In order to explore the total-pressure distortion test assessment method for a turbofan engine, a Controlled Variable Double-Baffle Distortion Generator(CVDBDG) with a horizontal symmetry moving form was developed, wh...In order to explore the total-pressure distortion test assessment method for a turbofan engine, a Controlled Variable Double-Baffle Distortion Generator(CVDBDG) with a horizontal symmetry moving form was developed, which can adjust the steady-state and time–variant distortion separately in real time. The inlet total-pressure distortion test was conducted on an afterburner turbofan engine. The distortion parameters of CVDBDG and the instability characteristics of the engine were measured. The experimental data were modeled and analyzed by using back propagation artificial neural networks, and the work envelope of CVDBDG was obtained. Based on the analysis of the data on the engine’s instability, the properties of CVDBDG used for the stability assessment were preliminarily evaluated. The results show that CVDBDG can simulate both steady-state and time–variant distortions simultaneously in a range determined by three envelopes.Under the condition of symmetric double baffles, a critical depth of insertion exists, beyond which the symmetric baffles will generate an asymmetric flow field. In the case of double baffles, compared to a single baffle, the engine exhibited different instability characteristics. Based on CVDBDG, it is expected that more efficient engine stability and durability assessment methods can be developed.展开更多
基金supported by the Beijing Aeronautical Technology Research Center
文摘In order to explore the total-pressure distortion test assessment method for a turbofan engine, a Controlled Variable Double-Baffle Distortion Generator(CVDBDG) with a horizontal symmetry moving form was developed, which can adjust the steady-state and time–variant distortion separately in real time. The inlet total-pressure distortion test was conducted on an afterburner turbofan engine. The distortion parameters of CVDBDG and the instability characteristics of the engine were measured. The experimental data were modeled and analyzed by using back propagation artificial neural networks, and the work envelope of CVDBDG was obtained. Based on the analysis of the data on the engine’s instability, the properties of CVDBDG used for the stability assessment were preliminarily evaluated. The results show that CVDBDG can simulate both steady-state and time–variant distortions simultaneously in a range determined by three envelopes.Under the condition of symmetric double baffles, a critical depth of insertion exists, beyond which the symmetric baffles will generate an asymmetric flow field. In the case of double baffles, compared to a single baffle, the engine exhibited different instability characteristics. Based on CVDBDG, it is expected that more efficient engine stability and durability assessment methods can be developed.
