应用EEMD和小波包分解的压力脉动信号时域特征提取方法

doi:10.16731/j.cnki.1671-3133.2018.07.001

现代制造工程 ›› 2018, Vol. 454 ›› Issue (7): 1-6.doi: 10.16731/j.cnki.1671-3133.2018.07.001

• 实验研究 • 下一篇

应用EEMD和小波包分解的压力脉动信号时域特征提取方法

李瑞, 谷立臣, 赵鹏军, 郭西惠

西安建筑科技大学机电工程学院,西安 710055

收稿日期:2017-04-14 出版日期:2018-07-20 发布日期:2018-07-20
作者简介:李瑞,硕士研究生,主要研究方向为流体传动与控制。谷立臣,博士,教授,博士生导师。E-mail:474163640@qq.com;gulichen@126.com
基金资助:
国家自然科学基金资助项目(51275375,51679399);陕西省教育厅专项科研计划项目(15JK1412)

A time-domain feature extraction method of pressure pulsation using EEMD and wavelet packet decomposition

Li Rui, Gu Lichen, Zhao Pengjun, Guo Xihui

School of Mech & Elec.Eng., Xi’an Univ.of Arch.& Tech., Xi’an 710055,China

Received:2017-04-14 Online:2018-07-20 Published:2018-07-20

摘要/Abstract

摘要： 柱塞马达压力信号是液压系统重要的信号源,其中压力脉动的特征变化能够反映系统局部乃至全局的运行状态。为从多成分混叠的压力信号中有效分离压力脉动成分,重构时域特征,提出基于集合经验模态分解(Ensemble Empirical Mode Decomposition,EEMD)与小波包分解的压力脉动信号时域特征提取方法。首先,利用EEMD将压力信号与干扰信号分离;其次,根据柱塞泵和柱塞马达压力脉动信号的时频特性,利用小波包分解并重构得到柱塞马达压力脉动信号,提取时域特征;最后,结合实验分析脉动特征随工况的变化规律。该方法经实验验证可行有效,且结果表明:压力脉动幅度随转速的升高而减小,随压力的增大而增大,与压力脉动变化机理一致。研究成果可为柱塞马达的运行状态监测提供方法支撑。

关键词: 柱塞马达, 压力脉动, EEMD分解, 小波包分解与重构

Abstract: The pressure signal of the piston motor is an important signal source of the hydraulic system,which changes the characteristics of pressure pulsation and reflects the local or global operation of the system state.In order to separate the component of pressure pulsation from the multi-component pressure signal and reconstruct its time domain feature,an extraction method of time-domain feature based on EEMD and wavelet packet decomposition is proposed.Firstly,the pressure signal and the interference signal are separated by EEMD.Secondly,according to the time-frequency characteristics of the pressure fluctuation of the piston pump and the piston motor,the pressure pulsation signal of the piston motor is obtained by wavelet packet decomposition and reconstruction,and the time-domain characteristics are extracted.Finally,combined with the experiment,the change regulation of the pulsating characteristic with the working condition is analyzed.The effectiveness of the proposed method is validated by the experiment,and the results show that:the amplitude of pressure pulsation decreases with increased speed,but increases with the increase of pressure,which is consistent with the mechanism of pressure fluctuation.The research achievement provides support for the operation condition monitoring of the piston motor.

Key words: piston motor, pressure pulsation, EEMD decomposition, wavelet packet decomposition and reconstruction

中图分类号:

李瑞, 谷立臣, 赵鹏军, 郭西惠. 应用EEMD和小波包分解的压力脉动信号时域特征提取方法[J]. 现代制造工程, 2018, 454(7): 1-6.

Li Rui, Gu Lichen, Zhao Pengjun, Guo Xihui. A time-domain feature extraction method of pressure pulsation using EEMD and wavelet packet decomposition[J]. Modern Manufacturing Engineering, 2018, 454(7): 1-6.

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应用EEMD和小波包分解的压力脉动信号时域特征提取方法

A time-domain feature extraction method of pressure pulsation using EEMD and wavelet packet decomposition

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