基于多尺度样本熵和VPMCD的自动机故障诊断
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摘要
针对自动机故障诊断过程中振动信号的非线性、非平稳性、非周期性导致的故障特征较难提取,以及故障识别率偏低这一问题,提出了一种基于多尺度样本熵和多变量预测模型(variable predictive model-based class discriminate,简称VPMCD)的自动机故障诊断方法。首先,对采集到的信号进行小波阈值降噪处理;其次,利用小波包分解的方法对振动信号进行分解,得到多个尺度下的信号分量;然后,计算不同尺度下信号的样本熵值,并提取对故障特征较为敏感的尺度因子,组成故障特征向量;最后,利用多变量预测模型对故障特征向量进行训练和识别,进而实现自动机的故障诊断。自动机故障诊断试验分析结果表明,利用多尺度样本熵和多变量预测模型的方法可以准确识别多种典型的自动机故障类型。
引文
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[2]许昕,潘宏侠,潘铭志.独立分量分析在自动机振动信号处理中的应用[J].振动、测试与诊断,2016,36(1):120-125.Xu Xin,Pan Hongxia,Pan Mingzhi.Application of independent component analysis in automata vibration signal process[J].Journal of Vibration,Measurement&Diagnosis,2016,36(1):120-125.(in Chinese)
[3]潘宏侠,都衡,马春茂.局域波信息熵在高速自动机故障诊断中的应用[J].振动、测试与诊断,2015,35(6):1159-1164.Pan Hongxia,Du Heng,Ma Chunmao.High-speed automaton fault diagnosis based on local wave and information entropy[J].Journal of Vibration,Measurement&Diagnosis,2015,35(6):1159-1164.(in Chinese)
[4]潘宏侠,兰海龙,任海峰.基于局域波降噪和双谱分析的自动机故障诊断研究[J].兵工学报,2014,35(7):1077-1082.Pan Hongxia,Lan Hailong,Ren Haifeng.Fault diagnosis for automata based on local wave noisereduction and bispectral analysis[J].Acta Armamentarii,2014,35(7):1077-1082.(in Chinese)
[5]潘宏侠,马百雪,许昕.基于小波尺度谱重排与小波排列熵的自动机故障诊断[J].火炮发射与控制学报,2015,36(2):64-67.Pan Hongxia,Ma Baixue,Xu Xin.Fault diagnosis of automatic cannon based on wavelet scalogram rearrangement and permutation entropy[J].Journal of Gun Launch&Control,2015,36(2):64-67.(in Chinese)
[6]李莎,潘宏侠,都衡.基于EEMD信息熵和PSO_SVM的自动机故障诊断[J].机械设计与研究,2014,30(6):26-29.Li Sha,Pan Hongxia,Du Heng.Automaton fault diagnosis based on information entropy and PSO-SVM[J].Machine Design and Research,2014,30(6):26-29.(in Chinese)
[7]Rao R,Samavedham L.Variable predictive models—a new multivariate classification approach for pattern recognition applications[J].Pattern Recognition,2009,42(7):7-16.
[8]罗颂荣,程军圣,郑近德,等.GA_VPMCD方法及其在机械故障智能诊断中的应用[J].振动工程学报,2014,27(2):289-294.Luo Songrong,Cheng Junsheng,Zheng Jinde,et al.GA-VPMCD method and its application in machineryfault intelligent diagnosis[J].Journal of Vibration Engineering,2014,27(2):289-294.(in Chinese)
[9]程军圣,马兴伟,杨宇.基于VPMCD和EMD的齿轮故障诊断方法[J].振动与冲击,2013,32(20):9-13.Cheng Junsheng,Ma Xingwei,Yang Yu.Gear fault diagnosis method based on VPMCD and EMD[J].Journal of Vibration and Shock,2013,32(20):9-13.(in Chinese)
[10]杨宇,李永国,程军圣.WVPMCD及其在滚动轴承故障诊断中的应用[J].湖南大学学报,2014,41(2):52-57.Yang Yu,Li Yongguo,Cheng Junsheng.Weighted least square-VPMCD and its applicationin roller bearing fault diagnosis[J].Journal of Hunan University,2014,41(2):52-57.(in Chinese)
[11]程军圣,郑近德,杨宇.变量预测模型在齿轮故障诊断中的应用[J].振动、测试与诊断,2013,33(1):111-114.Cheng Junsheng,Zheng Jinde,Yang Yu.Variable predictive model based class discriminate applicationin gearing fault diagnosis[J].Journal of Vibration,Measurement&Diagnosis,2013,33(1):111-114.(in Chinese)
[12]成娟,陈勋,彭虎.基于样本熵的肌电信号起始点检测研究[J].电子学报,2016,44(2):479-484.Cheng Juan,Chen Xun,Peng Hu.An onset detection method for action surface electromyography based on sample entropy[J].Acta Electronica Sinica,2016,44(2):479-484.(in Chinese)
[13]Yang Yu,Wang Huanghuang,Cheng Junsheng,et al.A fault diagnosis approach for roller bearing based on VPMCD under variable speed condition[J].Measurement,2013,46(2):2306-2312.