基于奇异峰态的钢轨踏面损伤弦测特征辨识
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U216.3;TH17

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国家自然科学基金地区科学基金资助项目(51468042);江西省自然科学基金资助项目(20142BAB206003)


The Characteristics Identification of Chord Measurement of Track Surface Defects Based Upon Singular Component Kurtosis
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    摘要:

    根据钢轨踏面非周期性损伤具有奇异性,分析了其中点弦测法的响应特征,提出多弦理论下的损伤辨识方法:选取合适的弦长组合可在抑制轨道不平顺弦测幅值增益的同时放大钢轨踏面损伤幅度,再利用奇异值分解将测量数据进行分离后,对包含有钢轨踏面损伤奇异特征的分量求滑动峰态序列,得到损伤的精确位置。理论仿真和实际线路测试表明,该方法仅利用轨道弦测数据就能提取被淹没的钢轨踏面损伤信息,适合在实际铁路工务中应用。

    Abstract:

    Chord measurement is a widely-used method of inspecting track irregularity at present. Considering the singular characteristics of rail track surface defects, a new method is proposed to identify these defects on the basis of multi-chord theory by analyzing their responses to mid-chord model. Then, the test data are separated by singular value decomposition, since the surface damage is enhanced when the track irregularity amplitude gain is reduced by proper combination of chords. Thus, the rail track surface defects characteristics and their positions are extracted through the sliding kurtosis sequence. Theoretical simulation and test results show that this approach is able to get rail track surface defects information which is hidden in chord measured value. The proposed method is suitable for engineering application.

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  • 在线发布日期: 2018-11-02
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