TY - JOUR
T1 - Real-time damage analysis of 2D C/SiC composite based on spectral characters of acoustic emission signals using pattern recognition
AU - Zeng, Xianglong
AU - Shao, Hongyan
AU - Pan, Rong
AU - Wang, Bo
AU - Deng, Qiong
AU - Zhang, Chengyu
AU - Suo, Tao
N1 - Publisher Copyright:
© 2022, The Chinese Society of Theoretical and Applied Mechanics and Springer-Verlag GmbH Germany, part of Springer Nature.
PY - 2022/10
Y1 - 2022/10
N2 - 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. [Figure not available: see fulltext.].
AB - 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. [Figure not available: see fulltext.].
KW - 2D C/SiC composites
KW - Acoustic emission
KW - Pattern recognition
KW - Real-time health monitoring
UR - http://www.scopus.com/inward/record.url?scp=85136716381&partnerID=8YFLogxK
U2 - 10.1007/s10409-022-22177-x
DO - 10.1007/s10409-022-22177-x
M3 - 文章
AN - SCOPUS:85136716381
SN - 0567-7718
VL - 38
JO - Acta Mechanica Sinica/Lixue Xuebao
JF - Acta Mechanica Sinica/Lixue Xuebao
IS - 10
M1 - 422177
ER -