多支承转子系统轴承载荷与振动耦合特性研究
|
摘要
随着汽轮发电机组等大型设备的日益细长化和复杂化,转子的支承点逐渐增多,对转子系统的状态监测和故障诊断也提出了更高的要求。多支承转子系统中轴承载荷是影响轴系稳定性的重要因素,同时轴承载荷的变化又与转子以及支承的振动存在耦合效应。单纯通过振动诊断技术可以诊断轴系失稳后产生的自激振动,但对于多支承转子系统自激振动的振源无法识别,这就给设备的维修和调整带来了巨大的困难。本文以大型汽轮发电机组的核心部件——多支承转子系统为研究对象,重点研究了轴承载荷变化与系统振动的耦合特性,研究结果一方面丰富了转子系统的振动诊断技术,另一方面为多支承转子系统自激振动振源的识别奠定了基础。
本文通过理论推导,提出了轴承径向位置(水平方向和垂直方向)的识别模型。首先通过集中质量得到多支承转子系统的简化模型,在此基础上利用传递矩阵求出静态和动态下轴承载荷的分配计算公式。其次研究了轴承径向位置变化和轴承载荷变化对各支承轴承载荷的影响,并得到敏感度矩阵。最后利用敏感度矩阵建立了轴承位置和轴承载荷的识别模型。
研究了试验台中轴承载荷工况监测的实现。轴承载荷的实时监测是轴系运行状况最直接最有效的监测手段,但由于安装的限制,使得轴承载荷的现场工况监测存在难度。为了研究轴承载荷与振动的耦合关系,本文对多支承转子试验台的轴承载荷工况监测进行了研究,分析了轴承载荷动态测量的可能性,提出利用间接测量法实现对轴承载荷的动态测量。介绍了课题组设计的某轴承载荷传感器；通过标定实验、回归分析,得到其静态特性性能指标；针对动态特性分别进行了采样分析、虚拟实验和有限元分析；重点研究了传感器的安装对转子系统动力学的影响。最后通过多支承转子试验台进行了实验验证。
提出了轴承载荷变化对多支承转子系统振动的耦合效应。针对轴承位置改变和扭矩扰动两种干扰源下轴承载荷的变化进行了动力学分析,研究了各支承点之间振动的传递性,建立了轴承载荷与转子系统的耦合振动模型,并通过龙格库塔法进行了数值分析。利用ANSYS软件对八支承转子系统进行了建模,计算了该系统的临界转速,针对柔性和刚性两种转子系统轴承径向位置变化与各支承点的振动特性进行了动力学分析与仿真,并得到各支承点的轴心轨迹特征,进一步提出利用轴心轨迹对轴承径向位置进行模糊识别的方法。
建立了八支承转子系统试验台,对轴承径向位置变化和扭矩扰动进行了模拟试验,得到不同支承处的轴承载荷值、振动特性以及轴心轨迹图,利用试验结果对轴承径向位置的识别和耦合特性进行了实验验证。
As the turbine-generator unit and other large equipment were increasingly slenderized and more complex, the support points of rotor are increasing. The rotor system condition monitoring and fault diagnosis is also putting forward higher requirements. Bearing load in the multi-support rotor system is an important factor that affects the stability of the axis, while the change in bearing load has the coupling effect on the vibration of the supports of rotor. Vibration diagnostic techniques can diagnose the self-excited vibration results from the axis vibration instability, but for the self-excited vibration sources of multi-support rotor aren't recognized. That brings great difficulties in the repairing and adjustment of the equipment. This paper's research object is a large turbine generator's core component, multi-support rotor system. It focuses on the coupling characteristics between the bearing load changes and system vibration. On the one hand, these results enrich the rotor system vibration diagnostic techniques, on the other hand they provide a foundation for the recognition of the self-excited vibration sources of the multi-support rotor system.
In this paper, it proposed the recognition model of the bearing radial position (horizontal and vertical) through the theoretical analysis. Firstly, it had a simplified model of the multi-support rotor system by lumped mass. On the base of this, the static and dynamic bearing load distribution formula are obtained through the transfer matrix. Secondly, it got the sensitivity matrix through the study of the impact of the support bearing loads between the change of the location of the bearings and the bearing load. Finally, it established the identification model of the bearing location and the bearing load by using the sensitivity matrix.
This paper studied how implemented the bearing load condition monitoring in the test. Real-time monitoring of the bearing load is the most direct and effective means of monitoring for axis running condition. However, due to the installation constraints, it had the difficulties in the on-site monitoring of the bearing load condition. To study the coupling relationship between the bearing load and vibration in the multi-support rotor system, we studied the real-time monitoring of the bearing load condition and analyzed the possibilities of the dynamic measuring of the bearing load. In the paper, it proposed the indirect measurement of achieving the dynamic measurement of the bearing load. This paper described a bearing load sensor. To get the static characteristics performance index, we did a lot of calibrating experiments and the regression analysis. To get the dynamics characteristics performance index, we carried out the sampling analysis, virtual experiments and finite element analysis. We focused on the rotor system dynamics effects of the installation of the sensor. Finally, it had the experimental verification on the multi-support rotor test.
The paper proposed the coupling effects on the rotor system vibration because of the change of multi-support bearing load. It carried on the dynamic analysis of the bearing load changes under the two kinds of the interference. That is the case of the bearing's location change and torque disturbance. That examined the transfer of vibration between the support points and established a coupling vibration model between the bearing load and the rotor system and did the numerical analysis through the Runge-Kutta methods. That did the modeling system of the8support rotors with the help of the ANSYS software and calculated the critical speed of the system. For the two sides of position changes of the flexible and rigid rotor system and the vibration characteristics of the support points, we did a dynamic analysis and simulation and got the axis orbit features of all the support points. In addition, it proposed the fuzzy recognition method of the radial position of the bearing by using the axis orbit trajectories.
8support rotor system test bed was established and radial position changes and torque disturbances of the bearing was simulated. That got the different values of bearing load, vibration characteristics and the axis orbit trajectories. In the end that did a lot of experimental verification of the identification of the bearing's radial location and coupling characteristics by the test results.
本文通过理论推导,提出了轴承径向位置(水平方向和垂直方向)的识别模型。首先通过集中质量得到多支承转子系统的简化模型,在此基础上利用传递矩阵求出静态和动态下轴承载荷的分配计算公式。其次研究了轴承径向位置变化和轴承载荷变化对各支承轴承载荷的影响,并得到敏感度矩阵。最后利用敏感度矩阵建立了轴承位置和轴承载荷的识别模型。
研究了试验台中轴承载荷工况监测的实现。轴承载荷的实时监测是轴系运行状况最直接最有效的监测手段,但由于安装的限制,使得轴承载荷的现场工况监测存在难度。为了研究轴承载荷与振动的耦合关系,本文对多支承转子试验台的轴承载荷工况监测进行了研究,分析了轴承载荷动态测量的可能性,提出利用间接测量法实现对轴承载荷的动态测量。介绍了课题组设计的某轴承载荷传感器；通过标定实验、回归分析,得到其静态特性性能指标；针对动态特性分别进行了采样分析、虚拟实验和有限元分析；重点研究了传感器的安装对转子系统动力学的影响。最后通过多支承转子试验台进行了实验验证。
提出了轴承载荷变化对多支承转子系统振动的耦合效应。针对轴承位置改变和扭矩扰动两种干扰源下轴承载荷的变化进行了动力学分析,研究了各支承点之间振动的传递性,建立了轴承载荷与转子系统的耦合振动模型,并通过龙格库塔法进行了数值分析。利用ANSYS软件对八支承转子系统进行了建模,计算了该系统的临界转速,针对柔性和刚性两种转子系统轴承径向位置变化与各支承点的振动特性进行了动力学分析与仿真,并得到各支承点的轴心轨迹特征,进一步提出利用轴心轨迹对轴承径向位置进行模糊识别的方法。
建立了八支承转子系统试验台,对轴承径向位置变化和扭矩扰动进行了模拟试验,得到不同支承处的轴承载荷值、振动特性以及轴心轨迹图,利用试验结果对轴承径向位置的识别和耦合特性进行了实验验证。
As the turbine-generator unit and other large equipment were increasingly slenderized and more complex, the support points of rotor are increasing. The rotor system condition monitoring and fault diagnosis is also putting forward higher requirements. Bearing load in the multi-support rotor system is an important factor that affects the stability of the axis, while the change in bearing load has the coupling effect on the vibration of the supports of rotor. Vibration diagnostic techniques can diagnose the self-excited vibration results from the axis vibration instability, but for the self-excited vibration sources of multi-support rotor aren't recognized. That brings great difficulties in the repairing and adjustment of the equipment. This paper's research object is a large turbine generator's core component, multi-support rotor system. It focuses on the coupling characteristics between the bearing load changes and system vibration. On the one hand, these results enrich the rotor system vibration diagnostic techniques, on the other hand they provide a foundation for the recognition of the self-excited vibration sources of the multi-support rotor system.
In this paper, it proposed the recognition model of the bearing radial position (horizontal and vertical) through the theoretical analysis. Firstly, it had a simplified model of the multi-support rotor system by lumped mass. On the base of this, the static and dynamic bearing load distribution formula are obtained through the transfer matrix. Secondly, it got the sensitivity matrix through the study of the impact of the support bearing loads between the change of the location of the bearings and the bearing load. Finally, it established the identification model of the bearing location and the bearing load by using the sensitivity matrix.
This paper studied how implemented the bearing load condition monitoring in the test. Real-time monitoring of the bearing load is the most direct and effective means of monitoring for axis running condition. However, due to the installation constraints, it had the difficulties in the on-site monitoring of the bearing load condition. To study the coupling relationship between the bearing load and vibration in the multi-support rotor system, we studied the real-time monitoring of the bearing load condition and analyzed the possibilities of the dynamic measuring of the bearing load. In the paper, it proposed the indirect measurement of achieving the dynamic measurement of the bearing load. This paper described a bearing load sensor. To get the static characteristics performance index, we did a lot of calibrating experiments and the regression analysis. To get the dynamics characteristics performance index, we carried out the sampling analysis, virtual experiments and finite element analysis. We focused on the rotor system dynamics effects of the installation of the sensor. Finally, it had the experimental verification on the multi-support rotor test.
The paper proposed the coupling effects on the rotor system vibration because of the change of multi-support bearing load. It carried on the dynamic analysis of the bearing load changes under the two kinds of the interference. That is the case of the bearing's location change and torque disturbance. That examined the transfer of vibration between the support points and established a coupling vibration model between the bearing load and the rotor system and did the numerical analysis through the Runge-Kutta methods. That did the modeling system of the8support rotors with the help of the ANSYS software and calculated the critical speed of the system. For the two sides of position changes of the flexible and rigid rotor system and the vibration characteristics of the support points, we did a dynamic analysis and simulation and got the axis orbit features of all the support points. In addition, it proposed the fuzzy recognition method of the radial position of the bearing by using the axis orbit trajectories.
8support rotor system test bed was established and radial position changes and torque disturbances of the bearing was simulated. That got the different values of bearing load, vibration characteristics and the axis orbit trajectories. In the end that did a lot of experimental verification of the identification of the bearing's radial location and coupling characteristics by the test results.
引文
[1]李朝峰.耦合故障复杂转子-轴承非线性系统的运行稳定性及其实验研究[D].沈阳：东北大学,2009.
[2]李录平.汽轮机组故障诊断技术[M].北京：中国电力出版社,2002.
[3]徐龙祥.高速旋转机械轴系动力学设计[M].北京：国防工业出版社,1994.
[4]虞烈,刘恒.轴承转子系统动力学[M].西安：西安交通大学出版社,2001.
[5]钟一谔等.转子动力学[M].北京：清华大学出版社,1987.
[6]顾家柳等.转子动力学[M].北京：国防工业出版社,1985.
[7]李建国,朱均,虞烈.多个滑动轴承支承的转子系统稳定性研究[J].应用力学学报,1990,7(3).
[8]孟光.转子动力学研究的回顾与展望[J].振动工程学报,2002,15(1)：1-7.
[9]张卫,朱均.大型转子—滑动轴承系统运动稳定性的研究[J].西安交通大学学报,1995,29(8)：65-70.
[10]Mohsen Rahimi. Mostafa Parniani. Dynamic behavior and transient stability analysis of fixed speed wind turbines[J].Renewable Energy,2009,6(8),1-12.
[11]李震,桂长林.变载荷作用下轴-轴承系统动力学行为研究[J].机械设计与研究,2005,21(1)：12-16.
[12]杨金福,杨晟博,陈策等.滑动轴承-转子系统的稳定性研究[J].航空动力学报,2008,23(8)：1420-1427.
[13]F.Jurado a, J. Carpio b. Improving distribution system stability by predictive control of gas turbines [J]. Energy Conversion and Management,2006,47:2961-2973.
[14]闻邦椿.高等转子动力学[M].北京：机械工业出版社,2000.
[15]黄文虎,武新华,焦映厚等.非线性转子动力学研究综述[J].动力工程,2000,13(4)：497-509.
[16]J.W. Larsena, R. Iwankiewiczb, S.R.K. Nielsena. Nonlinear stochastic stability analysis of wind turbine wings by Monte Carlo simulations[J]. Probabilistic Engineering Mechanics,2007,(22):181-193.
[17]Heung Soo Kima, Maenghyo Chob, Seung Jin Songb. Stability analysis of a turbine rotor system with Alford forces[J]. Journal of Sound and Vibration,2006,(260):167-182.
[18]Quanyuan Jianga, Shijie Chenga,Yijia Caob. Lyapunov stability analysis of turbine-generator including shaft system[J]. Electrical Power and Energy Systems, 2003,(25):741-746.
[19]寇胜利.汽轮发电机组的振动及现场平衡[M].北京：中国电力出版社,2007.
[20]黄文振.国产200M机组轴承负荷分析[J].重庆大学学报,1993,16(1)：25-31.
[21]刘荣强,夏松波,汪光明.汽轮发电机组轴系稳定性的诊断方法[J].汽轮机技术,1994,36(6)：327-332.
[22]崔颖,刘占生.200MW汽轮发电机组转子-轴承系统非线性稳定性研究[J].机械工程学报,2005,41(2)：170-175.
[23]戴其兵,傅行军.大型汽轮发电机组标高对轴承载荷的影响[J].江苏电机工程,2008,27(2)：64—66.
[24]彭泽军.大型机组轴承负荷异常诊断及其Internet调用方法研究[D].太原：太原理工大学,2002.
[25]杨建刚,周世新,黄葆华.多支撑汽轮发电机组轴承载荷灵敏度计算与分析[J].中国电机工程学报,2000,20(7)：79-82.
[26]杨建刚.旋转机械振动分析与工程应用[M].北京：中国电力出版社,2007.
[27]陈焰,袁小阳,孟庆集.秦岭电厂4号机轴承负荷识别[J]].西北电力技术,2001,(5)：29-42.
[28]呼浩,陈焰.汽轮发电机组轴系稳定性诊断的研究[J].西北电力技术,2005,(1)：36-39.
[29]田新启,高斖.二维PSD及其在轴系标高变化测试中的应用[J].传感器与微系统,2010.30(6)：638-641.
[30]杨兆建,丛红,谢友柏.大型汽轮发电机组四可倾瓦轴承负荷传感器的研究[J].机械科学与技术.1998,3(2)：247-249.
[31]杨兆建,谢友柏.大型汽轮发电机组轴承负荷在线监测方法研究[J].中国机械工程.1997,8(4).89-91.
[32]Wang Q.X., Yang Z. J., Ren F., Peng Z.J., Study on the Bearing Load Measuring Method of Multi-Support Rotor Bearing System[C]. Proceedings of 5th International Symposium on Test/Measurement Technology, Shenzhen, China, October,2003, v 4,3007-3010.
[33]施维新.机组振动故障诊断方法的研究[J].中国电力,1996,29(3)：15-19.
[34]张海军.机械故障诊断和预测中的信息提取[D].西安：西安交通大学,2002.
[35]A. Guascha, J. Quevedoa, R. Milneb. Fault diagnosis for gas turbines based on the control system[J]. Engineering Applications of Artificial Intelligence,2000,13:477-484.
[36]Silvio Simania, Cesare Fantuzzib. Dynamic system identification and model-based fault diagnosis of an industrial gas turbine prototype[J]. Mechatronics,2006,16:341-363.
[37]S.O.T. Ogaji, R. Singh, S.D. Probert. Multiple-sensor fault-diagnoses for a 2-shaft stationary gas-turbine [J]. Applied Energy,2002,71:321-339.
[38]阮跃.国产200MW机组常见故障的诊断和预防[J].汽轮机技术,1997,39(4)：200-205.
[39]李录平.汽轮发电机组振动与处理[M].北京：中国电力出版社,2007.
[40]施维新,石静波.汽轮机发电机组振动及事故[M].北京：中国电力出版社,2008.
[41]谷敬佩,梁平.汽轮机转子振动故障诊断新方法[J].湖北电力,2009,33(1)：37-39.
[42]D.F. Shi, W.J. Wang, P.J. Unsworthb etc. Purification and feature extraction of shaft orbits for diagnosing large rotating machinery[J]. Journal of Sound and Vibration, 2005,279:581-600.
[43]Kim,Passinob. Fault diagnosis for a turbine engine[J]. Control Engineering Practice, 2004,12:1151-1165.
[44]Murat Uyara, Selcuk Yildirima, Muhsin Tunay Gencoglub. An effective wavelet-based feature extraction method for classification of power quality disturbance signals[J].Electric Power Systems Research,2008,(78):1747-1755.
[45]S.K. LEE, P. R. WHITE. The Enhancement of Impulsive Noise and Vibration Signals for Fault Detection in Rotation and Reciprocating Machinery[J]. Journal of Sound and Vibration,1998,217(3):485-505.
[46]何正嘉,陈进.机械故障诊断理论及方法[M].北京：高等教育出版社,2010.
[47]廖庆斌,李舜酩.一种旋转机械振动信号特征提取的新方法[J].中国机械工程,2006,17(16)：1675-1679.
[48]Li Lin, Ji Hongbing. Signal feature extraction based on an improved EMD method[J].Measurement,2009,(42):796-803.
[49]褚福磊,彭志科,冯志鹏等.机械故障诊断中的现代信号处理方法[D].北京：科学出版社,2009.
[50]张艾萍,暴丽,叶荣学.汽轮机组振动故障多征兆模糊诊断专家系统及其应用[J].化工机械,2004,31(2)：71-74.
[51]A. Vaziri, H. Nayeb-Hashemi. A theoretical investigation on the vibrational characteristics and torsional dynamic response of circumferentially cracked turbo-generator shafts[J]. Solids and Structures,2006,(43):4063-4081.
[52]Jun Ye. Fault diagnosis of turbine based on fuzzy cross entropy of vague sets[J]. Expert Systems with Applications,2009,(36):8103-8106.
[53]吴明强,史慧,朱晓华等.故障诊断专家系统研究的现状与展望[J].计算机测量与控制,2005,13(12)：1301-1304.
[54]S.O.T. Ogaji, S. Sampath, L. Marinai etc. Evolution strategy for gas-turbine fault-diagnoses[J]. Applied Energy,2005, (81):222-230.
[55]Abdulhamit Subasi. EEG signal classification using wavelet feature extraction and a mixture of expert model[J]. Expert Systems with Applications,2007, (32):1084-1093.
[56]Bojan Kotnik, Zdravko Kacic. A noise robust feature extraction algorithm using joint wavelet packet subband decomposition and AR modeling of speech signals[J]. Signal Processing,2007, (87):1202-1223.
[57]马建仓,吴启彬.小波-神经网络-模糊识别在旋转机械故障诊断中的应用研究[J].机械科学与技术,1999,18(3)：459-462.
[58]张国斌.旋转机械故障诊断知识获取的理论与方法研究[D].哈尔滨：哈尔滨工业大学,2000.
[59]叶大鹏.基于2D-HMM的旋转机械故障诊断方法及其应用研究[D].杭州：浙江大学,2004.
[60]宋雪萍.旋转机械故障诊断若干理论与技术的研究[D].长春：东北大学,2005.
[61]张燕平.汽轮机轴系振动故障诊断中的信息融合方法研究[D].武汉：华中科技大学,2006.
[62]Peng,F.CHU, Y. HE. Vibration Signal Analysis and Feature Extraction Based on Reassigned Wavelet Scalogram[J]. Journal of Sound and Vibration,2002,253(5): 1087-1100.
[63]Elif Derya Ubeyli, Inan Guler. Feature extraction from Doppler ultrasound signals for automated diagnostic systems[J]. Computers in Biology and Medicine,2005, (35): 735-764.
[64]刘元峰.多故障转子系统非线性特性及转子故障信号分析方法的研究[D].上海：上海交通大学,2003.
[65]李晓峰.基于动力学的转子系统主要故障特征的研究[D].武汉：华中科技大学,2001.
[66]路海燕.多维轴承载荷传感器结构优化设计[D].太原：太原理工大学,2008.
[67]刘迎春.传感器原理、设计与应用[M].北京：国防科技大学出版社,1997.
[68]黄贤武,郑筱霞.传感器原理与应用[M].成都：电子科技大学出版社.1995.
[69]X.Y. Pang, Z.J. Yang, H.Y. Lu, Q.L. Liang & H. Sun. Seventh International Symposium on Instrumentation and Control Technology[C].'ISICT'2008,2008.10, Vol.7121,p.A.
[70]太原理工大学理学院数学系.应用数理统计[M].太原：太原理工大学,2001.
[71]陶仁诚,郭海峰.传感器动态特性方法研究[J].中国井矿盐,2006,7(4),35-38.
[72]丁卉.现代控制工程基础虚拟实验系统的研究[D].太原：太原理工大学,2011.
[73]机械设计手册编委会.机械设计手册(机械振动和噪声单行本)[M].北京：机械工业出版社,2007.
[74]李国华,张永忠.机械故障诊断[M].北京：化学工业出版社,1999.
[75]周长城,胡仁喜,熊文波ANSYS11.0基础与典型范例[M].北京：电子工业出版社,2007.
[76]翟霄雁,马金奎,路长厚.应变式油膜压力测量传感器特性研究[J].润滑与密封.2006(4),113-114.
[77]庞新宇,杨兆建,梁群龙等.转子系统轴承载荷传感器动态特性分析[J].太原理工大学学报,2009,40(5),461-464.
[78]Pang Xinyu, Yang Zhaojian. Analysis to Dynamic Characteristics Influence on Bearing-Load sensor to the Rotor System[J]. Advanced materials research, Vol.308-310(2011), 2551-2554.
[79]韩清凯,于涛等.故障转子系统的非线性振动分析与诊断方法[M].北京：科学出版社,2010.
[80]张艾萍,王德状,李守海.汽轮机组振动幅值与轴承载荷及油膜刚度之间的关系[J].汽轮机技术,2002,44(2)：80-81.
[81]李庆扬,王能超,易大义.数值分析[M].北京：清华大学出版社,2008.
[82]John H.Mathews, Kurtis D. Fink.数值方法[M].北京：电子工业出版社,2010.
[83]吴旭光,杨惠珍,王新民.计算机仿真技术[M].北京：化学工业出版社,2008.
[84]孙虎儿.基于扭矩激励的多轮盘细长轴转子系统弯振特性[D].太原：太原理工大学,2010.
[85]成大先.轴及其联接[M].机械设计手册,2004,32-35.
[86]吴淇泰.振动分析[M].杭州：浙江大学出版社,1999,2(10)：17-21.
[87]张锁怀,李磊,张江峰.基于ANSYS的曲轴—滑动轴承系统动力学模型的研究[J].系统仿真学报,2008,20(20)：5706-5706.
[88]Charles L.Kessler. Complex Modal Analysis of Rotating Machinery Doctorate of Philosophy[C]. University of Dayton,1991.
[89]张利民,王克明,吴志广.利用ANSYS进行转子临界转速计算[J].沈阳航空工业学院学报,2010,27(5)：34-37.
[90]徐哲,张介禄,焦映厚.200MW机组转子-轴承系统非线性动力学特性分析[J].机械工程师.2010,107(9).
[91]Farouk O.Hamdoon. Application of a Finite Element Package for Modeling[J]. Rotating Machinery Vibrations.Vol.27,No.12,2009.
[92]缪红燕,高金吉,徐鸿.转子系统瞬态不平衡响应的有限元分析[J].振动与冲击.2004,23(3).
[93]金晓娜,李帆,朱向哲.大型机组电机转子振动特性的有限元分析[J].辽宁石油化工大学学报,2008,28(4)：34-37.
[94]N.Lesaffre,J.-J.Sinou,F.Thouverez.Stability analysis of rotating beams rubbing on an elastic circular structure[J] Journal of Sound and Vibration,2007 (299),1005-1032.
[95]王学厚,张楠,董泽.基于模糊聚类分析的汽轮机振动故障自动诊断研究[J].汽轮机技术,2009,51(1)：58-60.
[96]黄文涛,赵学增,王伟杰.汽轮发电机组振动故障诊断的粗糙集模型[J].电力系统自动化,2004,28(15)：80-86.
[97]徐扬.模糊模式识别及其应用[M].成都：西南交通大学出版社,1999.
[98]边肇祺,张学工.模式识别[M].北京：清华大学出版社,2000.
[99]崔广心.相似理论与模型试验[M].徐州：中国矿业大学出版社.1990.
[100]席文奎.多支承转子—轴承系统轴承负荷辨识试验台设计及动力学分析[D].太原：太原理工大学,2007.
[101]Liang Qunlong,Sun Huer,Xi Wenkui etc. Design of Testing System on Test-bed of Large-scale Multi-support Rotor-bearing System[C]. Proceedings of the 7th International Symposium on Test and Measurement Beijing,China:2007,371-374.
[102]庞新宇,杨兆建,梁群龙等.轴承转子试验台测试系统设计及抗干扰技术[J].汽轮机技术,2010,52(5)：332-335.
[103]孙传友,孙晓斌.测控系统原理与设计[M].北京：北京航空航天大学出版社,2007.
[2]李录平.汽轮机组故障诊断技术[M].北京：中国电力出版社,2002.
[3]徐龙祥.高速旋转机械轴系动力学设计[M].北京：国防工业出版社,1994.
[4]虞烈,刘恒.轴承转子系统动力学[M].西安：西安交通大学出版社,2001.
[5]钟一谔等.转子动力学[M].北京：清华大学出版社,1987.
[6]顾家柳等.转子动力学[M].北京：国防工业出版社,1985.
[7]李建国,朱均,虞烈.多个滑动轴承支承的转子系统稳定性研究[J].应用力学学报,1990,7(3).
[8]孟光.转子动力学研究的回顾与展望[J].振动工程学报,2002,15(1)：1-7.
[9]张卫,朱均.大型转子—滑动轴承系统运动稳定性的研究[J].西安交通大学学报,1995,29(8)：65-70.
[10]Mohsen Rahimi. Mostafa Parniani. Dynamic behavior and transient stability analysis of fixed speed wind turbines[J].Renewable Energy,2009,6(8),1-12.
[11]李震,桂长林.变载荷作用下轴-轴承系统动力学行为研究[J].机械设计与研究,2005,21(1)：12-16.
[12]杨金福,杨晟博,陈策等.滑动轴承-转子系统的稳定性研究[J].航空动力学报,2008,23(8)：1420-1427.
[13]F.Jurado a, J. Carpio b. Improving distribution system stability by predictive control of gas turbines [J]. Energy Conversion and Management,2006,47:2961-2973.
[14]闻邦椿.高等转子动力学[M].北京：机械工业出版社,2000.
[15]黄文虎,武新华,焦映厚等.非线性转子动力学研究综述[J].动力工程,2000,13(4)：497-509.
[16]J.W. Larsena, R. Iwankiewiczb, S.R.K. Nielsena. Nonlinear stochastic stability analysis of wind turbine wings by Monte Carlo simulations[J]. Probabilistic Engineering Mechanics,2007,(22):181-193.
[17]Heung Soo Kima, Maenghyo Chob, Seung Jin Songb. Stability analysis of a turbine rotor system with Alford forces[J]. Journal of Sound and Vibration,2006,(260):167-182.
[18]Quanyuan Jianga, Shijie Chenga,Yijia Caob. Lyapunov stability analysis of turbine-generator including shaft system[J]. Electrical Power and Energy Systems, 2003,(25):741-746.
[19]寇胜利.汽轮发电机组的振动及现场平衡[M].北京：中国电力出版社,2007.
[20]黄文振.国产200M机组轴承负荷分析[J].重庆大学学报,1993,16(1)：25-31.
[21]刘荣强,夏松波,汪光明.汽轮发电机组轴系稳定性的诊断方法[J].汽轮机技术,1994,36(6)：327-332.
[22]崔颖,刘占生.200MW汽轮发电机组转子-轴承系统非线性稳定性研究[J].机械工程学报,2005,41(2)：170-175.
[23]戴其兵,傅行军.大型汽轮发电机组标高对轴承载荷的影响[J].江苏电机工程,2008,27(2)：64—66.
[24]彭泽军.大型机组轴承负荷异常诊断及其Internet调用方法研究[D].太原：太原理工大学,2002.
[25]杨建刚,周世新,黄葆华.多支撑汽轮发电机组轴承载荷灵敏度计算与分析[J].中国电机工程学报,2000,20(7)：79-82.
[26]杨建刚.旋转机械振动分析与工程应用[M].北京：中国电力出版社,2007.
[27]陈焰,袁小阳,孟庆集.秦岭电厂4号机轴承负荷识别[J]].西北电力技术,2001,(5)：29-42.
[28]呼浩,陈焰.汽轮发电机组轴系稳定性诊断的研究[J].西北电力技术,2005,(1)：36-39.
[29]田新启,高斖.二维PSD及其在轴系标高变化测试中的应用[J].传感器与微系统,2010.30(6)：638-641.
[30]杨兆建,丛红,谢友柏.大型汽轮发电机组四可倾瓦轴承负荷传感器的研究[J].机械科学与技术.1998,3(2)：247-249.
[31]杨兆建,谢友柏.大型汽轮发电机组轴承负荷在线监测方法研究[J].中国机械工程.1997,8(4).89-91.
[32]Wang Q.X., Yang Z. J., Ren F., Peng Z.J., Study on the Bearing Load Measuring Method of Multi-Support Rotor Bearing System[C]. Proceedings of 5th International Symposium on Test/Measurement Technology, Shenzhen, China, October,2003, v 4,3007-3010.
[33]施维新.机组振动故障诊断方法的研究[J].中国电力,1996,29(3)：15-19.
[34]张海军.机械故障诊断和预测中的信息提取[D].西安：西安交通大学,2002.
[35]A. Guascha, J. Quevedoa, R. Milneb. Fault diagnosis for gas turbines based on the control system[J]. Engineering Applications of Artificial Intelligence,2000,13:477-484.
[36]Silvio Simania, Cesare Fantuzzib. Dynamic system identification and model-based fault diagnosis of an industrial gas turbine prototype[J]. Mechatronics,2006,16:341-363.
[37]S.O.T. Ogaji, R. Singh, S.D. Probert. Multiple-sensor fault-diagnoses for a 2-shaft stationary gas-turbine [J]. Applied Energy,2002,71:321-339.
[38]阮跃.国产200MW机组常见故障的诊断和预防[J].汽轮机技术,1997,39(4)：200-205.
[39]李录平.汽轮发电机组振动与处理[M].北京：中国电力出版社,2007.
[40]施维新,石静波.汽轮机发电机组振动及事故[M].北京：中国电力出版社,2008.
[41]谷敬佩,梁平.汽轮机转子振动故障诊断新方法[J].湖北电力,2009,33(1)：37-39.
[42]D.F. Shi, W.J. Wang, P.J. Unsworthb etc. Purification and feature extraction of shaft orbits for diagnosing large rotating machinery[J]. Journal of Sound and Vibration, 2005,279:581-600.
[43]Kim,Passinob. Fault diagnosis for a turbine engine[J]. Control Engineering Practice, 2004,12:1151-1165.
[44]Murat Uyara, Selcuk Yildirima, Muhsin Tunay Gencoglub. An effective wavelet-based feature extraction method for classification of power quality disturbance signals[J].Electric Power Systems Research,2008,(78):1747-1755.
[45]S.K. LEE, P. R. WHITE. The Enhancement of Impulsive Noise and Vibration Signals for Fault Detection in Rotation and Reciprocating Machinery[J]. Journal of Sound and Vibration,1998,217(3):485-505.
[46]何正嘉,陈进.机械故障诊断理论及方法[M].北京：高等教育出版社,2010.
[47]廖庆斌,李舜酩.一种旋转机械振动信号特征提取的新方法[J].中国机械工程,2006,17(16)：1675-1679.
[48]Li Lin, Ji Hongbing. Signal feature extraction based on an improved EMD method[J].Measurement,2009,(42):796-803.
[49]褚福磊,彭志科,冯志鹏等.机械故障诊断中的现代信号处理方法[D].北京：科学出版社,2009.
[50]张艾萍,暴丽,叶荣学.汽轮机组振动故障多征兆模糊诊断专家系统及其应用[J].化工机械,2004,31(2)：71-74.
[51]A. Vaziri, H. Nayeb-Hashemi. A theoretical investigation on the vibrational characteristics and torsional dynamic response of circumferentially cracked turbo-generator shafts[J]. Solids and Structures,2006,(43):4063-4081.
[52]Jun Ye. Fault diagnosis of turbine based on fuzzy cross entropy of vague sets[J]. Expert Systems with Applications,2009,(36):8103-8106.
[53]吴明强,史慧,朱晓华等.故障诊断专家系统研究的现状与展望[J].计算机测量与控制,2005,13(12)：1301-1304.
[54]S.O.T. Ogaji, S. Sampath, L. Marinai etc. Evolution strategy for gas-turbine fault-diagnoses[J]. Applied Energy,2005, (81):222-230.
[55]Abdulhamit Subasi. EEG signal classification using wavelet feature extraction and a mixture of expert model[J]. Expert Systems with Applications,2007, (32):1084-1093.
[56]Bojan Kotnik, Zdravko Kacic. A noise robust feature extraction algorithm using joint wavelet packet subband decomposition and AR modeling of speech signals[J]. Signal Processing,2007, (87):1202-1223.
[57]马建仓,吴启彬.小波-神经网络-模糊识别在旋转机械故障诊断中的应用研究[J].机械科学与技术,1999,18(3)：459-462.
[58]张国斌.旋转机械故障诊断知识获取的理论与方法研究[D].哈尔滨：哈尔滨工业大学,2000.
[59]叶大鹏.基于2D-HMM的旋转机械故障诊断方法及其应用研究[D].杭州：浙江大学,2004.
[60]宋雪萍.旋转机械故障诊断若干理论与技术的研究[D].长春：东北大学,2005.
[61]张燕平.汽轮机轴系振动故障诊断中的信息融合方法研究[D].武汉：华中科技大学,2006.
[62]Peng,F.CHU, Y. HE. Vibration Signal Analysis and Feature Extraction Based on Reassigned Wavelet Scalogram[J]. Journal of Sound and Vibration,2002,253(5): 1087-1100.
[63]Elif Derya Ubeyli, Inan Guler. Feature extraction from Doppler ultrasound signals for automated diagnostic systems[J]. Computers in Biology and Medicine,2005, (35): 735-764.
[64]刘元峰.多故障转子系统非线性特性及转子故障信号分析方法的研究[D].上海：上海交通大学,2003.
[65]李晓峰.基于动力学的转子系统主要故障特征的研究[D].武汉：华中科技大学,2001.
[66]路海燕.多维轴承载荷传感器结构优化设计[D].太原：太原理工大学,2008.
[67]刘迎春.传感器原理、设计与应用[M].北京：国防科技大学出版社,1997.
[68]黄贤武,郑筱霞.传感器原理与应用[M].成都：电子科技大学出版社.1995.
[69]X.Y. Pang, Z.J. Yang, H.Y. Lu, Q.L. Liang & H. Sun. Seventh International Symposium on Instrumentation and Control Technology[C].'ISICT'2008,2008.10, Vol.7121,p.A.
[70]太原理工大学理学院数学系.应用数理统计[M].太原：太原理工大学,2001.
[71]陶仁诚,郭海峰.传感器动态特性方法研究[J].中国井矿盐,2006,7(4),35-38.
[72]丁卉.现代控制工程基础虚拟实验系统的研究[D].太原：太原理工大学,2011.
[73]机械设计手册编委会.机械设计手册(机械振动和噪声单行本)[M].北京：机械工业出版社,2007.
[74]李国华,张永忠.机械故障诊断[M].北京：化学工业出版社,1999.
[75]周长城,胡仁喜,熊文波ANSYS11.0基础与典型范例[M].北京：电子工业出版社,2007.
[76]翟霄雁,马金奎,路长厚.应变式油膜压力测量传感器特性研究[J].润滑与密封.2006(4),113-114.
[77]庞新宇,杨兆建,梁群龙等.转子系统轴承载荷传感器动态特性分析[J].太原理工大学学报,2009,40(5),461-464.
[78]Pang Xinyu, Yang Zhaojian. Analysis to Dynamic Characteristics Influence on Bearing-Load sensor to the Rotor System[J]. Advanced materials research, Vol.308-310(2011), 2551-2554.
[79]韩清凯,于涛等.故障转子系统的非线性振动分析与诊断方法[M].北京：科学出版社,2010.
[80]张艾萍,王德状,李守海.汽轮机组振动幅值与轴承载荷及油膜刚度之间的关系[J].汽轮机技术,2002,44(2)：80-81.
[81]李庆扬,王能超,易大义.数值分析[M].北京：清华大学出版社,2008.
[82]John H.Mathews, Kurtis D. Fink.数值方法[M].北京：电子工业出版社,2010.
[83]吴旭光,杨惠珍,王新民.计算机仿真技术[M].北京：化学工业出版社,2008.
[84]孙虎儿.基于扭矩激励的多轮盘细长轴转子系统弯振特性[D].太原：太原理工大学,2010.
[85]成大先.轴及其联接[M].机械设计手册,2004,32-35.
[86]吴淇泰.振动分析[M].杭州：浙江大学出版社,1999,2(10)：17-21.
[87]张锁怀,李磊,张江峰.基于ANSYS的曲轴—滑动轴承系统动力学模型的研究[J].系统仿真学报,2008,20(20)：5706-5706.
[88]Charles L.Kessler. Complex Modal Analysis of Rotating Machinery Doctorate of Philosophy[C]. University of Dayton,1991.
[89]张利民,王克明,吴志广.利用ANSYS进行转子临界转速计算[J].沈阳航空工业学院学报,2010,27(5)：34-37.
[90]徐哲,张介禄,焦映厚.200MW机组转子-轴承系统非线性动力学特性分析[J].机械工程师.2010,107(9).
[91]Farouk O.Hamdoon. Application of a Finite Element Package for Modeling[J]. Rotating Machinery Vibrations.Vol.27,No.12,2009.
[92]缪红燕,高金吉,徐鸿.转子系统瞬态不平衡响应的有限元分析[J].振动与冲击.2004,23(3).
[93]金晓娜,李帆,朱向哲.大型机组电机转子振动特性的有限元分析[J].辽宁石油化工大学学报,2008,28(4)：34-37.
[94]N.Lesaffre,J.-J.Sinou,F.Thouverez.Stability analysis of rotating beams rubbing on an elastic circular structure[J] Journal of Sound and Vibration,2007 (299),1005-1032.
[95]王学厚,张楠,董泽.基于模糊聚类分析的汽轮机振动故障自动诊断研究[J].汽轮机技术,2009,51(1)：58-60.
[96]黄文涛,赵学增,王伟杰.汽轮发电机组振动故障诊断的粗糙集模型[J].电力系统自动化,2004,28(15)：80-86.
[97]徐扬.模糊模式识别及其应用[M].成都：西南交通大学出版社,1999.
[98]边肇祺,张学工.模式识别[M].北京：清华大学出版社,2000.
[99]崔广心.相似理论与模型试验[M].徐州：中国矿业大学出版社.1990.
[100]席文奎.多支承转子—轴承系统轴承负荷辨识试验台设计及动力学分析[D].太原：太原理工大学,2007.
[101]Liang Qunlong,Sun Huer,Xi Wenkui etc. Design of Testing System on Test-bed of Large-scale Multi-support Rotor-bearing System[C]. Proceedings of the 7th International Symposium on Test and Measurement Beijing,China:2007,371-374.
[102]庞新宇,杨兆建,梁群龙等.轴承转子试验台测试系统设计及抗干扰技术[J].汽轮机技术,2010,52(5)：332-335.
[103]孙传友,孙晓斌.测控系统原理与设计[M].北京：北京航空航天大学出版社,2007.