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An algorithm to separate wind tunnel background noise from turbulent boundary layer excitation
Alternative TitleAn algorithm to separate wind tunnel background noise from turbulent boundary layer excitation
Zhao Xiaojian1; Yang Mingsui2; Zhou Jie3; Lei Juanmian1
2019
Source PublicationChinese Journal of Aeronautics
ISSN1000-9361
Volume32Issue:9Pages:2059-2067
AbstractWall pressure fluctuations generated by Turbulent Boundary Layers (TBL) provide a significant contribution in reducing the structural vibration and the aircraft cabin noise. However, it is difficult to evaluate these fluctuations accurately through a wind tunnel test because of the pollution caused by the background noise generated by the jet or the valve of the wind tunnel. In this study, a new technology named Subsection Approaching Method (SAM) is proposed to separate the wall pressure fluctuations from the background noise induced by the jet or the valve for a transonic wind tunnel test. The SAM demonstrates good performance on separating the background noise from the total pressure compared to the other method in this study. The investigation considers the effects of the sound intensity and the decay factor on the sound-source separation. The results show that the SAM can derive wall pressure fluctuations effectively even when the level of background noise is considerably higher than the level of the wall pressure fluctuations caused by the TBL. In addition, the computational precision is also analyzed based on the broad band noise tested in the wind tunnel. Two methods to improve the precision of the computation with the SAM are also suggested: decreasing the loop gain and increasing the sensors for the signal analysis. Keywords: Background noise, Sound source separation, Turbulent boundary layer, Wall pressure fluctuation, Wind tunnel
Other AbstractWall pressure fluctuations generated by Turbulent Boundary Layers(TBL) provide a significant contribution in reducing the structural vibration and the aircraft cabin noise. However, it is difficult to evaluate these fluctuations accurately through a wind tunnel test because of the pollution caused by the background noise generated by the jet or the valve of the wind tunnel. In this study, a new technology named Subsection Approaching Method(SAM) is proposed to separate the wall pressure fluctuations from the background noise induced by the jet or the valve for a transonic wind tunnel test. The SAM demonstrates good performance on separating the background noise from the total pressure compared to the other method in this study. The investigation considers the effects of the sound intensity and the decay factor on the sound-source separation. The results show that the SAM can derive wall pressure fluctuations effectively even when the level of background noise is considerably higher than the level of the wall pressure fluctuations caused by the TBL. In addition, the computational precision is also analyzed based on the broad band noise tested in the wind tunnel. Two methods to improve the precision of the computation with the SAM are also suggested: decreasing the loop gain and increasing the sensors for the signal analysis.
KeywordMotor vehicles. Aeronautics. Astronautics TL1-4050
Indexed ByCSCD
Language英语
CSCD IDCSCD:6591809
Citation statistics
Document Type期刊论文
Identifierhttp://ir.imr.ac.cn/handle/321006/146872
Collection中国科学院金属研究所
Affiliation1.Beijing Institute Technol, Sch Aerosp Engn, Beijing 100081, Peoples R China
2.中国科学院金属研究所
3.Hong Kong University Sci & Technol, Dept Mech & Aerosp Engn, Hong Kong, Peoples R China
Recommended Citation
GB/T 7714
Zhao Xiaojian,Yang Mingsui,Zhou Jie,et al. An algorithm to separate wind tunnel background noise from turbulent boundary layer excitation[J]. Chinese Journal of Aeronautics,2019,32(9):2059-2067.
APA Zhao Xiaojian,Yang Mingsui,Zhou Jie,&Lei Juanmian.(2019).An algorithm to separate wind tunnel background noise from turbulent boundary layer excitation.Chinese Journal of Aeronautics,32(9),2059-2067.
MLA Zhao Xiaojian,et al."An algorithm to separate wind tunnel background noise from turbulent boundary layer excitation".Chinese Journal of Aeronautics 32.9(2019):2059-2067.
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