Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/88424
Title: A review of feature extraction methods in vibration-based condition monitoring and its application for degradation trend estimation of low-speed slew bearing
Authors: Caesarendra, Wahyu
Tjahjowidodo, Tegoeh
Keywords: DRNTU::Engineering::Mechanical engineering
Vibration-based Condition Monitoring
Feature Extraction
Issue Date: 2017
Source: Caesarendra, W., & Tjahjowidodo, T. (2017). A review of feature extraction methods in vibration-based condition monitoring and its application for degradation trend estimation of low-speed slew bearing. Machines, 5(4), 21-. doi:10.3390/machines5040021
Series/Report no.: Machines
Abstract: This paper presents an empirical study of feature extraction methods for the application of low-speed slew bearing condition monitoring. The aim of the study is to find the proper features that represent the degradation condition of slew bearing rotating at very low speed (≈ 1 r/min) with naturally defect. The literature study of existing research, related to feature extraction methods or algorithms in a wide range of applications such as vibration analysis, time series analysis and bio-medical signal processing, is discussed. Some features are applied in vibration slew bearing data acquired from laboratory tests. The selected features such as impulse factor, margin factor, approximate entropy and largest Lyapunov exponent (LLE) show obvious changes in bearing condition from normal condition to final failure.
URI: https://hdl.handle.net/10356/88424
http://hdl.handle.net/10220/45772
ISSN: 2075-1702
DOI: 10.3390/machines5040021
Rights: © 2017 by The Author(s). Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:MAE Journal Articles

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