利用压电阻抗法对带裂缝木梁缺陷检测进行试验和数值仿真研究,并利用BP神经网络对木梁损伤位置进行分类识别。首先实测裂缝在不同深度和不同位置时对阻抗的影响规律,然后利用损伤指标均方根偏差来定量评估木梁阻抗值随损伤程度和损伤位置的变化关系。试验和数值计算均表明,木梁出现裂缝损伤后,阻抗峰值对应频率略微下降;损伤指标随损伤程度的增大而增大,随压电传感器和裂缝位置之间距离的增大而减小。

Both of the experiments and numerical simulations of damage detection for timber beams with cracks based on electromechanical impedance method were conducted. The BP neural network was used to classify and identify the location of timber beam damage. Firstly, the influence of the cracks at different depths and different positions on impedance was experimentally tested. Then the damage index, root mean square deviation (RMSD), was employed quantitatively to evaluate the relationship between the impedance values and the damage severity and location of the timber beams. Both of the experimental and numerical results indicate that the corresponding frequency at the peak impedance decreased slightly when the crack appeared in timber beam. In addition, the RMSD increased gradually with the increase of the damage severity, however, it decreased gradually with the increase of the distance between the piezoelectric sensors and crack location.