高速铁路弓网动态特性现代谱评估及故障图像智能识别
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摘要
我国铁路事业近年来蓬勃发展,而电气化牵引以其高效、节能、环保的特点获得了越来越多地应用。弓网系统是电气化牵引系统的核心之一,但由于接触网是工作在室外环境中单一无备用系统,弓网之间存在复杂地耦合和电能传输,因此故障率一直相对较高,是电力牵引系统的薄弱环节。随着电气化铁路通车里程不断增加,必须一方面从性能上有效地评估优化弓网动态特性,从基础上提高弓网性能,另一方面加强弓网系统安全检测监控,从而确保铁路高速、安全、可靠的运营。本文将改变目前主要以时域均值、标准差为主的简单统计特征弓网评估方法,将弓网动态特性一维物理信号和二维图像信号作为分析对象,利用现代信号处理手段,在频域/时频域对表征弓网基本动态性能和安全特征的信号展开研究。
本文主要受到铁道部科技开发计划“牵引供电可靠性技术研究-空气动力对高速铁路大张力接触网波动性能影响研究”(2011J016-B),国家自然科学基金“电气化高速铁路接触网线谱研究”(No.51007074),教育部新世纪优秀人才支持计划(No. NECT-08-0825)及西南交通大学博士创新基金项目支持。
为实现对表征弓网系统特性的信号进行更加准确的分析评估,论文将从弓网动态数据获取->弓网动态数据预处理方法->弓网动态数据统计特性评估->弓网时域评价指标改进->弓网频域评价指标改进->弓网故障图像信号识别方法研究几个方面出发,较为全面的研究了利用现代信号处理技术分析弓网系统特性的体系。主要研究工作如下：
(1)在弓网动态数据获取方面,利用二次开发方法进行弓网自动化建模可有效提高建模效率、增强模型重复利用率、减少模型出错概率,对不同参数模型进行对比研究时更加便利。通过降温法和非线性材料特性对弓网模型进行优化可以获得更佳精确合理的弓网仿真模型并给出了接触线有限单元长度建议选择范围。利用EN50318标准进行建模分析并与西门子仿真结果比较分析,模型具有较高可信度。
(2)为研究环境随机风对接触网波动特性的影响,在考虑大张力、接触线刚度、随机风条件下,提出了接触网波动传播速度修正计算公式。通过接触线截断风洞实验测定了两种高铁常用接触线的阻力系数和升力系数。构建了考虑风阻尼条件下弓网动力学方程。
(3)为准确评估弓网动态特性,利用EEMD分解研究了不同检测信号相关性问题,与传统的3σ预处理相比,通过相关系数对接触压力数据预处理更加有效。对弓网接触压力数据进行了平稳性、周期性等基本统计特性分析。针对弓网接触压力周期性特点,提出一种利用改进的二阶差分标准差更加准确地评估弓网动态特性的方法,并从受电弓对接触线疲劳寿命影响角度证明了方法合理性。
(4)利用现代信号谱分析方法,分析了不同参数下弓网动态特性谱特征。分析了利用ARMA模型进行弓网固有频率测试的可行性。利用弓网动态抬升谱分析了利用谱方法评估弓网耦合性能的优势,不但可识别弓网耦合优劣还可看到不良耦合出现的频率区间,为优化弓网关系提供参考。对弓网谱进行了量化表达方法的研究,为弓网动态特性分级评估提供了参考。
(5)利用现代信号稀疏表示方法,研究了弓网检测二维图像信号的故障特征提取问题。证明了利用超完备曲波变换,可以很好的处理图像信号预处理、受电弓故障检测、接触网绝缘子故障识别等一系列问题,算法对二维故障信息识别的准确率较高,算法实现时间较短,可在可接受的时间范围内实现可靠的故障信息自动分析识别任务,为实现故障信息自动化识别提供了可行的方案。
The railway industry in our country develops fast in the recent years. The electric railway is the most efficient, energy-saving and environment-friendly railway system, so it has been used widely. The pantograph-catenary system is one of the key technologies in the electric railway. But its fault rates are very high because this system is a solo system without any redundancy, the force and power transmission mechanism are complex. It's a weakness in the electric railway. In order to keep the electric railway operation trustworthy and safe, the pantograph-catenary system's dynamic characteristics must be assessed effectively to promote its personal performance, and in the other hand, the system must be monitored efficiently to keep the safety. This paper do not use the traditional methods like mean and standard deviation in the time domain. The one dimension physical signals and two dimension image signals of the pantograph-catenary system are analyzed using the modern signal processing technologies in frequency domain or time-frequency domain.
This paper is supported by the Scientific Project of Railway Ministry of China (2011J016-B); the National Natural Science Foundation of China(No.51007074); the New Century Excellent Talents in University of Education Ministry of China(No. NECT-08-0825); the PhD Innovation Fund of Southwest Jiaotong University.
The main purpose of this research is to assess pantograph-catenary system characteristic signal accurately. Based on the modern signal processing technologies, the main work in the paper includes:the obtain of pantograph-catenary dynamic data-> the pre-process of the data-> the analysis of basic statistic characteristic-> the new assessment method in time domain-> the new assessment method in frequency domain-> the fault image intelligent identification.
(1) The pantograph-catenary model automatic creation method using the secondary development technology is proposed to obtain the necessary data for analyzing the characteristic, and this method can promote the efficiency of model creation, improve the reuse rate, reduce the fault rate of creating the model and simplify the comparison between the different models. The model is modified using the falling temperature method and the nonlinear characteristics of material. The suggested choice of finite element length in the model is given. The model is proved reliable via the compare with EN50318and simulation of Siemens.
(2) In order to research the influence of the wind to the catenary, the formula of catenary wave speed is modified considering the high tension, catenary stiffness and random wind. The wind tunnel test is performed to measure the lift coefficient and damp coefficient of catenary. The pantograph-catenary dynamic formula is constructed considering the extra wind damp.
(3) In order to assess the pantograph-catenary characteristics, the correlation between different signals of system are analyzed using EEMD. The contact force data are pre-processed more accurately according to the correlation. The stationarity and periodicity of contact force data are assessed. A new second order difference standard deviation assessment method is proposed to assess the system characteristics. The rationality of this method is analyzed from the lifetime's point of view.
(4) The pantograph-catenary characteristics showed by spectrum are analyzed by the modern signal spectrum technology. The catenary inherent frequencies are obtained from ARMA model. The advantage of spectrum analysis is showed by analyzing the pantograph-catenary coupling performance using the uplift spectrum, and the bad coupling frequency range can be found besides the basic result. Finally, the quantitative representation of spectrum is researched, and this can provide the reference of grading the pantograph-catenary characteristics.
(5) The pantograph-catenary detection image signals are researched by using the modern signal sparse representation technology. The image pre-process, the pantograph crack fault, the insulator damage fault can be identified intelligently using curvelet transform. These algorithms are accurate and fast. Its time cost can be accepted. These algorithms provide the feasible scheme to monitor the pantograph-catenary system.
本文主要受到铁道部科技开发计划“牵引供电可靠性技术研究-空气动力对高速铁路大张力接触网波动性能影响研究”(2011J016-B),国家自然科学基金“电气化高速铁路接触网线谱研究”(No.51007074),教育部新世纪优秀人才支持计划(No. NECT-08-0825)及西南交通大学博士创新基金项目支持。
为实现对表征弓网系统特性的信号进行更加准确的分析评估,论文将从弓网动态数据获取->弓网动态数据预处理方法->弓网动态数据统计特性评估->弓网时域评价指标改进->弓网频域评价指标改进->弓网故障图像信号识别方法研究几个方面出发,较为全面的研究了利用现代信号处理技术分析弓网系统特性的体系。主要研究工作如下：
(1)在弓网动态数据获取方面,利用二次开发方法进行弓网自动化建模可有效提高建模效率、增强模型重复利用率、减少模型出错概率,对不同参数模型进行对比研究时更加便利。通过降温法和非线性材料特性对弓网模型进行优化可以获得更佳精确合理的弓网仿真模型并给出了接触线有限单元长度建议选择范围。利用EN50318标准进行建模分析并与西门子仿真结果比较分析,模型具有较高可信度。
(2)为研究环境随机风对接触网波动特性的影响,在考虑大张力、接触线刚度、随机风条件下,提出了接触网波动传播速度修正计算公式。通过接触线截断风洞实验测定了两种高铁常用接触线的阻力系数和升力系数。构建了考虑风阻尼条件下弓网动力学方程。
(3)为准确评估弓网动态特性,利用EEMD分解研究了不同检测信号相关性问题,与传统的3σ预处理相比,通过相关系数对接触压力数据预处理更加有效。对弓网接触压力数据进行了平稳性、周期性等基本统计特性分析。针对弓网接触压力周期性特点,提出一种利用改进的二阶差分标准差更加准确地评估弓网动态特性的方法,并从受电弓对接触线疲劳寿命影响角度证明了方法合理性。
(4)利用现代信号谱分析方法,分析了不同参数下弓网动态特性谱特征。分析了利用ARMA模型进行弓网固有频率测试的可行性。利用弓网动态抬升谱分析了利用谱方法评估弓网耦合性能的优势,不但可识别弓网耦合优劣还可看到不良耦合出现的频率区间,为优化弓网关系提供参考。对弓网谱进行了量化表达方法的研究,为弓网动态特性分级评估提供了参考。
(5)利用现代信号稀疏表示方法,研究了弓网检测二维图像信号的故障特征提取问题。证明了利用超完备曲波变换,可以很好的处理图像信号预处理、受电弓故障检测、接触网绝缘子故障识别等一系列问题,算法对二维故障信息识别的准确率较高,算法实现时间较短,可在可接受的时间范围内实现可靠的故障信息自动分析识别任务,为实现故障信息自动化识别提供了可行的方案。
The railway industry in our country develops fast in the recent years. The electric railway is the most efficient, energy-saving and environment-friendly railway system, so it has been used widely. The pantograph-catenary system is one of the key technologies in the electric railway. But its fault rates are very high because this system is a solo system without any redundancy, the force and power transmission mechanism are complex. It's a weakness in the electric railway. In order to keep the electric railway operation trustworthy and safe, the pantograph-catenary system's dynamic characteristics must be assessed effectively to promote its personal performance, and in the other hand, the system must be monitored efficiently to keep the safety. This paper do not use the traditional methods like mean and standard deviation in the time domain. The one dimension physical signals and two dimension image signals of the pantograph-catenary system are analyzed using the modern signal processing technologies in frequency domain or time-frequency domain.
This paper is supported by the Scientific Project of Railway Ministry of China (2011J016-B); the National Natural Science Foundation of China(No.51007074); the New Century Excellent Talents in University of Education Ministry of China(No. NECT-08-0825); the PhD Innovation Fund of Southwest Jiaotong University.
The main purpose of this research is to assess pantograph-catenary system characteristic signal accurately. Based on the modern signal processing technologies, the main work in the paper includes:the obtain of pantograph-catenary dynamic data-> the pre-process of the data-> the analysis of basic statistic characteristic-> the new assessment method in time domain-> the new assessment method in frequency domain-> the fault image intelligent identification.
(1) The pantograph-catenary model automatic creation method using the secondary development technology is proposed to obtain the necessary data for analyzing the characteristic, and this method can promote the efficiency of model creation, improve the reuse rate, reduce the fault rate of creating the model and simplify the comparison between the different models. The model is modified using the falling temperature method and the nonlinear characteristics of material. The suggested choice of finite element length in the model is given. The model is proved reliable via the compare with EN50318and simulation of Siemens.
(2) In order to research the influence of the wind to the catenary, the formula of catenary wave speed is modified considering the high tension, catenary stiffness and random wind. The wind tunnel test is performed to measure the lift coefficient and damp coefficient of catenary. The pantograph-catenary dynamic formula is constructed considering the extra wind damp.
(3) In order to assess the pantograph-catenary characteristics, the correlation between different signals of system are analyzed using EEMD. The contact force data are pre-processed more accurately according to the correlation. The stationarity and periodicity of contact force data are assessed. A new second order difference standard deviation assessment method is proposed to assess the system characteristics. The rationality of this method is analyzed from the lifetime's point of view.
(4) The pantograph-catenary characteristics showed by spectrum are analyzed by the modern signal spectrum technology. The catenary inherent frequencies are obtained from ARMA model. The advantage of spectrum analysis is showed by analyzing the pantograph-catenary coupling performance using the uplift spectrum, and the bad coupling frequency range can be found besides the basic result. Finally, the quantitative representation of spectrum is researched, and this can provide the reference of grading the pantograph-catenary characteristics.
(5) The pantograph-catenary detection image signals are researched by using the modern signal sparse representation technology. The image pre-process, the pantograph crack fault, the insulator damage fault can be identified intelligently using curvelet transform. These algorithms are accurate and fast. Its time cost can be accepted. These algorithms provide the feasible scheme to monitor the pantograph-catenary system.
引文
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