International Journal of New Developments in Engineering and Society, 2023, 7(7); doi: 10.25236/IJNDES.2023.070702.
Xing Zhao1, Yonghui Xia2
1Hohhot Vocational College, Hohhot, 010051, China
2Hohhot Communication Section of China Railway Hohhot Bureau Group Corporation, Hohhot, 010020, China
In recent years, deep learning has made significant advancements in fields such as image recognition, object detection, and fault diagnosis, serving as a powerful machine learning technique. This paper aims to address the problem of detecting cable clamp faults in railway tunnels using deep learning methods. By constructing a deep learning network model and training it on a large-scale dataset, we can automatically learn and extract the features of cable clamp faults in tunnels, achieving accurate detection.
railway tunnel; cable clamp; fault detection; deep learning
Xing Zhao, Yonghui Xia. Research on Deep Learning-Based Detection of Cable Clamp Faults in Railway Tunnels. International Journal of New Developments in Engineering and Society (2023) Vol.7, Issue 7: 9-14. https://doi.org/10.25236/IJNDES.2023.070702.
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