作者：王枭1, 陈永艳1, 高志鹰1,2, 张翠青1,3, 代元军2,4, 汪建文1,2
作者单位：1. 内蒙古工业大学能源与动力工程学院, 内蒙古 呼和浩特 010051;
2. 内蒙古工业大学 风能太阳能利用技术省部共建教育部重点实验室, 内蒙古 呼和浩特 010051;
3. 内蒙古机电职业技术学院电气工程系, 内蒙古 呼和浩特 010051;
4. 新疆工程学院电力工程系, 新疆 乌鲁木齐 830091
关键词：声学;声源识别;旋转噪声;波束形成;反卷积
摘要：
针对常规束形成声源识别技术分辨率低、未考虑声源旋转运动造成的识别误差等问题，推导得到DAMAS2修正算法。该方法在原本的静止框架中加入转速，得到修正的指向矢量与波束形成修正结果，随后结合波束形成修正结果建立阵列点传播函数与真实声源位置之间的卷积关系，最终通过迭代求解获得真实声源位置。首先通过数值模拟构建两个频率及幅值均一致的对称点声源，对比分析常规波束形成算法与DAMAS2修正算法的识别效果，然后结合激光测速原理及波束形成测试理论进行旋转声源实验研究。结果表明：DAMAS2修正算法主瓣宽度小、虚假声源少，不仅可以识别出旋转声源的径向位置，而且能得到运动声源某一时刻的周向位置，能够更精确地定位识别旋转声源。
Locating and recognition method of rotating sound source based on DAMAS2 correction algorithm
WANG Xiao1, CHEN Yongyan1, GAO Zhiying1,2, ZHANG Cuiqing1,3, DAI Yuanjun2,4, WANG Jianwen1,2
1. College of Energy and Power Engineering, Inner Mongolia University of Technology, Hohhot 010051, China;
2. Key Laboratory of Wind Energy and Solar Energy of the Ministry of Education, Inner Mongolia University of Technology, Hohhot 010051, China;
3. Department of Electrical Engineering, Inner Mongolia Technical College of Mechanics & Electrics, Hohhot 010051, China;
4. Department of Electric Power Engineering, Xinjiang Institute of Engineering, Urumqi 830091, China
Abstract: To address the problem of low resolution of conventional beamforming sound source recognition technology and poor recognition of rotating sound sources, DAMAS2 correction algorithm was introduced. This method applied rotation speed to the original stationary frame so that the correction result of directional vector and beamforming was obtained. Then, the convolution relationship between the array point propagation function and the position of real sound source was established by combining the beamforming correction results. Finally, the real sound source position was obtained by iterative solution. Recognition effects of the conventional beamforming algorithm and the DAMAS2 correction algorithm were compared by establishing a symmetric point source with consistent two frequencies and amplitudes via numerical simulation, and then an experiment about rotating sound source was performed in conjunction with the principle of laser speed measurement and the theory of beamforming test. The results indicate that the DAMAS2 correction algorithm has a smaller main lobe width and fewer false sound sources. It can not only identify the radial position of the rotating sound source, but also can obtain the circumferential position of the moving sound source at a certain moment, which can locate and identify the rotating sound source more accurately.
Keywords: acoustics;sound source recognition;rotating noise;beamforming;deconvolution
2018, 44(9): 109-114 收稿日期: 2018-03-02;收到修改稿日期: 2018-04-02
基金项目: 国家自然科学基金（51366010）；风能太阳能利用技术省部共建教育部重点实验室开放基金项目（201605）
作者简介: 王枭(1992-),男,陕西西安市人,硕士研究生,专业方向为风力机气动噪声研究
参考文献
[1] OERLEMANS S, FISHER M, MAEDER T, et al. Reduction of wind turbine noise using optimized airfoils and trailing-edge serrations[J]. Aiaa Journal, 2009, 47(6):1470-1481
[2] BARSIKOW B, Ⅲ W F K. On removing the Doppler frequency shift from array measurements of railway noise[J]. Journal of Sound & Vibration, 1988, 120(1):190-196
[3] BARSIKOW B. Diagnosis of noise sources from high-speed trains using the microphone-array technique[J]. Journal of the Acoustical Society of America, 1998, 103(5):3007
[4] SIJTSMA P, OERLEMANS S, HOLTHUSEN H. Location of rotating sources by phased array measurements[C]//Proceedings of 7th AIAA/CEAS Aeroacoustics Conference, 2001.
[5] SIJTSMA P. Using phased array beamforming to locate broadband noise sources inside a turbofan engine[J]. Interational Journal of Aeroacoustics, 2010, 9(3):357-374
[6] BROOKS T F, HUMPHREYS W M. A deconvolution approach for the mapping of acoustic sources(DAMAS) determined from phased microphone arrays[J]. Journal of Sound and Vibration, 2006, 294(4):856-879
[7] DOUGHERTY R. Extensions of DAMAS and benefits and limitations of deconvolution in beamforming[C]//11th AIAA/CEAS Aeroacoustics Conference, 2005.
[8] EHRENFRIED K, KOOP L. Comparison of iterative deconvolution algorithms for the mapping of acoustic sources[J]. Aiaa Journal, 2007, 45(7):1584-1595
[9] 杨洋, 褚志刚, 江洪, 等. 反卷积DAMAS2波束形成声源识别研究[J]. 仪器仪表学报, 2013, 34(8):1779-1786
[10] BRUSNIAK L. DAMAS2 validation for flight test airframe noisemeasurements[C]//Berlin Beamformin Conference, 2008.
[11] XENAKI A. Improving the resolution of beamforming measurements on wind turbines[C]//Proceedings of 20th International Congress on Acoustics, 2010.
[12] XENAKI A, JACOBSEN F, FERNANDEZ-GRANDE E. Improving the resolution of three-dimensional acoustic imaging with planar phased arrays[J]. Journal of Sound & Vibration, 2012, 331(8):1939-1950
