Estimation and Mitigation of Unknown Airplane Installation Effects on GPA Diagnostics

Machines

Konstantinos Kyprianidis¹  Mikael Stenfelt¹ 

[1] Future Energy Center, Mälardalen University, 72123 Vasteras, Sweden;

关键词: gas turbine diagnostics;    gas path analysis;    installation effects;    neural networks;   

DOI  :  10.3390/machines10010036

来源: DOAJ

【 摘 要 】

In gas turbines used for airplane propulsion, the number of sensors are kept at a minimum for accurate control and safe operation. Additionally, when data are communicated between the airplane main computer and the various subsystems, different systems may have different constraints and requirements regarding what data transmit. Early in the design process, these parameters are relatively easy to change, compared to a mature product. If the gas turbine diagnostic system is not considered early in the design process, it may lead to diagnostic functions having to operate with reduced amount of data. In this paper, a scenario where the diagnostic function cannot obtain airplane installation effects is considered. The installation effects in question is air intake pressure loss (pressure recovery), bleed flow and shaft power extraction. A framework is presented where the unknown installation effects are estimated based on available data through surrogate models, which is incorporated into the diagnostic framework. The method has been evaluated for a low-bypass turbofan with two different sensor suites. It has also been evaluated for two different diagnostic schemes, both determined and underdetermined. Results show that, compared to assuming a best-guess constant-bleed and shaft power, the proposed method reduce the RMS in health parameter estimation from 26% up to 80% for the selected health parameters. At the same time, the proposed method show the same degradation pattern as if the installation effects were known.

【 授权许可】

Unknown