吴荻非, 向晖, 刘成龙, 沈宾宾, 曾孟源. 基于振动传递率函数的水泥混凝土铺面脱空识别方法[J]. 北京工业大学学报. doi: 10.11936/bjutxb2022110018
    引用本文: 吴荻非, 向晖, 刘成龙, 沈宾宾, 曾孟源. 基于振动传递率函数的水泥混凝土铺面脱空识别方法[J]. 北京工业大学学报. doi: 10.11936/bjutxb2022110018
    WU Difei, XIANG Hui, LIU Chenglong, SHEN Binbin, ZENG Mengyuan. Void-Underneath Detection and Localization of Concrete Pavement Using Transmissibility Function Analysis[J]. Journal of Beijing University of Technology. doi: 10.11936/bjutxb2022110018
    Citation: WU Difei, XIANG Hui, LIU Chenglong, SHEN Binbin, ZENG Mengyuan. Void-Underneath Detection and Localization of Concrete Pavement Using Transmissibility Function Analysis[J]. Journal of Beijing University of Technology. doi: 10.11936/bjutxb2022110018

    基于振动传递率函数的水泥混凝土铺面脱空识别方法

    Void-Underneath Detection and Localization of Concrete Pavement Using Transmissibility Function Analysis

    • 摘要: 为提高水泥混凝土铺面脱空识别的准确性和便捷性,提出了一种基于振动传递率函数的的板底脱空识别方法。首先,建立了9块板全尺寸铺面结构三维有限元模型,获取冲击荷载作用下铺面板的多点加速度响应;其次,在两个振动传递方向上,分别计算相邻两个测点间的振动传递率函数,分析特定频段内传递率函数的差异,并提出传递率函数脱空判定指标(TDI)及其矩阵表达式;最后,计算分析11种不同脱空形式、程度下TDI指标的差异,并分析测点布设方式、信号噪声水平对TDI指标的影响。结果表明:该脱空判定指标能较好识别、定位板角和板边局部脱空。所得TDI指标在板角脱空的两个传递方向均十分显著,在板边脱空的垂直脱空边方向较为显著。而对于板中脱空,两个传递方向上的TDI指标均无法有效识别。板中脱空的分布与TDI指标的分布一致性较差。对于多区域脱空,其计算得到的TDI指标与单区域脱空类似,对于板角和板边局部脱空均能有效识别。测点布设越密,TDI指标的分布与脱空分布的一致性越高;然而,该识别方法对噪声水平较为敏感,噪声水平越高,识别精度越低,需要较高精度的传感器或设备予以支撑。

       

      Abstract: To improve the measurement accuracy and efficiency of void-underneath detection of concrete pavement, a novel identification method based on transmissibility function analysis was proposed. Numerical analyses were conducted to validate the method’s effectiveness. Firstly, a nine-slab 3-D finite element model of concrete pavement was developed in ABAQUS software, and then the acceleration responses induced by an impact load were collected for transmissibility function analysis; Secondly, the measurement point pairs were defined in two transmitting directions. Then, the two transmissibility-based identification indicator (TDI) matrices were calculated, representing the differences between the transmissibility functions of damaged status and undamaged status; Finally, 11 scenarios, including different types and degrees of void-underneath, were analyzed. Moreover, the effects of measurement points’ distribution and noise levels on identification performances were studied. The analysis results show that the two TDI matrices are suitable for the identifications of corner-void-underneath and edge-void-underneath. Both two TDI matrices are sensitive to corner-void-underneath, while only one TDI matrix whose transmitting direction is perpendicular to the corresponding edge is sensitive to edge-void-underneath. The effects of center-void-underneath on the two TDI matrices are not significant, as the distribution of void-underneath is not consistent with the distribution of TDIs. For multi-area void-underneath, the trends of the two TDI matrices are similar to the single-point void-underneath. The distribution of measurement points affect the identification performance significantly. Denser measurement points would provide more accurate identification results. In addition, this identification method is very sensitive to the noise, high noise level results in poor identification performance. It is recommended to use this method under low noise level.

       

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