Degradation Trend Prediction for Rotating Machinery Using Long-Range Dependence and Particle Filter Approach

Degradation Trend Prediction for Rotating Machinery Using Long-Range Dependence and Particle Filter Approach

Timely maintenance and accurate fault prediction of rotating machinery are essential for ensuring system availability, minimizing downtime, and contributing to sustainable production. This paper proposes a novel approach based on long-range dependence (LRD) and particle filter (PF) for degradation t...

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Bibliographic Details
Main Authors: Qing Li, Steven Y. Liang
Format: Article
Language:English
Published: MDPI AG 2018-06-01
Series:Algorithms
Subjects:
long-range dependence (LRD) model
particle filter (PF)
equivalent vibration severity (EVI)
kurtosis
Hurst exponent
rotating machinery
Online Access:http://www.mdpi.com/1999-4893/11/7/89

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http://www.mdpi.com/1999-4893/11/7/89

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