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Structural damage localization by outlier analysis of signal-processed mode shapes - Analytical and experimental validation

机译:通过信号处理模式形状的异常分析来确定结构损伤的位置-分析和实验验证

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摘要

Contrary to global modal parameters such as eigenfrequencies, mode shapes inherently provide structural information on a local level. Therefore, this particular modal parameter and its derivatives are utilized extensively for damage identification. Typically, more or less advanced mathematical methods are employed to identify damage-induced discontinuities in the spatial mode shape signals, hereby, potentially, facilitating damage detection and/or localization. However, by being based on distinguishing damage-induced discontinuities from other signal irregularities, an intrinsic deficiency in these methods is the high sensitivity towards measurement noise. In the present paper, a damage localization method which, compared to the conventional mode shape-based methods, has greatly enhanced robustness towards measurement noise is proposed. The method is based on signal processing of a spatial mode shape by means of continuous wavelet transformation (CWT) and subsequent application of a generalized discrete Teager-Kaiser energy operator (GDTKEO) to identify damage-induced mode shape discontinuities. In order to evaluate whether the identified discontinuities are in fact damage-induced, outlier analysis is conducted by applying the Mahalanobis metric to major principal scores of the sensor-located bands of the signal-processed mode shape. The method is tested analytically and benchmarked with other mode shape-based damage localization approaches on the basis of a free-vibrating beam and validated experimentally in the context of a residential-sized wind turbine blade subjected to an impulse load.
机译:与诸如特征频率之类的全局模态参数相反,模态形状固有地在局部水平上提供结构信息。因此,该特定的模态参数及其导数被广泛用于损伤识别。通常,采用或多或少的高级数学方法来识别空间模式形状信号中的损伤引起的不连续性,从而有可能促进损伤的检测和/或定位。但是,通过将损坏引起的不连续性与其他信号不规则性区分开来,这些方法的固有缺陷是对测量噪声的高灵敏度。在本文中,提出了一种损伤定位方法,与传统的基于模式形状的方法相比,该方法大大提高了对测量噪声的鲁棒性。该方法基于通过连续小波变换(CWT)对空间模式形状进行信号处理以及随后应用广义离散Teager-Kaiser能量算子(GDTKEO)来识别损伤引起的模式形状不连续性的方法。为了评估识别出的不连续性是否实际上是由损坏引起的,通过对信号处理模式形状的传感器定位带的主要主分数应用马哈拉诺比斯度量进行离群值分析。在自由振动梁的基础上,对该方法进行了分析测试,并使用其他基于模式形状的损伤定位方法进行了基准测试,并在承受脉冲负载的住宅大小的风力涡轮机叶片的情况下进行了实验验证。

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