利用光纤布拉格光栅(FBG)构建了传感器网络;结合小波分解与重构算法、频谱分析和支持向量多分类机算法研究了碳纤维复合材料板损伤的模式识别算法。首先, 对带有不同损伤模式的复合材料结构进行冲击试验, 探索损伤模式与信号特征之间的关系。然后, 对信号进行小波分解与重构去除基线干扰;采用傅里叶变换频谱分析提取信号幅频特性, 构建了复合材料结构损伤模式识别方法。最后, 将提取的信号幅频特性作输入, 复合材料结构损伤模式作输出, 利用支持向量多分类机, 实现了复合材料结构损伤模式识别。在500 mm×500 mm×2 mm的碳纤维复合材料板中心, 选定200 mm×200 mm的实验区域, 对30组测试样本进行了损伤模式识别。实验结果表明: 29组损伤模式得到了准确识别, 正确率为96.7%。研究结果为碳纤维复合材料板的损伤模式识别提供了一种可靠的方法。

A sensing network was constructed by a Fiber Bragg Grating (FBG) sensor, and a mode identification algorithm for the damage of carbon composite materials was researched by combining the wavelet decomposition and reconstruction, frequency spectrum analysis and support vector classifier algorithm. Firstly, according to the impact test on a composite material structure with different damage modes, the relationship between damage modes and signal characteristics was explored. Then, the wavelet decomposition and reconstruction were used to remove the signal baseline interference, and the identification method of damage mode for composite materials was constructed based on extracting signal amplitude frequency characteristic by Fourier transform analysis. Finally, the extracted signal amplitude frequency characteristic was used as an input and the damage mode as an output, the damage modes of composite materials were identified based on support vector classifiers. An experimental area with 200 mm×200 mm was selected in a 500 mm×500 mm×2 mm carbon fiber reinforced plastic plate center. The 30 damage modes are tested, and the result shows that 29 damage modes are identified accurately with identification accuracy of 96.7%. The research provides a reliable method for the identification of damage modes of composite materials.