CLEAN-SC算法在风洞声源定位与识别中的应用研究

发布时间：2017-12-31 00:30

本文关键词：CLEAN-SC算法在风洞声源定位与识别中的应用研究　出处：《实验流体力学》2016年03期 　论文类型：期刊论文

【摘要】：为了从麦克风阵列测量中得到更清晰的声成像图,在阵列波束成形数据处理上运用反卷积技术抑制旁瓣越来越普及。传统的反卷积技术假设声源图是由阵列点扩散函数建立起来的,但在航空领域内实际被测声源波束图通常与合成得到的点扩散函数不一样,使得该技术在应用中受到较大限制。本文介绍另一种基于空间声源相干的波束成形反卷积技术,用迭代方法逐步地将声源图中与峰值声源空间相干的部分去掉,从而将旁瓣从实际被测的波束图中移除。基于该技术原理,在波束成形技术基础上发展了用于阵列数据处理的CLEAN-SC算法,应用于风洞声学测量中获得了开/闭口风洞中的起落架和翼型的声源分布特性。实验对比分析表明该阵列数据处理优化技术在空间声源定位和抑制旁瓣能力上比传统波束成形技术都有显著提高。
[Abstract]:In order to get a clearer image sound from the microphone array measurement, the array beam forming data processing using the deconvolution technique of sidelobe suppression are becoming more and more popular. Deconvolution technique is the traditional assumption of sound source graph function established by point spread array, but in the field of aviation in the actual measured sound source and beam pattern synthesis are usually the point spread function is not the same, so the technology is restricted in application. This paper presents a sound source based on coherent beam shaping deconvolution technique, step by step and peak sound source sound source in coherent parts removed by iterative method, which will be removed from the actual measured sidelobe beamforming. The technology is based on the principle of the technology based on the development of beamforming algorithm for CLEAN-SC array data processing and application in wind tunnel acoustic measurements were obtained in the open / closed tunnel The sound source distribution characteristics of landing gear and airfoil are compared. The experimental comparison analysis shows that the array data processing optimization technology has significantly improved the location and suppression sidelobe ability of space source.

【作者单位】：中国空气动力研究与发展中心气动噪声控制重点实验室;
【基金】：气动预研基金(513130401)
【分类号】：V211.74
【正文快照】： 0引言近年来,随着军、民用飞行器等航空运输的快速发展,气动噪声问题日益引起世界范围的关注。对于军用飞行器,降低其噪声水平,有利于改善飞机的声隐身性能,提高其作战生存能力。同时可减少声疲劳对飞行器局部结构的破坏,延长飞行器的寿命以及减少噪声对机组人员的干扰。对于

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