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Damage and noise sensitivity evaluation of autoregressive features extracted from structure vibration

机译:从结构振动中提取的自回归特征的损伤和噪声敏感性评估

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摘要

In the past few decades many types of structural damage indices based on structural health monitoring signals have been proposed, requiring performance evaluation and comparison studies on these indices in a quantitative manner. One tool to help accomplish this objective is analytical sensitivity analysis, which has been successfully used to evaluate the influences of system operational parameters on observable characteristics in many fields of study. In this paper, the sensitivity expressions of two damage features, namely the Mahalanobis distance of autoregressive coefficients and the Cosh distance of autoregressive spectra, will be derived with respect to both structural damage and measurement noise level. The effectiveness of the proposed methods is illustrated in a numerical case study on a 10-DOF system, where their results are compared with those from direct simulation and theoretical calculation.
机译:在过去的几十年中,已经提出了许多类型的基于结构健康监测信号的结构损伤指数,需要以定量的方式对这些指标进行性能评估和比较研究。分析灵敏度分析是帮助实现此目标的一种工具,该方法已成功用于评估许多研究领域中系统操作参数对可观察特性的影响。本文从结构损伤和测量噪声水平两个方面推导了两种损伤特征的灵敏度表达式,即自回归系数的马氏距离和自回归光谱的科什距离。在10自由度系统的数值案例研究中说明了所提出方法的有效性,并将其结果与直接仿真和理论计算的结果进行了比较。

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