基于CEEMD与自适小波阈值组合降噪在OPAX方法的应用

摘要
图/表
参考文献(12)
相关文章 (15)

全文: PDF (2363 KB) HTML (1 KB)
输出: BibTeX | EndNote (RIS)

摘要针对如何从降噪的角度去提高扩展工况传递路径分析（OPAX）方法的分析精度，提出运用互补集合经验模态分解(CEEMD)与自适小波阈值相结合的降噪方法。采用样本熵将分解后信号的本征模态分量划分为噪声、含噪和信号分量。剔除噪声分量，将不同含噪分量的样本熵归一化后作为调参参数并应用于新构造的小波阈值函数，通过含噪情况调整阈值函数来提高降噪效果，并将降噪后的含噪分量跟信号分量一同重构得到完整信号，运用仿真计算验证上述方法能最大程度保留原始信号的完整性。应用到OPAX模型中，对其工况数据（时域振动信号）进行降噪，与其他降噪方法一同对比发动机二阶情况下目标点的计算的合成响应与实测响应，发现CEEMD与自适小波阈值组合降噪改进的OPAX方法吻合程度较高，效果较优。

	服务

	把本文推荐给朋友
	加入我的书架
	加入引用管理器
	E-mail Alert
	RSS
	作者相关文章
	陈克
	张晓冬
	李宁

关键词 ：扩展工况传递路径分析（OPAX）方法, 样本熵, 互补集合经验模态分解(CEEMD), 自适小波阈值降噪

Abstract：An improved method based on a combination of the complementary ensemble empirical mode decomposition (CEEMD) and adaptive wavelet threshold noise reduction was proposed for improving the analysis accuracy of operational path analysis with the exogeneous inputs (OPAX) method from the point of noise reduction.Sample entropy was used to divide the Intrinsic Mode Function of the decomposed signal into noise components, noisy components, and signal components.The noise components were eliminated, and the normalized sample entropy of different noisy components as the adjustable parameter was applied in the newly constructed wavelet threshold function to improve the noise reduction effect based on the noisy condition to adjust the threshold function.The noise components after noise reduction and the signal components were reconstructed together to obtain a complete signal, and simulation calculations verified that the above method can preserve the integrity of the original signal to the greatest extent.The method was used in the OPAX model to reduce the noise of its operating condition data (time-domain vibration signal).Compared the composite response and measured response of the target point in the second-order case of the engine with other noise reduction methods, it is found that the composite response in the improved OPAX method on a basis of the method of CEEMD and adaptive wavelet threshold combined noise reduction is very close to with the measured response.

Key words： operational path analysis with exogeneous inputs（OPAX） sample entropy complementary ensemble empirical mode decomposition（CEEMD） wavelet packet threshold noise reduction

收稿日期: 2020-02-17 出版日期: 2021-08-28

引用本文:

陈克，张晓冬，李宁. 基于CEEMD与自适小波阈值组合降噪在OPAX方法的应用[J]. 振动与冲击, 2021, 40(16): 192-198.
CHEN Ke,ZHANG Xiaodong,LI Ning. Application of CEEMD and adaptive wavelet threshold combined noise reduction in the OPAX method. JOURNAL OF VIBRATION AND SHOCK, 2021, 40(16): 192-198.

链接本文:

http://jvs.sjtu.edu.cn/CN/ 或 http://jvs.sjtu.edu.cn/CN/Y2021/V40/I16/192

［1］JANSSENS K, GAJDATSY P, GIELEN L, et al.OPAX: a new transfer path analysis method based on parametricload models［J］.Mechanical Systems & SignalProcessing, 2011, 25(4): 1321-1338.

［2］莫愁,陈吉清,兰凤崇.扩展工况传递路径分析方法改进［J］.振动与冲击,2015,34(8):129-133.
MO Chou, CHEN Jiqing, LAN Fengchong.Improvement of analysis method of transmission path of extended working conditions ［J］.Journal of Vibration and Shock, 2015, 34(8): 129-133.

［3］潘公宇,朱瑞.小波阈值降噪技术对OPAX方法的改进研究［J］.噪声与振动控制,2019,39(3):29-34.
PAN Gongyu, ZHU Rui.Wavelet threshold denoising technology improves opax method ［J］.Noise and Vibration Control, 2019, 39(3): 29-34.

［4］YEH J R，SHIEH J S． Complementary ensemble empirical mode decomposition: a novel noise enhanced data analysis method［J］．Advances in Adaptive Data Analysis，2010，2(2):135－156．

［5］周涛涛,朱显明,彭伟才,等.基于CEEMD和排列熵的故障数据小波阈值降噪方法［J］.振动与冲击,2015,34(23):207-211.
ZHOU Taotao, ZHU Xianming, PENG Weicai, et al.Wavelet threshold denoising method for fault data based on CEEMD and permutation entropy ［J］.Journal of Vibration and Shock, 2015, 34 (23): 207-211.

［6］王亚萍,匡宇麒,葛江华,等.CEEMD和小波半软阈值相结合的滚动轴承降噪［J］.振动、测试与诊断,2018,38(1): 80-86.
WANG Yaping, KUANG Yuqi, GE Jianghua, et al.Noise reduction of rolling bearings combined with CEEMD and wavelet semi-soft threshold ［J］.Journal of Vibration, Measurement and Diagnosis, 2018, 38(1): 80-86.

［7］石大磊,高宏力,李克斯.基于CEEMD与小波阈值的机械密封声发射信号自适应降噪方法［J］.润滑与密封,2019,44(7): 131-137.
SHI Dalei, GAO Hongli, LI Kesi.Adaptive noise reduction method for acoustic emission signal of mechanical seal based on CEEMD and wavelet threshold ［J］.Lubrication Engineering, 2019,44 (7): 131-137.

［8］郭学卫, 申永军, 杨绍普.基于样本熵和分数阶傅里叶变换的滚动轴承故障特征提取［J］.振动与冲击, 2017, 36(18): 65-69.
GUO Xuewei,SHEN Yongjun,YANG Shaopu.Application of sample entropy and fractional fourier transform in fault diagnosis of rolling bearing［J］.Journal of Vibration and Shock, 2017, 36(18): 65-69.

［9］周建,向北平,倪磊,等.基于样本熵的最优小波包阈值估计去噪算法［J］.机械设计与研究,2018,34(01):39-42.
ZHOU Jian, XIANG Beiping, NI Lei, et al.Optimal wavelet packet threshold estimation denoising algorithm based on sample entropy ［J］.Mechanical Design and Research, 2018, 34 (1): 39-42.

［10］向北平,周建,倪磊,等.基于样本熵的改进小波包阈值去噪算法［J］.振动、测试与诊断,2019,39(2):410-415.
XIANG Beiping, ZHOU Jian, NI Lei, et al.Improved wavelet packet threshold denoising algorithm based on sample entropy ［J］.Journal of Vibration, Measurement and Diagnosis, 2019, 39 (2): 410-415.

［11］CHEN Y, CHENG Y N, LIU H L.Application of improved wavelet adaptive threshold de-noising algorithm in FBG demodulation［J］.Optik-International Journal for Light and Electron Optics, 2017, 132:243-248.

［12］WANG Z W, ZHU P, SHEN Y, et al.An improved OPAX method based on moving multi-bandmodel［J］.Mechanical Systems and Signal Processing,2019,122:321-341.