基于SSWD优化LMD的高速电梯滚动导靴振动信号特征提取

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摘要针对奇异值分解（SVD）优化局部均值分解（LMD）方法提取高速电梯滚动导靴振动信号故障特征分量的模态混淆现象，提出一种基于自适应增强小波分解（SSWD）优化LMD的高速电梯滚动导靴振动信号特征提取方法。该方法构建低通滤波器、高通滤波器、小波基函数、尺度函数，利用小波分解（WD）的多分辨率滤波特性将原始信号分解为高频细节特征信号和低频近似信号；对高频细节特征信号进行信号增强、将增强后的高频细节特征信号与低频近似信号进行重构；采用LMD从重构信号中提取能够表征滚动导靴故障特征PF分量，求取PF分量的瞬时Teager能量波形进行对比分析。通过对实际工况信号处理、分析，实验结果表明，相比于SVD优化LMD方法，该方法完整地提取了滚动导靴振动信号的故障特征分量，避免了模态混淆现象出现。

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	陶然1
	2
	许有才2
	和杰2
	3
	鲁云波2
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	乔王治2
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	杨春宇2
	3
	张俊喃2
	3
	李珺2
	王华1

关键词 ：高速电梯, 滚动导靴, 局部均值分解(LMD), 自适应增强小波分解(SSWD), 小波分解(WD)

Abstract：Aiming at the phenomenon of mode mixing in the extraction of fault information from the vibration signal of a high speed elevator rolling guide shoe,by the method of singular value decomposition (SVD) optimizing local mean decomposition (LMD), a feature extraction method based on self-adaptive sharpening wavelet decomposition (SSWD) optimizing LMD was proposed.First of all, the low pass filter, high pass filter, wavelet basis function and scale function were constructed.The original signal was decomposed into a high-frequency detailed feature signal and a low-frequency approximate signal by the multi-resolution filtering characteristics of wavelet decomposition (WD).Then, signal enhancement was done on the high frequency detailed feature components, and the enhanced high frequency detailed characteristic signal and the low frequency approximate signal were reconstructed.Finally, the LMD method was used to extract the fault features’ PF component of the rolling guide shoe from the reconstructed signals.The instantaneous Teager energy waveform of the PF component was obtained for comparative analysis.Through the actual working condition signal processing and analysing, the experimental results show that, compared with the SVD optimizing LMD method, the method completely extracts the fault characteristic components of the vibration signal of the rolling guide shoe, and avoids the phenomenon of modal confusion.

Key words： high speed elevator rolling guide shoe local mean decomposition(LMD) self-adaptive sharpening wavelet decomposition (SSWD) wavelet decomposition(WD)

收稿日期: 2020-08-07 出版日期: 2021-05-28

引用本文:

陶然1,2，许有才2，和杰2,3，鲁云波2,3，乔王治2,3，杨春宇2,3，张俊喃2,3，李珺2，王华1. 基于SSWD优化LMD的高速电梯滚动导靴振动信号特征提取[J]. 振动与冲击, 2021, 40(10): 196-203.
TAO Ran1,2,XU Youcai2,HE Jie2,3,LU Yunbo2,3,QIAO Wangzhi2,3,YANG Chunyu2,3,ZHANG Junnan2,3,LI Jun2,WANG Hua1. Feature extraction of the vibration signal of a high-speed elevator rolling guide shoe based on SSWD optimizing LMD. JOURNAL OF VIBRATION AND SHOCK, 2021, 40(10): 196-203.

链接本文:

http://jvs.sjtu.edu.cn/CN/ 或 http://jvs.sjtu.edu.cn/CN/Y2021/V40/I10/196

［1］张进，冯志鹏，褚福磊.滚动轴承故障特征的时间-小波能量谱提取方法［J］.机械工程学报，2011,47（17）：44-49.
ZHANG Jin, FENG Zhipeng, CHU Fulei.Rolling bearing fault feature with time-the wavelet energy spectrum extraction method［J］.Journal of Mechanical Engineering, 2011, 47(17): 44-49.

［2］SMITH J S.The local mean decomposition and its application to EEG perception data［J］.Journal of the Royal Society Interface, 2005, 2(5):12.

［3］吴俊，张榆锋.经验模态分解和小波分解滤波特性的比较研究［J］.云南大学学报(自然科学版), 2012,34(3):285-290.
WU Jun, ZHANG Yufeng.The differences analysis on filtering properties of empirical mode decomposition and wavelet decomposition［J］.Journal of Yunnan University (Natural Sciences Edition),2012, 34(3):285-290.

［4］李志农,朱明,褚福磊,等.基于经验小波变换的机械故障诊断方法研究［J］.仪器仪表学报,2014,35(11)：2423-2432.
LI Zhinong, ZHU Ming, CHU Fulei, et al.Mechanical fault diagnosis method based on empirical wavelet transform［J］.Chinese Journal of Scientific Instrument,2014,35(11):2423-2432.

［5］陈志新,刘鑫,卢成林,等.基于经验小波变换的复杂强噪声背景下弱故障检测方法［J］.农业工程学报,2016,32(20)：202-208.
CHEN Zhixin，LIU Xin，LU Chenglin，et al.Weak fault detection method in complex strong noise condition based on empirical wavelet transform［J］.Transactions of the Chinese Society of Agricultural Engineering,2016,32(20): 202-208.

［6］许有才, 万舟.基于条件局部均值分解与变量预测模型的轴承故障诊断方法［J］.计算机应用, 2015, 35(9):150-154.
XU Youcai, WAN Zhou.Bearing fault diagnosis method based on conditional local mean decomposition and variable predictive model［J］.Journal of Computer Applications, 2015, 35(9):150-154.

［7］程军圣,张亢,杨宇.基于噪声辅助分析的总体局部均值分解方法［J］.机械工程学报, 2011,47(3):55-62.
CHENG Junsheng, ZHANG Kang, YANG Yu.Ensemble local mean decomposition method based on noise-assisted analysis［J］.Journal of Mechanical Engineering, 2011, 47(3): 55-62.

［8］程军圣,张亢,杨宇,等.局部均值分解与经验模式分解的对比研究［J］.振动与冲击,2009,28(5):13-16.
CHENG Junsheng, ZHANG Kang, YANG Yu, et al.The comparative study of local mean decomposition and empirical model decomposition［J］.Journal of Vibration and Shock, 2009, 28(5): 13-16.

［9］何田,林意洲,郝普刚,等.局部均值分解在齿轮故障诊断中的应用研究［J］.振动与冲击,2011,30(6):196-201.
HE Tian, LIN Yizhou, HAO Pugang, et al.Local mean decomposition in the application of gear fault diagnosis research［J］.Journal of Vibration and Shock, 2011, 30(6): 196-201.

［10］张先起,牛昂,宋超.基于小波分解-Elman 网络的灌区地下水埋深预测模型［J］ .华北水利水电大学学报( 自然科学版) , 2020,41(1): 1-7.
ZHANG Xianqi, NIU Ang, SONG Chao.Prediction model of the buried depth of groundwater in irrigation area based on wavelet decomposition and Elman network［J］.Journal of North China University of Water Resources and Electric Power (Natural Science Edition), 2020,41(1) :1-7.

［11］刘玉敏,周昊飞.基于小波重构与SVM-BPNN的动态过程在线智能监控［J］.系统工程理论与实践, 2016, 36(7): 1890-1897.
LIU Yumin, ZHOU Haofei.Online intelligent monitoring for dynamic process based on wavelet reconstruction and SVM-BPNN［J］.Systems Engineering-Theory & Practice, 2016, 36(7): 1890-1897.

［12］杨江天,周培钰.经验模态分解和Laplace小波在机车柴油机齿轮系故障诊断中的应用［J］.机械工程学报, 2011, 47(7): 109-115.
YANG Jiangtian, ZHOU Peiyu.Fault diagnosis for gear train of locomotive diesel engine based on empirical mode decomposition and laplace wavelet［J］.Journal of Mechanical Engineering, 2011, 47(7): 109-115.

［13］梅德庆,杜小强,陈子辰.基于滚动导靴-导轨接触模型的高速曳引电梯振动分析［J］.机械工程学报, 2009, 45(5): 264-270.
MEI Deqing, DU Xiaoqiang, CHEN Zichen.Vibration analysis of high-speed traction elevator based on guide roller-rail contact model［J］.Journal of Mechanical Engineering, 2009, 45(5): 264-270.

［14］易士琳,万舟,陶然,等.基于遗传算法优化支持向量机的电梯故障诊断［J］.计算机与数字工程, 2016, 44(1): 166-170.
YI Shilin, WAN Zhou, TAO Ran, et al.Diagnosis of elevator faults with SVM based on optimization by GA［J］.Computer & Digital Engineering, 2016, 44(1): 166-170.

［15］陈志平, 汪赞, 张国安, 等.基于大数据的电梯故障诊断与预测研究［J］.机电工程, 2019,36(1):90-94.
CHEN Zhiping, WANG Zan, ZHANG Guoan, et al.Reserrch of big-data-based elevator fault diagnosis and predication［J］.Journal of Mechanical & Electrical engineering ,2019,36(1): 90-94.

［16］陶然,许有才,邓方华,等.基于SVD优化LMD的电梯导靴振动信号故障特征提取［J］.振动与冲击, 2017, 36(22): 166-171.
TAO Ran, XU Youcai, DENG Fanghua, et al.Feature extraction of the elevator guide shoe vibration signal based on SVD optimizing LMD［J］.Journal of Vibration and Shock, 2017, 36(22): 166-171.

［17］杨淑莹.图像识别与项目实践-VC++、MATLAB技术实现［M］.北京：电子工业出版社, 2014.

［18］王天金,冯志鹏,郝如江,等.基于Teager能量算子的滚动轴承故障诊断研究［J］.振动与冲击,2012,31(2):1-5.
WANG Tianjin, FENG Zhipeng, HAO Rujiang, et al.Fault diagnosis of rolling element bearing bsed on Teager energy operator［J］.Journal of Vibration and Shock,2012,31(2): 1-5.

［19］李葵,范玉刚,吴建德.基于SVD和TKEO的轴承振动信号特征提取［J］.计算机工程与应用,2014,50(17): 195-199.
LI Kui, FAN Yugang, WU Jiande.Feature extraction of bearing vibration signal based on SVD and TKEO［J］.Computer Engineering and Applications, 2014,50(17):195-199.