轮轨垂向载荷连续测量与识别方法研究
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摘要
对铁道车辆的运行状态监测、诊断和预警是保障车辆行车安全的重要手段。通过轮轨力的监测可以及时发现列车设备的各种异常并做出诊断和预测,提出必要的整改措施,从而实现车辆的“状态修”,提高车辆及其设备的运用质量和使用效率。目前已经有很多不同的监测轮轨力的商业系统,但多数都只是峰值载荷的测试工具,或是需要对现有的轨道结构进行很大的改变才能实现连续轮轨力的测量与识别。基于这种状况,本文主要研究在不改变轨道结构的情况下连续测量与识别轮轨垂向载荷的方法。
本文从轨道分析模型入手,介绍了轨道分析模型在列车轮载作用下的响应,分析和研究钢轨在垂直载荷作用下的应力与变形,为有效测量轮轨垂直力提供理论依据。随之介绍了基于地面测量轮轨垂直力各种方法的力学原理和实现方法。分析不同方法对于轨道支撑状态的依赖性或敏感性,指出了它们存在的缺点和适用性。利用有限元分析软件建立起了钢轨有限元模型。通过对模型的加载与解算得到钢轨模型上节点对于移动的垂直荷载作用时的响应变化规律,具体分析了钢轨中性轴上的节点在载荷点移动变化时的剪应力的变化情况。通过对仿真结果数据的分析,找出了布置剪力传感器的最优的节点位置,并仿真计算了布点之后输出的灵敏性和线性度。仿真计算了同一钢轨截面上不同横向位置荷载时对测试系统响应输出的影响以及横向力对垂直力测试系统输出的影响。计算结果表明同一截面上荷载点位置的变化不影响测试系统的输出,当钢轨两侧的布点完全对称时,横向力对垂向力测试电桥输出的影响为零。为了验证有限元仿真分析的结果,实施了室内加载实验。试验的结果分析出,仿真分析与试验的结果得到了相识的波形,但在幅值上存在一定的差异。分析了出现幅值差异的原因。
针对轮轨垂直力测量数据中可能存在的基线漂移的干扰,本文详细研究比对了曲线拟合方法,移动中值滤波,数学形态滤波器和小波阈值去噪方法在去除基线漂移的效果,分析不同方法存在的缺点并提出了改进的意见与方案。结合轮轨垂直力信号的特点,提出针对平衡往复型的信号去除基线漂移的经验性的新方法,通过对分段数据的平稳性检验和对中值及方差的最近距离聚类,筛选出能够体现基线漂移走势的分段数据中值作为基线漂移基点,再基点进行曲线拟合得到基线。与简单的曲线拟合方法相比,本文通过数据分段的办法,尽可能多地增加了基点的数量,从而能够更细致地表达真实的基线。相比于移动中值滤波和数学形态学滤波,虽然这几种方法的本质都基于顺序滤波器,但由于本文的方法对于其他非基线的噪声对提取的基线的干扰有筛选的过程,使得其相对于另外两者有更好的表现。由于经过数据分段处理,使得整个过程的计算量大大地缩小,最后介绍了通过与小波滤波组合的方案来抑制提取的基线中含有其他干扰成分,从而获得了更好的消除效果。
本文最后部分提出一种连续测量和识别轮轨垂直力的方法。本方法基于梁格原理,将测试期间内的钢轨分成数量有限的梁单元,同时在钢轨上布置多组观测点。假设载荷点位于梁元内的任何位置时,所布置的所有观测点的观测值不变,而在不同的梁元上施加载荷时,所有观测值组成的响应向量肯定不同,由此可通过理论计算或现场测试的方法得到单位荷载下或固定荷载下所有观测点对于载荷位置在所有划分的梁单元上移动时得到标准的响应向量库。通过将单点载荷位置对应多观测点响应向单测点响应对应一群组载荷位置点的响应转换分析和验证了响应向量的适定性要求。在己获得标准响应向量库的情况下,利用相似性测度研究了实测任意时刻下的观测点的响应与响应向量库的每个向量的关系。比较研究了欧氏距离,夹角余弦和皮尔森相关系数三种多维空间向量相似性测度对于噪声的敏感性,以便于从中选取适当测度作为隶属函数。最后使用最大隶属度识别法认定当前响应向量最相似的标准向量,从而认为两个向量的载荷点在相同的梁单元上。得到荷载点位置信息后,利用两个向量的模的比例关系来确定荷载的大小。文中通过仿真数据检验了方法的有效性。并将其用于线路试验实测的数据中,取得了较好的识别效果。最后具体分析了引起该识别方法误差的可能因素。
Railway vehicle running status monitoring, diagnosis, and early warning is important means to ensure vehicle safety. Monitoring wheel-rail forces can find out various abnormalities of the train and its devices timely, then diagnose and predict, propose the necessary corrective measures. So as to realize the locomotive vehicle "condition base maintenance" which improve the using quality and efficiency of vehicles and their equipment. At present there are a lot of different business system of monitoring wheel/rail force, but majority just test tools for peak load, or needed great changes to existing rail structure so can be realized measurement and identify the wheel/rail force. Based on this situation, this paper mainly research and development a method of continuous measurement and recognition of the wheel rail vertical load without altering the track structure.
This thesis starting from the railway analysis model, introduced railway analysis model response under train wheel load, detailed analysis and study rail stresses and deformations under vertical loading, which providing theoretical basis for effectively measuring wheel/rail vertical force. Subsequently introduce mechanics principle and implementation of various methods for measuring wheel-rail vertical force. The dependence and sensitivity of different methods for rail support status were analyzed, and disadvantages of and applicability of various methods were pointed out. By using finite element analysis software the finite element model of rail was established. Through loading and solving the model we got the responses of rail model nodes when subjected to a moving vertical load. Through analyzing the simulation results, we found the optimal node for arrangement of shear force sensors, and got the sensitivity and linearity of sensors'output. In order to verify the results of the finite element simulation analysis, an indoor laboratory loading experiment was implemented. Indoor test decorate three different schemes in the same rail span. From compare of the results, simulation and laboratory experiment show similar waveforms, but there are differences in amplitude. Then, the possible factors for these differences are analyzed.
Wheel-rail vertical force measurement data may be interfered by baseline drift, and the baseline drift should be eliminated before amplitude analysis. this thesis studied the effects of curve fitting, mobile median filtering, mathematical morphology filter and wavelet threshold denoising method in removing the baseline drift, analyzed the disadvantages of different methods and put forward the improvement Suggestions and solutions. According to the characteristics of the wheel/rail vertical force signal, a new empirical method was proposed to remove baseline drift, which through clustering median values and variance of median values in data segments, and picking up the median values reflected baseline drift trends, then curve fitting the Selected points as the baseline. Compared to the simple curve fitting method, the number of basis points increase as much as possible, more detailed of the true baseline is expression. Compared to moving median filtering and morphological filtering, although the nature of these methods are based on order filter, but the proposed method Inhibit non-baseline noise interference to the extracted baseline with a sifting process, making it relative better performance to the others. Moreover, segmenting the data, making the calculation of whole process is greatly reduced. Then, a scheme through combining with wavelet filtering to suppress other interfering component contains in the extracted baseline was introduced, which obtained better eliminate effect.
In last part of this thesis, a continuous measurement and identification method for wheel-rail vertical force was proposed. The method is based on the principle beam frame. The test period is divided into a limited number of rail beam element. Then we arrange multiple sets of observation point on the rail. Assuming that when the loading point locate anywhere in the beam position, the observation values of all observations points unchanged. While the load is applied on a different beam element, all observation values response vector must be different. So, by theoretical calculation method or field testing, standard response vector library of all observation points'response for constant loads moving along all of beam element can be obtained. The request of well-posedness of response vector library was validated by convert multiple observation points for single load location point to single observation point for multiple load location points. After obtained the standard response vector library, similarity measure was employed to observer the relationship between any observation vector and each vector in response vector library. In this thesis, a comparative study of three kind of multidimensional vector space similarity measure Euclidean distance, Angle cosine and Pearson correlation coefficients for the noise sensitivity, in order to select the appropriate measure for the membership function. Then uses the maximum membership degree recognition method finds the most similar vector in the standard library to current vector, and firmly believes that both vector responses from a load located at the same beam element. After getting load point location information, the ratio of vector-mode can be used to determine the amplitude of load. Then the method was validated through simulation data, when applied to field test data from line experiment, it achieved a very good recognition. Finally, a detailed analysis of possible factors caused the recognition method error was present.
本文从轨道分析模型入手,介绍了轨道分析模型在列车轮载作用下的响应,分析和研究钢轨在垂直载荷作用下的应力与变形,为有效测量轮轨垂直力提供理论依据。随之介绍了基于地面测量轮轨垂直力各种方法的力学原理和实现方法。分析不同方法对于轨道支撑状态的依赖性或敏感性,指出了它们存在的缺点和适用性。利用有限元分析软件建立起了钢轨有限元模型。通过对模型的加载与解算得到钢轨模型上节点对于移动的垂直荷载作用时的响应变化规律,具体分析了钢轨中性轴上的节点在载荷点移动变化时的剪应力的变化情况。通过对仿真结果数据的分析,找出了布置剪力传感器的最优的节点位置,并仿真计算了布点之后输出的灵敏性和线性度。仿真计算了同一钢轨截面上不同横向位置荷载时对测试系统响应输出的影响以及横向力对垂直力测试系统输出的影响。计算结果表明同一截面上荷载点位置的变化不影响测试系统的输出,当钢轨两侧的布点完全对称时,横向力对垂向力测试电桥输出的影响为零。为了验证有限元仿真分析的结果,实施了室内加载实验。试验的结果分析出,仿真分析与试验的结果得到了相识的波形,但在幅值上存在一定的差异。分析了出现幅值差异的原因。
针对轮轨垂直力测量数据中可能存在的基线漂移的干扰,本文详细研究比对了曲线拟合方法,移动中值滤波,数学形态滤波器和小波阈值去噪方法在去除基线漂移的效果,分析不同方法存在的缺点并提出了改进的意见与方案。结合轮轨垂直力信号的特点,提出针对平衡往复型的信号去除基线漂移的经验性的新方法,通过对分段数据的平稳性检验和对中值及方差的最近距离聚类,筛选出能够体现基线漂移走势的分段数据中值作为基线漂移基点,再基点进行曲线拟合得到基线。与简单的曲线拟合方法相比,本文通过数据分段的办法,尽可能多地增加了基点的数量,从而能够更细致地表达真实的基线。相比于移动中值滤波和数学形态学滤波,虽然这几种方法的本质都基于顺序滤波器,但由于本文的方法对于其他非基线的噪声对提取的基线的干扰有筛选的过程,使得其相对于另外两者有更好的表现。由于经过数据分段处理,使得整个过程的计算量大大地缩小,最后介绍了通过与小波滤波组合的方案来抑制提取的基线中含有其他干扰成分,从而获得了更好的消除效果。
本文最后部分提出一种连续测量和识别轮轨垂直力的方法。本方法基于梁格原理,将测试期间内的钢轨分成数量有限的梁单元,同时在钢轨上布置多组观测点。假设载荷点位于梁元内的任何位置时,所布置的所有观测点的观测值不变,而在不同的梁元上施加载荷时,所有观测值组成的响应向量肯定不同,由此可通过理论计算或现场测试的方法得到单位荷载下或固定荷载下所有观测点对于载荷位置在所有划分的梁单元上移动时得到标准的响应向量库。通过将单点载荷位置对应多观测点响应向单测点响应对应一群组载荷位置点的响应转换分析和验证了响应向量的适定性要求。在己获得标准响应向量库的情况下,利用相似性测度研究了实测任意时刻下的观测点的响应与响应向量库的每个向量的关系。比较研究了欧氏距离,夹角余弦和皮尔森相关系数三种多维空间向量相似性测度对于噪声的敏感性,以便于从中选取适当测度作为隶属函数。最后使用最大隶属度识别法认定当前响应向量最相似的标准向量,从而认为两个向量的载荷点在相同的梁单元上。得到荷载点位置信息后,利用两个向量的模的比例关系来确定荷载的大小。文中通过仿真数据检验了方法的有效性。并将其用于线路试验实测的数据中,取得了较好的识别效果。最后具体分析了引起该识别方法误差的可能因素。
Railway vehicle running status monitoring, diagnosis, and early warning is important means to ensure vehicle safety. Monitoring wheel-rail forces can find out various abnormalities of the train and its devices timely, then diagnose and predict, propose the necessary corrective measures. So as to realize the locomotive vehicle "condition base maintenance" which improve the using quality and efficiency of vehicles and their equipment. At present there are a lot of different business system of monitoring wheel/rail force, but majority just test tools for peak load, or needed great changes to existing rail structure so can be realized measurement and identify the wheel/rail force. Based on this situation, this paper mainly research and development a method of continuous measurement and recognition of the wheel rail vertical load without altering the track structure.
This thesis starting from the railway analysis model, introduced railway analysis model response under train wheel load, detailed analysis and study rail stresses and deformations under vertical loading, which providing theoretical basis for effectively measuring wheel/rail vertical force. Subsequently introduce mechanics principle and implementation of various methods for measuring wheel-rail vertical force. The dependence and sensitivity of different methods for rail support status were analyzed, and disadvantages of and applicability of various methods were pointed out. By using finite element analysis software the finite element model of rail was established. Through loading and solving the model we got the responses of rail model nodes when subjected to a moving vertical load. Through analyzing the simulation results, we found the optimal node for arrangement of shear force sensors, and got the sensitivity and linearity of sensors'output. In order to verify the results of the finite element simulation analysis, an indoor laboratory loading experiment was implemented. Indoor test decorate three different schemes in the same rail span. From compare of the results, simulation and laboratory experiment show similar waveforms, but there are differences in amplitude. Then, the possible factors for these differences are analyzed.
Wheel-rail vertical force measurement data may be interfered by baseline drift, and the baseline drift should be eliminated before amplitude analysis. this thesis studied the effects of curve fitting, mobile median filtering, mathematical morphology filter and wavelet threshold denoising method in removing the baseline drift, analyzed the disadvantages of different methods and put forward the improvement Suggestions and solutions. According to the characteristics of the wheel/rail vertical force signal, a new empirical method was proposed to remove baseline drift, which through clustering median values and variance of median values in data segments, and picking up the median values reflected baseline drift trends, then curve fitting the Selected points as the baseline. Compared to the simple curve fitting method, the number of basis points increase as much as possible, more detailed of the true baseline is expression. Compared to moving median filtering and morphological filtering, although the nature of these methods are based on order filter, but the proposed method Inhibit non-baseline noise interference to the extracted baseline with a sifting process, making it relative better performance to the others. Moreover, segmenting the data, making the calculation of whole process is greatly reduced. Then, a scheme through combining with wavelet filtering to suppress other interfering component contains in the extracted baseline was introduced, which obtained better eliminate effect.
In last part of this thesis, a continuous measurement and identification method for wheel-rail vertical force was proposed. The method is based on the principle beam frame. The test period is divided into a limited number of rail beam element. Then we arrange multiple sets of observation point on the rail. Assuming that when the loading point locate anywhere in the beam position, the observation values of all observations points unchanged. While the load is applied on a different beam element, all observation values response vector must be different. So, by theoretical calculation method or field testing, standard response vector library of all observation points'response for constant loads moving along all of beam element can be obtained. The request of well-posedness of response vector library was validated by convert multiple observation points for single load location point to single observation point for multiple load location points. After obtained the standard response vector library, similarity measure was employed to observer the relationship between any observation vector and each vector in response vector library. In this thesis, a comparative study of three kind of multidimensional vector space similarity measure Euclidean distance, Angle cosine and Pearson correlation coefficients for the noise sensitivity, in order to select the appropriate measure for the membership function. Then uses the maximum membership degree recognition method finds the most similar vector in the standard library to current vector, and firmly believes that both vector responses from a load located at the same beam element. After getting load point location information, the ratio of vector-mode can be used to determine the amplitude of load. Then the method was validated through simulation data, when applied to field test data from line experiment, it achieved a very good recognition. Finally, a detailed analysis of possible factors caused the recognition method error was present.
引文
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