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DFAWnet

Denoising Fault-Aware Wavelet Network: a nueral network constructed under the frame work of signal processing informed neural network (SPINN)

故障感知去噪小波网络: 基于信号处理启发的神经网络框架

code for DFAWnet

  1. parameter setting: main.py
  2. training program:utils/train_utils.py
  3. Spectral kurtosis based Loss: physics_loss/kurtosis.py
  4. Energy-based channel (scale) selection layer (attention weighting layer):paper_model/weighting_layer.py
  5. The whole DFAWnet:paper_model/DFWnet.py
  6. Fused 1/2/3 wavelet convolution:fusion_modules/fuse_conv_wavelet.py
  7. Dynamic hard thresholding mask:dynconv.py

if you are intersted in this work, please cite

@article{shang2023denoising,
  title={Denoising Fault-Aware Wavelet Network: A Signal Processing Informed Neural Network for Fault Diagnosis},
  author={Shang, Zuogang and Zhao, Zhibin and Yan, Ruqiang},
  journal={Chinese Journal of Mechanical Engineering},
  volume={36},
  number={1},
  pages={9},
  year={2023},
  publisher={Springer}
}

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dfawnet's Issues

Missing of dataset

In running the program you have arranged all the datasets in a particular order in a directory.
It will be useful if you upload the actual dataset folder

融合小波基函数的p是如何更新的？

很高心能够看到有这篇好的文章，在融合小波的时候文章中提到用p进行加权小波基，以实现融合小波的作用，按照我的理解，p是随着网络更新而更新的，但我只看到了self.layeri_softmaxP这个权重因子，并没有看到他是如何通过网络进行更新的，期望您能就这个问题帮我解答一下，谢谢您

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