轮轨接触状态在线检测关键技术研究
|
摘要
轮轨接触状态的测量是车辆动力学理论与实践的重要环节,对于车辆动力性能研究、脱轨机理研究、轮轨接触状态研究及列车运行安全监测都具有重要的意义。随着中国铁路运输向高速、重载方向发展,轮轨作用力的测量在精度和速度上都有了更高的要求。测力轮对方法是以轮对作为检测轮轨力的传感器,通过测量轮对特定位置的应变实现轮轨力的连续检测,是目前最准确、最直接的轮轨力测量技术。由于车辆在运行过程中,轮对受到轨道时变、非平稳的作用力影响产生应变,这种应变又被轮对转动所调制,因此测力轮对的测量精度会受到多种因素的影响,如：贴片工艺、车轮均匀性、车辆速度(车轮转速)、轮轨力作用点位置变化及其它一些干扰因素,所以需要对车轮辐板应变测力轮对技术的测量理论和数据处理方法做更深入的研究。
论文综述了测力轮对的发展历程和目前国际国内测力轮对的发展现状,分析了轮轨载荷作用下轮对辐板和车轴的应力分布,提出了适用性较强的测力轮对测量模型及其对应的计算方法,并研制了基于精密时间测量技术的无线测力轮对检测系统。其主要内容与成果如下：
1、提出以轮对整体为检测对象的轮轨力测量模型
在车辆动力学试验中广泛使用的测力轮对技术,虽然经过了几十年的发展但在轮轨力连续测量中仍存在欠缺之处。目前的国标方案基于两个前提：1、轮对辐板上能找到只含一次谐波输出的组桥半径；2、轮对辐板上能找到横向力和垂向力输出没有交叉干扰的组桥半径。这些对于现在大部分轮对(特别是动车组直辐板轮对)很难完全做到,并且,国标方案认为轮对沿名义滚动圆滚动,没有考虑作用点位置变化对输出信号的影响,测量存在较大误差。
论文在对目前列车轮对进行仿真分析的基础上,分析了轮对辐板和车轴在横向力、垂向力和作用点位置变化作用下产生应变的分布规律,采用在同一半径(辐板)和同一截面位置(车轴)布置多个应变片组合来消除对应的干扰谐波。以车轮为测量对象的方案在组桥方式上易于实现,但是针对目前常用的高速动车组的直辐板轮对,不易在直辐板上找到适合的半径适合其假设条件。以轮对为测量对象的检测方法理论上适用所有型号的测力轮对,但其具体应用还要考虑具体型号轮对的安装方式的客观条件。
2、提出基于现代信号理论的测力轮对轮轨接触作用力估计方法
根据经验可知,在车辆正常平稳行驶阶段的任意较短时间内,导致轮对应变桥输出改变的作用因素的状态变量(包括横向力、垂向力、作用点位置和轮对旋转角度)在时间上存在一定的延续性。也就是说,在正常行驶状态下,只要保证采样时间足够短,则可以认为当前状态是在前一时刻状态基础上作出微小改变,这就导出了作用状态变量横向力、垂向力、作用点位置和轮对旋转角度在时间上的变化规律和递推关系。
论文通过研究的轮轨接触状态的变化特点,建立了测力轮对检测系统关于时间的递推模型,并讨论了各种条件下各种粒子滤波类算法对测力轮对模型的适用性。
3、研制了基于精密时间测量技术的无线测力轮对检测系统
基于精密时间测量的应变检测技术不同于常规的惠斯通电桥测量方法,通过测量应变片对精密电容的充放电时间计算应变值,具有高稳定性、较小增益误差和低功耗的特点。论文针对测力轮对的实际应用需要,研制了无线测力轮对应变采集方案,并通过测试试验对检测系统进行了验证。
The measure of wheel/rail loads is an important process of vehicle dynamics theory and practice, which has great significance on vehicle dynamics, derailment mechanism, wheel/rail contact theory and vehicle security measurement. As China's railway transportation develops towards high speed and overloading, it asks higher precision and speed on the measure of wheel/rail loads. The instrumented wheelset, which is now the most direct and the most precise technology of the wheel/rail force measuring, takes the wheel as the detecting sensor of wheel/rail force and realizes continuous measurement of wheel/rail loads by measuring the strain on particular position of the wheel plate. As the vehicle running, the strain is produced by the wheel/rail force which is changing and non-stationary, and then modulated by the wheel steering angle. And therefore, there are a number of factors that can affect the accuracy of instrumented wheelset, such as:strain gauges sticking technics, wheel uniformity, vehicle speed (wheel rotate speed), position change of the wheel/rail contact point and some other interference factors. So it need further study on both measuring theory and data processing method of the wheel plate strain instrumented wheelset.
This thesis reviewed the development history of instrumented wheelset and the international and domestic development present situation, analyzed the stress distribution of plate and axle under wheel/rail load, and put forward the general method of instrumented wheelset measurement and corresponding calculation methods, and designed the instrumented wheelset based on precision time measurement technique and wireless data transmission technology. The content and the results are as follows:
1. Put forward the wheel/rail force measurement model regarding the whole wheelset as the detecting object.
The instrumented wheelset widely used in the vehicle dynamics test still exists some places deficient, although the development of several decades. The current national standard scheme is based on two premise:1. The bridge radius contains only first harmonic output can be found.2. The bridge radius with no interferences between lateral force and vertical force can be found. For now, most wheelset especially straight plate can hardly achieve. In addition, national standard regards the wheelset's rolling as nominal rolling circle, without considering that the position change of contact point can act on the output signal, which leads to lager measurement error.
Based on the simulation analysis, this thesis analyzed the distribution regularity of strain caused by lateral force, vertical force and contact point position, eliminated the interference harmonic by several strain pieces arrangement in the position of the same radius on the plate and the same section of the axle. It is easy to realize for the wheel regarded as measuring object, which theoretically supports all types of instrumented wheelset, but not for straight plate. Also, it should be taken into consideration the installation of a specific type wheel.
2. Put forward the estimation method of wheel/rail contact force based on modern signal theory.
According to the experience, in any short time when vehicle is driving normally, there is certain continuity in this time on the value of state variable including lateral force, vertical force, contact point position and wheelset rotation angle which result in the output change of wheelset strain bridge. In other words, once the sampling time is short enough, it can be regarded the current state as the tiny change based on the state a moment before, and then it can be exported the change regularity and the recursion relation between lateral force, vertical force, contact point position and wheelset rotation angle
The thesis analyzed the characteristic of wheel/rail force signalnoise modulated by wheelset rolling, researched the time recursive discrete model of instrumented wheelset measuring system, and discussed the applicability of particle filter algorithm on various conditions.
3^Designed the instrumented wheelsets based on precision time measurement technique and wireless data transmission technology.
The strain measuring based on precise time measurement is different from Wheatstone bridge. Measuring the precision capacitors elapsed time of charge and discharge in order to calculate the strain value, has the characteristics of high stability, small gain error and low power consumption. This thesis was considerate the actual conditions in instrumented wheelset applications, researched the wireless strain acquisition system and confirmed it by measuring test.
论文综述了测力轮对的发展历程和目前国际国内测力轮对的发展现状,分析了轮轨载荷作用下轮对辐板和车轴的应力分布,提出了适用性较强的测力轮对测量模型及其对应的计算方法,并研制了基于精密时间测量技术的无线测力轮对检测系统。其主要内容与成果如下：
1、提出以轮对整体为检测对象的轮轨力测量模型
在车辆动力学试验中广泛使用的测力轮对技术,虽然经过了几十年的发展但在轮轨力连续测量中仍存在欠缺之处。目前的国标方案基于两个前提：1、轮对辐板上能找到只含一次谐波输出的组桥半径；2、轮对辐板上能找到横向力和垂向力输出没有交叉干扰的组桥半径。这些对于现在大部分轮对(特别是动车组直辐板轮对)很难完全做到,并且,国标方案认为轮对沿名义滚动圆滚动,没有考虑作用点位置变化对输出信号的影响,测量存在较大误差。
论文在对目前列车轮对进行仿真分析的基础上,分析了轮对辐板和车轴在横向力、垂向力和作用点位置变化作用下产生应变的分布规律,采用在同一半径(辐板)和同一截面位置(车轴)布置多个应变片组合来消除对应的干扰谐波。以车轮为测量对象的方案在组桥方式上易于实现,但是针对目前常用的高速动车组的直辐板轮对,不易在直辐板上找到适合的半径适合其假设条件。以轮对为测量对象的检测方法理论上适用所有型号的测力轮对,但其具体应用还要考虑具体型号轮对的安装方式的客观条件。
2、提出基于现代信号理论的测力轮对轮轨接触作用力估计方法
根据经验可知,在车辆正常平稳行驶阶段的任意较短时间内,导致轮对应变桥输出改变的作用因素的状态变量(包括横向力、垂向力、作用点位置和轮对旋转角度)在时间上存在一定的延续性。也就是说,在正常行驶状态下,只要保证采样时间足够短,则可以认为当前状态是在前一时刻状态基础上作出微小改变,这就导出了作用状态变量横向力、垂向力、作用点位置和轮对旋转角度在时间上的变化规律和递推关系。
论文通过研究的轮轨接触状态的变化特点,建立了测力轮对检测系统关于时间的递推模型,并讨论了各种条件下各种粒子滤波类算法对测力轮对模型的适用性。
3、研制了基于精密时间测量技术的无线测力轮对检测系统
基于精密时间测量的应变检测技术不同于常规的惠斯通电桥测量方法,通过测量应变片对精密电容的充放电时间计算应变值,具有高稳定性、较小增益误差和低功耗的特点。论文针对测力轮对的实际应用需要,研制了无线测力轮对应变采集方案,并通过测试试验对检测系统进行了验证。
The measure of wheel/rail loads is an important process of vehicle dynamics theory and practice, which has great significance on vehicle dynamics, derailment mechanism, wheel/rail contact theory and vehicle security measurement. As China's railway transportation develops towards high speed and overloading, it asks higher precision and speed on the measure of wheel/rail loads. The instrumented wheelset, which is now the most direct and the most precise technology of the wheel/rail force measuring, takes the wheel as the detecting sensor of wheel/rail force and realizes continuous measurement of wheel/rail loads by measuring the strain on particular position of the wheel plate. As the vehicle running, the strain is produced by the wheel/rail force which is changing and non-stationary, and then modulated by the wheel steering angle. And therefore, there are a number of factors that can affect the accuracy of instrumented wheelset, such as:strain gauges sticking technics, wheel uniformity, vehicle speed (wheel rotate speed), position change of the wheel/rail contact point and some other interference factors. So it need further study on both measuring theory and data processing method of the wheel plate strain instrumented wheelset.
This thesis reviewed the development history of instrumented wheelset and the international and domestic development present situation, analyzed the stress distribution of plate and axle under wheel/rail load, and put forward the general method of instrumented wheelset measurement and corresponding calculation methods, and designed the instrumented wheelset based on precision time measurement technique and wireless data transmission technology. The content and the results are as follows:
1. Put forward the wheel/rail force measurement model regarding the whole wheelset as the detecting object.
The instrumented wheelset widely used in the vehicle dynamics test still exists some places deficient, although the development of several decades. The current national standard scheme is based on two premise:1. The bridge radius contains only first harmonic output can be found.2. The bridge radius with no interferences between lateral force and vertical force can be found. For now, most wheelset especially straight plate can hardly achieve. In addition, national standard regards the wheelset's rolling as nominal rolling circle, without considering that the position change of contact point can act on the output signal, which leads to lager measurement error.
Based on the simulation analysis, this thesis analyzed the distribution regularity of strain caused by lateral force, vertical force and contact point position, eliminated the interference harmonic by several strain pieces arrangement in the position of the same radius on the plate and the same section of the axle. It is easy to realize for the wheel regarded as measuring object, which theoretically supports all types of instrumented wheelset, but not for straight plate. Also, it should be taken into consideration the installation of a specific type wheel.
2. Put forward the estimation method of wheel/rail contact force based on modern signal theory.
According to the experience, in any short time when vehicle is driving normally, there is certain continuity in this time on the value of state variable including lateral force, vertical force, contact point position and wheelset rotation angle which result in the output change of wheelset strain bridge. In other words, once the sampling time is short enough, it can be regarded the current state as the tiny change based on the state a moment before, and then it can be exported the change regularity and the recursion relation between lateral force, vertical force, contact point position and wheelset rotation angle
The thesis analyzed the characteristic of wheel/rail force signalnoise modulated by wheelset rolling, researched the time recursive discrete model of instrumented wheelset measuring system, and discussed the applicability of particle filter algorithm on various conditions.
3^Designed the instrumented wheelsets based on precision time measurement technique and wireless data transmission technology.
The strain measuring based on precise time measurement is different from Wheatstone bridge. Measuring the precision capacitors elapsed time of charge and discharge in order to calculate the strain value, has the characteristics of high stability, small gain error and low power consumption. This thesis was considerate the actual conditions in instrumented wheelset applications, researched the wireless strain acquisition system and confirmed it by measuring test.
引文
[1]张卫华.空间状态轮轮(轨)接触点计算方法[J].中国铁道科学,2006,27(4)：76-79
[2]曾庆元等.列车脱轨分析理论与应用[M].长沙：中南大学出版社,2006,12：38-73.
[3]俞展猷等.车轮脱轨及其评价[J].铁道学报,1999,21(3)：33-38.
[4]张卫华等.车辆运动稳定性试验台试验及与线路试验间误差分析[J].铁道机车车辆,1996,19(4)：69-72.
[5]张卫华等.单轮对脱轨实验及其理论分析[J].铁道学报,1998,20(1)：39-44.
[6]杨国桢.铁道车辆脱轨安全性的设计(上).铁道车辆,1994,(11)：8-27.
[7]杨国桢.铁道车辆脱轨安全性的设计(下).铁道车辆,1994,(12)：12-32.
[8]曾庆元等,列车脱轨的力学机理与防治脱轨的理论[J].铁道科学与工程学报,2004(11)：19-31.
[9]俞展猷等.防脱轨性能的评定[J].机车电传动,1999,(5)：1-4.
[10]曾宇清.车辆脱轨安全评判的动态限度[J].中国铁道科学,1999,20(4)：71-76.
[11]宫本昌幸.铁道车辆的脱轨机制[J].国外铁道车辆,1997,6：36-43.
[12]石田弘明.铁路车辆安全性评定标准[J].国外铁道车辆,1996,5：27-34.
[13]翟婉明,陈果.根据车轮抬升量评判车辆脱轨的方法与准则[J].铁道学报,2001,23(2)：17-26.
[15]廖庆斌.车辆的结构-声耦合振动分析及其控制研究[D],南京航空航天大学.2008.
[16]余卓平,高晓杰.车辆行驶过程中的状态估计问题综述[J].机械工程学报,2009,45(5)：20-33
[17]Matthew S. Allen, Thomas G. Carne. Delayed, multi-step inverse structural filterfor robust force identification. Mechanical Systems and Signal Processing 2008 (22):1036-1054
[18]Tadeusz Uhl. The inverse identification problem and its technical application. Archive of Applied Mechanics,77(5):325-337
[19]Li Ping. Estimation of railway vehicle suspension parameters for condition monitoring. Control Engineering Practice.15 (2007) 43-55
[20]Weber H. H. Zur Ermmilung der kraf tor Zwischen Rad und Schiene [J]. Eigenerlag des Institues fur Flugzeugustatick und Leichtbau der ETH Zurich,1968.
[21]A. Ronard Pocklington. The B. R. Load Measuring Wheel[J]. proceedingds of international conference on Wheel/rail load and Displacement Measurement Techniques,1981.
[22]Modransky. Instrumented Locomotive Wheels for Continuous Measurements of Vertical and Lateral Loads[J]. ASME Publication, Paper 79-RT-8,Feb.1980.
[23]Kesler J K. Measurement techniques for onboard wheel/rail loads[J]. Proceeeds of International Conference on Wheel/Rail Load and Displacement Techniques,1981:19-20.
[24]Johnson M R,Development and Use of an instrumented wheelset for the measurement of wheel/rail interaction forces[J]. Proceedings of international conference on wheel/rail load and displacement measurement techniques,1981,1:19-20.
[25]Olson P E, Johnson S. Lateral forces between wheels and rail, an experimental investigation[J]. ASME Publication. Paper No.79-RT-8,1980.
[26]Anderson,T. J. Calibration guidelines and equipments,important characteristics and error types for instrumented wheelsets [J]. Proceedings of the International Conference on Wheel/Rail and Displacement Measurement Techniques,1981(6):1-26.
[27]H. Kanehara. Measuring technique of dynamic characteristics of railway vehicles, Japan National Railways,1977(121):113-114.
[28]H. Kanehara. Study on online measurement of longitudinal creep force of railway vehicle[J]. Proceedinds of the conference J-Rail'98.
[29]Anders Johansson. Rail corrugation growth—Influence of powered wheelsets with wheel tread irregularities[J]. Wear,2007(262):1296-1307.
[30]O. Arias-Cuevas. Rolling-sliding laboratory tests of friction modifiers in dry and wet wheel-rail contacts. Wear,2010(268):543-551.
[31]Fujie Xia. The dynamic wheel-rail contact stresses for wagon on various tracks, Wear,2008(265):1549-1555
[32]Massimiliano Pau. Distribution of contact pressure in wheel-rail contact area. Wear 2002(253):265-274
[33]Shuguang Zhang. Effect of unsupported sleepers on wheel/rail normal load. Soil Dynamics and Earthquake Engineering 2008 (28):662-673
[34]Bakken,G. B. Development of a Wheel/Rail Measurement System-From Concept to Implemententation[J]. Proceedings of the International Conference on Wheel/Rail and Displacement Measurement Techniques,1981 (2):1-30.
[35]Boyd, P. Measurement Techniques for Onboard Wheel/Rail Loads [J]. Proceedings of the International Conference on Wheel/Rail and Displacement Measurement Techniques,1981(1):1-36.
[36]Pocklinton, A. R. Improved Data from Load-Measuring Wheels[J]. Railway Engineer,1977,2(4):37-43.
[37]Swenson,C. A. Development and Use of Instrumented Locomotive Wheelsets[J] Proceedings of the International Conference on Wheel/Rail and Displacement Measurement Techniques,1981 (5):1-10.
[38]Zuck, H. H. Determination of Wheel/Rail Forces by Forces by Means of Measuring Wheelsets on Deutsche Bundesbahn[J]. Proceedings of the International Conference on Wheel/Rail and Displacement Measurement Techniques,1981(1):1-22
[39]Otter D E. A Design for Next Generation Load Measuring Wheelsets[J]. IEEE/ASME,May 1991.
[40]Higgns R L. High Accuracy Load Measuring Wheelset.1992.
[41]Hiromichi Kanehara. Measuring rail/wheel contact points of running railway vehicles[J]. Wear,253 (2002):275-283.
[42]李富达等. 机车与线路间垂向力和横向力的测试[J].中国铁道科学.1986,7(1)：92-102.
[43]刘尚举等.提高测力轮对测量精度的研究[J].铁道车辆,1998,36(2)：32-34.
[44]吴铎等.测力轮对轮／轨力数据处理迭代方法[J],中国铁道科学,1995, 16(3)：49-55.
[45]曾宇清等.测力轮对连续测量的理论与实践[J].铁道学报,1998,20(6)：28-34.
[46]张立民,金学松.基于测力轮对的轮轨瞬态作用力仿真计算[J].铁道学报,1998,20(6)：28-34.
[47]陈建政.轮轨作用力和接触点位置在线测量理论研究[D],2008
[48]陈成元等.连续测量轮轨力的测力轮对技术[J].西南交通大学学报,1994,29(2)：263-267.
[49]Hiroaki Ishida.轮轨接触力新的连续测量法[J]. 国外铁道车辆,1998,2：19-24
[50]侯卫星,王卫东,曾宇清.高精度高速连续测量轮轨动态作用力的研究.铁道学报,2010,32(1)：24-29.
[51]张绍华等.辐板式测力轮对的研制[J],铁道学报,1992,14(2)：103-109.
[52]Fort J C. Solving a combinatorial problem via self-organizing process:an application of the Kohonen algorithm to the travelling salesman problem [J] Biol Cybern,1988,59(1):33-40.
[53]oLhede S.Walden A T. A generalized demodulation approach to time-frequency projections for multicomponent signals[J]. Proceedings of the Royal Society of London.Series A,2005,461:2159-2179.
[54]Mallat S, Zhang Z. Matching Pursuits with Time-frequency Dictionaries[J]. IEEE Trans. Signal Processing,1993,41(12):3397.
[55]Mann S, Haykin S. The Chirplet Transform-A Generalization of Gabors Logon Transform[J]. Vision Interface'91,1991,3:6.
[56]Mann S, Haykin S. Chirplets and Warblets:Novel Time-frequency Representations. Electron. Lett.1992,28 (2):114.
[57]Martin J G, Rasheed K. Using Singular Value Decomposition to Improve a Genetic Algorithm's Performance [J]. The Congresson Evolutionary Computation,2003, 3(8-12):612-617.
[58]Kirby M, Sirovich Application of Karhuner-Loeve Procedure For the Characterization of Human Faces[J]. IEEE Trans.1990,12(1):103-108.
[59]Algorithm for Time-varying Fourier[J]. Transform IEEE. Trans. SP.,1993, 41(7).
[60]Yeung,K. Y. and Ruzzo, W. L. Principal compo-nent analysis for clustering gene expression data.2001,17 (9):763-774.
[61]Erikssons J, Koivunen V. Complex random vectors and ICA models: Identif iabi lity, uniqueness, and separability [J]. IEEE Trans on Information Theory,2006,52(3):1017-1029.
[62]Bell A, Sejnowski T. An information maximaization approach to blind separation and blind deconvolution[J]. Neural Computation,1995,7:1129-1159.
[63]Weldon T P, Higgins W E. An algorithm for designing multiple gabor filters for segmenting multi-textured images [C]. In:Proc. Of IEEE Int'l. Conf. of ImageProc., Chicago, IL,1998,10.
[64]GirgisAA,PetersonWL. AdaPtive estintion of Powersystem frequency deviation and its rate change for calculating sudden powersystem overload[J]. IEEE Transactions on Power Delivery,1990,5(4):21-25.
[65]David W. P. Thomas,Malecolm. Evaluation of Frequency tracting methods[J]. IEEE Transctions on Power Delivery,2001,16(3):367-371.
[66]Taolin, Minel Tsuji,Eiji Yamada. A wavelet approach to real time estimation of power system frequeney[C], IEEE Digital object Identifier.2001:58-65.
[67]T. S. Sidhu. Accurate measurement of Power system frequency using a digital signal Processing teehnique[J]. IEEE Transactions on Instrumenttation and Measumentl,1999,48(1):75-80.
[68]Gusev V G, Yanover B I. The complex representation of a discrete signal on the basis of its Hilbert transform. Radio. Eng. and Electron Phys.,1983, 28(1):83-89.
[69]Leung Y, Guo Y. Degree of Population Diversity—A Perspective on Premature Convergence in Genetic Algorithms and its Markov Chain Analysis [J]. IEEE Trans On Neural Networks.1997,8(5):1165-1176.
[70]Srinivas M, Patnaik L M. Adaptive Probabilities of Crossover and Mutation in Genetic Algorithms[J]. IEEE Trans on System.1994,24(4):656-665.
[71]R. B RANDLL, LUO DEYANG, Hilber Transform Techniques for Torsional Vibration Anallysis[C]. Vibration and Noiseconference,1990:15-25
[72]Mallat S,Hwang W L. Singularity detection and processing with wavelets[J]. IEEE Trans, on Information Theory,1992(2):617-643.
[73]Hammond J, White P. The analysis of non-stationary signals using time-frequency methods [J]. Journal of Sound and Vibration,1996,190:419-447
[74]Huang N E, Shen Z, Long S R, et al. The empirical mode decomposition and the Hilbert spectrum for nonlinear and nonstationary time series analysis[J] Proceedings of the Royal Society of London,Series A,1998,454:903-995
[75]张贤达,保铮.非平稳信号分析与处理[M].北京：国防工业出版社,2001.
[76]胡广书.数字信号处理一理论、算法与实现[M].清华大学出版社,1996.
[77]L.科恩. 时-频分析：理论与应用[M].西安交通大学出版社,1998
[78]邹红星等.时频分析：回溯与前瞻[J].电子学报,2000,28(9)：78-84.
[80]刘庆云,李志舜,刘朝晖.时频分析技术及研究现状[J].计算机工程,2004,30(1)：171-173.
[81]金雷,李月,杨宝俊.用时频峰值滤波方法消减地震勘探资料中随机噪声的初步研究[J].地球物理学进展,2005,20(3)：724-728.
[82]苏峰,曲毅,陈军.线性时频分析在弱信号检测中的应用[J].广西民族学院学报2004,10(3)：63-65.
[83]周丹蔡坤宝.基于短时傅立叶变换的脉象信号的模式识别方法[J].重庆科技学院学报,2007,9(3)：49-52.
[84]王胜文,陈伏兵.一种基于奇异值分解的特征抽取方法[J].电子与信息学报,2005,27(2)：294-297.
[85]陈章位,潘宏.渐进信号瞬态频率的提取[J]Journal of vibration Engmeering, 1997,10(4):451-457.
[86]何仁贵,黄登山.一种改进的正弦波频率谱估计方法[J].西安工业大学学报,2004,24(4)：328-331.
[87]朱娟.蒙特卡洛滤波算法在目标跟踪中的应用[D].中国科学院长春光学精密机械与 物理研究所.2010
[88]罗飞腾.目标跟踪的粒子滤波技术研究[D],中国科学技术大学,2010
[89]郭鹏飞,任章等.机动加速度辅助的航姿系统扩展卡尔曼滤波[J].系统工程与电子技术,2009,31(3)：625-628
[90]张波.不完全信息下基于卡尔曼滤波的投资决策[D],哈尔滨工业大学,2008
[91]陈宇波.带有先验信息的动态定位贝叶斯滤波算法研究[D],中南大学,2010
[92]杨超.基于混合高斯模型和粒子滤波理论的视频车辆跟踪算法[D],哈尔滨工业大学,2008
[93]张鹏.基于卡尔曼滤波的航空发动机故障诊断技术研究[D],南京航空航天大学.2006.
[94]杨小军.基于粒子滤波的混合估计理论与应用[D],西北工业大学.2006
[95]龚亚信.基于粒子滤波的弱目标检测前跟踪算法研究[D].国防科技大学,2009
[96]王好勋.基于虚拟仪器技术的列车振动舒适度检测系统的研究[D].武汉理工大学,2008
[97]王昕.卡尔曼滤波在模型参数估计中的应用[D].哈尔滨工业大学,2008
[98]李鹏.卡尔曼滤波在信息融合理论中的应用[D].西安电子科技大学,2008
[99]梁军.粒子滤波算法及其应用研究[D].哈尔滨工业大学,2009
[100]朱志宇.粒子滤波算法及其应用[M].科学出版社.2010
[101]胡士强,敬忠良.粒子滤波原理及其应用[M].科学出版社.2010
[102]Kalman R E. A new approach to linear filtering and prediction problem. Transactions of the ASME-Journal of Basic Engineering,1960,82:35-45
[103]Sunahara Y. An approximate method of state estimation for nonlinear dynamical systems. Joint Automatic Control Conf, Univ. of Colorado,1969, 1:81-86.
[104]Nrgaard M, developments in state estimation for nonlinear system[J]. Automatica,2000,36(11):1627-1638
[105]Sorenson H, AlsPaeh D. Recursive Bayesian Estimation Using Gaussian Sum. Automatic,1971,7 (1):465-479.
[106]S. J. Julier, J. K. Uhimann, H. F. Durrant-Whyte. A new method for nonlinear transformation of means a and estimators, IEEE Trans Automatic Control, 2000,45(3):477-482.
[107]Wan E A, Vander Merwe R. The unscented kalman filter for nonlinear estimation [A]. In:Proc of the Symposium 2000 on Adaptive System for Signal Processing, Communication and Control(AS-SPCC) [C], Lake Louise, Alberta, Canada, October 2000,1:489-494
[108]Peihua, Li a an filter for visual curve tracking. In Proceed video processing, June,2002,2:314-321.
[109]Hammersley J M, Morton K W. Poor man's Monte Carlo[J]. J of the Royal Statistical Society B,1954,16 (1):23-38.
[110]Merwe v.d.R, Douce A, et al. The unscented particle filter[R]. Cambridge University Enginnering Department, England Cambridge University press, 2000:1-45
[111]Christophe Blanc, Laurent Trassoudaine, and Jean Gallice. EKF and particle filter track to track fusion:a quantitative comparison from radar/lidar obstacle tracks. In Proceedings of 8th International conference on Information Fusion, Philadelphia, PA,2005 July,2:1303-1310.
[112]文成林,周东华.多尺度估计理论及其应用[M].清华大学出版社.2002
[113]邓小龙等.用于状态估计的自适应粒子滤波[J].华南理工大学学报,2006,34(1)：57-61
[114]张莹,贺丰收,郑世友.基于强跟踪滤波器的交互式多模型算法[J],计算机工程与应用.
[115]冯志全,孟祥旭.一种强跟踪滤波器及其在人手跟踪中的应用[J],计算机辅助设计与图形学学报,
[116]崔乃刚,韩鹏鑫,穆荣军.基于强跟踪UKF的导航系统故障检测方法[J].哈尔滨工程大学学报
[117]叶斌,徐毓.强跟踪滤波器与卡尔曼滤波器对目标跟踪的比较[J].空军雷达学院学报,
[118]赵学梅,陈恳,李冬强.跟踪卡尔曼滤波在视频目标跟踪中的应用[J].计算机工程与应用
[119]吴秋平,万德钧,高钟毓.基于强跟踪滤波器的SINS/GPS系统故障检测方法[J].清华大学学报.
[120]韩红.基于TDC的事件计时器设计[D].中国科学院.2006
[121]张延,黄佩诚.高精度时间间隔测量技术与方法[J].天文学进展,2006,24(1)：1-15
[122]王福源,杨玉叶,时伟.高分辨率时间数字转换电路的PLD实现[J].半导体技术,200631(6)：452—455.
[123]LinLi, WeiZhou, FengweiWang, et al.A time to Digital Converter Based on Time-Space Relationship[C]. Proceedings of 2007 IEEE International Frequency Control Symposium,2007, PP:815-819
[124]徐振.基于TDC的时间间隔测量技术的研究[D].哈尔滨工业大学,2008
[125]M. Zielinski, D. Chaberski,S. Grzelak.Time interval measuring module with short dead-time[C].Metrol.Meas. Syst.2003,10
[126]J. Kailisz. Review of methods for time interval measurements with picoseconds resolution.Institute of Physics Publishing Metrologia.2004
[127]于建国等.精密时间间隔测量方法的改进[J].宇航计测技术.2003,23
[128]S. D. Brown. Field-Programmable Gate Arrays[M].Norwell, MA:Kluwer,1992
[129]宋健.基于FPGA的精密时间一数字转换电路研究[D].中国科学技术大学,2006
[130]朱小兰.超声波热测量芯片TDC核的设计与实现[D].山东大学硕士研究生论文,2010
[131]刘智军,于善云.集流环的接触电阻对信号传输的影响[J].莱阳农学院学报.1989,6(1)：57-61
[132]邹乐.准非接触电容式集流环的研究[D].哈尔滨工业大学,2008
[133]栗震宵.影响集流环信号传递精度的主要因素及改进措施的探讨[J].计量技术,1990,(6)：17-19
[134]冯艳波.基于无线传感器网络的列车运行安全监测系统[D].西南交通大学,2008
[135]杨骏.基于NanoPAN5375的测力轮对无线传输系统[J].工程与试验
[136]张曦煌.无线传感器网络的研究[D].江南大学.2008
[137]向锷.轮轨力无线检测系统研究[D].西南交通大学.2008
[138]肖俊芳.无线传感器网络的若干关键技术研究[D].上海交通大学.2009
[139]张雪凡.无线传感器网络节能技术研究[D].上海大学,2011
[140]陈伊卿.无线传感器网络时间同步算法研究[D].西安电子科技大学.2011
[141]张坤.无线传感器网络时钟同步技术的研究[D].西南大学.2007
[142]艾山江,克里木.嵌入式系统中无线通信技术的应用研究[D].江南大学.2009
[2]曾庆元等.列车脱轨分析理论与应用[M].长沙：中南大学出版社,2006,12：38-73.
[3]俞展猷等.车轮脱轨及其评价[J].铁道学报,1999,21(3)：33-38.
[4]张卫华等.车辆运动稳定性试验台试验及与线路试验间误差分析[J].铁道机车车辆,1996,19(4)：69-72.
[5]张卫华等.单轮对脱轨实验及其理论分析[J].铁道学报,1998,20(1)：39-44.
[6]杨国桢.铁道车辆脱轨安全性的设计(上).铁道车辆,1994,(11)：8-27.
[7]杨国桢.铁道车辆脱轨安全性的设计(下).铁道车辆,1994,(12)：12-32.
[8]曾庆元等,列车脱轨的力学机理与防治脱轨的理论[J].铁道科学与工程学报,2004(11)：19-31.
[9]俞展猷等.防脱轨性能的评定[J].机车电传动,1999,(5)：1-4.
[10]曾宇清.车辆脱轨安全评判的动态限度[J].中国铁道科学,1999,20(4)：71-76.
[11]宫本昌幸.铁道车辆的脱轨机制[J].国外铁道车辆,1997,6：36-43.
[12]石田弘明.铁路车辆安全性评定标准[J].国外铁道车辆,1996,5：27-34.
[13]翟婉明,陈果.根据车轮抬升量评判车辆脱轨的方法与准则[J].铁道学报,2001,23(2)：17-26.
[15]廖庆斌.车辆的结构-声耦合振动分析及其控制研究[D],南京航空航天大学.2008.
[16]余卓平,高晓杰.车辆行驶过程中的状态估计问题综述[J].机械工程学报,2009,45(5)：20-33
[17]Matthew S. Allen, Thomas G. Carne. Delayed, multi-step inverse structural filterfor robust force identification. Mechanical Systems and Signal Processing 2008 (22):1036-1054
[18]Tadeusz Uhl. The inverse identification problem and its technical application. Archive of Applied Mechanics,77(5):325-337
[19]Li Ping. Estimation of railway vehicle suspension parameters for condition monitoring. Control Engineering Practice.15 (2007) 43-55
[20]Weber H. H. Zur Ermmilung der kraf tor Zwischen Rad und Schiene [J]. Eigenerlag des Institues fur Flugzeugustatick und Leichtbau der ETH Zurich,1968.
[21]A. Ronard Pocklington. The B. R. Load Measuring Wheel[J]. proceedingds of international conference on Wheel/rail load and Displacement Measurement Techniques,1981.
[22]Modransky. Instrumented Locomotive Wheels for Continuous Measurements of Vertical and Lateral Loads[J]. ASME Publication, Paper 79-RT-8,Feb.1980.
[23]Kesler J K. Measurement techniques for onboard wheel/rail loads[J]. Proceeeds of International Conference on Wheel/Rail Load and Displacement Techniques,1981:19-20.
[24]Johnson M R,Development and Use of an instrumented wheelset for the measurement of wheel/rail interaction forces[J]. Proceedings of international conference on wheel/rail load and displacement measurement techniques,1981,1:19-20.
[25]Olson P E, Johnson S. Lateral forces between wheels and rail, an experimental investigation[J]. ASME Publication. Paper No.79-RT-8,1980.
[26]Anderson,T. J. Calibration guidelines and equipments,important characteristics and error types for instrumented wheelsets [J]. Proceedings of the International Conference on Wheel/Rail and Displacement Measurement Techniques,1981(6):1-26.
[27]H. Kanehara. Measuring technique of dynamic characteristics of railway vehicles, Japan National Railways,1977(121):113-114.
[28]H. Kanehara. Study on online measurement of longitudinal creep force of railway vehicle[J]. Proceedinds of the conference J-Rail'98.
[29]Anders Johansson. Rail corrugation growth—Influence of powered wheelsets with wheel tread irregularities[J]. Wear,2007(262):1296-1307.
[30]O. Arias-Cuevas. Rolling-sliding laboratory tests of friction modifiers in dry and wet wheel-rail contacts. Wear,2010(268):543-551.
[31]Fujie Xia. The dynamic wheel-rail contact stresses for wagon on various tracks, Wear,2008(265):1549-1555
[32]Massimiliano Pau. Distribution of contact pressure in wheel-rail contact area. Wear 2002(253):265-274
[33]Shuguang Zhang. Effect of unsupported sleepers on wheel/rail normal load. Soil Dynamics and Earthquake Engineering 2008 (28):662-673
[34]Bakken,G. B. Development of a Wheel/Rail Measurement System-From Concept to Implemententation[J]. Proceedings of the International Conference on Wheel/Rail and Displacement Measurement Techniques,1981 (2):1-30.
[35]Boyd, P. Measurement Techniques for Onboard Wheel/Rail Loads [J]. Proceedings of the International Conference on Wheel/Rail and Displacement Measurement Techniques,1981(1):1-36.
[36]Pocklinton, A. R. Improved Data from Load-Measuring Wheels[J]. Railway Engineer,1977,2(4):37-43.
[37]Swenson,C. A. Development and Use of Instrumented Locomotive Wheelsets[J] Proceedings of the International Conference on Wheel/Rail and Displacement Measurement Techniques,1981 (5):1-10.
[38]Zuck, H. H. Determination of Wheel/Rail Forces by Forces by Means of Measuring Wheelsets on Deutsche Bundesbahn[J]. Proceedings of the International Conference on Wheel/Rail and Displacement Measurement Techniques,1981(1):1-22
[39]Otter D E. A Design for Next Generation Load Measuring Wheelsets[J]. IEEE/ASME,May 1991.
[40]Higgns R L. High Accuracy Load Measuring Wheelset.1992.
[41]Hiromichi Kanehara. Measuring rail/wheel contact points of running railway vehicles[J]. Wear,253 (2002):275-283.
[42]李富达等. 机车与线路间垂向力和横向力的测试[J].中国铁道科学.1986,7(1)：92-102.
[43]刘尚举等.提高测力轮对测量精度的研究[J].铁道车辆,1998,36(2)：32-34.
[44]吴铎等.测力轮对轮／轨力数据处理迭代方法[J],中国铁道科学,1995, 16(3)：49-55.
[45]曾宇清等.测力轮对连续测量的理论与实践[J].铁道学报,1998,20(6)：28-34.
[46]张立民,金学松.基于测力轮对的轮轨瞬态作用力仿真计算[J].铁道学报,1998,20(6)：28-34.
[47]陈建政.轮轨作用力和接触点位置在线测量理论研究[D],2008
[48]陈成元等.连续测量轮轨力的测力轮对技术[J].西南交通大学学报,1994,29(2)：263-267.
[49]Hiroaki Ishida.轮轨接触力新的连续测量法[J]. 国外铁道车辆,1998,2：19-24
[50]侯卫星,王卫东,曾宇清.高精度高速连续测量轮轨动态作用力的研究.铁道学报,2010,32(1)：24-29.
[51]张绍华等.辐板式测力轮对的研制[J],铁道学报,1992,14(2)：103-109.
[52]Fort J C. Solving a combinatorial problem via self-organizing process:an application of the Kohonen algorithm to the travelling salesman problem [J] Biol Cybern,1988,59(1):33-40.
[53]oLhede S.Walden A T. A generalized demodulation approach to time-frequency projections for multicomponent signals[J]. Proceedings of the Royal Society of London.Series A,2005,461:2159-2179.
[54]Mallat S, Zhang Z. Matching Pursuits with Time-frequency Dictionaries[J]. IEEE Trans. Signal Processing,1993,41(12):3397.
[55]Mann S, Haykin S. The Chirplet Transform-A Generalization of Gabors Logon Transform[J]. Vision Interface'91,1991,3:6.
[56]Mann S, Haykin S. Chirplets and Warblets:Novel Time-frequency Representations. Electron. Lett.1992,28 (2):114.
[57]Martin J G, Rasheed K. Using Singular Value Decomposition to Improve a Genetic Algorithm's Performance [J]. The Congresson Evolutionary Computation,2003, 3(8-12):612-617.
[58]Kirby M, Sirovich Application of Karhuner-Loeve Procedure For the Characterization of Human Faces[J]. IEEE Trans.1990,12(1):103-108.
[59]Algorithm for Time-varying Fourier[J]. Transform IEEE. Trans. SP.,1993, 41(7).
[60]Yeung,K. Y. and Ruzzo, W. L. Principal compo-nent analysis for clustering gene expression data.2001,17 (9):763-774.
[61]Erikssons J, Koivunen V. Complex random vectors and ICA models: Identif iabi lity, uniqueness, and separability [J]. IEEE Trans on Information Theory,2006,52(3):1017-1029.
[62]Bell A, Sejnowski T. An information maximaization approach to blind separation and blind deconvolution[J]. Neural Computation,1995,7:1129-1159.
[63]Weldon T P, Higgins W E. An algorithm for designing multiple gabor filters for segmenting multi-textured images [C]. In:Proc. Of IEEE Int'l. Conf. of ImageProc., Chicago, IL,1998,10.
[64]GirgisAA,PetersonWL. AdaPtive estintion of Powersystem frequency deviation and its rate change for calculating sudden powersystem overload[J]. IEEE Transactions on Power Delivery,1990,5(4):21-25.
[65]David W. P. Thomas,Malecolm. Evaluation of Frequency tracting methods[J]. IEEE Transctions on Power Delivery,2001,16(3):367-371.
[66]Taolin, Minel Tsuji,Eiji Yamada. A wavelet approach to real time estimation of power system frequeney[C], IEEE Digital object Identifier.2001:58-65.
[67]T. S. Sidhu. Accurate measurement of Power system frequency using a digital signal Processing teehnique[J]. IEEE Transactions on Instrumenttation and Measumentl,1999,48(1):75-80.
[68]Gusev V G, Yanover B I. The complex representation of a discrete signal on the basis of its Hilbert transform. Radio. Eng. and Electron Phys.,1983, 28(1):83-89.
[69]Leung Y, Guo Y. Degree of Population Diversity—A Perspective on Premature Convergence in Genetic Algorithms and its Markov Chain Analysis [J]. IEEE Trans On Neural Networks.1997,8(5):1165-1176.
[70]Srinivas M, Patnaik L M. Adaptive Probabilities of Crossover and Mutation in Genetic Algorithms[J]. IEEE Trans on System.1994,24(4):656-665.
[71]R. B RANDLL, LUO DEYANG, Hilber Transform Techniques for Torsional Vibration Anallysis[C]. Vibration and Noiseconference,1990:15-25
[72]Mallat S,Hwang W L. Singularity detection and processing with wavelets[J]. IEEE Trans, on Information Theory,1992(2):617-643.
[73]Hammond J, White P. The analysis of non-stationary signals using time-frequency methods [J]. Journal of Sound and Vibration,1996,190:419-447
[74]Huang N E, Shen Z, Long S R, et al. The empirical mode decomposition and the Hilbert spectrum for nonlinear and nonstationary time series analysis[J] Proceedings of the Royal Society of London,Series A,1998,454:903-995
[75]张贤达,保铮.非平稳信号分析与处理[M].北京：国防工业出版社,2001.
[76]胡广书.数字信号处理一理论、算法与实现[M].清华大学出版社,1996.
[77]L.科恩. 时-频分析：理论与应用[M].西安交通大学出版社,1998
[78]邹红星等.时频分析：回溯与前瞻[J].电子学报,2000,28(9)：78-84.
[80]刘庆云,李志舜,刘朝晖.时频分析技术及研究现状[J].计算机工程,2004,30(1)：171-173.
[81]金雷,李月,杨宝俊.用时频峰值滤波方法消减地震勘探资料中随机噪声的初步研究[J].地球物理学进展,2005,20(3)：724-728.
[82]苏峰,曲毅,陈军.线性时频分析在弱信号检测中的应用[J].广西民族学院学报2004,10(3)：63-65.
[83]周丹蔡坤宝.基于短时傅立叶变换的脉象信号的模式识别方法[J].重庆科技学院学报,2007,9(3)：49-52.
[84]王胜文,陈伏兵.一种基于奇异值分解的特征抽取方法[J].电子与信息学报,2005,27(2)：294-297.
[85]陈章位,潘宏.渐进信号瞬态频率的提取[J]Journal of vibration Engmeering, 1997,10(4):451-457.
[86]何仁贵,黄登山.一种改进的正弦波频率谱估计方法[J].西安工业大学学报,2004,24(4)：328-331.
[87]朱娟.蒙特卡洛滤波算法在目标跟踪中的应用[D].中国科学院长春光学精密机械与 物理研究所.2010
[88]罗飞腾.目标跟踪的粒子滤波技术研究[D],中国科学技术大学,2010
[89]郭鹏飞,任章等.机动加速度辅助的航姿系统扩展卡尔曼滤波[J].系统工程与电子技术,2009,31(3)：625-628
[90]张波.不完全信息下基于卡尔曼滤波的投资决策[D],哈尔滨工业大学,2008
[91]陈宇波.带有先验信息的动态定位贝叶斯滤波算法研究[D],中南大学,2010
[92]杨超.基于混合高斯模型和粒子滤波理论的视频车辆跟踪算法[D],哈尔滨工业大学,2008
[93]张鹏.基于卡尔曼滤波的航空发动机故障诊断技术研究[D],南京航空航天大学.2006.
[94]杨小军.基于粒子滤波的混合估计理论与应用[D],西北工业大学.2006
[95]龚亚信.基于粒子滤波的弱目标检测前跟踪算法研究[D].国防科技大学,2009
[96]王好勋.基于虚拟仪器技术的列车振动舒适度检测系统的研究[D].武汉理工大学,2008
[97]王昕.卡尔曼滤波在模型参数估计中的应用[D].哈尔滨工业大学,2008
[98]李鹏.卡尔曼滤波在信息融合理论中的应用[D].西安电子科技大学,2008
[99]梁军.粒子滤波算法及其应用研究[D].哈尔滨工业大学,2009
[100]朱志宇.粒子滤波算法及其应用[M].科学出版社.2010
[101]胡士强,敬忠良.粒子滤波原理及其应用[M].科学出版社.2010
[102]Kalman R E. A new approach to linear filtering and prediction problem. Transactions of the ASME-Journal of Basic Engineering,1960,82:35-45
[103]Sunahara Y. An approximate method of state estimation for nonlinear dynamical systems. Joint Automatic Control Conf, Univ. of Colorado,1969, 1:81-86.
[104]Nrgaard M, developments in state estimation for nonlinear system[J]. Automatica,2000,36(11):1627-1638
[105]Sorenson H, AlsPaeh D. Recursive Bayesian Estimation Using Gaussian Sum. Automatic,1971,7 (1):465-479.
[106]S. J. Julier, J. K. Uhimann, H. F. Durrant-Whyte. A new method for nonlinear transformation of means a and estimators, IEEE Trans Automatic Control, 2000,45(3):477-482.
[107]Wan E A, Vander Merwe R. The unscented kalman filter for nonlinear estimation [A]. In:Proc of the Symposium 2000 on Adaptive System for Signal Processing, Communication and Control(AS-SPCC) [C], Lake Louise, Alberta, Canada, October 2000,1:489-494
[108]Peihua, Li a an filter for visual curve tracking. In Proceed video processing, June,2002,2:314-321.
[109]Hammersley J M, Morton K W. Poor man's Monte Carlo[J]. J of the Royal Statistical Society B,1954,16 (1):23-38.
[110]Merwe v.d.R, Douce A, et al. The unscented particle filter[R]. Cambridge University Enginnering Department, England Cambridge University press, 2000:1-45
[111]Christophe Blanc, Laurent Trassoudaine, and Jean Gallice. EKF and particle filter track to track fusion:a quantitative comparison from radar/lidar obstacle tracks. In Proceedings of 8th International conference on Information Fusion, Philadelphia, PA,2005 July,2:1303-1310.
[112]文成林,周东华.多尺度估计理论及其应用[M].清华大学出版社.2002
[113]邓小龙等.用于状态估计的自适应粒子滤波[J].华南理工大学学报,2006,34(1)：57-61
[114]张莹,贺丰收,郑世友.基于强跟踪滤波器的交互式多模型算法[J],计算机工程与应用.
[115]冯志全,孟祥旭.一种强跟踪滤波器及其在人手跟踪中的应用[J],计算机辅助设计与图形学学报,
[116]崔乃刚,韩鹏鑫,穆荣军.基于强跟踪UKF的导航系统故障检测方法[J].哈尔滨工程大学学报
[117]叶斌,徐毓.强跟踪滤波器与卡尔曼滤波器对目标跟踪的比较[J].空军雷达学院学报,
[118]赵学梅,陈恳,李冬强.跟踪卡尔曼滤波在视频目标跟踪中的应用[J].计算机工程与应用
[119]吴秋平,万德钧,高钟毓.基于强跟踪滤波器的SINS/GPS系统故障检测方法[J].清华大学学报.
[120]韩红.基于TDC的事件计时器设计[D].中国科学院.2006
[121]张延,黄佩诚.高精度时间间隔测量技术与方法[J].天文学进展,2006,24(1)：1-15
[122]王福源,杨玉叶,时伟.高分辨率时间数字转换电路的PLD实现[J].半导体技术,200631(6)：452—455.
[123]LinLi, WeiZhou, FengweiWang, et al.A time to Digital Converter Based on Time-Space Relationship[C]. Proceedings of 2007 IEEE International Frequency Control Symposium,2007, PP:815-819
[124]徐振.基于TDC的时间间隔测量技术的研究[D].哈尔滨工业大学,2008
[125]M. Zielinski, D. Chaberski,S. Grzelak.Time interval measuring module with short dead-time[C].Metrol.Meas. Syst.2003,10
[126]J. Kailisz. Review of methods for time interval measurements with picoseconds resolution.Institute of Physics Publishing Metrologia.2004
[127]于建国等.精密时间间隔测量方法的改进[J].宇航计测技术.2003,23
[128]S. D. Brown. Field-Programmable Gate Arrays[M].Norwell, MA:Kluwer,1992
[129]宋健.基于FPGA的精密时间一数字转换电路研究[D].中国科学技术大学,2006
[130]朱小兰.超声波热测量芯片TDC核的设计与实现[D].山东大学硕士研究生论文,2010
[131]刘智军,于善云.集流环的接触电阻对信号传输的影响[J].莱阳农学院学报.1989,6(1)：57-61
[132]邹乐.准非接触电容式集流环的研究[D].哈尔滨工业大学,2008
[133]栗震宵.影响集流环信号传递精度的主要因素及改进措施的探讨[J].计量技术,1990,(6)：17-19
[134]冯艳波.基于无线传感器网络的列车运行安全监测系统[D].西南交通大学,2008
[135]杨骏.基于NanoPAN5375的测力轮对无线传输系统[J].工程与试验
[136]张曦煌.无线传感器网络的研究[D].江南大学.2008
[137]向锷.轮轨力无线检测系统研究[D].西南交通大学.2008
[138]肖俊芳.无线传感器网络的若干关键技术研究[D].上海交通大学.2009
[139]张雪凡.无线传感器网络节能技术研究[D].上海大学,2011
[140]陈伊卿.无线传感器网络时间同步算法研究[D].西安电子科技大学.2011
[141]张坤.无线传感器网络时钟同步技术的研究[D].西南大学.2007
[142]艾山江,克里木.嵌入式系统中无线通信技术的应用研究[D].江南大学.2009