The codes implementation of the paper A Fault Diagnosis Method of Rotor System Based on Parallel Convolutional Neural Network Architecture with Attention Mechanism
** We present a novel rotor system fault diagnosis model based on parallel convolutional neural network architecture with attention mechanism (AMPCNN). The model uses convolution kernels of different sizes in parallel channels to process raw data, and based on late feature fusion, a more comprehensive feature map is obtained. Furthermore, the information sharing between the two channels is realized through the attention mechanism so that the effective features of one channel can be reflected in another channel.
Zhao, Z., Jiao, Y. & Zhang, X. A Fault Diagnosis Method of Rotor System Based on Parallel Convolutional Neural Network Architecture with Attention Mechanism. J Sign Process Syst (2023). https://doi.org/10.1007/s11265-023-01846-y