使用嵌入式PZT传感器对CFRP螺栓连接结构疲劳失效过程监测研究

Embedded PZT Sensor-Based Fatigue Failure Monitoring in CFRP Bolted Connections

摘要

螺栓连接作为碳纤维增强复合材料(CFRP)结构中常见的连接方式,其疲劳损伤过程复杂、失效突发性强,因此对其进行结构健康监测具有重要意义．针对传统传感方法存在布设复杂、操作不便等问题,本文提出一种基于嵌入式PZT传感器的监测技术,研究了疲劳加载过程中CFRP螺栓连接结构的损伤识别机制．通过断铅试验与频谱响应验证了优化嵌入工艺的有效性,PZT传感器存活率由传统方法的40%提高至80%．基于Hilbert-Huang变换(HHT)对PZT信号进行时频分析,识别出10 Hz频率分量在初始损伤阶段的显著突变特征．对比AE信号与SEM微观损伤形貌,验证了PZT信号与界面脱黏、微裂纹扩展等微损伤机制之间的对应关系．定量分析了加载频率与PZT信号中不同频率分量之间的响应相关性,指出加载频率主导的分量在疲劳过程中的演化趋势最能反映结构内部的损伤演进,其皮尔逊相关系数高达0.82．结果表明：PZT信号在损伤3阶段中均具有良好的识别能力,特别是在早期微裂纹萌生阶段的响应敏感性高,可实现结构状态的实时预警与演化识别．本文研究成果为嵌入式智能传感技术在复合材料结构健康监测中的应用提供了理论依据与工程参考．

Abstract

Bolted connections, a conventional method for joining carbon fiber reinforced polymer(CFRP)composite structures, undergo complex fatigue failure processes, which expose them to intense, unexpected failures. Therefore, monitoring their structural health is greatly significant. To address the challenges of complex deployment and unsuitable operation in traditional sensing methods, a monitoring technology is proposed based on embedded lead zirconate titanate(PZT)sensors after which the damage identification mechanism for CFRP bolted structures during fatigue loading is investigated. Next, the effectiveness of the optimized embedding process is verified via lead breakage experiments and spectral responses, revealing that this process increased the survival rate of the PZT sensor from 40%(obtained by conventional processes)to 80%. Additionally, the time-frequency analysis of the PZT signals based on the Hilbert-Huang transform(HHT) reveals the significant mutation characteristics of the 10 Hz frequency component in the initial damage stage. Subsequently, the correlations between the PZT signal and microdamage mechanisms, such as interface debonding and microcrack extension, are verified by comparing the acoustic emission signal with the scanning electron microscopy microdamage morphology. Furthermore, the response correlation between the loading frequency and different frequency components of the PZT signal is quantitatively analyzed, revealing that the evolution trend of the loading frequency-dominated component during fatigue best reflects the damage evolution within the structure, with a very high Pearson correlation coefficient(0.82). The results indicate that the PZT signal can effectively identify three damage stages with high sensitivity, especially the onset of the microcrack germination stage, which can facilitate real-time early warning of the structural health of CFRP bolt joints. Overall, the results offer a theoretical basis and an engineering reference for applying embedded intelligent sensing technologies to the monitoring of the health of composite structures.

关键词

碳纤维增强复合材料螺栓连接 / 压电陶瓷传感器 / 疲劳失效监测 / 结构健康监测

Key words

carbon fiber reinforced polymer(CFRP) bolted joint / piezoelectric ceramic sensor / fatigue failure monitoring / structural health monitoring

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基金资助

国家自然科学基金资助项目(52375461)

国家自然科学基金资助项目(52075380)

国家自然科学基金资助项目(52275459)

中国博士后科学基金-天津联合资助项目(2023T016T)