Research on classification and recognition of CFRP cylinder fiber layer fracture based on Wigner-Ville distribution images and HRNet

Fiber layer fracture in CFRP (Carbon Fiber Reinforced Polymer) cylinders is one of the most common damages during the usage of these cylinders. Once this damage occurs during the cylinder's load operation, it can develop and eventually lead to extremely serious consequences. Currently, there is very little research on the classification of the degree of fiber layer fracture. In this paper, we utilize acoustic emission response signals under artificially simulated scenarios of different degrees of fiber fracture, perform Wigner-Ville analysis to obtain feature images, and use an improved HRNet for damage degree recognition. The improved HRNet method introduces ASPP (Atrous Spatial Pyramid Pooling) into the classification network, which effectively resists environmental noise, and provides a stable and sensitive response to fiber fracture. In the experiments, it effectively recognizes three different degrees of fiber fracture damage.

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Publication Details

Published
2024-10-24
DOI
https://doi.org/10.1117/12.3050550
Primary Topic
Gait Recognition and Analysis
Type
article
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Research on classification and recognition of CFRP cylinder fiber layer fracture based on Wigner-Ville distribution images and HRNet

Dingding Fan, Shutao Xiong, Song Huang, Fei Wang et al.
Gait Recognition and Analysis
article

Research on classification and recognition of CFRP cylinder fiber layer fracture based on Wigner-Ville distribution images and HRNet

Dingding Fan, Shutao Xiong, Song Huang, Fei Wang, Longyi Zhang
article en

Abstract

Fiber layer fracture in CFRP (Carbon Fiber Reinforced Polymer) cylinders is one of the most common damages during the usage of these cylinders. Once this damage occurs during the cylinder's load operation, it can develop and eventually lead to extremely serious consequences. Currently, there is very little research on the classification of the degree of fiber layer fracture. In this paper, we utilize acoustic emission response signals under artificially simulated scenarios of different degrees of fiber fracture, perform Wigner-Ville analysis to obtain feature images, and use an improved HRNet for damage degree recognition. The improved HRNet method introduces ASPP (Atrous Spatial Pyramid Pooling) into the classification network, which effectively resists environmental noise, and provides a stable and sensitive response to fiber fracture. In the experiments, it effectively recognizes three different degrees of fiber fracture damage.

General Administration of Quality Supervision, Inspection and Quarantine (CN), China Special Equipment Inspection and Research Institute (CN)
Openalex Percentile: Top 83%
Gait Recognition and Analysis
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