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Real-time damage analysis of 2D C/SiC composite based on spectral characters of acoustic emission signals using pattern recognition

基于声发射信号频谱特征的2D C/SiC复合材料损伤模式实时分析

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Abstract

In this study, unsupervised and supervised pattern recognition were implemented in combination to achieve real-time health monitoring. Unsupervised recognition (k-means++) was used to label the spectral characteristics of acoustic emission (AE) signals after completing the tensile tests at ambient temperature. Using in-plane tensile at 800 and 1000°C as implementing examples, supervised recognition (K-nearest neighbor (KNN)) was used to identify damage mode in real time. According to the damage identification results, four main tensile damage modes of 2D C/SiC composites were identified: matrix cracking (122.6–201 kHz), interfacial debonding (201–294.4 kHz), interfacial sliding (20.6–122.6 kHz) and fiber breaking (294.4–1000 kHz). Additionally, the damage evolution mechanisms for the 2D C/SiC composites were analyzed based on the characteristics of AE energy accumulation curve during the in-plane tensile loading at ambient and elevated temperature with oxidation. Meanwhile, the energy of various damage modes was accurately calculated by harmonic wavelet packet and the damage degree of modes could be analyzed. The identification results show that compared with previous studies, using the AE analysis method, the method has higher sensitivity and accuracy.

摘要

本研究将无监督模式识别与有监督模式识别相结合, 实现对材料健康状况的实时监测. 常温下完成拉伸试验后, 采用无监督识别(k-mean++)标记声发射(AE)信号的频谱特征. 以800和1000°C面内拉伸为实施例, 采用有监督识别(K近邻(KNN))对损伤模式进行实时识别. 根据损伤识别结果, 确定了二维C/SiC复合材料的4种主要拉伸损伤模式: 基体开裂(122.6~201 kHz)、界面脱粘(201~294.4 kHz)、界面滑移(20.6~122.6 kHz)和纤维断裂(294.4~1000 kHz). 根据二维C/SiC复合材料在常温和高温拉伸过程中的声发射能量积累曲线特征, 分析其损伤演化机制. 同时, 利用谐波小波包精确计算了各损伤模式的损伤能量和损伤程度. 识别结果表明, 与以往研究相比, 采用本声发射分析方法, 具有更高的损伤识别灵敏度和准确性.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant No. 12172304) and the 111 Project (Grant No. BP0719007). We would like to thank the Analytical & Testing Center of Northwestern Polytechnical University for the help of microscopic morphology observation using scanning electron microscopy.

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Authors and Affiliations

  1. School of Aeronautics, Northwestern Polytechnical University, Xi’an, 710072, China

    Xianglong Zeng  (曾翔龙), Bo Wang  (王波), Qiong Deng  (邓琼) & Tao Suo  (索涛)

  2. AECC Sichuan Gas Turbine Research Establishment, Chengdu, 610500, China

    Hongyan Shao  (邵红艳) & Rong Pan  (潘容)

  3. School of Materials Science and Engineering, Northwestern Polytechnical University, Xi’an, 710072, China

    Chengyu Zhang  (张程煜)

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  1. Xianglong Zeng  (曾翔龙)
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  2. Hongyan Shao  (邵红艳)
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  3. Rong Pan  (潘容)
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  4. Bo Wang  (王波)
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Contributions

Xianglong Zeng set up the experiment, processed the experiment data and wrote the first draft of the manuscript. Hongyan Shao and Rong Pan managed and coordinated responsibility for the research activity planning and execution. Bo Wang designed the research and acquired the financial support for the project leading to this publication. Tao Suo helped organize the manuscript. Qiong Deng and Chengyu Zhang revised and edited the final version.

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Correspondence to Bo Wang  (王波).

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Zeng, X., Shao, H., Pan, R. et al. Real-time damage analysis of 2D C/SiC composite based on spectral characters of acoustic emission signals using pattern recognition. Acta Mech. Sin. 38, 422177 (2022). https://doi.org/10.1007/s10409-022-22177-x

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