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  • Isomap and deep belief network-based machine health combined assessment model
    Yin, Aijun ...
    This paper presents a novel combined assessment model (CAM) for machine health assessment, in which 38 original features of the vibration signal were extracted from time domain analysis, frequency ... domain analysis, and wavelet packet transform (WPT), following which the nonlinear global algorithm Isomap was adopted for dimensionality reduction and extraction of the more representative features. Next, the acquired low-dimensional features array is input into the well trained deep belief network (DBN) model to evaluate the performance status of the bearing. Finally, after the bearing accelerated degradation data from Cincinnati University were investigated for further research, through the comparison experiments with two other popular dimensionality reduction methods (principal component analysis (PCA) and Laplacian Eigenmaps) and two other intelligent assessment algorithms (hidden Markov model (HMM) and back-propagation neural network (BPNN), the proposed CAM has been proved to be more sensitive to the incipient fault and more effective for the evaluation of bearing performance degradation.
    Vir: Strojniški vestnik = Journal of mechanical engineering. - ISSN 0039-2480 (Vol. 62, no. 12, Dec. 2016, str. 740-750, SI 125)
    Vrsta gradiva - članek, sestavni del
    Leto - 2016
    Jezik - angleški
    COBISS.SI-ID - 15164699

    Povezava(-e):

    Digitalna knjižnica Slovenije - dLib.si
    DOI

vir: Strojniški vestnik = Journal of mechanical engineering. - ISSN 0039-2480 (Vol. 62, no. 12, Dec. 2016, str. 740-750, SI 125)

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