Shengnan Tang

Explainable Artificial Intelligence in Rotating Machinery Fault Diagnosis: A Comprehensive Review and Emerging Trends

Examining explainable artificial intelligence for rotating machinery fault diagnosis classifies existing methods into ante hoc and post hoc approaches according to their integration with model architectures according to physical interpretability, applicable fault scenarios, explanation quality, computational overhead, robustness, and edge-deployment potential are critically compared.