拖拉机动力输出轴载荷经验模态分解软阈值降噪研究

闫祥海; 周志立; 李忠利

doi:10.7652/xjtuxb201905010

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拖拉机动力输出轴载荷经验模态分解软阈值降噪研究

更新时间：2025-07-09

- 拖拉机动力输出轴载荷经验模态分解软阈值降噪研究
- Study on the Noise Reduction of Tractor Power Take-off Load by Empirical Mode Decomposition Soft-Threshold Method
- 西安交通大学学报 2019年53卷第5期页码：67-72+122
- 作者机构：
  
  河南科技大学车辆与交通工程学院,河南,洛阳,471003
- 作者简介：
- 基金信息：
  
  : 2018-09-06。作者简介: 闫祥海(1985—),男,博士生;周志立(通信作者),男,教授,博士生导师。基金项目: “十三五”国家重点研发计划资助项目(2016YFD0701002);河南省高校科技创新人才支持计划资助项目(18HASTIT026)
- DOI：10.7652/xjtuxb201905010
  中图分类号： S222.3;TN911.72
- 网络首发：2019-05-10，
  
  纸质出版：2019
- 稿件说明：
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闫祥海, 周志立, 李忠利. 拖拉机动力输出轴载荷经验模态分解软阈值降噪研究[J]. 西安交通大学学报, 2019,53(5):67-72+122.

Study on the Noise Reduction of Tractor Power Take-off Load by Empirical Mode Decomposition Soft-Threshold Method[J]. 2019, 53(5): 67-72+122.
闫祥海, 周志立, 李忠利. 拖拉机动力输出轴载荷经验模态分解软阈值降噪研究[J]. 西安交通大学学报, 2019,53(5):67-72+122. DOI： 10.7652/xjtuxb201905010.

Study on the Noise Reduction of Tractor Power Take-off Load by Empirical Mode Decomposition Soft-Threshold Method[J]. 2019, 53(5): 67-72+122. DOI： 10.7652/xjtuxb201905010.

摘要

针对拖拉机旋耕作业动力输出轴(PTO)载荷降噪中载荷先验特性预判的问题

提出了PTO载荷经验模态分解(EMD)软阈值降噪方法

得到了PTO载荷相同时域内不同频率固有模态函数(IMF)。利用边界局部特征尺度延拓算法对IMF出现的端点效应进行了抑制

与镜像对称延拓算法和多项式拟合延拓算法比较

在运行时间、正交指数及IMF数量3项评价指标中均占优势。利用IMF分量与载荷相关系数

辨识出前3阶IMF分量为噪声主导分量

对前3阶IMF分量分别进行了软阈值降噪

与剩余分量叠加重构了降噪后的PTO载荷。降噪后的PTO载荷主频为4.492 Hz

与试验中旋耕机刀轴旋转频率相符。与EMD低通滤波降噪算法比较

EMD软阈值降噪算法属于自适应数据驱动

不需要设定截止频率。以含噪信号与噪声误差比(d

nSNR

)为降噪性能评价指标

EMD软阈值降噪算法的d

nSNR

为12.712 5

小于EMD低通滤波降噪算法的d

nSNR

值13.266 6

对比结果表明EMD软阈值降噪算法对实测拖拉机PTO载荷降噪效果明显。

Abstract

Aiming at the prejudgment on prior characteristics of the power take-off(PTO)load measured during tractor rotary tillage

an empirical mode decomposition(EMD)soft-threshold denoising algorithm is proposed. The intrinsic mode functions(IMF)at different frequencies in the same time domain of PTO load are obtained by using EMD. The endpoint effect of IMF is suppressed by the boundary local feature scale extension algorithm. Compared with the mirror symmetric extension algorithm and polynomial fitting extension algorithm

this algorithm is dominant in the three evaluation indexes of running time

orthogonal index and IMF number. By analyzing the correlation coefficient between the IMF components and PTO load

the first three orders of the IMF components are identified as the noise dominant component. Soft-threshold denoising is performed on the first three orders of IMF components

and the denoised PTO load is reconstructed by superposition with the residual components. The denoised PTO load frequency is 4.492 Hz

which is consistent with the rotation frequency of the rotary cutter shaft in the test. Compared with the EMD low-pass filter denoising algorithm

the EMD soft-threshold denoising algorithm belongs to adaptive data driving and does not need to set the cutoff frequency. The noisy signal-to-noise reduction error ratio(d

nSNR

)is used as the denoising performance evaluation index. The d

nSNR

value of the EMD soft-threshold denoising algorithm is 12.712 5

smaller than the d

nSNR

value 13.266 6 by EMD low-pass filtering denoising algorithm. The comparison results show that the EMD soft-threshold denoising algorithm has obvious effect on the noise reduction of tractor PTO load.

关键词

Keywords

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