首页> 外文期刊>Journal of Reinforced Plastics and Composites >Discrete-wavelet Analysis of Acoustic Emissions During Fatigue Loading of Carbon Fiber Reinforced Composites
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Discrete-wavelet Analysis of Acoustic Emissions During Fatigue Loading of Carbon Fiber Reinforced Composites

机译:碳纤维增强复合材料疲劳载荷过程中声发射的离散小波分析

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摘要

Wavelet transfonn decomposition was used to gather time-frequency-based infonnation from acoustic emission signals generated during fatigue loading of unidirec- tional Carbon Fiber Reinforced Composite (FRC). The acoustic emissions were detected us- ing a resonant sensor and were digitized for analysis. The sensor response was de-convolved from the acquired signal using a point-by-point divisional spectral method. The analysis of the collected signals revealed that friction-related emissions due to the fretting of fractured surfaces are of very high frequency and can mask emissions due to actual damage. Through utilization of wavelet transfonns, it became possible to present the spectral com- position of a transient signal (AK signal) in a time-frequency map which is not easily achieved through conventional spectral analysis techniques. It was detennined that most of the acoustic energy (95% ) was localized in levels corresponding to central frequencies of 120, 250, and 310 kHz. Results indicate friction-related emissions are associated with levels 8 and 9 and have a frequency range of250-300kHz. There are indications that matrix related emissions are of high frequency and high acoustic energy. The results indicate that wavelet analysis would be an effective tool in the analysis of AE by providing infonnation relative to the frequency of the emissions.
机译:小波transfonn分解用于从单向碳纤维增强复合材料(FRC)的疲劳载荷过程中产生的声发射信号中收集基于时频的信息。使用谐振传感器检测声发射,并将其数字化以进行分析。使用逐点分割频谱方法将传感器响应从采集的信号中解卷积。对收集到的信号的分析表明,由于破裂表面的微动引起的与摩擦有关的排放具有很高的频率,并且可以掩盖由于实际损坏而产生的排放。通过利用小波变换,可以在时频图中显示瞬态信号(AK信号)的频谱组成,而这是常规频谱分析技术难以实现的。可以确定的是,大多数声能(95%)局限在与120、250和310 kHz中心频率相对应的水平上。结果表明,与摩擦有关的排放与级别8和9有关,并且频率范​​围为250-300kHz。有迹象表明,与基质有关的发射具有高频和高声能。结果表明,小波分析通过提供与排放频率有关的信息,将成为AE分析中的有效工具。

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