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Fractal theory and wavelet packet transform based damage detection method for beam structures

机译:基于分形理论和小波包变换的梁结构损伤检测方法

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The presence of noise greatly affects the effectiveness and robustness of structural damage detection methods. In this study, a new damage detection method for beam structures is presented, utilizing time, frequency and space domain information effectively. Local free vibrations of both undamaged and damaged signals are firstly extracted utilizing the Natural Excitation Technique (NExT). Then the signals are decomposed into the low frequency region and high frequency region by the wavelet packet transform (WPT). The Higuchi's fractal dimension (HFD) is applied to measure the complexity of new local signals, which combine the low frequency component of undamaged signals and high frequency component of damaged signals. Damage can be localized by the peak value of Katz's fractal dimension (K.FD) analyzing the spatial curve of the calculated HFD values along the structure. For validation, the numerical studies of a simple supported beam were conducted. The results demonstrate that the method is capable of localizing single and multiple damage of various severity accurately. Furthermore, it is found that the proposed damage index is directly connected to damage severity. And the results of tests under heavy noise reveal strong robustness of the proposed method.
机译:噪声的存在极大地影响了结构损伤检测方法的有效性和鲁棒性。在这项研究中,提出了一种新的梁结构损伤检测方法,该方法有效地利用了时间,频率和空间域信息。首先利用自然激发技术(NExT)提取未损坏和损坏信号的局部自由振动。然后,通过小波包变换(WPT)将信号分解为低频区域和高频区域。 Higuchi的分形维数(HFD)用于测量新本地信号的复杂度,该信号结合了未损坏信号的低频分量和损坏信号的高频分量。可以通过分析沿结构计算的HFD值的空间曲线来确定Katz分形维数(K.FD)的峰值来确定破坏程度。为了验证,进行了简单支撑梁的数值研究。结果表明,该方法能够准确定位各种严重程度的单个和多个损伤。此外,发现拟议的损害指数与损害的严重程度直接相关。重噪声条件下的测试结果表明,该方法具有较强的鲁棒性。

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