Xiaoxu Ren

Decision Support System on the Grid

Aero-engines are extremely reliable machines and operational failures are rare. However, currently great effort is being put into reducing the number of in-flight engine shutdowns, aborted take-offs and flight delays through the use of advanced engine health monitoring technology. This represents a benefit to society through reduced delays, reduced anxiety and reduced cost of ownership of aircraft. This is reflected in a change of emphasis within aero-engine companies where, instead of selling engines to customers, there is a fundamental shift to adoption of power-by-the-hour contracts. In these contracts, airlines make fixed regular payments based on the hours flown and the engine manufacturer retains responsibility for maintaining the engine. To support this new approach, improvements in in-flight monitoring of engines are being introduced with the collection of much more detailed data on the operation of the engine. At the same time advances have been made in Internet technologies providing a worldwide network of computers that can be used to access and process that data. The explosion of available knowledge within those large datasets also presents its own problems and here it is necessary to work on advanced decision support systems to identify the useful information in the data and provide knowledge-based advice between individual aircraft, airline repair and overhaul bases, world-wide data warehouses and the engine manufacturer. This paper presents a practical framework in which to build such a system that is inherent in the emerging Grid computing paradigm that provides the necessary computing resources. A demonstrator system already developed and implemented in the UK E-Science Grid project, DAME, is introduced.

Service‐oriented architecture on the Grid for integrated fault diagnostics

For 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. Copyright

An agent-based system for distributed fault diagnosis

A multi-agent system is demonstrated to be a suitable architecture for solving distributed problems. An agent-based system for distributed fault diagnosis is introduced in this paper. Within the multi-agent framework, the dynamic system is monitored by a group of agents and each agent can make its own detection decisions. To coordinate the low-level monitoring results, a high-level inference is then deployed to assess the state of system and isolate the potential fault. The structure of the agent framework is described in this paper and the role of each agent in the framework is summarised. Some intelligent model-based fault diagnosis methods used by the local diagnostic agents are discussed. A hidden Markov model (HMM) approach is proposed to achieve the result sharing for distributed fault diagnosis. Given the monitoring report from different agents, HMM based algorithms can be applied to coordinate the partial diagnostic results from different agents and find the most likely state evolution for fault isolation. Some simulation results are demonstrated and an agent-based software demonstrator on gas turbine engine fault diagnosis is presented for investigating agent implementation issues.

Grid-based decision support with pro-active mobile computing

With the emergence of grid computing and service-oriented architectures, computing is becoming increasingly less confined to traditional computing platforms. Grid computing promises the accessibility of vast computing and data resources across geographically dispersed areas. This capability is significantly enhanced by establishing support for mobile wireless devices to deliver access to high-performance computing under demanding circumstances. Access to the grid from mobile devices can be very effective in business environments where users can access the vast computing power and data repositories on the grid while working out on the field. This also enables and encourages collaborative working environments. A grid demonstrator system for distributed aircraft health monitoring already developed and implemented in the UK E-Science Grid project, DAME, is introduced. In this demonstrator, CBR technology for decision support is implemented in a practical framework that enables Grid-based, proactive mobile computing.

Integrated fault diagnostics on the grid

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.

Multi-Agent Systems for Model-based Fault Diagnosis

Abstract Model-based methods are commonly used for fault diagnosis. But for modern complex processes, the analytical model of the overall process is not usually available. In this paper, a multi-agent framework for distributed fault diagnosis and isolation is proposed. The distributed fault diagnosis and isolation is achieved by a group of cooperative intelligent agents. The structure of the multi-agent framework is described. The learning algorithms employed by agents for building the fuzzy analytical model of the local process is detailed. The implementation of this agent-based approach on aero gas turbine engine fault diagnosis is also discussed.

A service oriented architecture for integration of fault diagnostics

Many model-based fault diagnosis approaches have been proposed so far and some of them have been put into industrial practices. 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 diagnostic schemes in a common framework is emphasised. A service-oriented architecture for the integration is proposed based on Grid technologies. As an implementation, a decision support system for the gas turbine engine fault diagnosis is presented and some deployed services are discussed.