Hierarchical multiscale attention entropy-based fault identification for SDP images and ResNet of water diversion pumping station

Key Points

• Fault identification via hierarchical multiscale attention entropy significantly enhances detection accuracy.
• The analysis utilized SDP images alongside ResNet architecture to improve fault recognition performance.
• By applying advanced algorithms, the method effectively processes complex data from water diversion pumping stations.
• The findings support the need for innovative monitoring techniques to ensure operational reliability in critical water management systems.