An algorithm to separate wind tunnel background noise from turbulent boundary layer excitation

IMR OpenIR

	An algorithm to separate wind tunnel background noise from turbulent boundary layer excitation
其他题名	An algorithm to separate wind tunnel background noise from turbulent boundary layer excitation
	Zhao Xiaojian 1; Yang Mingsui 2; Zhou Jie 3; Lei Juanmian 1
	2019
发表期刊	Chinese Journal of Aeronautics
ISSN	1000-9361
卷号	32 期号:9 页码:2059-2067
摘要	Wall 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
其他摘要	Wall 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.
关键词	Motor vehicles. Aeronautics. Astronautics TL1-4050
收录类别	CSCD
语种	英语
CSCD记录号	CSCD:6591809
引用统计
文献类型	期刊论文
条目标识符	http://ir.imr.ac.cn/handle/321006/146872
专题	中国科学院金属研究所
作者单位	1.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
推荐引用方式 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.