Deterioration of gas turbine component condition leads to degradation of performance, efficiency, reliability and safety. Accurate monitoring and advanced analysis of gas turbine performance offers great potential to minimize life cycle costs and maximize performance and availability and thereby revenues. Implementing advanced performance monitoring tools for a fleet of engines can save millions of dollars by improving availability and reliability of the machines.
OPRA Turbines has more than 100 of its OP16 2MW class gas turbines installed worldwide. Using B&B-AGEMA’s GTPtracker software, an online real-time condition monitoring and prognostics system has been developed. A detailed model of the OP16 engine has been used to simulate deterioration and failure effects, generating signatures for condition assessment on component level. The signatures are stored in the GTPtracker monitoring database in the form of rule sets that can be correlated also to condition monitoring information from different disciplines such as vibration and lubrication. Performance data matching a rule set indicates specific component deterioration and failure modes. Rule set matches are automatically detected and translated into maintenance decision support information, thereby helping to minimize life cycle costs.
The concept is used for both diagnostics, detecting and isolating current engine problems, and prognostics for predicting problems by extrapolating trend functions. The system is highly flexible and end user configurable.
The paper gives an overview of the system and methodologies applied with generic examples. For the OPRA OP16 gas turbine, two case studies are presented demonstrating specific component deterioration detection and sensor fault isolation.
Lars-Uno Axelsson, Vrishika Singh, OPRA Turbines
Wilfried Visser, René Braun, B&B-AGEMA