A review of feature extraction methods in vibration-based condition monitoring and its application for degradation trend estimation of low-speed slew bearing

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...

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Main Authors:	Caesarendra, Wahyu, Tjahjowidodo, Tegoeh
Other Authors:	School of Mechanical and Aerospace Engineering
Format:	Article
Language:	English
Published:	2018
Subjects:	DRNTU::Engineering::Mechanical engineering Vibration-based Condition Monitoring Feature Extraction
Online Access:	https://hdl.handle.net/10356/88424 http://hdl.handle.net/10220/45772
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Institution:	Nanyang Technological University
Language:	English

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spelling	sg-ntu-dr.10356-884242023-03-04T17:16:48Z A review of feature extraction methods in vibration-based condition monitoring and its application for degradation trend estimation of low-speed slew bearing Caesarendra, Wahyu Tjahjowidodo, Tegoeh School of Mechanical and Aerospace Engineering DRNTU::Engineering::Mechanical engineering Vibration-based Condition Monitoring Feature Extraction 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. Published version 2018-08-30T08:24:36Z 2019-12-06T17:03:03Z 2018-08-30T08:24:36Z 2019-12-06T17:03:03Z 2017 Journal Article 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 2075-1702 https://hdl.handle.net/10356/88424 http://hdl.handle.net/10220/45772 10.3390/machines5040021 en Machines © 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/). 28 p. application/pdf
institution	Nanyang Technological University
building	NTU Library
continent	Asia
country	Singapore Singapore
content_provider	NTU Library
collection	DR-NTU
language	English
topic	DRNTU::Engineering::Mechanical engineering Vibration-based Condition Monitoring Feature Extraction
spellingShingle	DRNTU::Engineering::Mechanical engineering Vibration-based Condition Monitoring Feature Extraction Caesarendra, Wahyu Tjahjowidodo, Tegoeh A review of feature extraction methods in vibration-based condition monitoring and its application for degradation trend estimation of low-speed slew bearing
description	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.
author2	School of Mechanical and Aerospace Engineering
author_facet	School of Mechanical and Aerospace Engineering Caesarendra, Wahyu Tjahjowidodo, Tegoeh
format	Article
author	Caesarendra, Wahyu Tjahjowidodo, Tegoeh
author_sort	Caesarendra, Wahyu
title	A review of feature extraction methods in vibration-based condition monitoring and its application for degradation trend estimation of low-speed slew bearing
title_short	A review of feature extraction methods in vibration-based condition monitoring and its application for degradation trend estimation of low-speed slew bearing
title_full	A review of feature extraction methods in vibration-based condition monitoring and its application for degradation trend estimation of low-speed slew bearing
title_fullStr	A review of feature extraction methods in vibration-based condition monitoring and its application for degradation trend estimation of low-speed slew bearing
title_full_unstemmed	A review of feature extraction methods in vibration-based condition monitoring and its application for degradation trend estimation of low-speed slew bearing
title_sort	review of feature extraction methods in vibration-based condition monitoring and its application for degradation trend estimation of low-speed slew bearing
publishDate	2018
url	https://hdl.handle.net/10356/88424 http://hdl.handle.net/10220/45772
_version_	1759858010336788480

A review of feature extraction methods in vibration-based condition monitoring and its application for degradation trend estimation of low-speed slew bearing

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