Rolling Bearing Fault Diagnosis Based on Singular Value Decomposition and Composite Square Envelope Spectrum
It was difficult to select the fault points of sub signals and the number of rows of Hankel matrix in traditional SVD fault diagnosis methods.A rolling bearing diagnosis method based on singular value decomposition and composite square enve-lope spectrum was proposed.Firstly,the difference between two commonly used sub signal reconstruction methods was analyzed.Then,DR index was introduced to determine the singular value decomposition sequence,and the optimal range of Hankel matrix rows for bearing fault diagnosis was obtained by numerical simulation.Due to the distortion of the sub signals and the singular value distribution of the energy distribution between the sub signals,the anti angle average method and the composite square en-velope spectrum are used to diagnose the bearing fault.Finally,experiments show that the proposed method can achieve effective bearing fault diagnosis without prior knowledge.
Rolling BearingFault DiagnosisSingular Value DecompositionSquare Envelope Spectrum
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