| Issue |
MATEC Web Conf.
Volume 255, 2019
Engineering Application of Artificial Intelligence Conference 2018 (EAAIC 2018)
|
|
|---|---|---|
| Article Number | 02017 | |
| Number of page(s) | 7 | |
| Section | Smart Manufacturing and Industrial 4.0 | |
| DOI | https://doi.org/10.1051/matecconf/201925502017 | |
| Published online | 16 January 2019 | |
A Review on Variational Mode Decomposition for Rotating Machinery Diagnosis
1 Institute of Noise and Vibration, Universiti Teknologi Malaysia, Jalan Sultan Yahya Petra, 54100 Kuala Lumpur, Malaysia
2 Sekolah Kejuruteraan Mekanikal, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia
* Corresponding author: firdaus060609@gmail.com
Signal processing method is very important in most diagnosis approach for rotating machinery due to non-linearity, non-stationary and noise signals. Recently, a new adaptive signal decomposition method has been proposed by Dragomiretskiy and Zosso known as variational mode decomposition (VMD). The VMD method has merit in solving mode mixing problem in most conventional signal decomposition method. This paper aims to review the applications of the VMD method in rotating machinery diagnosis. The advantages and limitations of the VMD method are discussed. Current solution on VMD limitation also have been review and discussed. Lastly, the future research suggestion has been pointed out in order to enhance the performance of the VMD method on rotating machinery diagnosis.
© The Authors, published by EDP Sciences, 2019
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