[1]张晨阳,张亚,李培英,等.基于变分模态分解的侵彻过载信号特征提取[J].探测与控制学报,2021,43(03):16.[doi:.]
 ZHANG Chenyang,ZHANG Ya,LI Peiying,et al.Feature Extraction of Penetration Overload Signal Based on Variational Mode Decomposition[J].,2021,43(03):16.[doi:.]
点击复制

基于变分模态分解的侵彻过载信号特征提取()
分享到:

《探测与控制学报》[ISSN:1008-1194/CN:61-1316/TJ]

卷:
43
期数:
2021年03
页码:
16
栏目:
出版日期:
2021-08-01

文章信息/Info

Title:
Feature Extraction of Penetration Overload Signal Based on Variational Mode Decomposition
文章编号:
1008-1194(2021)03-0016-06
作者:
张晨阳1张亚1李培英2李世中1赵海峰3
1.中北大学机电工程学院,山西 太原 030051;2.邯郸学院,河北 邯郸 056005;3.南京信息职业技术学院机电学院,江苏 南京 210023
Author(s):
ZHANG Chenyang1 ZHANG Ya1 LI Peiying2 LI Shizhong1 ZHAO Haifeng3
1.School of Mechanical Engineering, North University of China, Taiyuan 030051, China;2.Handan College, Handan 056005, China; 3.School of Mechanical Engineering, Nanjing Institute of Information Technology, Nanjing 210032, China
关键词:
侵彻过载信号变分模态分解重构信号信噪比侵彻深度
Keywords:
penetration overload signal variational mode decomposition reconstruction signal signal to noise ratio penetration depth
分类号:
TN911.7
DOI:
.
文献标志码:
A
摘要:
针对传统侵彻过载信号处理方法存在滤波效果不佳、模态混叠、端点效应、自适应性差的问题,提出基于变分模态分解的侵彻过载信号特征提取方法。该方法将侵彻过载信号的特征提取过程转移到变分框架内进行处理,通过寻找变分模型的最优解获取本征模态函数,能够自适应地实现信号的频域划分和各分量的有效分离,并有效地提取出侵彻过载信号的数据统计特性。实验验证结果表明,与经验模态分解相比,变分模态分解的特征提取效果更佳、信噪比更高,重构信号的积分结果更好地反映了弹体的实际侵彻深度,是一种用于侵彻实验数据事后处理的可行的新方法。
Abstract:
Aiming at the problems of poor filtering effect, modal aliasing, end effect, and poor adaptability existing in the traditional processing methods of penetration overload signal, a characteristic extraction method of penetration overload signal based on variational modal decomposition was proposed. This method transfered the feature extraction process of the intrusion overload signal to the variational framework for processing, and obtained the eigenmode function by finding the optimal solution of the variational model, which could adaptively realize the frequency domain division of the signal and the analysis of each component effective separation, and effectively extracted the statistical characteristics of the data penetrating the overload signal. Experimental verification results showed that, compared with empirical mode decomposition, the feature extraction effect of variational mode decomposition was better and the signal-to-noise ratio was higher. The integration result of the reconstructed signal better reflected the actual penetration depth of the projectile.

参考文献/References:

[1]唐林,陈刚,吴昊.基于总体经验模态分解和连续均方误差的侵彻过载信号分析方法[J].高压物理学报,2018,32(5):126-132.
[2]张兵,石庚辰.侵彻硬目标识别技术中的机械滤波[J].探测与控制学报,2010,32(4):25-29.
[3]赵海峰,张亚,李世中,等.基于奇异值分解的侵彻过载信号降噪方法[J].振动、测试与诊断,2015,35(4):770-776.
[4]赵海峰,张亚,李世中.侵彻过载信号的欠定盲源分离与特征提取[J].仪器仪表学报,2019,40(10):208-218.
[5]范锦标,祖静,徐鹏,等.弹丸侵彻混凝土目标减加速度信号的处理原则[J].探测与控制学报,2012,34(4):1-5.
[6]刘时华,张亚.基于小波分析对信号噪声的处理及应用[J].机械工程与自动化,2015,1:84-88.
[7]肖力伟.一种基于小波包和主成分分析的超声信号特征提取方法[J].无损检测,2019,41(12):41-48.
[8]黄翔.基于EMD重构地震信号的去噪方法[J].油气地球物理,2017,15(2):18-23.
[9]卢秋悦.改进的EMD在地震勘测随机噪声压制中的应用[D].长春:吉林大学,2016.
[10]温志平.基于模态分解技术的地震信号随机噪声压制[D].上海:华东理工大学,2018.
[11]DRAGOMIRETSKIY K, ZOSSO D.Variational mode decomposition[J].IEEE Transactionson Signal Processing, 2014, 62(3):531-544.
[12]ZHENG Yi, YUE Jun, SUN Xiaofeng, et al.Studies of filtering effect on intern-al solitary wave flow field data in the south China sea using EMD[J]. Advanced Mat-erials Research, 2012, 1793(1041):1422-1425.
[13]ZHENG Yi, XIN Daqi, LI Shuxia, et al.Current field features and propagation characteristics of suspected internal solitary wave packet[J].Oceanengineering, 2013, 72(1):448-452.
[14]鲁逸杰,宫志华,张群,等.基于变分模态分解的进动目标微多普勒特征提取方法[J].探测与控制学报,2019,41(4):30-35.
[15]王大为,王召巴,李鹏,等.基于变分模态分解的超声检测信号降噪研究[J].中国测试,2019,45(12):106-111.

备注/Memo

备注/Memo:
收稿日期:2020-12-26
作者简介:张晨阳(1997—),男,河南周口人,硕士研究生。
更新日期/Last Update: 2021-08-04