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- Delsing, Jerker, et al.
(författare)
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A service oriented architecture to enable a holistic system approach to large system maintenance information
- 2010
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Ingår i: The Seventh International Conference on Condition Monitoring and Machinery Failure Prevention Technologies. - Northampton : Coxmoor Publishing Co.. - 9781901892338 ; , s. 907-914
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Konferensbidrag (refereegranskat)abstract
- Heavy machinery in today's process industry is equipped with an increasing number of sensors for control and maintenance purposes. Each sensor is engineered and configured for a dedicated purpose; thus, the data or information provided by each sensor is confined to a specific purpose. Changing this individual approach to a holistic approach for control, operation and maintenance allows the data to be used in new ways, such as new control strategies, operation strategies and maintenance management. The holistic approach is demonstrated for a process of continuous energy generation and distribution: district heating. The purpose-based approach is replaced with the holistic approach, which focuses on system optimization and failure detection. The system was first set up in a Simulink simulation model to capture the thermodynamic behavior of the houses attached to the district heating system. In this model, each sensor is seen as a service that can be accessed for different purposes. Model analysis in this case led to new approaches for control and maintenance of critical parts in a district heating system.The new holistic approach is realized as a service-oriented architecture (SOA)-based wireless sensor network. It is currently installed in a small part of a district heating system in Piteå, Sweden. The system utilizes a wireless sensor network with service-oriented architecture using device profile web services (DPWS). Based on the data and information provided by the SOA wireless sensor network, the system can be identified. For the district heating example, the system identification provides system parameters that can be used to improve the thermodynamic Simulink model. Thus, comparisons can be made over time to determine system degradation. Furthermore, possible maintenance actions can be modeled, which allows prediction of system performance improvements related to specific maintenance actions.
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