Bivariate Empirical Mode Decomposition and Its Applications in Machine Condition Monitoring

Yang, W

doi:10.1007/978-3-319-56126-4_11

Bivariate Empirical Mode Decomposition and Its Applications in Machine Condition Monitoring

Lookup NU author(s): Dr Wenxian Yang ORCiD

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Abstract

Attributed to providing a more realistic representation of the signal without the artifacts imposed by non-adaptive limitations suffered by both Fourier- and Wavelet-transform based methods, Empirical Mode Decomposition (EMD) has been widely accepted as a favored tool for interpreting nonlinear, non-stationary signals, which are often associated with the occurrence of faults or variable operations of rotating machinery. In this chapter,the fundamental theory of the EMD will be explained. But more context will be spent on discussing its two dimensional form, namely Bivariate Empirical Mode Decomposition, and the powerful capacity of this innovative technique in the application of machine condition monitoring.