基于随机梯度下降法的纯输出土木结构状态评估方法

P. Ni, X. Ye, Yang Ding
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引用次数: 1

摘要

利用结构健康监测数据来评估结构的状态已经引起了人们的广泛关注。现有的方法大都要求在受力位置进行测量。本文提出了一种新的仅输出状态评估方法,该方法不需要在力位置进行测量。采用随机梯度下降法对未知结构损伤指标和输入力进行识别。对未知结构损伤指标和输入力的动态加速度响应灵敏度进行了解析推导。通过最小化振动测量值与计算值之间的差异,可以识别未知损伤指标和未知输入力。通过二维桁架和七层框架的数值研究和钢架结构的实验研究,验证了该方法的准确性和有效性。结果表明,该方法可以识别损伤程度、位置和未知输入力。此外,不需要在力位置进行测量。在考虑20%的测量噪声时,识别误差小于5%。
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An output‐only structural condition assessment method for civil structures by the stochastic gradient descent method
The interesting to assess the condition of a structure with structural health monitoring data has gained many attentions. Most of the existing methods require the measurement at the force location. This paper presents a novel output‐only condition assessment method that does not require measurement at the force location. The unknown structural damage indices and input force can be identified with the stochastic gradient descent method. The dynamic acceleration response sensitivities with respect to the unknown structural damage indices and input force are derived analytically. Both unknown damage indices and unknown input force can be identified by minimizing the discrepancy between the measured and calculated vibration data. Numerical studies on a two‐dimensional truss and seven‐floor frame and experimental studies on a steel frame structure are presented to verify the accuracy and efficiency of the proposed method. Results demonstrate that the damage severity, location, and unknown input force can be identified. Also, the measurement at the force location is not required. Furthermore, when 20% measurement noise is considered, the identified error is less than 5%.
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