基于PZT结Lamb波方向算法的损伤定位方法
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TH145.9;TB332

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(国家自然科学基金及民航联合基金重点支持项目(U1333201)


Damage Location Detection Method Based on Lamb Wave Direction Algorithm and Piezoelectric Knot
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    摘要:

    基于Lamb波在板中的传播特性,针对复合材料的损伤检测,提出一种新型的损伤定位方法。该方法采用3个压电陶瓷片( piezoelectric transducers,简称PZT)组成PZT结,通过从各PZT中提取出损伤散射信号,找到其损伤波包到达的时间差,并依据Lamb波的传播速度得到位移差。首先,结合PZT结中各PZT的几何位置,具体推导出损伤方向算法,运用方向算法找到Lamb波在损伤位置发生散射后的其中一个传播方向,通过传播方向的交点来实现损伤位置的判定;其次,分析了互相关理论的基本原理,并运用互相关算法提取出损伤散射信号;最后,在碳纤维增强树脂基复合材料薄板上对该算法进行实验验证,求出了损伤方向以及损伤位置。验证结果表明,该方法能够对复合材料损伤进行有效的定位。

    Abstract:

    In this work, based on the propagation properties of Lamb wave, an approach is proposed to detect damage location in composite material. Two piezoelectric knots are utilized in this approach, each knot includes three piezoelectric transducers. Damage scattering signals are collected using piezoelectric knots. In this method, the difference of time and displacement between each transducer is obtained using the propagation speed of Lamb wave. Considering the geometrical position of piezoelectric transducers, the spreading direction of scattering signals is computed with a direction algorithm, in which the arrival time of the wave packet to each transducer is utilized. This direction is the one that the lamb wave occurs scattering from the damage position. By this way, each piezoelectric knot can detect one spreading direction from the damage location. Therefore, the damage location is determined with the intersection of these identified directions. Moreover, the validation of the damage location detection method is given in this work. The fundamental theory of cross correlation is investigated, and the cross-correlation algorithm is used to extract the damage scattering signal. Experimental tests have been performed on carbon fiber reinforced resin matrix composite plates to validate the detection method. The damage location is obtained and compared with the experimental results. It reaches a good agreement, and this scenario indicates the robustness of this method to detect the damage location.

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  • 在线发布日期: 2019-05-13
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