R. Uma Maheswari1,*, R. Umamaheswari2
Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 479-488, 2020, DOI:10.32604/iasc.2020.013924
Abstract To enhance the predictive condition-based maintenance (CBMS), a reliable
automatic Drivetrain fault detection technique based on vibration monitoring is
proposed. Accelerometer sensors are mounted on a wind turbine drivetrain at
different spatial locations to measure the vibration from multiple vibration
sources. In this work, multi-channel signals are fused and monocomponent
modes of oscillation are reconstructed by the Multivariate Empirical Mode
Decomposition (MEMD) Technique. Noise assisted methodology is adapted to
palliate the mixing of modes with common frequency scales. The instantaneous
amplitude envelope and instantaneous frequency are estimated with the Hilbert
transform. Low order and high order statistical moments, signal feature… More >
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