Affiliation:
1. College of Electronic Information and Automation, Civil Aviation University of China, Tianjin, China
Abstract
Carbon fiber reinforced polymers (CFRPs) have been widely applied in the aerospace industry, and the health conditions of CFRPs largely affect aerospace safety. Due to the limitations of traditional detection methods, electrical impedance tomography (EIT) has been gradually applied in the damage detection of CFRP composite materials. Aiming at the problems of poor imaging quality and low identification rate in the traditional EIT reconstruction algorithm, an EIT algorithm based on the one-dimensional multi-scale residual convolution neural network (1D-MSK-ResNet) is proposed in this paper. A “voltage vector-conductivity media distribution” dataset is first established, and the training results of the testing dataset are used to verify and evaluate the algorithm. Simulation and experimental results indicated that the 1D-MSK-ResNet EIT algorithm could enhance the ability of damage identification and significantly improve the imaging quality.
Funder
National Natural Science Foundation of China
Scientific Research Project of Tianjin Educational Committee
Cited by
7 articles.
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