可以列举两篇将一维数据转换为二维图像进行输入的CNN故障诊断文献
时间: 2024-06-02 09:07:14 浏览: 12
Sure, I can provide you with two research papers that convert one-dimensional data into two-dimensional images for CNN-based fault diagnosis. However, please note that my knowledge may be limited and these papers may not be the only ones that exist in this area.
1. "Deep Residual Networks for Fault Diagnosis Using Spectral Analysis and Image Processing on Raw Vibration Signals" by Zebin Yang, Lei Wan, and Weidong Chen. This paper proposes a method that uses a combination of fast Fourier transform (FFT) and image processing techniques to convert vibration signals into 2D images, which are then fed into a deep residual network for fault diagnosis.
2. "Convolutional Neural Networks for Fault Diagnosis Using Image Processing" by Shu Wang, Jie Li, and Xiaolin Wang. In this paper, the authors use wavelet transform and image processing to convert vibration signals and acoustic signals into 2D grayscale images. These images are then used to train a deep CNN for fault diagnosis.
I hope this helps! Let me know if you have any other questions.
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