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Bivariate Empirical Mode Decomposition and Its Applications in Machine Condition Monitoring

Lookup NU author(s): Dr Wenxian YangORCiD


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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.

Publication metadata

Author(s): Yang W

Series Editor(s): Yan, Ruqiang

Publication type: Book Chapter

Publication status: Published

Book Title: Structural Health Monitoring - An Advanced Signal Processing Perspective

Year: 2017

Volume: 26

Pages: 293-319

Print publication date: 30/04/2017

Acceptance date: 30/03/2017

Series Title: Smart Sensors, Measurement, Instrumentation

Publisher: Springer

Place Published: India


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

Library holdings: Search Newcastle University Library for this item

ISBN: 9783319561257