基于VMD和AP聚类的结构损伤识别方法
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1.苏州科技大学土木工程学院,江苏 苏州 215011;2.江苏省结构工程重点试验室,江苏 苏州 215011

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TP212.9;TP391

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国家自然科学基金(51308369)


Structural damage identification based on VMD and AP clustering
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1.College of Civil Engineering, Suzhou University of Science and Technology, Suzhou, Jiangsu 215011, China; 2.Key Laboratory of Jiangsu Province Structural Engineering, Suzhou, Jiangsu 215011,China

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    摘要:

    为了能够用少量无标签监测数据识别结构损伤状态,提出一种创新的损伤识别方法。首先将试验中各个长标距光纤布拉格(fiber Bragg grating,FBG)传感器测得的动态响应数据进行变分模态分解(variational modal decomposition,VMD),提取分量信号(intrinsic mode functions,IMF)的时域特征和频域特征,通过Relief-F算法选择出各个传感器信号的敏感特征,组合成敏感特征集输入亲和传播(affinity propagation,AP)聚类算法中进行损伤识别。本文采用两组不同的试验来验证方法的效果和鲁棒性,在两组试验中分别获得了100%和98.7%的损伤识别率,结果表明方法具有实际应用价值。

    Abstract:

    In order to identify the structural damage status with a small amount of unlabeled monitoring data, an innovative damage identification method is proposed in this paper. Firstly, the dynamic response data measured by each long-gauge fiber Bragg grating sensor in the experiment is subjected to variational modal decomposition, and the time-domain and frequency-domain characteristics of each component signal are extracted. The sensitive features of each sensor signal are selected by Relief-F, combined into a sensitive feature set and input into the affinity propagation clustering for damage identification. Two different sets of experiments are used to verify the effectiveness and robustness of the method, and damage recognition rates of 100% and 98.7% are obtained in the two sets of experiments. The results show that the method has practical application value.

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罗家豪,王大鹏.基于VMD和AP聚类的结构损伤识别方法[J].电子测量技术,2022,45(17):51-55

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  • 在线发布日期: 2024-04-02
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