The gas path diagnosis of gas turbines usually uses the thermal model to obtain the offset of the characteristic parameters of the gas path components to describe the gas path performance degradation. Due to the existence of online measurement data errors

the simulation results of the thermal model always have a certain deviation from the measurement results of the actual operation of the unit. This limitation limits the realization of accurate gas path diagnosis. To effectively diagnose the gas path of the gas turbine

this paper proposes a gas path diagnosis method based on data coordination. Constructing an objective function combining the data-coordinated equations with the mean-square error of the simulated and measured values

replacing the original simulated values with the data-coordinated values. The particle swarm optimization algorithm (PSO) is used to obtain the accurate solution of the component characteristic parameter offset. The simulation test of gas path diagnosis is carried out based on the simulated degenerated fault cases. The test results show that the maximum relative deviation of this method is less than 0.96%

which is better than the traditional method of gas path diagnosis without data coordination.