基于L-M算法的神经网络在环境振动分析中消除本底振动的应用

耿传飞1,卢文良1,俞醒2

振动与冲击 ›› 2016, Vol. 35 ›› Issue (13) : 14-19.

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振动与冲击 ›› 2016, Vol. 35 ›› Issue (13) : 14-19.
论文

基于L-M算法的神经网络在环境振动分析中消除本底振动的应用

  • 耿传飞1,卢文良1,俞醒2
作者信息 +

Application of Neural Network based on L-M Algorithm in removing background vibration from environmental vibration analysis

  • GENG Chuanfei1, LU Wenliang1, YU Xing2
Author information +
文章历史 +

摘要

公路、铁路及城市轨道交通引起的环境振动实测数据中含有本底振动的干扰,从时域分析角度提出基于 ( )算法的神经网络法消除本底振动,阐述了该法的基本原理和实现步骤,采用 算法对神经网络进行训练,具有收敛速度快、计算精度高的特点。通过一段交通振动加速度时程与一段本底振动加速度时程叠加合成实测振动加速度时程,分别用 神经网络法和其他几种方法对合成的实测振动加速度时程进行本底振动消除计算和对比分析。计算结果表明, 神经网络法能更加精确的计算出真实交通振动产生的时程曲线、功率谱密度曲线、1/3倍频程中心频率处振动加速度级和计权振级。

Abstract

Background vibration can disturb environmental vibration induced by highway, railway and urban rail transit. Neural Network method based on L-M (Levenberg-Marquardt) algorithm, a time-domain analysis approach, was proposed to remove background vibration from environmental vibration testing data. The basic principle and implementation steps were discussed. Neural Network was trained by using L-M algorithm which sped up the network training rate and improved the accuracy of network training. A background vibration acceleration time history was superimposed on a traffic vibration to synthesize a testing vibration record, which was used to remove background vibration by L-M Neural Network approach and other approaches. The calculated results indicated that L-M Neural Network method can obtain time history, power spectral density, vibration acceleration level on one-third octave band center frequency and weighted level of the true traffic vibration more accurately, which showed that L-M Neural Network method was superior to other current methods.

关键词

环境振动 / 本底振动 / / 神经网络 / 功率谱密度 / 振动加速度级

Key words

 environment vibration / background vibration / L-M / Neural Network / power spectral density / vibration acceleration level

引用本文

导出引用
耿传飞1,卢文良1,俞醒2. 基于L-M算法的神经网络在环境振动分析中消除本底振动的应用[J]. 振动与冲击, 2016, 35(13): 14-19
GENG Chuanfei1, LU Wenliang1, YU Xing2. Application of Neural Network based on L-M Algorithm in removing background vibration from environmental vibration analysis[J]. Journal of Vibration and Shock, 2016, 35(13): 14-19

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