摘要
基于反卷积DAMAS2波束形成理论,设计声源识别算法,开发相应软件。针对已知单声源、不相干双声源、相干双声源的模拟计算结果表明:新方法能够有效消除旁瓣,显著提高空间分辨率,更准确地识别声源。某发动机标定工况下的噪声源识别试验结果表明:气缸盖罩1#和2#缸中间及3#和4#缸中间的位置、缸体、排气旁通阀和发电机是其主要噪声源,试验验证了反卷积DAMAS2波束形成在发动机噪声源识别中的有效性。
Based on DAMAS2 beamforming principle, the sound source identification algorithm was designed and the corresponding software was developed. Simulation calculations for a single source, two incoherent sources and two coherent sources were conducted. Results show that this method eliminates sidelobe effectively and improves spacial resolution remarkably,so can identify sound sources more precisely. Results of the noise source identification test for an engine under rated load and speed conditions indicate that positions between first and second cylinders, third and fourth cylinders of cylinder head cover, cylinder block, exhaust by-pass valve and electric generator are major noise sources. This work provides a direction for improving engine acoustic properties,also validates the DAMAS2 beamforming effectiveness in engine noise source identification.
出处
《内燃机工程》
EI
CAS
CSCD
北大核心
2014年第2期59-65,共7页
Chinese Internal Combustion Engine Engineering
基金
国家自然科学基金资助项目(50975296)
牵引动力国家重点实验室开发课题(TPL0903)
关键词
内燃机
发动机
噪声源识别
波束形成
反卷积
算法设计
软件开发
IC engine
noise source identification
beamforming
deconvolution
algorithm design
software development
