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首页> 外文会议>3rd International Workshop on Structural Health Monitoring, Sep 12-14, 2001, Stanford University >The Use of Nonlinear Time Series-Based Features in Assessing Structural Degradation
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The Use of Nonlinear Time Series-Based Features in Assessing Structural Degradation

机译：基于非线性时间序列的特征在评估结构退化中的应用

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摘要

In the field of vibration-based structural damage assessment, traditional approaches have relied upon the extraction of linear features from the measured responses. Typically, such features include direct modal properties (natural frequencies, mode shapes), derived modal features (strain energy damage indices, flexibility changes), or auto-regressive (ARMA) parameters. In this work, we report on a novel time series based technique whereby a specialized nonlinear excitation is imparted on the structure and properties of the associated output attractor are analyzed. It is shown that certain attractor properties can yield features which are considerably more sensitive to subtle damage-inflicted changes in the structure than many of the traditional modal-based features. In addition the attractor based features demonstrate superior performance in correctly identifying the location of damage as compared to a strain energy damage index method. Specific data are presented for a simple plate model with damage modeled through a degrading weld line.
机译：在基于振动的结构损伤评估领域，传统方法依赖于从测得的响应中提取线性特征。通常，此类特征包括直接的模态属性（固有频率，模态形状），派生的模态特征（应变能破坏指数，柔韧性变化）或自回归（ARMA）参数。在这项工作中，我们报告了一种新颖的基于时间序列的技术，其中在结构和相关输出吸引子的性质上进行了专门的非线性激励分析。结果表明，某些吸引子特性所产生的特征比许多传统的基于模态的特征对微妙的结构破坏变化更为敏感。此外，与应变能损伤指数法相比，基于吸引子的特征在正确识别损伤位置方面表现出卓越的性能。给出了一个简单的板模型的具体数据，该模型具有通过退化焊接线建模的损伤。

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