ABIGX: A Unified Framework for Explainable Fault Detection and Classification

ABIGX is a framework that makes fault detection and classification (the process of identifying when a system is broken and what type of problem it is) more explainable by showing which parts of the input data matter most. The framework uses a technique called Adversarial Fault Reconstruction (AFR, which treats fault diagnosis like an adversarial attack problem to better identify what causes failures) and proves it can improve on older explanation methods, particularly by fixing a problem called fault class smearing where explanations become unclear when multiple failure types are present.