Damage degree prediction method of CFRP structure based on fiber Bragg grating and epsilon-support vector regression
Damage degree prediction method of CFRP structure based on fiber Bragg grating and epsilon-support vector regression
复制标题
基于光纤布拉格光栅和epsilon-支持向量回归的CFRP结构损伤程度预测方法
DOI：
10.1016/j.ijleo.2018.11.086
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发表时间：
2019-02
期刊：
影响因子：
3.1
通讯作者：
Su Chenhui
中科院分区：
文献类型：
--
作者：
Lu Shizeng;Jiang Mingshun;Wang Xiaohong;Yu Hongliang;Su Chenhui
结构损伤评估对于保证碳纤维增强塑料（CFRP）结构的使用安全具有重要意义。研究了基于光纤光栅和ε-支持向量回归的CFRP结构损伤程度预测方法。采用光纤光栅传感器检测结构的动态响应信号。然后，利用傅立叶变换提取结构的动力特性作为损伤特征，并利用RReliefF算法对损伤特征进行降维。在此基础上，建立了基于ε-支持向量回归的CFRP结构损伤程度预测模型。最后对本文提出的方法进行了实验验证。结果表明，ε-支持向量回归模型能够准确预测未知样本的损伤程度，30次试验中，27次试验的绝对相对误差小于10%。为CFRP结构的损伤程度预测提供了一种可行的方法。
The assessment of structural damage is of great significance for ensuring the service safety of carbon fiber reinforced plastics (CFRP) structures. In this paper, the damage degree prediction method of CFRP structure based on fiber Bragg grating and epsilon-support vector regression was studied. The structural dynamic response signals were detected by fiber Bragg grating sensors. Then, the Fourier transform was used to extract the dynamic characteristics of the structure as the damage feature, and the damage feature dimensionality was reduced by using the RReliefF algorithm. On this basis, the damage degree prediction model of CFRP structure based on epsilon-support vector regression was established. Finally, the method proposed in this paper was experimentally verified. The results showed that the epsilon-support vector regression model can accurately predict the damage degree of unknown samples, and the absolute relative error of 27 experiments was less than 10% for 30 testing experiments. This paper provided a feasible method for predicting the damage degree of CFRP structures.
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