Variable convergence train noise active control algorithm based on feedforward reference

LI Tao; HE Yuyao; WANG Ning; LI Zhuang; SHEN Zhaoyuan; XIAO Gang

doi:10.13890/j.issn.1000-128X.2022.01.005

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Variable convergence train noise active control algorithm based on feedforward reference

Intelligent Technology Column | 更新时间：2024-08-02

- Variable convergence train noise active control algorithm based on feedforward reference
- Electric drive for locomotives Issue 1, Pages: 25-30(2022)
- 作者机构：
  
  1.湖南工业大学　轨道交通学院，湖南株洲　412007
  2.中车株洲所电气技术与材料工程研究院，湖南株洲 412001
  3.江西科骏实业有限公司，江西南昌 330199
- 作者简介：
- 基金信息：
- DOI：10.13890/j.issn.1000-128X.2022.01.005
  CLC： U270.1⁺6
- Published：10 January 2022，
  
  Received：03 December 2020，
  
  Revised：20 December 2021，
- 稿件说明：
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LI Tao, HE Yuyao, WANG Ning, et al. Variable convergence train noise active control algorithm based on feedforward reference. [J]. Electric drive for locomotives (1):25-30(2022)
DOI：

LI Tao, HE Yuyao, WANG Ning, et al. Variable convergence train noise active control algorithm based on feedforward reference. [J]. Electric drive for locomotives (1):25-30(2022) DOI： 10.13890/j.issn.1000-128X.2022.01.005.

摘要

研究了一种基于前馈信号参考的可变收敛列车噪声主动控制算法，通过构建基于前馈信号参考的可变收敛函数，改善系统非零失调问题，并应用于列车低频噪声降噪中。仿真结果表明，该算法能够提高收敛速度、跟踪速率和稳态误差之间的均衡性。试验结果表明，该算法对于频率低于1 000 Hz的列车低频噪声在目标区域内平均降噪量约为12.0 dB，与固定收敛FxLMS算法、可变收敛NLMS算法和SVSLMS算法相比，具有最高约3.6 dB的降噪优势。

Abstract

An active control algorithm for train noise based on feed-forward reference with variable convergence was studied. By constructing a variable convergence function based on the feed-forward signal reference

the non-zero offset problem of the system was improved. Then it was applied to the low-frequency noise reduction of trains. Simulation results show that the algorithm can improve the balance between convergence speed

tracking speed and steady-state error. And the experimental results show that the algorithm achieves an average noise reduction of 12.0 dB for low-frequency train noise which below 1 000 Hz in the target area. Compared with the fixed-convergence FxLMS

variable-convergence NLMS

and SVSLMS control algorithms

it has the advantage of noise reduction up to about 3.6 dB.

关键词

列车低频噪声主动噪声控制可变收敛系数前馈信号参考仿真

Keywords

low-frequency train noiseactive noise controlvariable convergence coefficientfeed-forward signal referencesimulation

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