The Rotating Components Performance Diagnosis of Gas Turbine Based on the Hybrid Filter

Processes

Shaojiang Dong¹  Li Zeng²  Wei Long² 

[1] Vehicle Engineering, Chongqing Jiaotong University, Chongqing 400074, China;;School of Mechatronics &

关键词: unscented kalman filter;    particle filter;    weight optimization;    hybrid filter;    gas turbine;   

DOI  :  10.3390/pr7110819

来源: DOAJ

【 摘 要 】

Gas turbine converts chemical energy into mechanical energy and provide energy for aircraft, ships, etc. The performance diagnosis of rotating components of gas turbine are essential in terms of the high failure rate of these parts. A problem that the sudden changing of operation state of turbines may lead to the misdiagnosis due to the defect of gas turbine’s model. This paper constructs the strong tracking filter based on the unscented Kalman filter to achieve accurate estimation of gas turbine’s measured parameters when the state changes suddenly. In the strong tracking filter, a parameter optimization method based on the residual similarity of measured parameters is proposed. Next, adopt the measured parameters filtered by the strong tracking filter to construct the health parameters estimation algorithm based on the particle filter. The particle weight is optimized by the mean adjustment method. Performance diagnosis is realized by checking the changes of health parameters output by particle filter. The results show that the proposed method improves the accuracy of performance diagnosis obviously.

【 授权许可】

Unknown