Abstract
Maintenance efficiency of complex industrial systems is an important economical and business issue. Main difficulties come from the choice of maintenance actions. A wrong choice can lead to maintenance costs that are not acceptable. In this paper, we propose a generic health monitoring system that integrates some diagnostic and prognostic capabilities to determine the current and future state of a large and complex system such as an aircraft. The diagnostic function aims at identifying faulty components that may cause global system failures. The prognostic function estimates the remaining time until the next global system failure. A formal and generic modeling framework for a complex system encapsulating the knowledge required to get the consistent coordination of the diagnostic and prognostic functions is presented. We propose in this framework to take into account component redundancies which is common in systems like aircrafts. Moreover, an original coupling of diagnosis and prognosis is established based on the characterization of the system operational modes and on a decentralized architecture of the monitoring system.
Highlights
Maintenance efficiency of industrial systems, like aircrafts or cars, is an economical and business issue
The characterization is modular, it introduces a decentralized architecture for diagnosis and prognosis that is consistent
We introduce the notion of mode trajectory which is an abstraction of the underlying evolution of the system that is sufficient for the maintenance decision
Summary
Maintenance efficiency of industrial systems, like aircrafts or cars, is an economical and business issue. INTERNATIONAL JOURNAL OF PROGNOSTICS AND HEALTH MANAGEMENT tion of a generic on-line health monitoring system (HMS for short) for the maintenance of complex system like an aircraft that embeds diagnosis and prognosis capabilities. This contribution relies on a detailed analysis of a real industrial HMS that is developed by our aeronautical partner AIRBUS. Our characterization is formal and modular and defines the requirements that local diagnosis/prognosis methods should implement to guarantee the global health monitoring function This characterization is motivated by a set of challenges and difficulties that any realistic HMS should deal with (see Section 2 for details).
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