Turbine Simulation Model Evolution for Performance Degradation
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Solution Overview
Problem
There is a deviation between the operating characteristics of turbine devices predicted by simulation models and their actual performance due to performance degradation over time.
Innovation Solution
A method involving data acquisition, preprocessing, and machine learning to generate an updated performance curve for the simulation model, reflecting the current operating characteristics of the turbine device, by classifying and combining input and output data sets and using a mapping model to replace the previous performance curve.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a simulation model is constructed based on turbine device in actual operation, then the operating characteristics can be predicted, but there is a deviation between the simulation output and actual operating characteristics
Solution Approach 1:
The simulation model is transformed from a static model to a dynamic evolving model that adapts to performance degradation over time. The model dynamically updates its parameters based on actual operating data collected at different lifecycle stages, allowing it to maintain accuracy as the turbine device ages and its characteristics change.
Solution Approach 2:
A feedback mechanism is established where actual operating characteristics are continuously measured and fed back to the simulation model. This feedback loop enables the model to identify deviations between simulation predictions and actual performance, triggering updates to correct these deviations and improve future predictions.
2Adaptability or versatility
If the simulation model uses fixed performance curves, then the model structure remains simple, but it cannot reflect performance degradation at different lifecycle stages
Solution Approach 1:
The model transitions from using fixed static performance curves to dynamic performance curves that evolve with the turbine's lifecycle. The performance curves are no longer fixed but are continuously updated based on actual operating data, enabling the model to adapt to changes in turbine characteristics over time while maintaining a manageable structure through systematic update procedures.
Data Source
AI summary
A method for evolving a simulation model for a turbine device includes: acquiring current operation data of the turbine device with an inlet parameter as a design parameter; pre-checking the simulation model based on the current operation data; preprocessing the current operation data to obtain a combined dataset when a result of the pre-check indicates that the simulation model requires evolution, the combined dataset including input data and output data corresponding to the input data; constructing a mapping model based on the combined dataset and outputting, using the mapping model, an updated performance curve of the turbine device with the inlet parameter as the design parameter; and replacing a previous performance curve of the simulation model with the updated performance curve to evolve the simulation model.