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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 Projected Input Residuals in Damage Identification
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The Use of Projected Input Residuals in Damage Identification

机译：预计的输入残差在损坏识别中的使用

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摘要

The topic of this paper is model-based damage identification, i.e. damage identification based 1.) on measurements taken from the structure and 2.) on a mathematical model of the structure for the purpose of diagnosis, simulation and identification. The adjustment of mathematical models by means of measured data is equivalent to model correction within system identification. It is an ill-posed inverse problem, which often has to be solved with incomplete measurements, the latter dependent on the information content and the number of measuring points for the output quantities. This problem is handled without a model reduction by projection methods introduced first in [1]. This method, the Projective Input Residual Method (PIR.M), is an identification method based on input and incomplete output measurements in the frequency domain. In [2] on the basis of the PIRM and projected input residuals, a damage indicator is defined and applied. This indicator was shown to be sensitive to system modifications, e.g. decreased stiffness due to a damage, using only a small fraction of the total number of possible meausuring points. In our contribution this indicator is improved by the introduction of special rcgularization methods that make the indicator more robust in case of noisy measurements. This work is part of the collaborative research center 477 in Braunschweig, Germany, and as such supported by the DFG, the Deutsche Forschungsgescllschaft.
机译：本文的主题是基于模型的损伤识别，即基于1.）基于结构的测量值和2.）基于结构的数学模型的损伤识别，以进行诊断，模拟和识别。通过测量数据对数学模型进行的调整等效于系统识别中的模型校正。这是一个不适定的逆问题，通常必须通过不完整的测量来解决，不完整的测量取决于信息内容和输出量的测量点数量。通过首先在[1]中引入的投影方法，无需模型简化即可解决该问题。这种方法称为投影输入残差法（PIR.M），是一种基于频域中输入和不完整输出测量值的识别方法。在[2]中，基于PIRM和预计的输入残差，定义并应用了损坏指标。该指标显示对系统修改敏感，例如由于损坏而导致刚度降低，仅使用了可能的测量点总数的一小部分。在我们的贡献中，通过引入特殊的规则化方法改进了该指标，该方法使该指标在有噪声测量的情况下更加可靠。这项工作是位于德国不伦瑞克的协作研究中心477的一部分，因此得到了DFG Deutsche Forschungsgescllschaft的支持。

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