Effect of frequency domain attributes of wavelet analysis filter banks for structural damage localisation using the relative wavelet entropy index
Effect of frequency domain attributes of wavelet analysis filter banks for structural damage localisation using the relative wavelet entropy index
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DOI：
10.1504/ijsmss.2015.078365
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发表时间：
2015
期刊：
影响因子：
--
通讯作者：
K. Gkoktsi;A. Giaralis
中科院分区：
文献类型：
--
作者：
K. Gkoktsi;A. Giaralis
相对小波熵（RWE）是一种常用的损伤敏感指标，它是通过对给定结构在宽带激励下的健康/参考和损伤状态下的线性响应加速度信号进行小波变换而得到的。在这里，四个不同的能量保持小波分析滤波器组计算RWE两个基准结构通过算法，可以有效地运行板上的无线传感器分散的结构健康监测。结果表明，滤波器组的小波基compoundly支持在频域中是有利的，因为它们实现了增强的频率选择性之间的尺度，因此，尺度/频率相关的贡献者RWE变得更容易解释。此外，它表明，滤波器组具有大的恒定Q值（即，有效频率与有效带宽之比）更适合于捕获与高频相关的损伤信息，而非恒定Q分析滤波器组对于基于RWE的稳态损伤检测最有效。
The relative wavelet entropy (RWE) is a commonly considered in the literature damage-sensitive index derived by wavelet transforming linear response acceleration signals from healthy/reference and damaged states of a given structure subject to broadband excitation. Herein, four different energy-preserving wavelet analysis filter banks are employed to compute the RWE for two benchmark structures via algorithms that may efficiently run on-board wireless sensors for decentralised structural health monitoring. It is shown that filter banks of wavelet bases compactly supported in the frequency domain are advantageous since they achieve enhanced frequency selectivity among scales and, therefore, the scale/frequency dependent contributors to the RWE become easier to interpret. Moreover, it is demonstrated that filter banks with large constant Q values (i.e., ratio of effective frequency over effective bandwidth) are better qualified to capture damage information associated with high frequencies, while non-constant Q analysis filter banks are most effective for RWE-based stationary damage detection.