碳纤维增强复合材料层合板的非线性机电阻抗谱综合监测

Runye Lu, Yanfeng Shen
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引用次数: 0

摘要

提出了一种用于碳纤维增强复合材料(CFRC)层合板综合监测的非线性机电阻抗谱(NEMIS)方法。该方法结合了传统EMIS技术和非线性超声技术的优点,可以获取结构阻抗谱,捕捉非线性超声特征,用于损伤检测。对传统EMIS和NEMIS进行了对比分析。综述了CFRC层合板的各种损伤类型和损伤机理。通过对降阶一维接触声学非线性(CAN)模型的数值研究,揭示了啁啾引起的非线性特性。此外。建立了有限元模型,验证了该方法用于损伤检测的可行性。宏观尺度的损伤类型是通过材料性能的变化来模拟的,而分层等早期损伤是通过设置层状剥离区域之间的接触界面条件来模拟的。相应的,基于啁啾的阻抗谱通过共振峰的偏差来检测宏观尺度的损伤,而利用高次谐波和波调制等非线性特征来监测分层。建立了两个损伤指标来量化宏观损伤和早期损伤的严重程度。最后对全文进行了总结,并对今后的工作提出了建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Nonlinear Electro-Mechanical Impedance Spectroscopy for Comprehensive Monitoring of Carbon Fiber Reinforced Composite Laminates
This paper presents a Nonlinear Electromechanical Impedance Spectroscopy (NEMIS) methodology for the comprehensive monitoring of carbon fiber reinforced composite (CFRC) laminates. This method can obtain structural impedance spectra and capture nonlinear ultrasonic features for damage detection, combining the merits of the conventional EMIS and the nonlinear ultrasonic techniques. A comparative illustration between the conventional EMIS and NEMIS is presented. Various damage types and damage mechanisms of CFRC laminates are reviewed. Numerical investigation on a reduced-order 1-D Contact Acoustic Nonlinearity (CAN) model are conducted to demonstrate the chirp-induced nonlinear features. Furthermore. a finite element (FE) model is established to verify the feasibility of the NEMIS for damage detection. The macro-scale damage types are modeled by the changes of material properties, while the incipient damage like delamination is simulated by setting the contact interfacing condition between the laminate debonding areas. Correspondingly, the chirp-based impedance spectra are employed to detect the macro-scale damage via the deviation of resonance peaks, while the nonlinear features, such as higher harmonics and wave modulation are utilized to monitor the delamination. Two damage indices are developed to quantify the severity of both the macro and incipient damage. This paper finishes with conclusion and suggestions for future work.
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