We provide an overview 1 , 2 of the DAME project, and a discussion of the progress made to date on the development of a distributed aeroengine diagnosis environment as a proof of concept demonstration for grid computing. We discuss the development of a demonstration diagnosis workbench system for this complex, data intensive, diagnosis application that must be operated as a distributed 'virtual organisation'. We describe the core diagnosis applications that have been implemented as grid services, and explain how these services are being deployed within the overall diagnosis process.
SUMMARYFor industrial fault diagnostics, many model-based fault diagnosis approaches have been proposed so far and some of them have been put into practice. However, for modern complex processes, owing to the variable nature of faults and model uncertainty, no single method can diagnose all faults and meet different contradictory criteria. In this paper, the importance of integration of different fault detection and isolation schemes in a generic problem-solving environment is emphasized. A service-oriented architecture for the integration is proposed, based on Grid technologies. As an engineering implementation, a decision support system for the gas turbine engine fault diagnosis is presented and some deployed services are discussed.
The cross-disciplinary work in this paper presents the key challenges faced in ongoing efforts to develop novel, fully-scalable, fault-tolerant wireless sensing systems for use in complex and demanding engineering environments where the primary objectives are to optimise performance, enhance equipment health management capability and reduce maintenance costs. Challenging issues need to be addressed in the aspects of performance, fault-tolerance, energy efficiency, survivability in harsh environments and propagation inside/around metal structures. Case studies are presented for the Aerospace and Marine domains that exemplify two very different design objectives that place different demands on embedded wireless solutions. In a novel aerospace application, Active Skin-Friction Reduction systems, implemented using hundreds to thousands of embedded wireless 'Smart Patches' to form a 'Smart Skin' system, could provide a crucial step change in fuel efficiency and carbon reduction by reducing aerodynamic drag through active modulation and suppression of turbulent airflow. The marine case study examines the potential for embedded wireless technologies to enhance existing marine control and automation systems onboard marine vessels. The advantage offered by wireless sensors over their conventional wired counterparts has significant potential to enhance diagnostic and prognostic capability in both new equipment designs as well as to provide a cost-efficient retrofit solution for legacy systems, therefore creating unique opportunities to improve performance, increase reliability, optimise maintenance schedules and reduce costly down-time.
Model-based methods are commonly used for fault diagnosis. Many model-based fault diagnosis approaches have been proposed so far. But for modern complex processes, due to the variable nature of faults and model uncertainty, no single approach can diagnose all faults and meet different contradictory criteria. In this paper, the importance of integration of different fault diagnosis schemes in a common framework is emphasised. A service-oriented architecture for the integration is proposed based on Grid technologies. The preliminary implementation of this integration for the gas turbine engine fault diagnosis is discussed.
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