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将压电传感与主动Lamb波监测技术相结合,研究在静拉伸加载状态下碳纤维复合材料T型接头(T700/BA9916)界面脱粘及扩展过程中的信号特征,并采用改进后的BP神经网络系统对接头损伤状态进行识别。实验结果表明:T型接头脱粘首先发生在三角填充区,后向突缘扩展;接头失效前,信号能量和最小二乘峰值因子随时间呈线性递减,能够表征脱粘程度,利用自适应微粒群算法改进后的网络训练值与实验观测值之间的误差为3.8%～4.7%。
Combining the piezoelectric sensing and the active Lamb wave monitoring technology, the signal characteristics during the process of debonding and expanding the interface of carbon fiber composite T-junction (T700 / BA9916) under static tensile loading were studied. The improved BP Neural network system to identify the damage status of joints. The experimental results show that the debonding of T-joints first takes place in the triangular filling zone and the backward flange expands. Before the failure of joints, the signal energy and the least square peak factor decrease linearly with time, and the degree of debonding can be characterized. The error between the improved network training value and the experimental observation value is 3.8% ~ 4.7%.