列车轴承故障轨边声学检测系统关键技术研究
|
摘要
列车轴承故障一直以来都是列车故障的主要类型,严重影响着列车的行驶安全,因此加强对列车轴承的状态监测和故障诊断对列车的安全运行具有非常重要的意义。列车轴承故障轨边声学检测系统在对列车轴承的故障诊断和状态监测方面具备诸多优点,但由于列车轨边声信号具有陡畸变、强噪声、多声源等特点使得该检测系统的实现存在一定的困难。
本文以现役列车轴承NJ(P)3226X1为研究对象,设计了该类型轴承的专用实验平台,重点针对列车轴承故障轨边声学检测系统存在的多普勒畸变校正和强噪声滤波两大技术难点,研究探讨了解决这两项技术难点的方法,并对方法进行改进和验证,为最终实现列车轴承故障轨边声学检测系统的研制提供一定的基础理论和解决思路。
首先对列车轴承进行了故障分析,并针对该型号轴承的每个组件进行了基于ANSYS的模态分析和固有频率声学测量,准确地得到了各组件的固有频率,为轴承故障诊断提供了一定的参考数据。考虑列车轴承实际运行时的旋转速度和加载载荷等参数,设计并制作了一套列车轴承测试实验平台,通过线切割的方法人为设置列车轴承外圈故障、内圈故障和滚子故障三类最为常见的轴承故障,通过该实验平台测量了不同健康状态下列车轴承的声学信号,奠定了数据基础。
提出了一种基于瞬时频率估计的多普勒畸变校正方法。通过畸变信号的时频分布提取瞬时频率,并基于运动声源声辐射理论对瞬时频率作非线性拟合,使用拟合参数建立重采样时间序列,最终经重采样消除信号的多普勒畸变。对仿真信号以及列车轴承内外圈故障多普勒畸变信号的分析处理结果,验证了该方法校正畸变信号的有效性。
详细讨论了影响上述校正方法精度的误差来源,从提高瞬时频率估计精度的角度,提出了基于短时离散频谱校正法的瞬时频率估计方法,并进一步分析了整周期采样对提高估计精度的原理,以及变窗长短时离散频谱校正法对抑制随机误差影响的有效性。
提出了一种基于多普勒效应的强噪声滤除方法。采用Crazy Climber算法分层提取幅值较大的瞬时频率,通过运动声源声辐射理论拟合获取瞬时频率所属信号源的位置信息以确定噪声信号,设计可变带宽带阻滤波器将噪声瞬时频率滤除以增强轴承信号信噪比。对仿真信号以及含强噪声列车轴承内外圈故障信号的分析处理结果,验证了该方法滤除噪声的有效性。
针对上述滤波方法存在的计算量大的缺点,在信号源和噪声源的瞬时频率并没有出现交错的前提下,提出了针对噪声频率的畸变校正滤波法和针对目标频率的畸变校正法。在识别信号中的噪声源和信号源瞬时频率后,针对噪声频率或是信号频率先对信号进行多普勒畸变校正,进而通过定带宽滤波器滤除噪声源瞬时频率以实现滤除噪声的结果。这两种方法都在一定程度上降低了计算量,能够得到较好的效果。
The defect of the roller bearing is the dominant type of fault for a train, which lead to serious accidents and significant costs for the rail transport industry. Consequently, to develop the techniques of condition monitoring and fault diagnosis for the train bearings is indispensable. The wayside acoustic defective bearing detector system has attracted widespread attention recently for its particular advantages in fault diagnosis for the train bearings. However, some characteristics of the wayside acoustic signal, such as steep distortion, strong noises and multi-sources make the construction of that system difficult.
The train bearings with the type of NJ(P)3226X1which is the dominated type in China, is selected to be the research object in our study. A test bench was designed for this type of bearings to achieve the acoustic signal. Then the core of this paper is to study the methods to overcome some of the technical difficulties which include the removal of Doppler Shift and the filtering of the noises in the wayside acoustic defective bearing detector system. Furthermore, some improvements and verification have been discussed. The whole work is aimed to provide some basic theories and ideas to the development of the system eventually.
Firstly the analysis of the train bearings was discussed. The modal analysis based on ANSYS for all the components of the train bearing had been carried out. The vibration of each component was excited by the hammer with an accelerometer. The respondent acoustic signals were acquired by the microphone and the natural frequencies were obtained, which provides the reference data for further research in fault diagnosis of the bearing. Meanwhile, under the consideration of the rotation speed and load, the test bench was designed. The artificial cracks had been set by the wire-electrode cutting machine on the outer race, inner race and the roller respectively to acquire the acoustic signal of those three typical types of the bearing fault.
A new Doppler Shift removal method based on the instantaneous frequencies (IFs) evaluation for the train bearings is proposed. Specifically, the IF estimation based on short time Fourier transform (STFT) is applied to attain the IF vector. According to the acoustic theory of the moving source, the data fitting is then carried out to achieve the fitting IFs with which the re-sampling sequence can be established as the re-sampling vector in time domain. To demonstrate the effectiveness of this method, a simulation with three adjacent frequencies and an experiment with practical acoustic signals of the train bearings with a crack on the outer race and the inner race had been carried out.
The Doppler Shift removal error based on the method above had been analyzed. Then from the perspective of improving the precision of IF estimation, the method to estimate the IFs based on the Short time discrete spectrum correction was proposed. Based on this method, the criterion of full-period sampling was employed to increase the precision of the IF estimation and the using of variable window length was implemented to restrain the affection of the Gauss noise.
A novel de-noising method has been proposed based on Doppler Shift. With the crazy climber detection algorithm, the IFs with relatively high level could be extracted. According to the acoustic theory of the moving source, the information of the position of these acoustic sources is revealed. Finally, the variable digital filtering was employed to remove the noises from the other positions of the train. A simulation on the signal with several frequency components and the experiment with the acoustic signal of the faulted bearing mixed with several noises with high amplitude demonstrated the validity of this method.
Considering the drawbacks of the proposed method above, the filtering method based on the Doppler Shift removal with the noisy frequencies and with the objective frequencies were proposed respectively under the promise that interleaves of the IFs does not appeared in the signal. After the pre-processing of distinguish the signal frequencies from the noises, the Doppler Shift removal was carried out with the parameters of the noisy frequencies or the objective frequencies. Then a filter with certain frequency band could be used to remove the noises. Both of the methods could decrease the calculating time.
本文以现役列车轴承NJ(P)3226X1为研究对象,设计了该类型轴承的专用实验平台,重点针对列车轴承故障轨边声学检测系统存在的多普勒畸变校正和强噪声滤波两大技术难点,研究探讨了解决这两项技术难点的方法,并对方法进行改进和验证,为最终实现列车轴承故障轨边声学检测系统的研制提供一定的基础理论和解决思路。
首先对列车轴承进行了故障分析,并针对该型号轴承的每个组件进行了基于ANSYS的模态分析和固有频率声学测量,准确地得到了各组件的固有频率,为轴承故障诊断提供了一定的参考数据。考虑列车轴承实际运行时的旋转速度和加载载荷等参数,设计并制作了一套列车轴承测试实验平台,通过线切割的方法人为设置列车轴承外圈故障、内圈故障和滚子故障三类最为常见的轴承故障,通过该实验平台测量了不同健康状态下列车轴承的声学信号,奠定了数据基础。
提出了一种基于瞬时频率估计的多普勒畸变校正方法。通过畸变信号的时频分布提取瞬时频率,并基于运动声源声辐射理论对瞬时频率作非线性拟合,使用拟合参数建立重采样时间序列,最终经重采样消除信号的多普勒畸变。对仿真信号以及列车轴承内外圈故障多普勒畸变信号的分析处理结果,验证了该方法校正畸变信号的有效性。
详细讨论了影响上述校正方法精度的误差来源,从提高瞬时频率估计精度的角度,提出了基于短时离散频谱校正法的瞬时频率估计方法,并进一步分析了整周期采样对提高估计精度的原理,以及变窗长短时离散频谱校正法对抑制随机误差影响的有效性。
提出了一种基于多普勒效应的强噪声滤除方法。采用Crazy Climber算法分层提取幅值较大的瞬时频率,通过运动声源声辐射理论拟合获取瞬时频率所属信号源的位置信息以确定噪声信号,设计可变带宽带阻滤波器将噪声瞬时频率滤除以增强轴承信号信噪比。对仿真信号以及含强噪声列车轴承内外圈故障信号的分析处理结果,验证了该方法滤除噪声的有效性。
针对上述滤波方法存在的计算量大的缺点,在信号源和噪声源的瞬时频率并没有出现交错的前提下,提出了针对噪声频率的畸变校正滤波法和针对目标频率的畸变校正法。在识别信号中的噪声源和信号源瞬时频率后,针对噪声频率或是信号频率先对信号进行多普勒畸变校正,进而通过定带宽滤波器滤除噪声源瞬时频率以实现滤除噪声的结果。这两种方法都在一定程度上降低了计算量,能够得到较好的效果。
The defect of the roller bearing is the dominant type of fault for a train, which lead to serious accidents and significant costs for the rail transport industry. Consequently, to develop the techniques of condition monitoring and fault diagnosis for the train bearings is indispensable. The wayside acoustic defective bearing detector system has attracted widespread attention recently for its particular advantages in fault diagnosis for the train bearings. However, some characteristics of the wayside acoustic signal, such as steep distortion, strong noises and multi-sources make the construction of that system difficult.
The train bearings with the type of NJ(P)3226X1which is the dominated type in China, is selected to be the research object in our study. A test bench was designed for this type of bearings to achieve the acoustic signal. Then the core of this paper is to study the methods to overcome some of the technical difficulties which include the removal of Doppler Shift and the filtering of the noises in the wayside acoustic defective bearing detector system. Furthermore, some improvements and verification have been discussed. The whole work is aimed to provide some basic theories and ideas to the development of the system eventually.
Firstly the analysis of the train bearings was discussed. The modal analysis based on ANSYS for all the components of the train bearing had been carried out. The vibration of each component was excited by the hammer with an accelerometer. The respondent acoustic signals were acquired by the microphone and the natural frequencies were obtained, which provides the reference data for further research in fault diagnosis of the bearing. Meanwhile, under the consideration of the rotation speed and load, the test bench was designed. The artificial cracks had been set by the wire-electrode cutting machine on the outer race, inner race and the roller respectively to acquire the acoustic signal of those three typical types of the bearing fault.
A new Doppler Shift removal method based on the instantaneous frequencies (IFs) evaluation for the train bearings is proposed. Specifically, the IF estimation based on short time Fourier transform (STFT) is applied to attain the IF vector. According to the acoustic theory of the moving source, the data fitting is then carried out to achieve the fitting IFs with which the re-sampling sequence can be established as the re-sampling vector in time domain. To demonstrate the effectiveness of this method, a simulation with three adjacent frequencies and an experiment with practical acoustic signals of the train bearings with a crack on the outer race and the inner race had been carried out.
The Doppler Shift removal error based on the method above had been analyzed. Then from the perspective of improving the precision of IF estimation, the method to estimate the IFs based on the Short time discrete spectrum correction was proposed. Based on this method, the criterion of full-period sampling was employed to increase the precision of the IF estimation and the using of variable window length was implemented to restrain the affection of the Gauss noise.
A novel de-noising method has been proposed based on Doppler Shift. With the crazy climber detection algorithm, the IFs with relatively high level could be extracted. According to the acoustic theory of the moving source, the information of the position of these acoustic sources is revealed. Finally, the variable digital filtering was employed to remove the noises from the other positions of the train. A simulation on the signal with several frequency components and the experiment with the acoustic signal of the faulted bearing mixed with several noises with high amplitude demonstrated the validity of this method.
Considering the drawbacks of the proposed method above, the filtering method based on the Doppler Shift removal with the noisy frequencies and with the objective frequencies were proposed respectively under the promise that interleaves of the IFs does not appeared in the signal. After the pre-processing of distinguish the signal frequencies from the noises, the Doppler Shift removal was carried out with the parameters of the noisy frequencies or the objective frequencies. Then a filter with certain frequency band could be used to remove the noises. Both of the methods could decrease the calculating time.
引文
曹树谦,张文德,萧龙翔.2001.振动结构模态分析：理论、实验与应用[M].天津：天津大学出版社,225.
陈克兴,李川奇.1991.设备状态监测与故障诊断技术[M].北京：科学技术出版社,1-16,327.
陈平,李庆民,赵彤.2006.瞬时频率估计算法研究进展综述[J].电测与仪表,43(7)：1-7.
成大先,王德夫,姬奎生,等.2004.机械设计手册单行本——机械传动[M].北京：化学工业出版社,(11-4)-(11-14).
成大先,王德夫,姬奎生,等.2004.机械设计手册单行本——减(变)速器·电机与电器[M]北京：化学工业出版社,(16-3)-(16-67).
丁康,江利旗.2001.离散频谱的能量重心校正法[J].振动工程学报,14(3)：354-358.
丁康,谢明.1996.离散频谱三点卷积幅值修正法的误差分析[J].振动工程学报,9(1)：92-98.
丁康,朱文英,杨志坚,等.2010.FFT+FT离散频谱校正法参数估计精度[J].机械工程学报,46(7)：68-73.
丁康,朱小勇,谢明,等.2002.离散频谱综合相位差校正法[J].振动工程学报,15(1)：114-118.
丁康,朱小勇.2001.适用于加各种窗的一种离散频谱相位差校正法[J].电子学报,29(7)：987-989.
丁康,谢明,杨志坚.2008.离散频谱分析校正理论与技术[M].北京：科学出版社,100-155.
董锡明.2008.高速列车维修及其保障技术[M].北京：中国铁道出版社.
傅炜娜.2010.基于Vold Kalman跟踪滤波的旋转机械阶比分析方法研究[D]：[硕士].重庆：重庆大学,24-25.
高文志,郝志勇.1997.大型汽轮发电机组轴系扭振控制研制的现状与展望[J].发电设备,3：6-9.
郝如江,卢文秀,褚福磊.2008.声发射检测技术用于滚动轴承故障诊断的研究综述[J].振动与冲击,27(3)：75-79.
何宾.2011.高速列车车外噪声分布特征及车轮阻尼控制措施初步探讨[D]：[硕士].成都：西南交通大学,3-13.
何清波.2007.多元统计分析在设备状态监测诊断中的应用研究[D]：[博士],合肥：中国科学技术大学.
何正嘉,陈进,王太勇,等.2010.机械故障诊断理论及应用[M].北京：高等教育出版社,1-12.
胡劲松,吴昭同.2002.提高旋转机械振动信号整周期采样精度的一种方法[J].浙江大学学报：工学版,36(3)：273-274.
黄莎.2009.高速列车车外气动噪声数值模拟研究[D]：[硕士].长沙：中南大学,1-2.
姜诚君,李孟源,杨黎明.2004.采用声发射技术对货车轮对轴承故障进行诊断[J].铁道车辆,42(1)：20-20.
蒋振庭.1990.客车滚动轴承故障与行车安全[J].铁道车辆,7：53-56.
康立山,谢云,尤矢勇,等.1998.非数值并行算法—模拟退火算法[M].北京：科学出版社,22-38.
孔凡让,冯志华,刘志刚,等.2001.直流电机换向火花图像监测与客观评价方法的应用[J].设备管理与维修,1-18.
李兵.2010.运动汽车声场可视化方法研究[D]：[博士].北京：清华大学,82-88.
李凌志.2005.运动车辆最大辐射噪声源定位方法和试验研究[D]：[硕士].吉林：吉林大学,97-101.
李明华,罗世民.2010.铁道概论[M].长沙：中南大学出版社.
李鹏.2011.多尺度分析方法在旋转机械状态监测中的应用研究[D]：[博士].合肥：中国科学技术大学,6-8.
李帅,刘岩,杨冰,等.2011.牵引电机传动系统噪声及振动分析[J].噪声与振动控制,31(3)：149-152.
李帅.2011.牵引电机传动系统噪声与振动特性分析[D]：[硕士].大连交通大学,29-54.
李应强,孔庆春.2000.设备故障诊断技术的进展[C]//第十届全国设备监测与诊断技术学术会议论文集.
李智慧.2004.列车轴承故障监测系统研究[D]：[硕士].天津：天津大学,2-11.
刘浩.2011.货车轴承声发射信号特征提取与智能诊断研究[D]：[硕士]长沙：中南大学,5-13.
刘加利.2009.高速列车气动噪声的理论研究与数值模拟[D]：[硕士].四川：西南交通大学,1-5.
刘进明,应怀樵.1995.FFT谱连续细化分析的富里叶变换法[J].振动工程学报,8(2)：162-166.
刘琚,何振亚.2002.盲源分离和盲反卷积[J].电子学报,30(4)：570-576.
刘瑞扬,王毓民.2005.铁路货车滚动轴承早期故障轨边声学诊断系统(TADS)原理及应用[M].北京：中国铁道出版社,70-123.
刘瑞扬.2004.北美铁路车辆安全轨边检测系统的现状及思考[J].中国铁路,7：57-60.
刘永斌.2011.基于非线性信号分析的滚动轴承状态检测诊断研究[D]：[博士].合肥：中国科学技术大学,19,23-24.
刘渝.1998.正弦波频率快速估计方法[J].数据采集与处理,13(1)：8-11.
马心坦.2007.轮轨滚动噪声预测与控制研究[D]：[博士].北京：北京交通大学,3746.
倪振华.1990.振动力学[M].西安：西安交通大学出版社,182-186
宁国英,王辉.1991.客车轴温集中监测的现状及发展趋势[J].中国铁路,9：17-19.
屈维德,唐恒龄.2000.机械振动手册[M].第二版.北京：机械工业出版社,15,125-146
全子一,周利清,门爱东.2002.数字信号处理基础[M].北京：北京邮电大学出版社,145-152.
尚晓江,邱峰,赵海峰等.2008ANSYS结构有限元高级分析方法与范例应用[M].第二版.北京：中国水利水电出版社,122-126.
孙国钧,赵社戌.2006.材料力学[M].上海：上海交通大学出版社,168-187.
铁道部.2007.151132489-2007,铁路客车轮对和滚动轴承轴箱组装及检修规则[S].北京：中国铁道出版社.
涂善东,葛世荣,孟光,等.2006.机械结构强度与失效,机械与制造科学学科发展战略报告(2006-2010年)[M].北京：科学出版社,74-104.
王浩川,张赫磊.1990.轨道车辆直流牵引电机噪声的分析与研究[J].大连铁道学院学报,4：51-54.
王磊,郝士琦,戎雁.2008.瞬时频率的Prony方法提取及MATLAB实现[J].计算机仿真,25(002)：303-305.
王玉波.2010.600MW汽轮机故障智能诊断系统研究[D].[硕士].长沙：长沙理工大学.
吴强,孔凡让,何清波,等.2012.基于重采样技术的声学信号多普勒畸变校正[J].信号处理,28(9)：1308-1313.
吴伟,唐斌.2007.基于扩展傅里叶变换的可变带宽滤波器设计[J].仪器仪表学报,28(5)：826-831.
吴伟,唐斌.2008.可变带宽FIR数字滤波器的高最小二乘设计及实现[J].仪器仪表学报,29(3)：550-555.
吴伟,唐斌.2008.可变带宽线性相位FIR滤波器的设计和实现术[J].仪器仪表学报,29(4).782-786.
吴昭同,杨世锡,等.2012.旋转机械故障特征提取与模式分类新方法[M].北京：科学出版社,1-25
谢福科.2007.基于近场声全息的运动车辆噪声源识别方法研究[D]：[硕士].吉林：吉林大学,33-38.
谢明,丁康.1995.离散频谱分析的一种新校正方法[J].重庆大学学报：自然科学版,18(2)：48-54.
谢明,张晓飞,丁康.1999.频谱分析中用于相位和频率校正的相位差校正法[J].振动工程学报,12(4)：454-459.
胥永刚.2003.机电设备监测诊断时域新方法的应用研究[D]：[博士].西安：西安交通大学,2003.
徐敏.1998.设备故障诊断手册——机械设备状态监测与故障诊断[M].西安：西安交通出版社,1-12.
许立群,张弘,蔡炳台,等.1997.货车滚动轴承燃切轴原因分析及防范措施[J].铁道车辆,35(4)：55-57.
杨殿阁,李兵,王子腾,等.2012.运动声源识别的动态波叠加方法研究[J].物理学报,61(5)：054306.
杨殿阁,郑四发,罗禹贡,等.2002.运动声源的声全息识别方法[J].声学学报,27(4)：357-362.
杨国安.2012.滚动轴承故障诊断实用技术[M].北京：中国石化出版社,18-34,42-43.
杨景义,王信义.1990.试验模态分析[M].北京：北京理工大学出版社,82-110.
俞悟周,王晨,毛东兴,等.2009.高速铁路动车组列车的噪声特性[J].环境污染与防治,31(1)：74-77.
虞和济.1989.机械故障诊断丛书：故障诊断的基本原理[M].北京：冶金工业出版社.
张长会.2005.固有频率测量精度的声频法及其工程应用[J].合肥工业大学学报(自然科学版),28(12)：1556-1560.
张朝解.2006.小波分析在旋转机械故障诊断中的应用[D]：[硕士J.大连：大连理工大学,1-6.
张生.2009.基于振动信号处理及模态分析的机械故障诊断技术研究[D]：[硕士].秦皇岛：燕山大学,4-5.
张曙光.2009.350km/h高速列车噪声机理,声源识别及控制[J].中国铁道科学,30(1)：86-90.
张晓冬.2003基于脊提取的信号表示和重建[D]：[博士].南京：东南大学.21-25.
张正松,傅尚新,冯冠平.1991.旋转机械振动监测及故障诊断[M].北京：机械工业出版社.
赵长波,陈雷.2009.红外线轴温探测系统的发展与思考[J].铁道车辆,47(1)：28-30.
赵纪元.1997.基于小波理论,神经网络的实用诊断技术研究[D]：[博士].西安：西安交通大学.
中华人民共和国国家质量监督检验检疫总局,中国国家标准化管理委员会.2008.GB/T15530.12008,中华人民共和国国家标准-铸造铜合金技术条件[S].北京：中国标准出版社.
中华人民共和国国家质量监督检验检疫总局.2002.GB\T 18254-2002-2002,中华人民共和国国家标准-高碳铬轴承钢[S].北京：中国标准出版社.
中华人民共和国国务院.2006.国家中长期科学和技术发展规划纲要(2006-2020).
钟群鹏,张峥,有移亮.2007.我国安全生产(含安全制造)的科学发展若干问题木[J].机械工程学报,43(1)：7-18.
周仕仁,钟声,章鹏.2009.列车滚轴轴承故障诊断研究现状分析[J].中国铁路,11：35-39.
朱革,彭东林,张兴红,等.2002.齿轮振动噪声分析及控制[J].现代制造工程,10：48-51.
朱小勇,丁康.2001.离散频谱校正方法的综合比较[J].信号处理,17(1)：91-97.
左鹤声,彭玉莺.1995.振动试验模态分析[M].北京：中国铁道出版社,124-126.
Ahuja SS, Roy SD.1978. Variable-cutoff two-dimensional lowpass FIR digital filters[J]. Electronics Letters,14(14):422-423.
Ahuja SS, Roy SD.1980. Variable digital filters[J]. Circuits and Systems, IEEE Transactions on, 27(9):836-838.
Anderson GB, Smith RL.1997. Acoustic Identification of a Spun Cone Roller Bearing Defect[C]//ASME Paper presented at the Winter Annual Meeting, Dallas, TX:19-25.
Barsikow B, King WF, Pfizenmaier E.1987. Wheel/rail noise generated by a high-speed train investigated with a line array of microphones[J]. Journal of sound and vibration,118(1): 99-122.
Barsikow B, King WF.1988. On removing the Doppler frequency shift from array measurements of railway noise[J]. Journal of Sound and Vibration,102:190-196.
Barthel K.1977. The Shock Pulse Method for Measuring the Condition of Antifriction Bearing[J]. Tappi,60(8):111-113.
Bladon K, Rennison D, Izbinsky G, et al.2004. Predictive condition monitoring of railway rolling stock[C]//Proceedings of the Conference on Railway Engineering, Darwin:20-23.
Boashash B.1992. Estimating and interpreting the instantaneous frequency of a signal. Ⅰ. Fundamentals[J]. Proceedings of the IEEE,80(4):520-538.
Boashash B.1992. Estimating and interpreting the instantaneous frequency of a signal. Ⅱ. Algorithms and applications[J]. Proceedings of the IEEE,80(4):540-568.
Boudraa AO, Cexus JC, Salzenstein F, et al.2004. IF estimation using empirical mode decomposition and nonlinear Teager energy operator[C]//Control, Communications and Signal Processing First International Symposium on. IEEE:45-48.
Burel G.1992. Blind separation of sources:A nonlinear neural algorithm[J]. Neural networks,5(6): 937-947.
Carmona R, Hwang WL, Torresani B.1998. Practical Time-Frequency Analysis:Gabor and Wavelet Transforms, with an Implementation in S[M]. San Diango, CA:Academic Press, 292-296.
Carmona RA, Hwang WL, Torresani B.1999. Multiridge detection and time-frequency reconstruction[J]. Signal Processing, IEEE Transactions on,47(2):480-492.
Carson MJ, Fry TC.1937. Variable frequency electric circuit theory with application to the theory of frequency modulation[J]. Bell System Technical Journal,16:513-540.
Choe HC, Wan Y, Chan AK.1997. Neural pattern identification of railroad wheel-bearing faults from audible acoustic signals:comparison of FFT, CWT and DWT features[C]//Harold H. Szu. SPIE Proceedings on Wavelet Applications,3087. Orlando:SPIE,480-496.
Cline JE, Bilodeau JR, Smith RL.1998. Acoustic wayside identification of freight car roller bearing defects[C]//Railroad Conference, Proceedings of the 1998 ASME/IEEE Joint. IEEE. Philadelphia, PA:79-83.
Cohen L.1998时-频分析：理论与应用[M].白宪居,译.西安：西安交通大学出版社,23-33.
Cong WX, Chen NX, Gu BY.1998. Recursive algorithm for phase retrieval in the fractional Fourier transform domain[J]. Applied optics,37(29):6906-6910.
Cong WX, Chen NX, Gu BY.1999. Phase retrieval in the Fresnel transform system:a recursive algorithm[J]. Journal of the Optical Society of America A,16(7):1827-1830.
Constantinides AG.1970. Spectral transformations for digital filters[C]//Proceedings of the Institution of Electrical Engineers. IET Digital Library,117(8):1585-1590.
Crochiere R, Rabiner L.1976. On the properties of frequency transformations for variable cutoff linear phase digital filters[J]. Circuits and Systems, IEEE Transactions on,23(11):684-686.
Deng TB, Okamoto E.2003. SVD-based design of fractional-delay 2-D digital filters exploiting specification symmetries[J]. Circuits and Systems Ⅱ:Analog and Digital Signal Processing, IEEE Transactions on,50(8):470-480.
Deng TB.2000. Weighted least-squares method for designing arbitrarily variable 1-D FIR digital filters[J]. Signal processing,80(4):597-613.
Deng TB.2003. Vector-array decomposition-based design of variable digital filters[C]//Circuits and Systems, ISCAS'03. Proceedings of the 2003 International Symposium on. IEEE,3: Ⅲ-550-Ⅲ-553.
Ding K, Luo J, Xie M.2002. Time-shifting correcting method of phase difference on discrete spectrum[J]. Applied Mathematics and Mechanics,23(7):819-827.
Ding K, Xie M, Zhang X.2000, Phase difference correction method for phase and frequency in spectral analysis[J]. Mechanical Systems and Signal Processing,14(5):835-843.
Dybala J, Gatezia A, Maczak J.2008. Verification of Doppler Effect removal method for the needs of pass-by railway condition monitoring system[J]. Diagnostyka,4(48):5-8.
Dybala J, Radkowski S.2012. Reduction of Doppler effect for the needs of wayside condition monitoring system of railway vehicles[J]. Mechanical Systems and Signal Processing. In press.
Dybala J.2008. Use of task-oriented dynamic resampling in reduction of signal non-stationaity[J], Diagnostyka,4(48):25-30.
El-Ghoroury H, Gupta S.1976. Wave digital filter structures with variable frequency characteristics[J]. Circuits and Systems, IEEE Transactions on,23(10):624-630.
Florom RL, Hiatt JE, Smith RL.1987. Wayside acoustic detection of railroad roller bearing defects[C]. Proceedings of the 1987 Winter Annual Meeting of the ASME. Boston, MA
Florom RL.1988. Wayside acoustic detection of railroad roller bearing defects[J]. ASME WINTER.79-92.
Gabor D.1946. Theory of communication[J]. Journal of the Institution of Electrical Engineers,93: 429-457.
He Q, Wang J, Liu Y, et al.2011. Bearing defect diagnosis by stochastic resonance with parameter tuning[C]//Prognostics and System Health Management Conference (PHM-Shenzhen), IEEE: 1-5.
He Q, Yan R, Kong F, et al.2009. Machine condition monitoring using principle component responsentations[J]. Mechanical System and Signal Processing,23(2):446-466.
Heylen W, Lammens S, Sas P.2001模态分析理论与试验[M].白化同,郭继忠,译.北京：北京理工大学出版社,9-11.
Hu F, He Q, Wang J, et al.2012. Commutation Sparking Image Monitoring for DC Motor[J]. Journal of Manufacturing Science and Engineering,134:024501-1.
Huang NE, Shen Z, Long SR, et al.1998. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[J]. Proceedings of the Royal Society of London. Series A:Mathematical, Physical and Engineering Sciences,454(1971): 903-995.
Hyvarinen A, Oja E.2000. Independent component analysis:algorithms and applications[J]. Neural networks,2000,13(4):411-430.
Imam I, Azzaro S H, Bankert R J, et al.1989. Development of an on-line rotor crack detection and monitoring system[J]. Journal of Vibration Acoustics Stress and Reliability in Design,111: 241.
Irani FD, et al.2002先进道旁车辆状态监视系统的开发和应用[J].吴朝院,译.国外铁道车辆,39(2)：39-45.
Jarske P, Mitra SK, Neuvo Y.1988. Signal processor implementation of variable digital filters[J]. Instrumentation and Measurement, IEEE Transactions on,37(3):363-367.
Johnson D.1979. Variable digital filters having a recursive structure[J]. Acoustics, Speech and Signal Processing, IEEE Transactions on,27(1):98-99.
Johnson M, Freitag L, Stojanovic M.1997. Improved Doppler tracking and correction for underwater acoustic communications[C]//Acoustics, Speech, and Signal Processing, ICASSP-97.,1997 IEEE International Conference on. IEEE,1:575-578.
Karam LJ, McClellan JH.1996. Efficient design of families of FIR filters by transformation[C]//Acoustics, Speech, and Signal Processing,1996. ICASSP-96. Conference Proceedings, IEEE International Conference on. IEEE,3:1359-1362.
King WF, Bechert D.1979. On the sources of wayside noise generated by high-speed trains[J]. Journal of Sound and Vibration,66(3):311-332.
Kitagawa T, Nagakura K.2000. Aerodynamic noise generated by Shinkansen cars[J]. Journal of Sound and vibration,231(3):913-924.
Kitagawa T, Thompson DJ.2010. The horizontal directivity of noise radiated by a rail and implications for the use of microphone arrays[J]. Journal of sound and vibration,329(2): 202-220.
Kwok HK, Jones DL.1995. Instantaneous frequency estimation using an adaptive short-time Fourier transform[C]//Signals, Systems and Computers, Conference Record of the Twenty-Ninth Asilomar Conference on. IEEE,1:543-547.
Kwok HK, Jones DL.2000. Improved instantaneous frequency estimation using an adaptive short-time Fourier transform[J]. Signal Processing, IEEE Transactions on,48(10): 2964-2972.
Kwon HS, Kim YH.1998. Moving frame technique for planar acoustic holography[J]. The Journal of the Acoustical Society of America,103:1734.
Lagneback R.2007. Evaluation of wayside condition monitoring technologies for condition-based maintenance of railway vehiclesfD]:[Licentiate], Sweden:Lulea University of Technology, 5-6.
Lee H, Bien Z.2004. Bandpass variable-bandwidth filter for reconstruction of signals with known boundary in time-frequency domain[J]. Signal Processing Letters, IEEE,11(2):160-163.
Li P, He Q, Kong F.2010. An approach for fault diagnosis of bearings using wavelet-based fractal analysis[C]//Information and Automation (ICIA),2010 IEEE International Conference on. IEEE:2338-2343.
Morse PM, Ingard KU.1986.理论声学(下册)[M].杨训仁,赵慧芝译.北京：科学出版社,842-850.
Nagakura K.2006. Localization of aerodynamic noise sources of Shinkansen trains[J]. Journal of sound and vibration,293(3):547-556.
Oppenheim A, Mecklenbrauker W, Mersereau R.1976. Variable cutoff linear phase digital filters[J]. Circuits and Systems, IEEE Transactions on,23(4):199-203.
Park SH, Kim YH.2001. Visualization of pass-by noise by means of moving frame acoustic holography[J]. The Journal of the Acoustical Society of America,110:2326.
Poisson F, Gautier PE, Letourneaux F.2008. Noise sources for high speed trains:A review of results in the TGV case[M]//Noise and Vibration Mitigation for Rail Transportation Systems. Springer Berlin Heidelberg:71-77.
Ram SS, Li Y, Lin A, et al.2008. Doppler-based detection and tracking of humans in indoor environments[J]. Journal of the Franklin Institute,345(6):679-699.
Roy SD, Ahuja S.1979. Frequency transformations for linear-phase variable-cutoff digital filters[J]. Circuits and Systems, IEEE Transactions on,26(1):73-75.
Scalise L, Paone N.2002. Laser Doppler vibrometry based on self-mixing effect[J]. Optics and lasers in Engineering,38(3):173-184.
SchuBlerHW, Kolb HJ.1982. Variable digital filters[J]. Archiv Elektronik und Uebertragungstechnik,36:229-237.
Schussler HW, Winkelnkemper W.1970. Variable digital filters, Archiv Elektronik und Uebertragungstechnik,24(11):219-220.
Smith RL, Bambara JE, Florom RL.1988. Railcar bearing end-life failure distances and acoustical defect censuring methods[C]. Proceedings of the 1988 Winter Annual Meeting of the ASME, Chicago, IL.
Sneed WH, Smith RL.1998. On-board real-time railroad bearing defect detection and monitoring[C]//Railroad Conference, Proceedings of the 1998 ASME/IEEE Joint. IEEE, Philadelphia, PA:149-153.
Snell OD, Nairne I.2008. Acoustic bearing monitoring-the future RCM 2008[C]//Railway Condition Monitoring,2008 4th IET International Conference on. IET:1-5.
Southern C, Kopke U.2002. Railbam and WCM wayside detection systems[C]//Journal and report of proceedings-Permanent Way Institution. Permanent Way Institution,120:361-368.
Southern C, Rennison D, Kopke U.2004. RailBAM-an Advanced Bearing Acoustic Monitor: Initial Operational Performance Results[J]. CORE:New Horizons for Rail:23.
Stojanovic M, Catipovic JA, Proakis JG.1994. Phase-coherent digital communications for underwater acoustic channels[J]. Oceanic Engineering, IEEE Journal of,19(1):100-111.
Stoyanov G, Kawamata M.1997. Variable digital filters[J]. Journal of Signal Processing,1(4): 275-289.
Streit RL, Barrett RF.1990. Frequency line tracking using hidden Markov models[J]. Acoustics, Speech and Signal Processing, IEEE Transactions on,38(4):586-598.
Talotte C, Gautier PE, Thompson DJ, et al.2003. Identification, modelling and reduction potential of railway noise sources:a critical survey [J]. Journal of Sound and Vibration,267(3): 447-468.
Talotte C.2000. Aerodynamic noise:a critical survey[J]. Journal of sound and vibration,231(3): 549-562.
Tandon N, Choudhury A.1999. A review of vibration and acoustic measurement methods for the detection of defects in rolling element bearings[J]. Tribology International,32(8):469-480.
Thompson D.2008. Railway noise and vibration:mechanisms, modelling and means of control[M]. Amsterdam:Elsevier Science.6-9.
Van der Pol B.1946. The fundamental principles of frequency modulation[J], Proceeding of the IEEE,93:153-158.
Ville J.1948. Theorie et applications de la notion de signal analytique[J]. Cables et transmission, 2(1):61-74.
Wang C, Amin MG.1997. Zero-tracking time-frequency distributions[C]//Acoustics, Speech, and Signal Processing, ICASSP-97, IEEE International Conference on. IEEE,3:2021-2024.
Wang Y, He Z, Zi Y.2001. A comparative study on the local mean decomposition and empirical mode decomposition and their applications to rotating machinery health diagnosis[J]. Journal of vibration and acoustics,132(2).
Working Group Railway Noise of the European Commission.2003. Position Paper on the European strategies and priorities for railway noise abatement[M]. Luxembourg:Office for Official Publications of the European Communities.14-17.
Xie M, Ding K.1996. Correction for the frequency, amplitude and phase in FFT of harmonic signal[J]. Mechanical Systems and Signal Processing.10(2):211-221.
Xu X, Sun L, Cannata JM, et al.2008. High-frequency ultrasound Doppler system for biomedical applications with a 30-MHz linear array[J]. Ultrasound in medicine & biology,2008,34(4): 638-646.
Zarour R, Fahmy MM.1989. A design technique for variable digital filters[J]. Circuits and Systems, IEEE Transactions on,36(11):1473-1478.
Zhang Z, Pouliquen P, Waxman A, et al.2007. Acoustic micro-Doppler gait signatures of humans and animals[C]//Information Sciences and Systems,2007. CISS'07.41st Annual Conference on. IEEE:627-630.
陈克兴,李川奇.1991.设备状态监测与故障诊断技术[M].北京：科学技术出版社,1-16,327.
陈平,李庆民,赵彤.2006.瞬时频率估计算法研究进展综述[J].电测与仪表,43(7)：1-7.
成大先,王德夫,姬奎生,等.2004.机械设计手册单行本——机械传动[M].北京：化学工业出版社,(11-4)-(11-14).
成大先,王德夫,姬奎生,等.2004.机械设计手册单行本——减(变)速器·电机与电器[M]北京：化学工业出版社,(16-3)-(16-67).
丁康,江利旗.2001.离散频谱的能量重心校正法[J].振动工程学报,14(3)：354-358.
丁康,谢明.1996.离散频谱三点卷积幅值修正法的误差分析[J].振动工程学报,9(1)：92-98.
丁康,朱文英,杨志坚,等.2010.FFT+FT离散频谱校正法参数估计精度[J].机械工程学报,46(7)：68-73.
丁康,朱小勇,谢明,等.2002.离散频谱综合相位差校正法[J].振动工程学报,15(1)：114-118.
丁康,朱小勇.2001.适用于加各种窗的一种离散频谱相位差校正法[J].电子学报,29(7)：987-989.
丁康,谢明,杨志坚.2008.离散频谱分析校正理论与技术[M].北京：科学出版社,100-155.
董锡明.2008.高速列车维修及其保障技术[M].北京：中国铁道出版社.
傅炜娜.2010.基于Vold Kalman跟踪滤波的旋转机械阶比分析方法研究[D]：[硕士].重庆：重庆大学,24-25.
高文志,郝志勇.1997.大型汽轮发电机组轴系扭振控制研制的现状与展望[J].发电设备,3：6-9.
郝如江,卢文秀,褚福磊.2008.声发射检测技术用于滚动轴承故障诊断的研究综述[J].振动与冲击,27(3)：75-79.
何宾.2011.高速列车车外噪声分布特征及车轮阻尼控制措施初步探讨[D]：[硕士].成都：西南交通大学,3-13.
何清波.2007.多元统计分析在设备状态监测诊断中的应用研究[D]：[博士],合肥：中国科学技术大学.
何正嘉,陈进,王太勇,等.2010.机械故障诊断理论及应用[M].北京：高等教育出版社,1-12.
胡劲松,吴昭同.2002.提高旋转机械振动信号整周期采样精度的一种方法[J].浙江大学学报：工学版,36(3)：273-274.
黄莎.2009.高速列车车外气动噪声数值模拟研究[D]：[硕士].长沙：中南大学,1-2.
姜诚君,李孟源,杨黎明.2004.采用声发射技术对货车轮对轴承故障进行诊断[J].铁道车辆,42(1)：20-20.
蒋振庭.1990.客车滚动轴承故障与行车安全[J].铁道车辆,7：53-56.
康立山,谢云,尤矢勇,等.1998.非数值并行算法—模拟退火算法[M].北京：科学出版社,22-38.
孔凡让,冯志华,刘志刚,等.2001.直流电机换向火花图像监测与客观评价方法的应用[J].设备管理与维修,1-18.
李兵.2010.运动汽车声场可视化方法研究[D]：[博士].北京：清华大学,82-88.
李凌志.2005.运动车辆最大辐射噪声源定位方法和试验研究[D]：[硕士].吉林：吉林大学,97-101.
李明华,罗世民.2010.铁道概论[M].长沙：中南大学出版社.
李鹏.2011.多尺度分析方法在旋转机械状态监测中的应用研究[D]：[博士].合肥：中国科学技术大学,6-8.
李帅,刘岩,杨冰,等.2011.牵引电机传动系统噪声及振动分析[J].噪声与振动控制,31(3)：149-152.
李帅.2011.牵引电机传动系统噪声与振动特性分析[D]：[硕士].大连交通大学,29-54.
李应强,孔庆春.2000.设备故障诊断技术的进展[C]//第十届全国设备监测与诊断技术学术会议论文集.
李智慧.2004.列车轴承故障监测系统研究[D]：[硕士].天津：天津大学,2-11.
刘浩.2011.货车轴承声发射信号特征提取与智能诊断研究[D]：[硕士]长沙：中南大学,5-13.
刘加利.2009.高速列车气动噪声的理论研究与数值模拟[D]：[硕士].四川：西南交通大学,1-5.
刘进明,应怀樵.1995.FFT谱连续细化分析的富里叶变换法[J].振动工程学报,8(2)：162-166.
刘琚,何振亚.2002.盲源分离和盲反卷积[J].电子学报,30(4)：570-576.
刘瑞扬,王毓民.2005.铁路货车滚动轴承早期故障轨边声学诊断系统(TADS)原理及应用[M].北京：中国铁道出版社,70-123.
刘瑞扬.2004.北美铁路车辆安全轨边检测系统的现状及思考[J].中国铁路,7：57-60.
刘永斌.2011.基于非线性信号分析的滚动轴承状态检测诊断研究[D]：[博士].合肥：中国科学技术大学,19,23-24.
刘渝.1998.正弦波频率快速估计方法[J].数据采集与处理,13(1)：8-11.
马心坦.2007.轮轨滚动噪声预测与控制研究[D]：[博士].北京：北京交通大学,3746.
倪振华.1990.振动力学[M].西安：西安交通大学出版社,182-186
宁国英,王辉.1991.客车轴温集中监测的现状及发展趋势[J].中国铁路,9：17-19.
屈维德,唐恒龄.2000.机械振动手册[M].第二版.北京：机械工业出版社,15,125-146
全子一,周利清,门爱东.2002.数字信号处理基础[M].北京：北京邮电大学出版社,145-152.
尚晓江,邱峰,赵海峰等.2008ANSYS结构有限元高级分析方法与范例应用[M].第二版.北京：中国水利水电出版社,122-126.
孙国钧,赵社戌.2006.材料力学[M].上海：上海交通大学出版社,168-187.
铁道部.2007.151132489-2007,铁路客车轮对和滚动轴承轴箱组装及检修规则[S].北京：中国铁道出版社.
涂善东,葛世荣,孟光,等.2006.机械结构强度与失效,机械与制造科学学科发展战略报告(2006-2010年)[M].北京：科学出版社,74-104.
王浩川,张赫磊.1990.轨道车辆直流牵引电机噪声的分析与研究[J].大连铁道学院学报,4：51-54.
王磊,郝士琦,戎雁.2008.瞬时频率的Prony方法提取及MATLAB实现[J].计算机仿真,25(002)：303-305.
王玉波.2010.600MW汽轮机故障智能诊断系统研究[D].[硕士].长沙：长沙理工大学.
吴强,孔凡让,何清波,等.2012.基于重采样技术的声学信号多普勒畸变校正[J].信号处理,28(9)：1308-1313.
吴伟,唐斌.2007.基于扩展傅里叶变换的可变带宽滤波器设计[J].仪器仪表学报,28(5)：826-831.
吴伟,唐斌.2008.可变带宽FIR数字滤波器的高最小二乘设计及实现[J].仪器仪表学报,29(3)：550-555.
吴伟,唐斌.2008.可变带宽线性相位FIR滤波器的设计和实现术[J].仪器仪表学报,29(4).782-786.
吴昭同,杨世锡,等.2012.旋转机械故障特征提取与模式分类新方法[M].北京：科学出版社,1-25
谢福科.2007.基于近场声全息的运动车辆噪声源识别方法研究[D]：[硕士].吉林：吉林大学,33-38.
谢明,丁康.1995.离散频谱分析的一种新校正方法[J].重庆大学学报：自然科学版,18(2)：48-54.
谢明,张晓飞,丁康.1999.频谱分析中用于相位和频率校正的相位差校正法[J].振动工程学报,12(4)：454-459.
胥永刚.2003.机电设备监测诊断时域新方法的应用研究[D]：[博士].西安：西安交通大学,2003.
徐敏.1998.设备故障诊断手册——机械设备状态监测与故障诊断[M].西安：西安交通出版社,1-12.
许立群,张弘,蔡炳台,等.1997.货车滚动轴承燃切轴原因分析及防范措施[J].铁道车辆,35(4)：55-57.
杨殿阁,李兵,王子腾,等.2012.运动声源识别的动态波叠加方法研究[J].物理学报,61(5)：054306.
杨殿阁,郑四发,罗禹贡,等.2002.运动声源的声全息识别方法[J].声学学报,27(4)：357-362.
杨国安.2012.滚动轴承故障诊断实用技术[M].北京：中国石化出版社,18-34,42-43.
杨景义,王信义.1990.试验模态分析[M].北京：北京理工大学出版社,82-110.
俞悟周,王晨,毛东兴,等.2009.高速铁路动车组列车的噪声特性[J].环境污染与防治,31(1)：74-77.
虞和济.1989.机械故障诊断丛书：故障诊断的基本原理[M].北京：冶金工业出版社.
张长会.2005.固有频率测量精度的声频法及其工程应用[J].合肥工业大学学报(自然科学版),28(12)：1556-1560.
张朝解.2006.小波分析在旋转机械故障诊断中的应用[D]：[硕士J.大连：大连理工大学,1-6.
张生.2009.基于振动信号处理及模态分析的机械故障诊断技术研究[D]：[硕士].秦皇岛：燕山大学,4-5.
张曙光.2009.350km/h高速列车噪声机理,声源识别及控制[J].中国铁道科学,30(1)：86-90.
张晓冬.2003基于脊提取的信号表示和重建[D]：[博士].南京：东南大学.21-25.
张正松,傅尚新,冯冠平.1991.旋转机械振动监测及故障诊断[M].北京：机械工业出版社.
赵长波,陈雷.2009.红外线轴温探测系统的发展与思考[J].铁道车辆,47(1)：28-30.
赵纪元.1997.基于小波理论,神经网络的实用诊断技术研究[D]：[博士].西安：西安交通大学.
中华人民共和国国家质量监督检验检疫总局,中国国家标准化管理委员会.2008.GB/T15530.12008,中华人民共和国国家标准-铸造铜合金技术条件[S].北京：中国标准出版社.
中华人民共和国国家质量监督检验检疫总局.2002.GB\T 18254-2002-2002,中华人民共和国国家标准-高碳铬轴承钢[S].北京：中国标准出版社.
中华人民共和国国务院.2006.国家中长期科学和技术发展规划纲要(2006-2020).
钟群鹏,张峥,有移亮.2007.我国安全生产(含安全制造)的科学发展若干问题木[J].机械工程学报,43(1)：7-18.
周仕仁,钟声,章鹏.2009.列车滚轴轴承故障诊断研究现状分析[J].中国铁路,11：35-39.
朱革,彭东林,张兴红,等.2002.齿轮振动噪声分析及控制[J].现代制造工程,10：48-51.
朱小勇,丁康.2001.离散频谱校正方法的综合比较[J].信号处理,17(1)：91-97.
左鹤声,彭玉莺.1995.振动试验模态分析[M].北京：中国铁道出版社,124-126.
Ahuja SS, Roy SD.1978. Variable-cutoff two-dimensional lowpass FIR digital filters[J]. Electronics Letters,14(14):422-423.
Ahuja SS, Roy SD.1980. Variable digital filters[J]. Circuits and Systems, IEEE Transactions on, 27(9):836-838.
Anderson GB, Smith RL.1997. Acoustic Identification of a Spun Cone Roller Bearing Defect[C]//ASME Paper presented at the Winter Annual Meeting, Dallas, TX:19-25.
Barsikow B, King WF, Pfizenmaier E.1987. Wheel/rail noise generated by a high-speed train investigated with a line array of microphones[J]. Journal of sound and vibration,118(1): 99-122.
Barsikow B, King WF.1988. On removing the Doppler frequency shift from array measurements of railway noise[J]. Journal of Sound and Vibration,102:190-196.
Barthel K.1977. The Shock Pulse Method for Measuring the Condition of Antifriction Bearing[J]. Tappi,60(8):111-113.
Bladon K, Rennison D, Izbinsky G, et al.2004. Predictive condition monitoring of railway rolling stock[C]//Proceedings of the Conference on Railway Engineering, Darwin:20-23.
Boashash B.1992. Estimating and interpreting the instantaneous frequency of a signal. Ⅰ. Fundamentals[J]. Proceedings of the IEEE,80(4):520-538.
Boashash B.1992. Estimating and interpreting the instantaneous frequency of a signal. Ⅱ. Algorithms and applications[J]. Proceedings of the IEEE,80(4):540-568.
Boudraa AO, Cexus JC, Salzenstein F, et al.2004. IF estimation using empirical mode decomposition and nonlinear Teager energy operator[C]//Control, Communications and Signal Processing First International Symposium on. IEEE:45-48.
Burel G.1992. Blind separation of sources:A nonlinear neural algorithm[J]. Neural networks,5(6): 937-947.
Carmona R, Hwang WL, Torresani B.1998. Practical Time-Frequency Analysis:Gabor and Wavelet Transforms, with an Implementation in S[M]. San Diango, CA:Academic Press, 292-296.
Carmona RA, Hwang WL, Torresani B.1999. Multiridge detection and time-frequency reconstruction[J]. Signal Processing, IEEE Transactions on,47(2):480-492.
Carson MJ, Fry TC.1937. Variable frequency electric circuit theory with application to the theory of frequency modulation[J]. Bell System Technical Journal,16:513-540.
Choe HC, Wan Y, Chan AK.1997. Neural pattern identification of railroad wheel-bearing faults from audible acoustic signals:comparison of FFT, CWT and DWT features[C]//Harold H. Szu. SPIE Proceedings on Wavelet Applications,3087. Orlando:SPIE,480-496.
Cline JE, Bilodeau JR, Smith RL.1998. Acoustic wayside identification of freight car roller bearing defects[C]//Railroad Conference, Proceedings of the 1998 ASME/IEEE Joint. IEEE. Philadelphia, PA:79-83.
Cohen L.1998时-频分析：理论与应用[M].白宪居,译.西安：西安交通大学出版社,23-33.
Cong WX, Chen NX, Gu BY.1998. Recursive algorithm for phase retrieval in the fractional Fourier transform domain[J]. Applied optics,37(29):6906-6910.
Cong WX, Chen NX, Gu BY.1999. Phase retrieval in the Fresnel transform system:a recursive algorithm[J]. Journal of the Optical Society of America A,16(7):1827-1830.
Constantinides AG.1970. Spectral transformations for digital filters[C]//Proceedings of the Institution of Electrical Engineers. IET Digital Library,117(8):1585-1590.
Crochiere R, Rabiner L.1976. On the properties of frequency transformations for variable cutoff linear phase digital filters[J]. Circuits and Systems, IEEE Transactions on,23(11):684-686.
Deng TB, Okamoto E.2003. SVD-based design of fractional-delay 2-D digital filters exploiting specification symmetries[J]. Circuits and Systems Ⅱ:Analog and Digital Signal Processing, IEEE Transactions on,50(8):470-480.
Deng TB.2000. Weighted least-squares method for designing arbitrarily variable 1-D FIR digital filters[J]. Signal processing,80(4):597-613.
Deng TB.2003. Vector-array decomposition-based design of variable digital filters[C]//Circuits and Systems, ISCAS'03. Proceedings of the 2003 International Symposium on. IEEE,3: Ⅲ-550-Ⅲ-553.
Ding K, Luo J, Xie M.2002. Time-shifting correcting method of phase difference on discrete spectrum[J]. Applied Mathematics and Mechanics,23(7):819-827.
Ding K, Xie M, Zhang X.2000, Phase difference correction method for phase and frequency in spectral analysis[J]. Mechanical Systems and Signal Processing,14(5):835-843.
Dybala J, Gatezia A, Maczak J.2008. Verification of Doppler Effect removal method for the needs of pass-by railway condition monitoring system[J]. Diagnostyka,4(48):5-8.
Dybala J, Radkowski S.2012. Reduction of Doppler effect for the needs of wayside condition monitoring system of railway vehicles[J]. Mechanical Systems and Signal Processing. In press.
Dybala J.2008. Use of task-oriented dynamic resampling in reduction of signal non-stationaity[J], Diagnostyka,4(48):25-30.
El-Ghoroury H, Gupta S.1976. Wave digital filter structures with variable frequency characteristics[J]. Circuits and Systems, IEEE Transactions on,23(10):624-630.
Florom RL, Hiatt JE, Smith RL.1987. Wayside acoustic detection of railroad roller bearing defects[C]. Proceedings of the 1987 Winter Annual Meeting of the ASME. Boston, MA
Florom RL.1988. Wayside acoustic detection of railroad roller bearing defects[J]. ASME WINTER.79-92.
Gabor D.1946. Theory of communication[J]. Journal of the Institution of Electrical Engineers,93: 429-457.
He Q, Wang J, Liu Y, et al.2011. Bearing defect diagnosis by stochastic resonance with parameter tuning[C]//Prognostics and System Health Management Conference (PHM-Shenzhen), IEEE: 1-5.
He Q, Yan R, Kong F, et al.2009. Machine condition monitoring using principle component responsentations[J]. Mechanical System and Signal Processing,23(2):446-466.
Heylen W, Lammens S, Sas P.2001模态分析理论与试验[M].白化同,郭继忠,译.北京：北京理工大学出版社,9-11.
Hu F, He Q, Wang J, et al.2012. Commutation Sparking Image Monitoring for DC Motor[J]. Journal of Manufacturing Science and Engineering,134:024501-1.
Huang NE, Shen Z, Long SR, et al.1998. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[J]. Proceedings of the Royal Society of London. Series A:Mathematical, Physical and Engineering Sciences,454(1971): 903-995.
Hyvarinen A, Oja E.2000. Independent component analysis:algorithms and applications[J]. Neural networks,2000,13(4):411-430.
Imam I, Azzaro S H, Bankert R J, et al.1989. Development of an on-line rotor crack detection and monitoring system[J]. Journal of Vibration Acoustics Stress and Reliability in Design,111: 241.
Irani FD, et al.2002先进道旁车辆状态监视系统的开发和应用[J].吴朝院,译.国外铁道车辆,39(2)：39-45.
Jarske P, Mitra SK, Neuvo Y.1988. Signal processor implementation of variable digital filters[J]. Instrumentation and Measurement, IEEE Transactions on,37(3):363-367.
Johnson D.1979. Variable digital filters having a recursive structure[J]. Acoustics, Speech and Signal Processing, IEEE Transactions on,27(1):98-99.
Johnson M, Freitag L, Stojanovic M.1997. Improved Doppler tracking and correction for underwater acoustic communications[C]//Acoustics, Speech, and Signal Processing, ICASSP-97.,1997 IEEE International Conference on. IEEE,1:575-578.
Karam LJ, McClellan JH.1996. Efficient design of families of FIR filters by transformation[C]//Acoustics, Speech, and Signal Processing,1996. ICASSP-96. Conference Proceedings, IEEE International Conference on. IEEE,3:1359-1362.
King WF, Bechert D.1979. On the sources of wayside noise generated by high-speed trains[J]. Journal of Sound and Vibration,66(3):311-332.
Kitagawa T, Nagakura K.2000. Aerodynamic noise generated by Shinkansen cars[J]. Journal of Sound and vibration,231(3):913-924.
Kitagawa T, Thompson DJ.2010. The horizontal directivity of noise radiated by a rail and implications for the use of microphone arrays[J]. Journal of sound and vibration,329(2): 202-220.
Kwok HK, Jones DL.1995. Instantaneous frequency estimation using an adaptive short-time Fourier transform[C]//Signals, Systems and Computers, Conference Record of the Twenty-Ninth Asilomar Conference on. IEEE,1:543-547.
Kwok HK, Jones DL.2000. Improved instantaneous frequency estimation using an adaptive short-time Fourier transform[J]. Signal Processing, IEEE Transactions on,48(10): 2964-2972.
Kwon HS, Kim YH.1998. Moving frame technique for planar acoustic holography[J]. The Journal of the Acoustical Society of America,103:1734.
Lagneback R.2007. Evaluation of wayside condition monitoring technologies for condition-based maintenance of railway vehiclesfD]:[Licentiate], Sweden:Lulea University of Technology, 5-6.
Lee H, Bien Z.2004. Bandpass variable-bandwidth filter for reconstruction of signals with known boundary in time-frequency domain[J]. Signal Processing Letters, IEEE,11(2):160-163.
Li P, He Q, Kong F.2010. An approach for fault diagnosis of bearings using wavelet-based fractal analysis[C]//Information and Automation (ICIA),2010 IEEE International Conference on. IEEE:2338-2343.
Morse PM, Ingard KU.1986.理论声学(下册)[M].杨训仁,赵慧芝译.北京：科学出版社,842-850.
Nagakura K.2006. Localization of aerodynamic noise sources of Shinkansen trains[J]. Journal of sound and vibration,293(3):547-556.
Oppenheim A, Mecklenbrauker W, Mersereau R.1976. Variable cutoff linear phase digital filters[J]. Circuits and Systems, IEEE Transactions on,23(4):199-203.
Park SH, Kim YH.2001. Visualization of pass-by noise by means of moving frame acoustic holography[J]. The Journal of the Acoustical Society of America,110:2326.
Poisson F, Gautier PE, Letourneaux F.2008. Noise sources for high speed trains:A review of results in the TGV case[M]//Noise and Vibration Mitigation for Rail Transportation Systems. Springer Berlin Heidelberg:71-77.
Ram SS, Li Y, Lin A, et al.2008. Doppler-based detection and tracking of humans in indoor environments[J]. Journal of the Franklin Institute,345(6):679-699.
Roy SD, Ahuja S.1979. Frequency transformations for linear-phase variable-cutoff digital filters[J]. Circuits and Systems, IEEE Transactions on,26(1):73-75.
Scalise L, Paone N.2002. Laser Doppler vibrometry based on self-mixing effect[J]. Optics and lasers in Engineering,38(3):173-184.
SchuBlerHW, Kolb HJ.1982. Variable digital filters[J]. Archiv Elektronik und Uebertragungstechnik,36:229-237.
Schussler HW, Winkelnkemper W.1970. Variable digital filters, Archiv Elektronik und Uebertragungstechnik,24(11):219-220.
Smith RL, Bambara JE, Florom RL.1988. Railcar bearing end-life failure distances and acoustical defect censuring methods[C]. Proceedings of the 1988 Winter Annual Meeting of the ASME, Chicago, IL.
Sneed WH, Smith RL.1998. On-board real-time railroad bearing defect detection and monitoring[C]//Railroad Conference, Proceedings of the 1998 ASME/IEEE Joint. IEEE, Philadelphia, PA:149-153.
Snell OD, Nairne I.2008. Acoustic bearing monitoring-the future RCM 2008[C]//Railway Condition Monitoring,2008 4th IET International Conference on. IET:1-5.
Southern C, Kopke U.2002. Railbam and WCM wayside detection systems[C]//Journal and report of proceedings-Permanent Way Institution. Permanent Way Institution,120:361-368.
Southern C, Rennison D, Kopke U.2004. RailBAM-an Advanced Bearing Acoustic Monitor: Initial Operational Performance Results[J]. CORE:New Horizons for Rail:23.
Stojanovic M, Catipovic JA, Proakis JG.1994. Phase-coherent digital communications for underwater acoustic channels[J]. Oceanic Engineering, IEEE Journal of,19(1):100-111.
Stoyanov G, Kawamata M.1997. Variable digital filters[J]. Journal of Signal Processing,1(4): 275-289.
Streit RL, Barrett RF.1990. Frequency line tracking using hidden Markov models[J]. Acoustics, Speech and Signal Processing, IEEE Transactions on,38(4):586-598.
Talotte C, Gautier PE, Thompson DJ, et al.2003. Identification, modelling and reduction potential of railway noise sources:a critical survey [J]. Journal of Sound and Vibration,267(3): 447-468.
Talotte C.2000. Aerodynamic noise:a critical survey[J]. Journal of sound and vibration,231(3): 549-562.
Tandon N, Choudhury A.1999. A review of vibration and acoustic measurement methods for the detection of defects in rolling element bearings[J]. Tribology International,32(8):469-480.
Thompson D.2008. Railway noise and vibration:mechanisms, modelling and means of control[M]. Amsterdam:Elsevier Science.6-9.
Van der Pol B.1946. The fundamental principles of frequency modulation[J], Proceeding of the IEEE,93:153-158.
Ville J.1948. Theorie et applications de la notion de signal analytique[J]. Cables et transmission, 2(1):61-74.
Wang C, Amin MG.1997. Zero-tracking time-frequency distributions[C]//Acoustics, Speech, and Signal Processing, ICASSP-97, IEEE International Conference on. IEEE,3:2021-2024.
Wang Y, He Z, Zi Y.2001. A comparative study on the local mean decomposition and empirical mode decomposition and their applications to rotating machinery health diagnosis[J]. Journal of vibration and acoustics,132(2).
Working Group Railway Noise of the European Commission.2003. Position Paper on the European strategies and priorities for railway noise abatement[M]. Luxembourg:Office for Official Publications of the European Communities.14-17.
Xie M, Ding K.1996. Correction for the frequency, amplitude and phase in FFT of harmonic signal[J]. Mechanical Systems and Signal Processing.10(2):211-221.
Xu X, Sun L, Cannata JM, et al.2008. High-frequency ultrasound Doppler system for biomedical applications with a 30-MHz linear array[J]. Ultrasound in medicine & biology,2008,34(4): 638-646.
Zarour R, Fahmy MM.1989. A design technique for variable digital filters[J]. Circuits and Systems, IEEE Transactions on,36(11):1473-1478.
Zhang Z, Pouliquen P, Waxman A, et al.2007. Acoustic micro-Doppler gait signatures of humans and animals[C]//Information Sciences and Systems,2007. CISS'07.41st Annual Conference on. IEEE:627-630.