Open access
Aug 2026
Fault Signature Maps: A Signal-Level Explainable Artificial Intelligence Framework for Bearing Fault Diagnosis
This study establishes that fault discrimination relies on transient impulse morphology rather than bearing characteristic frequencies, a finding invisible to feature-level XAI, and introduces a multi-resolution diagnostic framework bridging deep learning accuracy with physically interpretable vibration analysis for trustworthy deployment in safety-critical industrial environments.
T. Suharto, Kadarsah Suryadi, B. Iskandar et al.
· Emerging Science Journal · 0 citations