摘要
由于列车尺寸大、通过噪声频率低,利用声阵列技术分析列车通过噪声时需要大型传声器阵列,测试成本很高。为降低测量成本,提出一种用于列车通过噪声分析的传声器阵列优化设计方法。在该方法中首先利用遗传算法对四分之一阵列的传声器位置进行优化,然后将优化的部分进行旋转形成优化阵列。仿真结果表明,与使用相同数目的常规规则阵列相比,优化阵列拥有更小的主瓣宽度和更低的旁瓣水平,用于噪声源识别时表现更加优异,并且具有更好的抗噪性能。
Due to the large size of the train and the low frequency of the pass-by noise,large microphone arrays are required for the measurement and analysis of the pass-by noise.However,the cost of the measurement test is very high.To reduce the cost of measurement,a microphone array optimization design method is proposed for the analysis of train pass-by noise.This method uses the genetic algorithm to optimize the microphone position of the quarter of the array,and then rotates the optimized part to form the optimized array.The simulation results show that the optimized array has a smaller main lobe width and lower side lobe level compared with the regular arrays which uses the array with the same number of microphones.The optimized array performs better when used for noise source identification and has better noise immunity.
作者
詹天宇
胡定玉
师蔚
廖爱华
ZHAN Tianyu;HU Dingyu;SHI Wei;LIAO Aihua(School of Urban Railway Transportation,Shanghai University of Engineering Science,Shanghai 201620,China;Shanghai Engineering Research Center of Railway Noise and Vibration Control,Shanghai 201620,China)
出处
《噪声与振动控制》
CSCD
北大核心
2022年第6期149-153,225,共6页
Noise and Vibration Control
基金
国家自然科学基金资助项目(51605274)
上海市地方院校能力建设资助项目(20030501000)。
关键词
声学
列车通过噪声
阵列优化
遗传算法
波束形成
acoustics
train’s pass-by noise analysis
array optimization
genetic algorithm
beamforming
