Picture of person typing on laptop with programming code visible on the laptop screen

World class computing and information science research at Strathclyde...

The Strathprints institutional repository is a digital archive of University of Strathclyde's Open Access research outputs. Strathprints provides access to thousands of Open Access research papers by University of Strathclyde researchers, including by researchers from the Department of Computer & Information Sciences involved in mathematically structured programming, similarity and metric search, computer security, software systems, combinatronics and digital health.

The Department also includes the iSchool Research Group, which performs leading research into socio-technical phenomena and topics such as information retrieval and information seeking behaviour.

Explore

Model-based condition monitoring of gas turbines for power generation duty

Booth, C.D. and McDonald, J.R. and Donald, P.H. and Lines, N. and Cooke, N. and Smith, C. (2001) Model-based condition monitoring of gas turbines for power generation duty. IEEE Power Engineering Review, 21 (4). pp. 62-63. ISSN 0272-1724

Full text not available in this repository. Request a copy from the Strathclyde author

Abstract

This letter has presented an overview of activities to date with respect to the development and demonstration of anomaly detection functions, which analyze key parameters from an industrial gas turbine during its starting sequence. The software modules have been shown to be able to successfully detect anomalies in the start sequences. The software has been developed using a combination of simulated and actual plant performance data and is currently in the process of being implemented in the field. In the longer term, as the level of operational experience and knowledge grows, the anomaly detection functions can be augmented to include prognostic and diagnostic functionality. This will permit not only the detection of anomalous behavior but also the provision of information to plant operators as to the suspected cause of the anomaly