Deep learning-based corrosion-like defect localization technique for high-voltage cable aluminum sheaths using guided waves

Abstract

As an important part of the power system, high voltage cable accessories need to ensure the reliability of the electrical connection. However, its aluminum sheath is prone to corrosion with complex working conditions, which has a bad effect on the normal operation of the electric system. Ultrasonic guided wave detection is a promising non-destructive testing method suited to detecting corrosion of aluminum sheaths in complex structures of high-voltage cable accessories. However, current ultrasonic guided wave detection methods still require manual extraction of the signal features and have a high reliance on professional knowledge. This paper proposes a deep learning-based corrosion-like defect localization technique for high-voltage cable aluminum sheath using guided wave. Firstly, the original ultrasonic guided wave signals of corrosion defects at different locations are obtained using ultrasonic guided wave detection platform. Then, the original signals are input into the variable auto-encoder (VAE) network to obtain a low-dimensional representation for automatic feature extraction. Finally, the low-dimensional representation is input into a gate recurrent unit (GRU) based recurrent network for corrosion defects localization. In the feature extraction stage, the VAE can automatically extract the effective features and avoid the interference of noisy signals. In the defect localization stage, GRU method can accurately identify the location of corrosion defects. The maximum error of the training median is 0.072 m, and the maximum error of the test median is 0.0021 m. The experimental results indicate that the VAE-GRU method is capable to accurately identify corrosion defects based on the original signals.

Data-powered NDE for smart structure manufacturing and maintenance

“…The paper by Zhang et al [8] introduces a deep learning-based defect localization technique for corrode-like defects in high-voltage cable aluminum sheathing. This technology is a corrosion defect localization technology based on deep learning, which is used for guided wave inspection of high-voltage cable aluminum sheath.…”