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Erschienen in:
Advanced Signal Processing for Structural Health Monitoring Kapitel lesen Erstes Kapitel lesen

2017 | OriginalPaper | Buchkapitel

Bivariate Empirical Mode Decomposition and Its Applications in Machine Condition Monitoring

verfasst von : Wenxian Yang

Erschienen in: Structural Health Monitoring

Verlag: Springer International Publishing

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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.

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Vorheriges Kapitel Fault Diagnosis of Rotating Machinery Based on Empirical Mode Decomposition
Nächstes Kapitel Time-Frequency Demodulation Analysis Based on LMD and Its Applications
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Metadaten
Titel
Bivariate Empirical Mode Decomposition and Its Applications in Machine Condition Monitoring
verfasst von
Wenxian Yang
Copyright-Jahr
2017
Buch
Structural Health Monitoring

Print ISBN: 978-3-319-56125-7

Electronic ISBN: 978-3-319-56126-4

Copyright-Jahr: 2017

DOI
https://doi.org/10.1007/978-3-319-56126-4_11

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