CAJ | 학술논문

为了克服传统波束形成声源识别方法受旁瓣限制而无法识别次声源的缺点，将奇异值分析与波束形成算法相结合，给出了奇异值分解波束形成声源识别新方法：首先对阵列传声器测量信号的互谱矩阵进行奇异值分解重构，然后基于分解后的各互谱矩阵进行波束形成运算，从而识别主声源及各次声源。在仿真及算例试验均验证了其准确性及有效性的基础上，利用奇异值分解波束形成对某汽车前围板隔声薄弱环节进行识别，结果表明：空调进风口为第一声源，暖风机进出水管安装孔及空调漏水管安装孔分别为第二和第三声源。该方法准确高效，能够获得更全面的声源信息，提高了波束形成的声源识别性能，为识别次声源提供了有力工具。
위료극복전통파속형성성원식별방법수방판한제이무법식별차성원적결점，장기이치분석여파속형성산법상결합，급출료기이치분해파속형성성원식별신방법：수선대진열전성기측량신호적호보구진진행기이치분해중구，연후기우분해후적각호보구진진행파속형성운산，종이식별주성원급각차성원。재방진급산례시험균험증료기준학성급유효성적기출상，이용기이치분해파속형성대모기차전위판격성박약배절진행식별，결과표명：공조진풍구위제일성원，난풍궤진출수관안장공급공조루수관안장공분별위제이화제삼성원。해방법준학고효，능구획득경전면적성원신식，제고료파속형성적성원식별성능，위식별차성원제공료유력공구。
In order to overcome the disadvantage that the minor source cannot be identified because of the side lobe limitation by traditional beamforming method, a new sound source identification method named singular value de-composition beamforming was presented, which combined the singular value decomposition and beam-forming algo-rithm.Signal cross-spectral matrix measured by microphones was decomposed and recombined, and then the main source and other minor sources can be identified when the decomposed cross-spectral matrix was calculated with beam-forming.The simulation and verifiable experiment validated the correctness and effectiveness of the new method.The weak parts of a vehicle’ s dash panel were identified by singular value decomposition beam-forming. The results show that the first source is the air condition inlet, the installation holes of air blower outlet-inlet pipe and the leak pipe of air condition are the second and third source, respectively.The method can improve the per-formance of sound source identification and provides a powerful tool for the identification of minor sources for its ac-curacy and efficiency in getting more comprehensive information of sound source.