Model-Based Diagnosis for Cyber-Physical Production Systems Based on Machine Learning and Residual-Based Diagnosis Models

摘要: This paper introduces a novel approach to Model-Based Diagnosis (MBD) for hybrid technical systems. Unlike existing approaches which normally rely on qualitative diagnosis models expressed in logic, our applies learned quantitative model that is used derive residuals. Based these residuals generated and root cause identification. The new solution has several advantages such as the easy integration of machine learning algorithms into MBD, seamless models, significant speed-up runtime. at hand formally defines approach, outlines its drawbacks, presents an evaluation with real-world use cases.