Journal
MACHINES
Volume 5, Issue 4, Pages -Publisher
MDPI
DOI: 10.3390/machines5040021
Keywords
vibration-based condition monitoring; feature extraction; low-speed slew
Funding
- University ofWollongong, Australia through International Postgraduate Research Scholarship (IPRS)
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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 (approximate to 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.
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