轨道车辆平轮实时检测技术研究
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摘要
本课题来源于黑龙江省科技计划项目“平轮检测平台研究与开发”,作为项目的重要组成部分,论文对基于DSP的平轮检测系统的总体方案进行了论证,并研究开发了相应的基于DSP的平轮检测算法。
车轮扁疤是列车重大行车事故的隐患之一,对它的准确、快速检测在保障列车行车安全方面起着至关重大的作用,因此研制一种在线实时平轮检测系统具有重大的现实意义。
论文首先通过分析比较目前国内外采用的各种动态检测方法,选择振动加速度检测法对平轮信号进行检测。然后根据振动加速度检测法的原理和系统设计指标的要求,对设计的基于DSP的平轮检测系统的具体方案作了详细论证。根据DSP平轮检测系统的工作流程,论文提出了基于DSP的平轮检测算法并进行了详细的阐述。在算法开发部分,首先依据由振动加速度传感器采集到的平轮信号具有持续时间短、突变快等非平稳特征,对现有的适用于平轮信号检测的非平稳时频分析方法进行了分析,通过分析对比首次提出采用S变换的时频分析方法对平轮信号进行检测和定位,并通过仿真验证了S变换的方法相对于现有方法的优越性；然后系统地阐述了平轮检测的整体算法,包括信号的预处理、信号特征提取、位置判别三部分算法,其中信号特征提取部分主要采用多种阈值判别方法和S变换检测定位方法,并提出采用短时能量判决的方法对信号进行阈值判别,仿真证明该方法能够较好地排除漏检、误检现象的发生；最后给出了检测算法在DSP上实现的具体方法,其中主要分析了AD采集算法和DSP与ARM通信算法的实现。论文最后完成了基于CCS硬仿真的DSP单板调试和整个检测平台的联调,调试结果表明系统各方面性能指标均达到系统设计指标,同时通过长期大量数据实验验证了平轮检测算法的正确性和系统设计的可靠性与稳定性。
As the important part of the project "The Research and Development of Wheel-flat Detection Platform" which comes from Heilongjiang Province Science and Technology Department, this dissertation demonstrated the overall scheme of wheel-flat detection system based on DSP and developed the corresponding algorithm of wheel-flat detection based on DSP.
The wheel-flat is one of the hidden dangers of major train operation accidents, it has a great significance to detect the wheel-flat accurately and rapidly for guaranteeing the train's traffic safety. Thus there is a great practical significance to develop an on-line and real time wheel-flat detection system.
Firstly the thesis choosed the vibrational acceleration detection method to detect wheel-flat through analyzing and comparing various existing dynamic detection methods at home and abroad. According to the principle of vibrational acceleration detection method and the requirements of the system design specifications, the thesis demonstrated the scheme of wheel-flat detection system based on DSP in detail. In accordance with the working flow of wheel-flat detection system based on DSP, the algorithm of wheel-flat detection based on DSP was given and expounded detailedly. In the part of algorithm development, the thesis firstly analysed the existing nonstationary time-frequency analysis methods which were applicable to wheel-flat detection, based on the nonstationary characteristics of short lasting time and fast mutation for wheel-flat signal collected by vibration accelerometer. Through analysis and comparation time-frequency analysis method based on S-transform was proposed for the first time to detect and locate vibration signal with wheel-flat, and the superiority of S-transform compared with the presented methods was verified by simulation. Afterward, the thesis systematically expounded the whole algorithm of wheel-flat detection including signal pretreatment, characteristics extraction and location detection. In the part of characteristics extraction algorithm, the thesis mainly used threshold judgement methods and S-transform detection algorithm, and the method of short-time energy estimation was proposed in the threshold judgement. Simulation results showed that by short-time energy estimation the algorithm could prevent undetection and misjudgment efficiently. Finally, the detection algorithm's realizations on DSP were also provided, mainly including algorithm for AD acquisition and communication between DSP and ARM. In the end, the thesis accomplished the debugging on the board of DSP in the CCS emulator environment and the whole detection platform's united debugging. The debugging results have manifested that the performance indexes in every respect of the system are all achieved the system design specifications, and the validity of the algorithm and the reliability and stability of the system are all verified through a great deal data experiments for a long time.
车轮扁疤是列车重大行车事故的隐患之一,对它的准确、快速检测在保障列车行车安全方面起着至关重大的作用,因此研制一种在线实时平轮检测系统具有重大的现实意义。
论文首先通过分析比较目前国内外采用的各种动态检测方法,选择振动加速度检测法对平轮信号进行检测。然后根据振动加速度检测法的原理和系统设计指标的要求,对设计的基于DSP的平轮检测系统的具体方案作了详细论证。根据DSP平轮检测系统的工作流程,论文提出了基于DSP的平轮检测算法并进行了详细的阐述。在算法开发部分,首先依据由振动加速度传感器采集到的平轮信号具有持续时间短、突变快等非平稳特征,对现有的适用于平轮信号检测的非平稳时频分析方法进行了分析,通过分析对比首次提出采用S变换的时频分析方法对平轮信号进行检测和定位,并通过仿真验证了S变换的方法相对于现有方法的优越性；然后系统地阐述了平轮检测的整体算法,包括信号的预处理、信号特征提取、位置判别三部分算法,其中信号特征提取部分主要采用多种阈值判别方法和S变换检测定位方法,并提出采用短时能量判决的方法对信号进行阈值判别,仿真证明该方法能够较好地排除漏检、误检现象的发生；最后给出了检测算法在DSP上实现的具体方法,其中主要分析了AD采集算法和DSP与ARM通信算法的实现。论文最后完成了基于CCS硬仿真的DSP单板调试和整个检测平台的联调,调试结果表明系统各方面性能指标均达到系统设计指标,同时通过长期大量数据实验验证了平轮检测算法的正确性和系统设计的可靠性与稳定性。
As the important part of the project "The Research and Development of Wheel-flat Detection Platform" which comes from Heilongjiang Province Science and Technology Department, this dissertation demonstrated the overall scheme of wheel-flat detection system based on DSP and developed the corresponding algorithm of wheel-flat detection based on DSP.
The wheel-flat is one of the hidden dangers of major train operation accidents, it has a great significance to detect the wheel-flat accurately and rapidly for guaranteeing the train's traffic safety. Thus there is a great practical significance to develop an on-line and real time wheel-flat detection system.
Firstly the thesis choosed the vibrational acceleration detection method to detect wheel-flat through analyzing and comparing various existing dynamic detection methods at home and abroad. According to the principle of vibrational acceleration detection method and the requirements of the system design specifications, the thesis demonstrated the scheme of wheel-flat detection system based on DSP in detail. In accordance with the working flow of wheel-flat detection system based on DSP, the algorithm of wheel-flat detection based on DSP was given and expounded detailedly. In the part of algorithm development, the thesis firstly analysed the existing nonstationary time-frequency analysis methods which were applicable to wheel-flat detection, based on the nonstationary characteristics of short lasting time and fast mutation for wheel-flat signal collected by vibration accelerometer. Through analysis and comparation time-frequency analysis method based on S-transform was proposed for the first time to detect and locate vibration signal with wheel-flat, and the superiority of S-transform compared with the presented methods was verified by simulation. Afterward, the thesis systematically expounded the whole algorithm of wheel-flat detection including signal pretreatment, characteristics extraction and location detection. In the part of characteristics extraction algorithm, the thesis mainly used threshold judgement methods and S-transform detection algorithm, and the method of short-time energy estimation was proposed in the threshold judgement. Simulation results showed that by short-time energy estimation the algorithm could prevent undetection and misjudgment efficiently. Finally, the detection algorithm's realizations on DSP were also provided, mainly including algorithm for AD acquisition and communication between DSP and ARM. In the end, the thesis accomplished the debugging on the board of DSP in the CCS emulator environment and the whole detection platform's united debugging. The debugging results have manifested that the performance indexes in every respect of the system are all achieved the system design specifications, and the validity of the algorithm and the reliability and stability of the system are all verified through a great deal data experiments for a long time.
引文
[1]马钧培.中国铁路信息化建设与展望[J].交通运输系统工程与信息,2005,5(5)：1-5.
[2]王炎孝,杨占平.车轮扁疤动态检测方法综述[J].铁道车辆,2002,40(6)：6-12.
[3]史鸿样.客车车轮踏面擦伤及其危害[J].铁道车辆,1994(11)：56-57.
[4]张开俊.车轮扁疤动态检测技术[J].郑铁科技通讯,1998(1)：1-3.
[5]杨良澎.车轮踏面擦伤深度对轴承影响的探讨[J].上海铁道科技,1995(1)：21-23.
[6]王方程,迟宝全.平轮在线自动检测方法综述[J].城市轨道交通研究,2006(1)：31-33.
[7]张渝,王黎,高晓蓉等.国内外车轮踏面损伤检测技术综述[J].机车车辆工艺,2002,2(1)：1-4.
[8]杨凯.车轮踏面擦伤检测系统研究[D].成都：西南交通大学,2005.
[9]李景泉,刘继.车轮踏面擦伤自动检测方法的研究和试验[J].同济大学,2003,31(4)：473-476.
[10]王亦军.WTFDS-Ⅰ型车辆轮对踏面故障检测系统的研究[D].成都：西南交通大学,2007.
[11]杨志刚.轮疤检测数据采集和处理系统的研究与开发[D].哈尔滨：哈尔滨工程大学,2008.
[12]江思敏,刘畅.TMS320C6000DSP应用开发教程[M].北京：机械工业出版社,2005：6-9.
[13]徐志军,徐光辉.CPLD/FPGA的开发与应用[M].北京：电子工业出版社,2002：127-159.
[14]Texas Instruments.500kHz,12-Bit,6-Channel Simultaneous Sampling Analog-to-Digital Converter[EB/OL]. http://www.ti.com/lit/gpn/ADSxxx, 2003.
[15]靳庆贵.基于小波变换的实时平轮检测系统[D].哈尔滨：哈尔滨工程大学,2005.
[16]翟婉明.铁路车轮扁疤的动力学效应[J].铁道车辆,1994(7)：1-5.
[17]王雪,谢歆,赵国华.基于小波反弹神经网络的车轮擦伤检测方法[J].中国机械工程,2003,14(20)：1783-1785.
[18]Vittorio Belotti, Francesco Crenna. Wheel-flat diagnostic tool via wavelet transform[J]. Mechanical System and Signal Processing,2006 (20): 1953-1966.
[19]程军圣,于德介.离散余弦变换在滚动轴承故障诊断中的应用[J].振动与冲击,2000,19(3)：20-22.
[20]陈安华,余小华,黄采伦.Hilbert-Huang变换在列车踏面故障识别中的应用木[J].电子测量与仪器学报,2009,23(8)：90-94.
[21]胡昌华,张军波,夏军等.基于MATLAB的系统分析与设计——小波分析[M].西安：西安电子科技大学出版社,1999：4-6.
[22]赵淑红.时频分析方法及其在地震数据处理中的应用[D].西安：长安大学,2006.
[23]R.G.Stockwell, L.Mansinha, R.P.Lowe. Localization of the complex spectrum:the S transform [J]. IEEE Transactions on Signal Processing, 1996,44 (4):998-1001.
[24]邹文.S变换时频分析技术及其在地震勘探中的应用研究[D].北京：中国地质大学,2005.
[25]陈学华,贺振华.改进的S变换及在地震信号处理中的应用[J].数据采集与处理,2005,20(4)：449-453.
[26]刘守亮,肖先勇.基于S变换的短时电能质量扰动检测与分类[J].四川电力技术,2005(z1)：40-47.
[27]徐红梅,郝志勇,贾维新等.基于S变换的内燃机噪声信号时频特性[J]. 江苏大学学报,2008,29(2)：115-118.
[28]全惠敏,戴瑜兴.基于S变换模矩阵的电能质量扰动信号检测与定位[J].电工技术学报,2007,22(8)：119-125.
[29]王鹏飞,张兴周,胡文飞.基于小波变换的火车车轮扁疤信号能量分析[J].应用科技,2000,36(6)：25-28.
[30]楼顺天,李博菡.基于MATLAB的系统分析与设计——信号处理[M].西安：西安电子科技大学出版社,1998：25-29.
[31]彭中心.消除工频干扰的自适应滤波器[J].黄石理工学院学报,2006,22(1)：30-32.
[32]阳雄,程玉胜.短时能量分析及人耳的主观听觉在船舶辐射噪声特征提取中的研究[J].声学技术,2004,23(1)：11-13.
[33]孟永鹏,贾申利,荣命哲.短时能量分析法在断路器机械状态监测中的应用[J].西安交通大学学报,2004,38(12)：1301-1305.
[34]王鹏飞.车轮扁疤检测系统开发与算法研究[D].哈尔滨：哈尔滨工程大学,2009.
[35]徐士良.C语言常用算法程序集[M].北京：清华大学出版社.1996,115-118.
[36]李方慧,王飞,何佩琨.TMS320C6000系列DSPs原理与应用[M].北京：电子工业出版社.2003,110-134.
[37]尹勇,欧光军,关荣峰.DSP集成开发环境CCS使用指南[M].北京：北京航空航天大学出版社.2003,1-279.
[38]韩钧,康怡.双口RAM在DSP与单片机数据通信中的应用[J].电力系统通信,2006,27(166)：56-58.
[39]殷福亮,宋爱军.数字信号处理C语言程序集[M].沈阳：辽宁科学技术出版社,1997：57-61.
[40]美国德州仪器公司.TMS320C6000系列DSP编程工具与指南[M].北京：清华大学出版社,2006：301-326.
[2]王炎孝,杨占平.车轮扁疤动态检测方法综述[J].铁道车辆,2002,40(6)：6-12.
[3]史鸿样.客车车轮踏面擦伤及其危害[J].铁道车辆,1994(11)：56-57.
[4]张开俊.车轮扁疤动态检测技术[J].郑铁科技通讯,1998(1)：1-3.
[5]杨良澎.车轮踏面擦伤深度对轴承影响的探讨[J].上海铁道科技,1995(1)：21-23.
[6]王方程,迟宝全.平轮在线自动检测方法综述[J].城市轨道交通研究,2006(1)：31-33.
[7]张渝,王黎,高晓蓉等.国内外车轮踏面损伤检测技术综述[J].机车车辆工艺,2002,2(1)：1-4.
[8]杨凯.车轮踏面擦伤检测系统研究[D].成都：西南交通大学,2005.
[9]李景泉,刘继.车轮踏面擦伤自动检测方法的研究和试验[J].同济大学,2003,31(4)：473-476.
[10]王亦军.WTFDS-Ⅰ型车辆轮对踏面故障检测系统的研究[D].成都：西南交通大学,2007.
[11]杨志刚.轮疤检测数据采集和处理系统的研究与开发[D].哈尔滨：哈尔滨工程大学,2008.
[12]江思敏,刘畅.TMS320C6000DSP应用开发教程[M].北京：机械工业出版社,2005：6-9.
[13]徐志军,徐光辉.CPLD/FPGA的开发与应用[M].北京：电子工业出版社,2002：127-159.
[14]Texas Instruments.500kHz,12-Bit,6-Channel Simultaneous Sampling Analog-to-Digital Converter[EB/OL]. http://www.ti.com/lit/gpn/ADSxxx, 2003.
[15]靳庆贵.基于小波变换的实时平轮检测系统[D].哈尔滨：哈尔滨工程大学,2005.
[16]翟婉明.铁路车轮扁疤的动力学效应[J].铁道车辆,1994(7)：1-5.
[17]王雪,谢歆,赵国华.基于小波反弹神经网络的车轮擦伤检测方法[J].中国机械工程,2003,14(20)：1783-1785.
[18]Vittorio Belotti, Francesco Crenna. Wheel-flat diagnostic tool via wavelet transform[J]. Mechanical System and Signal Processing,2006 (20): 1953-1966.
[19]程军圣,于德介.离散余弦变换在滚动轴承故障诊断中的应用[J].振动与冲击,2000,19(3)：20-22.
[20]陈安华,余小华,黄采伦.Hilbert-Huang变换在列车踏面故障识别中的应用木[J].电子测量与仪器学报,2009,23(8)：90-94.
[21]胡昌华,张军波,夏军等.基于MATLAB的系统分析与设计——小波分析[M].西安：西安电子科技大学出版社,1999：4-6.
[22]赵淑红.时频分析方法及其在地震数据处理中的应用[D].西安：长安大学,2006.
[23]R.G.Stockwell, L.Mansinha, R.P.Lowe. Localization of the complex spectrum:the S transform [J]. IEEE Transactions on Signal Processing, 1996,44 (4):998-1001.
[24]邹文.S变换时频分析技术及其在地震勘探中的应用研究[D].北京：中国地质大学,2005.
[25]陈学华,贺振华.改进的S变换及在地震信号处理中的应用[J].数据采集与处理,2005,20(4)：449-453.
[26]刘守亮,肖先勇.基于S变换的短时电能质量扰动检测与分类[J].四川电力技术,2005(z1)：40-47.
[27]徐红梅,郝志勇,贾维新等.基于S变换的内燃机噪声信号时频特性[J]. 江苏大学学报,2008,29(2)：115-118.
[28]全惠敏,戴瑜兴.基于S变换模矩阵的电能质量扰动信号检测与定位[J].电工技术学报,2007,22(8)：119-125.
[29]王鹏飞,张兴周,胡文飞.基于小波变换的火车车轮扁疤信号能量分析[J].应用科技,2000,36(6)：25-28.
[30]楼顺天,李博菡.基于MATLAB的系统分析与设计——信号处理[M].西安：西安电子科技大学出版社,1998：25-29.
[31]彭中心.消除工频干扰的自适应滤波器[J].黄石理工学院学报,2006,22(1)：30-32.
[32]阳雄,程玉胜.短时能量分析及人耳的主观听觉在船舶辐射噪声特征提取中的研究[J].声学技术,2004,23(1)：11-13.
[33]孟永鹏,贾申利,荣命哲.短时能量分析法在断路器机械状态监测中的应用[J].西安交通大学学报,2004,38(12)：1301-1305.
[34]王鹏飞.车轮扁疤检测系统开发与算法研究[D].哈尔滨：哈尔滨工程大学,2009.
[35]徐士良.C语言常用算法程序集[M].北京：清华大学出版社.1996,115-118.
[36]李方慧,王飞,何佩琨.TMS320C6000系列DSPs原理与应用[M].北京：电子工业出版社.2003,110-134.
[37]尹勇,欧光军,关荣峰.DSP集成开发环境CCS使用指南[M].北京：北京航空航天大学出版社.2003,1-279.
[38]韩钧,康怡.双口RAM在DSP与单片机数据通信中的应用[J].电力系统通信,2006,27(166)：56-58.
[39]殷福亮,宋爱军.数字信号处理C语言程序集[M].沈阳：辽宁科学技术出版社,1997：57-61.
[40]美国德州仪器公司.TMS320C6000系列DSP编程工具与指南[M].北京：清华大学出版社,2006：301-326.