Jia-Dong Meng

A lightweight convolutional neural network method for bearing fault diagnosis based on dynamic weighting and variable-scale feature extraction

Experiments show that the proposed adaptive variable-scale lightweight convolutional neural network (AVS-LCNN) achieves a diagnostic accuracy rate of over 99% with only 0.17 M parameters, demonstrating a favorable balance among computational accuracy, robustness and inference efficiency.