A WT-ResNet based fault diagnosis model for the urban rail train transmission system
<|reference_start|>A WT-ResNet based fault diagnosis model for the urban rail train transmission system: This study presents a novel fault diagnosis model for urban rail transit systems based on Wavelet Transform Residual Neural Network (WT-ResNet). The model integrates the advantages of wavelet transform for feature extraction and ResNet for pattern recognition, offering enhanced diagnostic accuracy and robustness. Experimental results demonstrate the effectiveness of the proposed model in identifying faults in urban rail trains, paving the way for improved maintenance strategies and reduced downtime.<|reference_end|>
@article{cheng2024a,
    title={A WT-ResNet based fault diagnosis model for the urban rail train
  transmission system},
    author={Zuyu Cheng and Zhengcai Zhao and Yixiao Wang and Wentao Guo and Yufei
  Wang and Xiang Gao},
    journal={arXiv preprint arXiv:2406.06031},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.06031},
    primaryClass={cs.IR}
}