【摘要】 利用小波变换和人工神经网络技术,对激光激发单向纤维增强复合板产生的兰姆波信号进行分析,进而反演出单向纤维增强复合板的弹性常数。对小波变换和神经网络算法加以优化以提高反演结果的准确性,并分别对纤维方向和垂直于纤维方向的实验波形进行弹性常数的反演,两个方向的反演结果十分吻合。研究表明,利用该方法可直接从激光激发兰姆波的瞬态实验波形中反演出复合板的弹性常数,既不用事先知道兰姆波各模式传播的群速度,也不必采用传统的最小二乘法拟合色散曲线来反演弹性常数。更多还原

【Abstract】 An inverse method is presented to determine the elastic constants of an experimental sample, a titanium graphite unidirectional fiber-reinforced composite plate, using wavelet transform and neural networks. Optimal algorithms of wavelet transform and neural networks are given here in order to improve the accuracy of inversion results. Coherent results were shown in both fiber direction and cross fiber direction, proving the feasibility of this method. Neither the group velocity of the Lamb wave modes are needed, as in the conventional method, and no direct least-square fitting of the experimental waveforms is necessary.更多还原