Mono-Component Feature Extraction for Condition Assessment in Civil Structures Using Empirical Wavelet Transform
Mono-Component Feature Extraction for Condition Assessment in Civil Structures Using Empirical Wavelet Transform
复制标题
使用经验小波变换进行土木结构状态评估的单分量特征提取
DOI：
10.3390/s19194280
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发表时间：
2019-10
期刊：
影响因子：
3.9
通讯作者：
Yun-Lai Zhou
中科院分区：
文献类型：
--
作者：
Yun-Xia Xia;Yun-Lai Zhou
提出了一种基于尺度空间经验小波变换（EWT）的土木结构健康监测信号处理方法。FREEVIB方法是一种广泛应用的瞬时模态参数识别方法，它首先从EWT分离出的单个部件中确定结构特性。尺度空间EWT将频率边界的检测转化为傅立叶谱的尺度空间表示。同时，寻找有意义的模式成为一个最小尺度空间曲线长度上的聚类问题。采用大津算法确定聚类分析的阈值。为了保留时变特性，EWT提取的单分量分析的FREEVIB方法，以获得瞬时模态参数和结构的线性特性。仿真和真实的土木结构SHM信号验证了该方法的有效性。实验结果表明，该方法能够高精度地分离信号成分，即使是频域中间隔较近的成分，也能可靠地提取信号的结构特征。
This paper proposes a methodology to process and interpret the complex signals acquired from the health monitoring of civil structures via scale-space empirical wavelet transform (EWT). The FREEVIB method, a widely used instantaneous modal parameters identification method, determines the structural characteristics from the individual components separated by EWT first. The scale-space EWT turns the detecting of the frequency boundaries into the scale-space representation of the Fourier spectrum. As well, to find meaningful modes becomes a clustering problem on the length of minima scale-space curves. The Otsu’s algorithm is employed to determine the threshold for the clustering analysis. To retain the time-varying features, the EWT-extracted mono-components are analyzed by the FREEVIB method to obtain the instantaneous modal parameters and the linearity characteristics of the structures. Both simulated and real SHM signals from civil structures are used to validate the effectiveness of the present method. The results demonstrate that the proposed methodology is capable of separating the signal components, even those closely spaced ones in frequency domain, with high accuracy, and extracting the structural features reliably.
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发表时间：
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期刊：
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