斜下降旋翼桨涡干扰声源定位及表面压力

刘正江; 汪文涛; 林永峰; 曹亚雄

doi:10.7527/S1000-6893.2020.24060

航空学报 >

2020 , Vol. 41 >Issue 12: 124060 - 124060

DOI: https://doi.org/10.7527/S1000-6893.2020.24060

流体力学与飞行力学

斜下降旋翼桨涡干扰声源定位及表面压力

刘正江 ,
汪文涛 ,
林永峰 ,
曹亚雄

展开

中国直升机设计研究所重点实验室, 景德镇 333000

收稿日期: 2020-04-07

修回日期: 2020-04-28

网络出版日期: 2020-06-24

基金资助

航空科学基金（201957002003）

收起

Rotor blade-vortex interaction noise location and surface pressure in skew descending flight

LIU Zhengjiang ,
WANG Wentao ,
LIN Yongfeng ,
CAO Yaxiong

Expand

Key Laboratory, China Helicopter Research and Development Institute, Jingdezhen 333000, China

Received date: 2020-04-07

Revised date: 2020-04-28

Online published: 2020-06-24

Supported by

Aeronautical Science Foundation of China (201957002003)

Fold

摘要

旋翼桨-涡干扰（BVI）是直升机在进场和离场等近地飞行时后行桨叶切割前行桨叶脱落桨尖涡产生的气动扰动，该扰动不仅对桨叶表面压力载荷产生激励作用，同时也会引起旋翼噪声出现激增，旋翼噪声激增的主要成分为桨-涡干扰噪声。本文首先对斜下降桨-涡干扰状态桨叶表面载荷进行数值计算；然后分别阐述了基于改进整周期同步平均旋翼噪声去噪方法、基于多层小波包分解的桨-涡干扰声源识别和分离方法以及基于bartlett时延计算和球面插值的声源定位方法，设计并开展了风洞斜下降状态桨-涡干扰桨叶表面压力和声源定位试验，给出了开发的声源定位软件界面、声源定位图像畸变校准方法及声阵列现场校准方法；最后对比分析了不同试验状态的桨-涡干扰噪声声源特性以及和桨叶表面压力之间的关联性，并给出了声源定位及表面压力试验数据分析结果。结果表明典型斜下降状态后行侧桨-涡干扰主要出现在方位角310°~330°、径向位置1.6~1.8 m桨盘平面区域。

关键词： 斜下降; 旋翼; 桨叶; 干扰; 声源; 定位; 表面压力

本文引用格式

刘正江 , 汪文涛 , 林永峰 , 曹亚雄 . 斜下降旋翼桨涡干扰声源定位及表面压力[J]. 航空学报, 2020 , 41(12) : 124060 -124060 . DOI: 10.7527/S1000-6893.2020.24060

Abstract

Rotor Blade-Vortex Interaction (BVI) is the aerodynamic disturbance caused by rotors of the retreading side cutting the shedding vortex of the advancing side blade during the approach and departure of helicopters. Apart from exciting the blade surface pressure load, the interactions also sharply increase the rotor noise predominated by the BVI noise. This article first presents the numerical simulation of the rotor BVI load, followed by elaboration of the denoising method based on the period time synchronous averaging, the recognition and separation approach of the BVI noise from the rotor noise using wavelet decomposition reconstruction, and the noise location method based on bartlett time delay calculation and spherical interpolation. A rotor blade-vortex interaction noise test in the wind tunnel is designed and completed to verify these methods. We also develop the software applied to rotor BVI noise location and surface pressure test in skew descending flight status, and the research of the temporal and spatial relationship between the rotor BVI noise and blade surface pressure load. The main software interfaces, the vibration measurement system, and the modification method of noise source location aberrations are presented. The test results indicate that the rotor blade vortex interaction on the rotor disk mainly appears at the section of 310°-320° azimuth and 1.6-1.8 m radial position.

Key words： skew descending; rotors; blades; interactions; noise source; location; surface pressure

参考文献

[1] JOHNSON W. Helicopter theory[M]. Princeton:Princeton University Press, 1980:903-909.
[2] 王适存, 徐国华. 直升机旋翼空气动力学的发展[J]. 南京航空航天大学学报, 2001, 33(3):203-211. WANG S C, XU G H. Progress of helicopter rotor aerodynamics[J]. Journal of Nanjing University of Aeronautics & Astronautics, 2001, 33(3):203-211(in Chinese).
[3] 徐国华, 史勇杰, 招启军. 直升机旋翼气动噪声的研究新进展[J]. 航空学报, 2017, 38(2):520991. XU G H, SHI Y J, ZHAO Q J. New research progress in helicopter rotor aerodynamic noise[J]. Acta Aeronautica et Astronautica Sinica, 2017, 38(2):520991(in Chinese).
[4] YU Y. The HART Ⅱ test-Rotor wakes and aeroacoustics with Higher-Harmonic pitch Control (HHC) inputs-the joint German/French/Dutch/US project[C]//58th Annual Forum of the American Helicopter Society. Fairfax:American Helicopter Society, 2002.
[5] LIM J W, TUNG C, YU Y H, et al. HART Ⅱ:Prediction of blade-vortex interaction loading[C]//29th European Rotorcraft Forum Proceedings, 2003:16-18.
[6] MURASHIGE A, KOBIKI N, TSUCHIHASHI A, et al. Final report of ATIC model rotor test at DNW:57-00076[R]. Kakamigahara:Advance Technology Insitute of Commuter-Helicopter, 2000.
[7] YIN J P. Representative test results from HELINOVI aeroacoustics main rotor/tail rotor/fuselage test in DNW[C]//43th Annual Forum of the Europe Helicopter Society.[S.l.]:Europe Helicopter Society, 2005:19887.
[8] 陈正武, 王勋年, 卢翔宇. 直升机旋翼气动噪声源识别定位技术研究[C]//第32届全国直升机年会. 北京:中国航空学会, 2016:130-136. CHEN Z W, WANG X N, LU X Y. Investigation identification and location technique of helicopter rotor aerodynamic noise sources[C]//32th CHS Annual Forum. Beijing:Chinese Society of Aeronautics and Astronautics, 2016:130-136(in Chinese).
[9] 朱正, 招启军, 陈丝雨. 共轴双旋翼悬停状态气动噪声特性分析[J]. 声学学报, 2016, 41(6):833-842. ZHU Z, ZHAO Q J, CHEN S Y. Analyses on aeroacoustics characteristics of coaxial rotos in hover[J]. Acta Acustica, 2016, 41(6):833-842(in Chinese).
[10] 史勇杰, 苏大成, 徐国华. 桨叶气动外形对直升机桨-涡干扰噪声影响研究[J]. 南京航空航天大学学报, 2015, 47(2):235-242. SHI Y J, SU D C, XU G H. Research on influence of shape parameters on blade-vortex interaction noise of helicopter rotor[J]. Journal of Nanjing University of Aeronautics & Astronautics, 2015, 47(2):235-242(in Chinese).
[11] 何瑞恒, 黄汉超, 龚亮, 等. 直升机尾桨涡干扰噪声试验研究[C]//第26届(2010)全国直升机年会. 北京:中国航空学会, 2010. HE R H, HUANG H C, GONG L, et al. Study on helicopter tail rotor-blade vortex noise[C]//26th CHS Annual Forum. Beijing:Chinese Society of Aeronautics and Astronautics, 2010(in Chinese).
[12] 曹亚雄, 樊枫, 林永峰, 等. 带先进桨尖的模型旋翼悬停噪声计算与试验[J]. 南京航空航天大学学报, 2016, 48(2):180-185. CAO Y X, FAN F, LIN Y F, et al. Numerical calculations and test research on aeroacoustics blade tip with anhedral angle hovering test numerical simulation rotor[J]. Journal of Nanjing University of Aeronautics & Astronautics, 2016, 48(2):180-185(in Chinese).
[13] 刘正江, 黄建萍, 陈焕, 等. 旋翼桨-涡干扰噪声特性试验技术研究[J]. 直升机技术, 2019(1):43-47. LIU Z J, HUANG J P, CHEN H, et al. Study on characteristic of rotor-blade vortex interaction noise[J]. Helicopter Technique, 2019(1):43-47(in Chinese).
[14] 林永峰, 刘平安, 陈文轩, 等. 三维桨尖旋翼桨叶表面压力测量试验[J]. 南京航空航天大学学报, 2011, 43(3):346-350. LIN Y F, LIU P A, CHEN W X, et al. Measurement of blade pressure distribution for three-dimensional blade tip[J]. Journal of Nanjing University of Aeronautics & Astronautics, 2011, 43(3):346-350(in Chinese).
[15] 周晓峰, 杨世锡, 甘春标. 一种旋转机械振动信号的盲源分离消噪方法[J]. 振动、测试与诊断, 2012, 32(5):714-717. ZHOU X F, YANG S X, GAN C B. Denoising vibration signal of rotating machinery[J]. Journal of Vibration, Measurement & Diagnosis, 2012, 32(5):714-717(in Chinese).
[16] 杨世锡, 梁文军, 于保华. 振动信号多通道同步整周期. 数据采集卡的设计[J].振动、测试与诊断, 2013, 33(1):23-28. YANG S X, LIANG W J, YU B H. Design of vibration signal multi-channel integer period synchronous acquisition card[J]. Journal of Vibration, Measurement, 2013, 33(1):23-28(in Chinese).
[17] 胡劲松, 杨世锡. 转子振动信号同步整周期重采样的研究[J]. 动力工程, 2008, 28(3):488-492. HU J S, YANG S X. Study on method of vibration signal full period synchronous resample for rotor[J]. Journal of Power Engineering, 2008, 28(3):488-492(in Chinese).
[18] 袁莉芬, 孙业胜, 何怡刚. 基于小波包优选的模拟电路故障特征提取方法[J]. 电工技术学报, 2018, 33(1):158-165. YUAN L F, SUN Y S, HE Y G. Fault feature extraction method for analog circuit based on preferred wavelet packet[J]. Transactions of China Electrotechnical Society, 2018, 33(1):158-165(in Chinese).
[19] 孙健, 王成华, 杜庆波. 基于小波包能量谱和NPE的模拟电路故障诊断[J]. 仪器仪表学报, 2013, 34(9):2021-2027. SUN J, WANG C H, DU Q B. Analog circuit fault diagnosis based on wavelet packet energy spectrum and NPE[J]. Chinese Journal of Scientific Instrument, 2013, 34(9):2021-2027(in Chinese).
[20] 李彬, 夏虹. 基于最优小波基的主泵裂纹转子特征识别研究[J]. 振动与冲击, 2014, 33(21):207-212. LI B, XIA H. Feature recognition of cracked rotor of RCP based on optimal wavelet basis[J]. Journal of Vibration and Shock, 2014, 33(21):207-212(in Chinese).
[21] 常国勇, 袁富宇, 崔杰. 基于不同能量值特征优选的水声目标识别[J]. 指挥控制与仿真, 2016, 38(2):60-65. CHANG G Y, YUAN F Y, CUI J. Underwater acoustic target recognition based feature selection of different energy feature[J]. Command Control & Simulation, 2016, 38(2):60-65(in Chinese).
[22] 顾光武, 朱博. 航空声学风洞背景噪声测试及频谱分析[J]. 噪声与振动控制, 2016(2):156-158. GU G W, ZHU B. Measurement and spectrum analysis of background noise of aeroacoustics wind tunnel[J]. Noise and Vibration Control, 2016(2):156-158(in Chinese).
[23] 安连锁, 冯强, 沈国清. 基于多时延识别的电站锅炉多源泄漏被动定位方法[J]. 动力工程学报, 2015, 35(10):798-804. AN L S, FENG Q, SEHN G Q. Passive location of multi-source leakage in power plant boilers based on multiple TDOA recognition[J]. Journal of Chinese Society of Power Engineering, 2015, 35(10):798-804(in Chinese).
[24] 张莉, 吕明. 基于特征分解的一步最小二乘声源定位算法[J]. 电声技术, 2007, 31(5):42-45. ZHANG L, LV M. A closed-form one-step least-square algorithm of acoustic source localization based on eigenvalue decomposition[J]. Audio Engineering, 2007, 31(5):42-45(in Chinese).
[25] 于振华, 付晓. 基于声学无线传感器网络的目标跟踪系统研究[J]. 电子科技大学学报, 2011, 40(4):568-572. YU Z H, FU X. On target tracking based on acoustic wireless sensor networks[J]. Journal of University of Electronic Science and Technology of China, 2011, 40(4):568-572(in Chinese).
[26] HUANG Y, BENESTY J, ELKO G W. Passive acoustic source localization for video camera steering[C]//IEEE International Conference on Acoustics, Speech, and Signal Processing. Piscataway:IEEE Press, 2000:909-912.

Options

文章导航

模态框（Modal）标题

摘要

本文引用格式

Abstract

参考文献