Combining design and operational knowledge to enhance generator plant diagnostics

Abstract

An approach to the construction of an intelligent system for performing generator plant diagnosis in which a model of diagnostic expertise is constructed prior to actual system development is considered. The use of the expertise of both plant designers and operators has allowed an enhanced model of generator plant diagnostics to be constructed which can identify a fault from a set of observed symptoms in addition to predicting the likely operational impact of the identified fault. This will assist the operator in making better decisions when under severe time pressure. Furthermore, it will allow the operator to assess an appropriate course of remedial actions. The paper discusses the features of design and operational knowledge and how these can be used to derive enhanced diagnostics. A methodology for creating the model of diagnostic expertise is then described. Once the model has been constructed an intelligent system can be developed. An architecture for such an intelligent system is discussed in the paper. An advantage of the modelling approach is that it allows flexibility in the actual implementation. The use of a number of potential intelligent system technologies for implementing the system is discussed. A hybrid power station implementation is described which utilises many intelligent system technologies to further extend the decision support available to operators.