China Mechanical Engineering

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Research on Noise Diagnosis Technology Based on HELS Method#br#

Liu Congzhi;Wang Lingyan;Ren Bingyu;Ma Luping;Liu Weiqun;Hu Guangdi#br#   

  1. Southwest Jiaotong University,Chengdu,610031
  • Online:2016-04-10 Published:2016-04-11
  • Supported by:

基于HELS方法的噪声诊断技术研究

刘丛志;王铃燕;任冰禹;马卢平;刘伟群;胡广地   

  1. 西南交通大学,成都,610031
  • 基金资助:
    中央高校基本科研业务费专项资金资助项目(SWJTU12CX036);四川省应用基础研究(重大前沿)项目(2015JY0281);四川省重大科技成果转化专项(2015CC0003);四川省国际科技合作与交流研究计划项目(2015HH0062);西南交通大学研究生创新实验实践项目(YC201402104) 

Abstract: The noise diagnosis technology based on HELS applied the Helmholtz equation for noise diagnosis. It transformed the superposition of sound pressure into superposition of a set of linear independent functions. Then the method of least squares was used to reestablish the surface pressure of the sound source according to the known noise signals. The paper innovatively established a new type of HELS-PSO model to research the noise source identification and sound field reconstruction in order to improve solution accuracy. In the experiments the speakers were as simulated noise source and verified by experiments. The experimental results verify the effectiveness and efficiency of the algorithm and the accuracy of the new algorithm is higher than that of the traditional HELS algorithm.

Key words: fast noise diagnosis, Helmholtz equation, nonlinear optimization model, Helmholtz equation least squares(HELS)-particle swarm optimization(PSO) algorithm

摘要: 基于赫姆霍兹方程最小二乘法(HELS)的噪声诊断技术,将赫姆霍兹方程应用于噪声诊断技术中,把声场中声压转化为一组线性无关的独立函数的叠加,使用最小二乘法根据已知的较少噪声信号准确高效地重建声源表面的声压。建立基于非线性优化理论的新型HELS-PSO模型进行噪声源识别和声场重建研究,在实验室中以音箱作为模拟噪声源,通过实验进行验证。实验结果验证了该算法的有效性和高效性,表明新算法的求解精度较高。

关键词: 快速噪声诊断, 赫姆霍兹方程, 非线性优化模型, HELS-PSO算法

CLC Number: