Research on simulation of gas turbine component degradation mechanism based on nonlinear exponential law and onboard adaptive modelling

Abstract

To address the issue of decreased modeling accuracy caused by the performance degradation of gas turbine components, this paper focuses on the study of degradation mechanism simulation and identification based on nonlinear exponential laws, on the basis of a linear parameter-varying model constructed from the linearization of multiple steady-state points. By introducing component characteristic degradation factors, an independently developed performance degradation simulation program following the nonlinear exponential evolution law was established, successfully reproducing the real physical degradation mechanism of gas turbine components, which exhibit rapid initial decay followed by stabilization in the later stage. On this basis, the augmented Kalman filter algorithm was used for online identification and adaptive correction of the degradation trajectory. Simulation results show that the program can simulate the actual operating state of the unit with high fidelity, and under specific nonlinear degradation disturbances, it can still maintain the speed error within a very low range, providing a reliable digital experimental platform for gas turbine performance prediction and condition-based maintenance.