An Integrated Framework for Diagnosis and Prognosis of Hybrid Systems

TL;DR

This paper introduces an integrated theoretical framework for diagnosing and predicting faults in hybrid systems, combining continuous and discrete behaviors to improve maintenance strategies.

Contribution

It presents a novel formalism that tracks fault evolution and a methodology for integrating diagnosis and prognosis in hybrid systems.

Findings

Enhanced fault detection capabilities for hybrid systems.

Ability to follow fault aging over time.

Improved maintenance decision support.

Abstract

Complex systems are naturally hybrid: their dynamic behavior is both continuous and discrete. For these systems, maintenance and repair are an increasing part of the total cost of final product. Efficient diagnosis and prognosis techniques have to be adopted to detect, isolate and anticipate faults. This paper presents an original integrated theoretical framework for diagnosis and prognosis of hybrid systems. The formalism used for hybrid diagnosis is enriched in order to be able to follow the evolution of an aging law for each fault of the system. The paper presents a methodology for interleaving diagnosis and prognosis in a hybrid framework.