A Lightweight and Small Sample Bearing Fault Diagnosis Algorithm Based on Probabilistic Decoupling Knowledge Distillation and Meta-Learning.

This process enables model lightweighting, reduces computational costs, and improves inference speed, making it highly significant in resource-constrained scenarios.

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