Cycle Model Development for Gas Turbine Fault Diagnostics
A client sought to improve their ability to detect and diagnose equipment faults in their gas turbine fleet before they led to costly unplanned outages. Traditional monitoring approaches were reactive, often identifying problems only after performance had already degraded significantly. The client needed a more proactive solution that could recognize the early signatures of common fault conditions.
Turbine Logic was engaged to develop analytical cycle deck models capable of simulating various fault conditions and their effects on measurable operating parameters. The work involved creating a calibrated reference model, validating it against real-world performance data, and then systematically simulating how different types of degradation and faults would manifest in the data streams available to operators and monitoring systems.
The project delivered a library of fault signatures that could be integrated into the client's diagnostic and trending tools. These signatures enable pattern recognition approaches to identify developing problems based on subtle changes in operating parameters, supporting earlier intervention and more informed maintenance decisions.
Turbine Logic brings deep expertise in thermodynamic cycle modeling, performance analysis, and the translation of engineering knowledge into practical diagnostic tools. If your organization is looking to enhance equipment monitoring capabilities or develop physics-based models to support predictive maintenance initiatives, we would welcome the opportunity to discuss how we can help.
