Research On Gas Path Fault Diagnosis Of Gas Turbine Based On Kalman Filter

As gas turbines mature in technology,their use in various industries has also become more extensives gas turbines mature in technology,their use in various industries has also become more extensive,including aerospace,ships,energy and other cutting-edge technologies.The industry of equipment requirements is very high,gas turbine is very prone to failure,the complexity and its structure and working environment of harsh,one of the most possible gas turbine gas path problem is particularly prominent,once produced abnormal gas path will cause great influence to the whole machine.Therefore,many scholars have listed the gas circuit failure issue as the research focus of gas turbines.The timely and effective gas path fault estimation is the base of stable work.The timely and effective evaluation of gas line failures is the basis for the stable operation of equipment.On the one hand,it can ensure the safety of industrial working processes,while at the same time it can increase economic efficiency.Theoretical significance and engineering application value.This paper studies the application of kalman filter in gas turbine gas path fault diagnosis technology.The specific research contents are as follows:Firstly,this paper elaborates the main failure modes of gas turbine road faults,and analyzes the fault characteristics of gas turbine on this basis.The linear state space model of three shaft gas turbine is established and normalized.In order to characterize the degree of degeneration of the performance of gas circuit components,this paper select 10 health parameters description of health condition of all parts,describes the component damaged degree of introducing the state space,flow rate and efficiency for three shaft gas turbine of health parameters linear model of the gas path fault.This paper combines the linear model with kalman filter(KF)technique to build a discretized nonlinear model suitable for extended kalman filter(EKF).Secondly,the paper introduces the basic principle of kalman filter.According to the characteristics of the linear gas path fault model of three shaft gas turbine.The internal components of the gas turbine are damaged by using the parameter synchronization analysis function of KF.In the case,the health parameter estimation steps of the air path components are listed,and the gradual changes and the catastrophic components are respectively diagnosed.The simulation shows that the KF estimation result is more accurate and the estimation is reasonable,but there is a certain error.Therefore,based on the nonlinear model of gas turbine discretization,the paper deduced the extended kalman filter algorithm,and diagnosed faults of gradient and fast-varying faults respectively.The efficiency and flow rate estimation of six parameters of the gas turbine showed that the changes.The smaller range of parameters has a better tracking effect.Finally,the paper studies Unscented Kalman Filtering(UKF)algorithm.Using kalman linear filtering framework,using UT transformation to process mean value and covariance in one-step prediction equation,realizes nonlinear data application,and solves the problem of excessively dependent linear model.The symmetric sampling kalman filter algorithm is presented in this paper.Fault detection is performed on the gradual component and the abrupt component respectively.The health parameter estimation results of the gas turbine component indicate that the unscented kalman filter can effectively detect the fault.And it works well.