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STRUCTURAL DAMAGE DETECTION BASED ON ENERGY TRANSFER BETWEEN INTRINSIC MODES

机译:基于内在模态之间能量转移的结构损伤检测

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In this study, a new damage detection algorithm for specific types of damages such as breathing cracks, which are called "active discontinuities" in this paper, is proposed. The algorithm is based on the nonlinear behavior of this class of damages and hence, is more precise and sensitive to damage compared to other common linear methods. The active discontinuities can be regarded as additional degrees of freedom (DOFs) which need energy to be excited. Because the input energy of both the intact and the damaged structures is finite, the energy content of vibrating modes will be changed due to damage. Thus, the properties of distribution of energy between vibrating modes can be used as indices for detecting damage. An essential detectability condition using this concept is decomposing a signal such that no spurious mode imposed to its expansion. In order to satisfy this condition, Empirical Mode decomposition (EMD) is used to extract the vibrating modes since all nonlinearities in a signal are preserved while no spurious mode or assumption of stationarity is imposed on the problem. Prevention of mode mixing, which is an important drawback of EMD, is another necessary condition for robustness of the algorithm. A solution is proposed in this paper to satisfy this condition in which special constraints are imposed on the normal procedure of EMD. Then, the fourth central moment, kurtosis, is used to compare the distribution of energy between the modified vibrating modes. The algorithm is verified through experimental testing of a simple steel cantilever structure under various damage scenarios. Results demonstrate the efficacy of the method for detecting discontinuities in a real structure.
机译:在这项研究中,针对特定类型的损伤(如呼吸裂纹)提出了一种新的损伤检测算法,在本文中将其称为“主动不连续性”。该算法基于此类损坏的非线性行为,因此,与其他常见的线性方法相比,该算法更加精确且对损坏更敏感。主动间断可以视为需要能量被激发的附加自由度(DOF)。由于完整结构和受损结构的输入能量都是有限的,因此振动模式的能量含量会因损坏而发生变化。因此,振动模式之间的能量分布特性可以用作检测损伤的指标。使用此概念的基本可检测性条件是分解信号,使得不会对其扩展施加任何杂散模式。为了满足此条件,由于保留了信号中的所有非线性,而没有对问题施加任何杂散模式或平稳性的假设,因此采用经验模式分解(EMD)提取振动模式。防止模式混合是EMD的重要缺点,这是算法鲁棒性的另一个必要条件。本文提出了一种解决方案来满足此条件,其中对EMD的常规过程施加了特殊约束。然后,使用第四中心矩峰度来比较修改后的振动模式之间的能量分布。通过在各种损伤情况下对简单钢悬臂结构进行实验测试,验证了该算法。结果证明了该方法在实际结构中检测不连续性的有效性。

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