Gas turbine adaptive gas circuit component performance diagnostic method based on combination of thermal model and particle swarm optimization

Abstract

The invention aims at providing a gas turbine adaptive gas circuit component performance diagnostic method based on the combination of a thermal model and particle swarm optimization. The method comprises the steps that the gas turbine nonlinear thermal model is established, gas circuit health indexes of a gas compressor and a turbine are redefined with similarity reduced parameters, gar circuit measurement parameters in a certain time frame in the stable running process of a current object gas turbine are collected and subjected to noise reduction processing and then serve as measurement parameters of a gas circuit to be subjected to offline diagnosis, and gas circuit health indexes of current components are obtained through iteration optimizing calculation of the particle swarm optimization and used for evaluating the practical performance health condition of the object gas turbine. By means of the method, the problem that the diagnostic precision of a traditional gas turbine gas circuit component performance diagnostic method is likely to be affected by changes of environment conditions and operation conditions is solved, the local optimization feature of the traditional diagnostic algorithm is changed, the accuracy of a diagnostic result is improved, the diagnostic process is simplified, and the method can be effectively applied to performance diagnostic situations with measurement noise and for complex gas turbine units.

Description

technical field [0001] The invention relates to a diagnostic method, in particular to a gas turbine performance diagnostic method. Background technique [0002] In the second half of the 20th century, with the widespread application of gas turbines in the aviation industry, more and more attention has been paid to the field of industrial power stations, oil and gas pipeline transportation, and the shipbuilding industry. During operation, due to the harsh working conditions of high temperature, high pressure, high speed and high stress, and environmental pollution, the performance of various types of gas turbines will gradually decline. The main gas circuit components of a gas turbine include a compressor, a combustor and a turbine. These major components are subject to different degradation phenomena over time, such as dirt, leakage, corrosion, thermal distortion, foreign object damage, etc., which will cause performance deterioration and easily lead to various serious fail...

AI Technical Summary

Problems solved by technology

When the number of components participating in the diagnosis in the gas turbine increases, the dimension of the failure coefficient matrix will increase accordingly, coupled with the interference of measurement noise, the blurring effect (that is, although some components do not actually degrade in performance, the diagnosed The performance degradation is almost distributed on all components on the gas path health index) may be very strong, causing the actual performance degradation of the components not to be identified

Images