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Gas-Turbine Condition Monitoring Using Qualitative Model-Based Diagnosis
May-June 1997 (vol. 12 no. 3)
pp. 22-31

By integrating several AI technologies-including qualitative model-based reasoning--the Tiger System dramatically improves condition monitoring for gas-turbine engines.

Gas turbines are critical to the operation of most industrial plants, and their associated maintenance costs can be extremely high. To reduce those costs and increase the availability of their gas turbines, plant operators for many years have relied on routine preventative maintenance--routinely checking and solving small problems before they grow into major ones. Recently, however, the power industry has moved sharply toward condition-based maintenance and monitoring. In this approach, intelligent computerized systems monitor gas turbines to establish maintenance needs based on the turbine's condition rather than on a fixed number of operating hours. As this article shows, the Tiger system we have developed significantly cuts costs and improves performance by using control-system information to perform gas-turbine condition monitoring.

Citation:
Louise Travé-Massuyès, Robert Milne, "Gas-Turbine Condition Monitoring Using Qualitative Model-Based Diagnosis," IEEE Intelligent Systems, vol. 12, no. 3, pp. 22-31, May-June 1997, doi:10.1109/64.590070
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