多重分形的振动信号故障特征提取方法
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摘要
针对非线性振动信号故障特征提取问题,提出一种广义维数均值(MeanDq)联合多重分形谱参数(Δα和Δf)的动特征提取方法。首先分析了振动信号的多重分形特性,然后计算出MeanDq,Δα和Δf分别作为故障特征量,并将其应用于滚动轴承故障状态的检测。研究表明:MeanDq,Δα和Δf能够有效地反映滚动轴承振动信号的状态,并且特征量MeanDq和Δα较Δf具有更好的灵敏度。实践证明该方法在实际应用中切实可行。
Considering fault feature extraction difficulty to the non-linear vibration signals,a feature extraction method is proposed based on the general dimension mean(MeanDq) and the parameters of singular spectrum(Δα and Δf).Firstly,characteristics of multi-fractal for the vibration signals are analyzed,then MeanDq,Δα and Δf are calculated,respectively.Subsequently,they are used as fault characteristic values.Finally,fault feature extraction method is applied to fault detection for rolling bearing.The result shows that the state of the vibration signals for rolling bearing can be effectively identified by MeanDq,Δα and Δf together.Besides,MeanDq and Δα have a stronger sensibility than Δf.Apparently,the example proves that the integrated method is feasible.
Considering fault feature extraction difficulty to the non-linear vibration signals,a feature extraction method is proposed based on the general dimension mean(MeanDq) and the parameters of singular spectrum(Δα and Δf).Firstly,characteristics of multi-fractal for the vibration signals are analyzed,then MeanDq,Δα and Δf are calculated,respectively.Subsequently,they are used as fault characteristic values.Finally,fault feature extraction method is applied to fault detection for rolling bearing.The result shows that the state of the vibration signals for rolling bearing can be effectively identified by MeanDq,Δα and Δf together.Besides,MeanDq and Δα have a stronger sensibility than Δf.Apparently,the example proves that the integrated method is feasible.
引文
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[16]Brown G,Micho G,Pevriere J.On the multifractalanalysis[J].Journal of Stat Phys,1992,66(3/4):775-790.
[17]周炜星,王延杰,于遵宏.多重分形奇异谱的几何特性I.经典Renyi定义法[J].华东理工大学学报,2000,26(4):385-389.Zhou Weixing,Wang Yanjie,Yu Zunhong.Geomet-rical characteristics of singularity spectra of multi-fractals[J].Journal of East China University of Sci-ence and Technology,2000,26(4):385-389.
[2]钟明寿,龙源,谢全明,等.基于分形盒维数和多重分形的爆破地震波信号分析[J].振动与冲击,2010,29(1):7-12.Zhong Mingshou,Long Yuan,Xie Quanmin,et al.Signal analysis for blasting seismic wave based onfractal box dimension and multi-fractal[J].Journalof Vibration and Shock,2010,29(1):7-12.
[3]Li Meng,Ma Wenxing,Liu Xiujuan.Investigation ofrolling bearing fault diagnosis based on multi-fractaland general fractal dimension[C]//Second IntelligentComputation Technology and Automation.Chang-sha:IEEE Computer Society,2009:545-548.
[4]王金东,王巍,李宏灿.往复压缩机轴承故障的多重分形特征提取[J].振动与冲击,2008,27(S):313-315.Wang Jindong,Wang Wei,Li Hongcan,et al.Mul-tifractal features extraction of bearing faults for cipro-cating compressor[J].Journal of Vibration andShock,2008,27(S):313-315.
[5]王炳成,任朝晖,侯荣涛.碰摩耦合故障诊断识别的分形方法研究[J].润滑与密封,2010,35(5):42-45.Wang Bingcheng,Ren Zhaohui,Hou Rongtao.Frac-tal method on diagnoses of rub-impact coupling fault[J].Lubrication Engineering,2010,35(5):42-45.
[6]Yuan Yu,Li Baoliang,Shang Jingshan,et al.Theapplication of vibration signal multi-fractal in fault di-agnosis[C]//Second International Conference on Fu-ture Networks.Sanya:IEEE Computer Society,2010:164-167.
[7]王炳成,任朝晖,侯荣涛.故障诊断中的多重分形分析[J].现代制造工程,2010,25(7):1-3.Wang Bingcheng,Ren Zhaohui,Hou Rongtao.Multi-fractal analysis on fault diagnoses[J].ModernManufacturing Engineering,2010,25(7):1-3.
[8]岳建海,董科强,赵晓军.基于多重分形分析的故障诊断[J].科学技术与工程,2010:2079-2082.Yue Jianhai,Dong Keqiang,Zhao Xiaojun.Fault di-agnosis based on analysis of multifractal[J].ScienceTechnology and Engineering,2010:2079-2082.
[9]刘小刚,赵慧洁,李娜.基于多重分形谱的高光谱数据特征提取[J].光学学报,2009,29(3):844-847.Liu Xiaogang,Zhao Huijie,Li Na.Feature extrac-tion based on multifractal spectrum for hyper spectraldata[J].Acti optica Sinica,2009,29(3):844-847.
[10]于功志,关德林,段树林.基于多重分形的齿轮故障特征提取方法[J].大连海事大学学报,2009,35(1):111-114.Yu Gongzhi,Guan Delin,Duan Shulin,et al.Faultfeature extraction method for gear based onmulti2fractional spectrum[J].Journal of Dalian Mar-itime University,2009,35(1):111-114.
[11]陈亦望,徐鑫,傅强.基于多个无标度区的多重分形分析方法[J].计算物理,2010,27(6):905-911.Chen Yiwang,Xu Xin,Fu Qiang.Multifractal anal-ysis method based on several scale-free sones[J].Chinese Journal of Computational Physics,2010,27(6):905-911.
[12]李国宾,关德林,王宏志,等.柴油机磨合状态下振动信号多重分形研究[J].内燃机工程,2009,30(2):15-19.Li Guobin,Guan Delin,Wang Hongzhi,et al.Studyon multifractal parameters of vibration signal duringrunning in of diesel engine[J].Chinese Internal Com-bustion Engine Engineering,2009,30(2):15-19.
[13]石博强,申焱华.机械故障诊断的分形方法[M].北京:冶金工业出版社,2001.Shi Fuqiang,Sheng Yanhua.Fractal methods of me-chanical fault diagnosis[M].Beijing:MetallurgicalIndustry Press,2001.
[14]Halsey T C,Jensen M H,Kadanoff L P,et al.Fractal measures and their singularities:the charac-terization of strange sets[J].Phys Rev A,1986,33(2):1141-1151.
[15]Li Tong,Shang Pengjian.A multifractal approach topalmprint recognition[J].Chinese Physics,2007,56(8):4393-4400.
[16]Brown G,Micho G,Pevriere J.On the multifractalanalysis[J].Journal of Stat Phys,1992,66(3/4):775-790.
[17]周炜星,王延杰,于遵宏.多重分形奇异谱的几何特性I.经典Renyi定义法[J].华东理工大学学报,2000,26(4):385-389.Zhou Weixing,Wang Yanjie,Yu Zunhong.Geomet-rical characteristics of singularity spectra of multi-fractals[J].Journal of East China University of Sci-ence and Technology,2000,26(4):385-389.
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