Spectrum-envelope attention-driven adaptive time-frequency enhancement network and its application in trustworthy cross-machine fault diagnosis

Key Points

• The model achieves improved diagnosis accuracy, significantly elevating reliability across various machine types.
• Key metrics indicate over 90% accuracy in identifying faults for tested systems, enhancing fault detection capabilities.
• Analysis harnesses an innovative adaptive network combined with attention-driven techniques for effective results.
• This study suggests promising advancements in machine diagnostics, with potential for large-scale applications.