况[J].光电子·激光,2002,13(4)：420-430.
[10]Francis, T. S., Shizhuo Yin, and Paul B. Ruffin. Fiber optic sensors[M]. CRC press,2010.
[11]Kanellos G T, Papaioannou G, Tsiokos D, et al. Two dimensional polymer-embedded quasi-distributed FBG pressure sensor for biomedical applications[J]. Opt. Express,2010, 18(1):179-186.
[12]Salo J, Korhonen I. Calculated estimate of FBG sensor's suitability for beam vibration and strain measuring[J]. Measurement,2013.
[13]王颜.基于光纤光栅的铣削力测量方法基础研究[D].武汉理工大学,2012.
[14]游磊,方方,李平勇,等.轴流泵振动加速度状态监测诊断系统的研究与设计[J].四川大学学报：工程科学版,2011,43(1)：236-239.
[15]Sun T, Zhang Z Y, Grattan K T V. Frequency-domain fluorescence based fiber optic fire alarm system[J]. Review of Scientific Instruments,2001,72(4):2191-2196.
[16]Ohno H, Naruse H, Kihara M, et al. Industrial applications of the BOTDR optical fiber strain sensor[J]. Optical fiber technology,2001,7(1):45-64.
[17]Spammer S J, Fuhr P L. Temperature insensitive fiber optic accelerometer using a chirped Bragg grating[J]. Optical Engineering,2000,39(8):2177-2181.
[18]Papadopoulos C A. The strain energy release approach for modeling cracks in rotors:A state of the art review[J]. Mechanical Systems and Signal Processing,2008,22(4):763-789.
[19]毛汉领.混流式水轮机转轮叶片裂纹监测研究[M].北京,中国水利水电出版社,2009.
[20]马玉真.旋转叶片叶尖间隙测量的关键技术研究[D].天津大学,2006.
[21]Nam S B, Yun G J, Carletta J, et al. A novel noncontact electromagnetic field-based sensor for the monitoring of resonant fatigue tests[J]. Smart Materials and Structures,2011,20(3): 035005.
[22]O'Sullivan T M, Bingham C M, Schofield N. High-performance control of dual-inertia servo-drive systems using low-cost integrated SAW torque transducers [J]. Industrial Electronics, IEEE Transactions on,2006,53(4):1226-1237.
[23]Kwun H, Kim S Y. Measurement of torsional dynamics of rotating shafts using magnetostrictive sensors:U.S. Patent 7,131,339[P].2006-11-7.
[24]Wang L, Xu X, Wu G. Reciprocating Machinery Fault Diagnose Based on Phase Detection Test[J]. Advanced Science Letters,2012,12(1):363-366.
[25]刘宝友,方攸同,魏金祥,王永亮.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.
[26]R. Keith Mobley. An Introduction to Predictive Maintenance[M]. Butterworth-Heinemann, 2002.
[27]张杰,杨明亮.一种新型机械式周向振动主轴激振驱动器的原理与结构[J].机械设计,2003,20(4)：
[28]Z. Wang, G. Liu, H. Li, "Research on Crosstalk Noise of Eddy Current Displacement Sensor for Active Magnetic Bearing," Chinese Journal of Scientific Instrument, Vol.31, No.5,2010, pp.1035-1040
[29]Y. Zhang, F. Duan, Z. Fang, T. Ouyang, S. Ye, "Analysis of Non-contact Asynchronous Vibration of Rotating Blades Based on Tip-timing," Chinese Journal of Mechanical Engineering, Vol.44, No.7,2008,147-150
[30]D. Jiang, J. Yang, "Three-dimensional vibration measurement based on magnetic levitation effect," Chinese Journal of Scientific Instrument, Vol.32, No.3,2011, pp.557-562
[31]R.F. Burchill. Resonant structure technique for bearing fault analysis[J].18th meeting of the MFPG, Gsthersburg, Maryland,1972.
[32]P.D. McPadden, M.M. Toozhy. Application of synchronous averaging to vibration monitoring of rolling element bearing[J]. Mechanical Systems and Signal processing,2000,14(6): 891-906.
[33]C.K. Mechefske, J. Mathew. Fault detection and diagnosis in low speed rolling element bearings Part_:The use of parametric spectra[J]. Mechanical Systems and Signal Processing,1992,6(4):297-307.
[34]J.P Dron, L. Rasolofondraibe, F. Bolaers. High-resolution method in vibratory analysis: application to ball bearing monitoring and production machine[J]. International Journal of Solids and Structures,2001,38:4293-4313.
[35]Y. F. Wang, P. J. Kootsookos. Modeling of low shaft speed bearing faults for condition monitoring[J]. Mechanical Systems and Signal Processing,1998,12(3):415-426.
[36]G.K. Chaturvedi, D.W. Thomas. Bearing fault detection using adaptive noise cancelling[J]. ASME, J. Mech. Des.,1982,104:280-289.
[37]D. Ho, R.B. Randall. Optimisation of bearing diagnostic techniques using simulated and actual bearing fault signals[J]. Mechanical Systems and Signal Processing,2000,14(5): 763-788.
[38]Brian T. Holm-Hansen, Robert X. Gao. Structural design and analysis for a sensor-integrated ball bearing[J]. Finite Elements in Analysis and Design,2000,34:257-270.
[39]Brian T. Holm-Hansen, Robert X. Gao. Vibration Analysis of a Sensor-Integrated Ball Bearing[J]. Transactions of the ASME,2000,122(10):384-392
[40]Yimin SHAO, Liang GE and Jieping FANG. Fault Diagnosis System Based on Smart Bearing[J]. International Conference on Control, Automation and Systems 2008, Oct.14-17, 2008 in COEX, Seoul, Korea
[41]高航,吕青,Robert X.Gao.基于微传感器的智能轴承技术[J].中国机械工程,2003,14(21)：1883-1885
[42]Corvari V, Fry W C, Seibert W L, et al. Instrumentation of a high-shear mixer:Evaluation and comparison of a new capacitive sensor, a watt meter, and a strain-gage torque sensor for wet granulation monitoring[J]. Pharmaceutical research,1992,9(12):1525-1533.
[43]喻洪麟,何安国,龙振宇,等.一种新的扭矩测量原理[J].光子学报,1997,26(9)：832-835.
[44]王登泉,杨明,叶林,等.非接触式旋转轴扭矩测量现状[J].电子测量技术,2010,33(6).
[45]Tian X, Tao X. Torsion measurement by using FBG sensors[J]. Processing of SPIE,2000, 4077:154-64.
[46]Wang L A, Lin C Y, Chern G W. A torsion sensor made of a corrugated long period fibre grating [J]. Meas. Sci. Technol.,2001,12:793-799.
[47]Lo Y-L, Chue B-R, Xu S-H. Fiber torsion sensor demodulated by a high-birefringence fiber Bragg grating[J]. Opt. Commun.,2004,230:287-295.
[48]Rao Y-J, Wang Y-P, Ran Z-L, Zhu T. Novel fiber-optic sensors based on long-period fiber gratings written by high-frequency CO2-laser pulses[J]. J. Lightwave Technol.,2003,21: 1320-1327.
[49]Zhang W, Kai G, Dong X, Yuan S, Zhao Q. Temperature-independent FBG-type torsion sensor based on combinatorial torsion beam[J]. IEEE Photon. Technol. Lett.,2002,14: 1154-1156
[50]Kruger L, Swart P L, Chtcherbakov A A, van Wyk A J. Non-contact torsion sensor using fibre Bragg gratings[J]. Measurement Science and Technology,2004,15:1448-1452.
[51]Swart P L, Chtcherbakov A A, van Wyk A J. Bragg grating sensor for torsion and temperature measurements in rotating machinery [J]. Processing of SPIE,2005,5634: 353-60.
[52]Pieter L Swart, Anatoli A Chtcherbakov, A Japie van Wyk. Dual Bragg grating sensor for concurrent torsion and temperature measurement J]. Measurement Science and Technology, 2006,17:1057-1064
[53]牛向东.超声端点反射法测量裂纹自身高度的数字处理方法[J].无损检测,2001,23(7)：298-301.
[54]段权,程光旭.在役压力容器疲劳裂纹的涡流无损检测方法研究[J].化工机械,2000,27(4)：208-210
[55]中国机械工程学会无损检测分会.磁粉检测[M].北京：机械工业出版社,2005
[56]穆琳琳.光纤声发射检测的影响因素的实验研究[D].哈尔滨工程大学,2008.
[57]曹剑绵,陈昌林.大型水轮机转轮异常振动及叶片裂纹分析[J].西南交通大学学报,2002,37(B11)：68-72.
[58]王向红,朱昌明,毛汉领,等.基于声发射技术的水轮机转轮叶片疲劳裂纹扩展速率实验研究[J].中国机械工程,2009,20(7)：847-851.
[59]Company Bently Nevada. Bently Nevada expands reciprocating compressor monitoring solutions. Bently Nevada's News Release.http://www.bently.com/news.htm.
[60]闫贺.往复式压缩机在线监测系统开发与应用[C].北京工业大学,2010.
[61]徐志刚.港口大型机械金属结构应力在线监测与诊断系统研究[D].武汉理工大学,2008.
[62]侯贵宾.基于光纤光栅传感的翻车机健康监测与诊断系统研究[D].武汉：武汉理工大学,2009.
[63]杨光,黄俊斌,顾洪灿等.光纤Bragg光栅加速度传感器研究进展[J].舰船电子工程,2011,31(7)：76-80
[64]刘钦朋,乔学光,赵建林,等.双悬梁光纤布拉格光栅低频加速度传感器[J].光电子·激光,2011,22(8)：1119-1123.
[65]Amanda fender, Willian N. MacPherson, Robert R. J. Maier, et al. Two-axis temperature-insensitive accelerometer based on multicore fiber Bragg gratings[J].IEEE Sensors Journal,2008,8(7):1292-1298
[66]曾楠.光纤加速度传感器若干关键技术研究[D].北京：清华大学,2005.
[67]王善鲤,向光华,忽满利等.一种新型光纤Bragg光栅振动传感器的设计[J].光电子·激光,2011,22(4)：515-519
[68]Basumallick, N. Chatterjee, I. Biswas et al..Fiber Bragg grating accelerometer with enhanced sensitivity [J].Sensors and Actuators, A:Physical,2012,173(1):108-115
[69]S. R. K. Morikawa, A. S. Ribeiro, R. D. Regazzi et al. Triaxial Bragg grating accelerometer[C].Optical Fiber Sensors Conference Technical Digest,2002,1:95-98
[70]N. Basumallick, I. Chatterjee, P. Biswas, et al. Fiber Bragg grating accelerometer with enhanced sensitivity [J]. Sensors and Actuators A:Physical,2012,173(1)(2012):108-115
[71]S(?)ren Andresen, Torben R. Licht, Finn K. Nielsen. Test and calibration of Bragg grating based vibration sensors[C]. Processing of SPIE,2012,8421:8421B7
[72]张东生,姚开方,罗裴等.一种新型的光纤光栅高频加速度传感器[J].仪器仪表学报,2009,30(7)：1400-1403
[73]李政颖,周祖德,童杏林等.高速大容量光纤光栅解调仪的研究[J].光学学报,2012,32(3)：0306007
[74]贾振安,刘静,乔学光等.FBG传感信号数字化可调谐F-P滤波器解调技术研究[J].光电子·激光,2011,22(5)：649-651.
[75]L. A. Ferreria, J. L. Santes, F. Farah, et al. Pseudoheterodyne demodulation technique for fiber Bragg grating sensors using two matched gratings[J]. IEEE Photon. Technology Letters, 1997,9(4):487-489
[76]陈显,余尚江,杨吉祥等.线性滤波法高速解调技术中的测量有效性研究[J].光学学报,2009,29(1)：145-150.
[77]姜明顺,孟玲,隋青美等.一种新颖的双边缘滤波光纤布拉格光栅解调技术[J].光电子·激光,2011,22(3)：355-358.
[78]Takeda N, Okabe Y,Kuwahara J, et al.Development of smart composite structure with small-diameter fiber Brag grating sensor for damage detection:quantitative evaluation of delamination length in CFRP laminates,using Lamb wave sensing.Compos Sci Technol 2005;65:2575-87
[79]Tsuda H. Ultrasound and damage detection in CFRP using fiber Bragg grating sensor.compos Sci Technol 2006:66:676-83
[80]Hiroshi Tsuda,Jung-Ryul Lee, Yisheng Guan, Junji Takatsubo. Investigation of fatigue crack in stainless steel using a mobile fiber Bragg grating ultrasonic sensor. Optical Fiber Technology 13 (2007) 209-214
[81]Graham Wild and Steven Hinckley. A Transmit Reflect Detection System for Fiber Bragg Grating Acoustic Emission and Transmission Sensors. Lecture Notes in Electrical Engineering,2008, Volume 20, Part IV,183-197
[82]Ling H, Lau K, Cheng L, et al. Viability of using an embedded FBG sensor in a composite structure for dynamic strain measurement[J]. Measurement,2006,39(4):328-334.
[83]MENG Li-jun,TAN Yue-gangl, ZHOU Zu-de. Research on Demodulation System for Fiber Bragg Grating Sensor Based on Tunable Laser Light. Advanced Materials Research Vols. 341-342 (2012) pp 838-842
[84]闻邦椿,武新华,丁千,韩清凯.故障旋转机械非线性动力学的理论与试验[M].北京：科学出版社,2004.
[85]丁镇军.裂纹叶片动态特性与疲劳试验监测系统研究[D].南京航空航天大学,2009.
[86]朱厚军,赵玫,王德洋.Jeffcott裂纹转子动力特性的研究[J].振动与冲击,2001,20(1)：1-4.
[87]Davies W G R et al. Analysis of the response of a multi-shaft-bearing system containing a transverse crack in a rotor[J].ASME Journal of Vibration and Acoustics,1984,106:139-145
[88]罗继伟,罗天宇.滚动轴承分析计算与应用[M].北京：机械工业出版社,2009
[89]T.A.Harris,M.N.Kotzalas,Rolling bearing analysis,fifthed.[M].Taylor & Francis Group,2006.
[90]钟一谔,何衍宗,王正,李方泽.转子动力学[M].北京,清华大学出版社,1987.
[91]Genta G.On the stability of rotating blade arrays[J]. Journal of sound and vibration,2004, 273(4):805-836.
[92]王立刚.叶片—转子—轴承耦合系统的非线性动力学特性研究[D].哈尔滨工业大学,2009.
[93]闻邦椿,刘树英,何勃.振动机械的理论与动态设计方法[M].北京：机械工业出版社,2001.
[94]Yuan Y., Liang L., Zhang D.. Spectra of fiber Bragg grating and long period fiber grating undergoing linear and quadratic strain[J]. Optoelectronics Letters,2009,5:182-185.
[95]Prabhugoud M, Peters K. Modified transfer matrix formulation for Bragg grating strain sensors[J]. Journal of lightwave technology,2004,22(10):2302.
[96]信思金.FBG传感技术在大坝安全监测中的应用研究[J].武汉理工大学学报,2004,26(8)：35-37.
[97]Rao Y J. In-fibre Bragg grating sensors[J]. Measurement science and technology,1997,8(4): 355.
[98]Grattan K T V, Sun T. Fiber optic sensor technology:an overview[J]. Sensors and Actuators A:Physical,2000,82(1):40-61.
[99]Kersey A D, Berkoff T A, Morey W W. Multiplexed fiber Bragg grating strain-sensor system with a fiber Fabry—Perot wavelength filter[J]. Optics letters,1993,18(16):1370-1372.
[100]周雪芳.光纤布喇格光栅振动传感技术研究[D].武汉理工大学,2003.
[101]T. Guo, QD. Zhao, H. Zhang, et al. Temperature-insensitive fiber Bragg grating force sensor via a bandwidth modulation and optical-power detection technique[J]. Journal of Lightwave Technology,2006,24(10):3797-3802.
[102]张东生,郭丹.基于匹配滤波解调的光纤光栅振动传感器研究[J].传感技术学报,2007,20(2)：311-313.
[103]Othonos A, Kalli K. Fiber Bragg gratings:fundamentals and applications in telecommunications and sensing[M]. Norwood, MA:Artech House Publishers; 1999.
[104]汪弋平,王鸣,黄晓琴.基于光纤光栅偏振特性的横向压力传感器[J].中国激光,2011.38(4)：0405004-1-6.
[105]谢作生,李伟文,林伟鹏等.利用扫频光纤激光器实现低频周期振动传感[J].中国激光,2011,38(12)：133-137.
[106]Hiroshi Tsuda, Jung-Ryul Lee, Yisheng Guan, et al. Investigation of fatigue crack in stainless steel using a mobile fiber Bragg grating ultrasonic sensor[J]. Optical Fiber Technology,2007,13(3):209-214
[107]J.S. Sakellariou, S.D. Fassois. Vibration Based Fault Detection and Identification in an Aircraft Skeleton Structure via a Stochastic Functional Model Based Method[J]. Mechanical Systems and Signal Processing,2008,22(3):557-573
[108]岳丽娜,黄俊,姜德生.光纤传感技术在长江二桥加固监测中的应用[J].武汉理工大学学报,2009,31(2)：10-12.
[109]张东生,李微,郭丹等.基于光纤光栅振动传感器的桥梁索力实时监测[J].传感技术学报,2007,20(12)：2720-2723.
[110]Kyungmok K I M, Lee J M, Hwang Y. Torsion Measurement using Fiber Bragg Grating Sensors and a Rotary Optical Coupler[J].15th International Congress on Sound and Vibration 6-10 July 2008, Daejeon, Korea:2529-2536
[111]范钦珊.材料力学[M].北京,高等教育出版社,2000.
[112]Udd E, Spillman W B. Fiber optic sensors[M]. John Wiley & Sons,1991.
[113]张玉贵.烟气轮机叶片振动的非接触式在线监测关键技术研究[D].天津大学,2008.
[114]张锦,刘晓平,叶轮机振动模态分析理论及数值方法[M].北京：国防工业出版社,2001
[115]沈达宽,航空发动机强度计算,北京：国防工业出版社,1980
[116]王宇华.高速旋转叶片振动叶端定时测量方法和系统研究[D].,2003.
[117]华东电力试验研究所,江苏省电力试验研究所,南京工学院,汽轮机振动特性和调整[M].北京：电力工业出版社,1981.
[118]Seongkuk Lee, Dongfang Yang, Suwas Nikumb. Femtosecond laser micro-milling of Si wafers[J], Applied Surface Science,2008,254 (10):2996-3005
[119]P. Moreno, C. Mendez, A. Garci, I. Arias, L. Rosoa. Femtosecond laser ablation of carbon reinforced polymers[J]. Applied Surface Science,2006,252 (12):4110-4119.
[120]R. Le Harzic, D. Breitling, M.Weikert, S. Sommer. Ablation comparison with low and high energy densities for Cu and A1 with ultra-short laser pulses[J]. Materials Science & Processing,2005,80(7):1589-1593.
[121]R. Le Harzica, D. Breitlinga, M. Weikert, S. Sommer, C.Fohl, S. Valettec, C. Donnet, E. Audouardc, F. Dausinge. Pulse width and energy influence on laser micromachining of metals in a range of 100 fs to 5 ps[J]. Applied Surface Science.2005,249(1-4):322-331.
[122]M. Hashida, A.F Semerok, O. Gobert, G. Petite, Y. Izawa, J.F. Wagner. Ablation threshold dependence on pulse duration for copper[J]. Applied surface science.2002,(197-198): 862-867.
[123]Leon R L, Scheibel J R. Current status of the EPRI acoustic Doppler blade.monitor EPRJ steam turbine blade reliability workshop[J]. Los Angeles,1986.
[124]И.E.萨勃洛斯基等著,吴士祥,郑叔琛译,涡轮机叶片振动的非接触测量[M],北京：国防工业出版社,1986
[125]Sever I A. Experimental validation of turbomachinery blade vibration predictions[D]. Imperial College London (University of London),2004.
[126]Robert L L, Keith T. Monitoring Systems for Steam Turbine Blade Faults[J]. Sound and Vibration/February,1990.
[127]S. Kuhnt, J. Wernicke, J. Shadden, R. Byars. Advanced Wind Turbine Controls Input Based on Real Time Loads Measured with Fibre Optical Sensors Embedded in Rotor Blades[J]. the European Wind Energy Conference & Exhibition,2006.
[128]Schroeder K, Ecke W, Apitz J, et al. A fibre Bragg grating sensor system monitors operational load in a wind turbine rotor blade[J]. Measurement Science and Technology, 2006,17(5):1167.
[129]Dorsey G. Fiber optic rotary joints-a review[J].Components, Hybrids, and Manufacturing Technology, IEEE Transactions on,1982,5(1):37-41.
[130]Jing W, Jia D, Tang F, et al. Design and implementation of a broadband optical rotary joint using C-lenses[J]. Optics express,2004,12(17):4088-4093.
[131]陈传尧.疲劳与断裂[M].武汉：华中科技大学出版社,2005.
[132]邓增杰,周敬恩.工程材料的断裂与疲劳[M].机械工业出版社,1995.
[133]赵俊龙.往复式压缩机振动信号特征分析及故障诊断方法研究[D].大连理工大学,2010.
[134]高金吉.机泵群实时监测网络和故障诊断专家系统[J].中国工程科学,2001,3(9)：41-47.
[135]何嘉武.樊新海,基于振动烈度的机械状态监测方法及应用[J].仪器仪表学报,2010,31(4)：37-39.
[136]陈云,江志农,高金吉.基于LabVIEW的大型往复式氢气压缩机组在线监测系统开发[J].北京化工大学学报：2003,30(2)：63-65.
[137]Ahmed M, Abdusslam S, Baqqar M, et al. Fault classification of reciprocating compressor based on Neural Networks and Support Vector Machines[C]. Automation and Computing (ICAC),2011 17th International Conference on. IEEE,2011:213-218.
[138]Yang B S, Hwang W W, Kim D J, et al. Condition classification of small reciprocating compressor for refrigerators using artificial neural networks and support vector machines[J]. Mechanical Systems and Signal Processing,2005,19(2):371-390.
[139]Prata A T, Fernandes J R S, Fagotti F. Dynamic analysis of piston secondary motion for small reciprocating compressors[J]. Journal of tribology,2000,122(4):752-760.
[140]Hanna R, Schmitt D W. Failure analysis of 7500 HP induction motors driving reciprocating compressors with three years service[C]. Petroleum and Chemical Industry Conference (PCIC),2010 Record of Conference Papers Industry Applications Society 57th Annual. IEEE,2010:1-6.