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EMD and AR model-based fault diagnosis method of rolling bearings

Conditions and fault patterns produced by this method each of the template feature vector, calculation of the signal was diagnosed with the template feature vector among the feature vectors Maha-lanobis distance,[link widoczny dla zalogowanych], finally select the appropriate weighting factors derived synthetic discriminant distance, whichever is the smallest from the Comprehensive Assessment of the status of corresponding signal to be diagnosed type of state recognition, which can determine the state of rolling bearings and fault type. Analysis of experimental signals to verify the combination of EMD and AR model can be applied to roller bearing fault diagnosis, fault diagnosis of rolling bearings provide a new approach. References 1 Ding Yulan, stone to Germany. Machinery fault diagnosis technology. Shanghai: Shanghai Science and Technology Literature Press ,1994:225-23O2 Liutian Xiong, Zheng Minggang, Mr Justice can, and so on. AR model and fractal geometry in the equipment condition monitoring application. Mechanical strength, 2001; 23 (1) :61-653HuangNE, ShenZ, LongSR. Theempiricalmodede-compositionandtheHilbertspectrumfornonlinearandnon-stationarytimeseriesanalysis. In: Proc. R. Soc. Lond. A,[link widoczny dla zalogowanych], 1998; 454:9 O3-9954HuangNE, ShenZ,[link widoczny dla zalogowanych], LongSR. Anewviewofnonlin-earwaterwaves! TheHilbertSpectrum. Annu. Rev. FluidMech. , 1999; 31; 417-4575 Yang Shuzi,[link widoczny dla zalogowanych], Wu Ya. Application of time series analysis (I-). Wuhan: Huazhong University Press ,1992:31-3566 Fan Jincheng, lining epithelial. Data analysis. Beijing; Science Press, 2002:】 59-162AFaultDiagnosisApproachforRollerBearingsBasedonEMDMethodandARModelYuDejieChengJunshengYangYu (CollegeofMechanicalandAutomotiveEngineering, HunanUniversity, Changsha, 410082, China) Abstract: AfaultdiagnosisapproachforrollerbearingbasedonEMD (EmpiricalModeDecomposition) methodandARrood-elisproposed. TheEMDmethodisusedtOdecomposethevibrationsignalofarollerbearingintoanumberofintrinsicmodefunctioncomponentsandthentheARmodelofeachIMFcomponentisestablished. Theaut0 a regressiVeparametersandthevarianceofremnantareregardedasthefeaturevectors. ThedistancecriterionfunctionisusedtOidentifytheconditionandfaultpatternofrollerbearings. PracticalexamplesshowthattheproposedapproachcanbeappliedtOtherollerbearingfaultdiagnosiseffectively. Keywords: featurevectors; EMDmethod; ARmodel; distancecriterionfunction first author: De-Jie, male, professor,[link widoczny dla zalogowanych], Ph.D., 1957. Tel: (0731) 8823191; E-mail: djyu @ hnv. net. cn

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