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Remaining useful life estimation for bearings based on segmented projection error and fuzzy inference system

Abstract : Bearings remaining useful life (RUL) estimation is crucial for condition-based maintenance of some rotating mechanics. This research aims to extract an efficient indicator of degradation to establish an RUL estimation model for bearings. For that purpose, an approach is presented based on segmented projection error (SPE) and a fuzzy inference system (FIS). The approach utilizes the time domain features of bearings vibration signals to describe the bearing degradation roughly. Thus, SPE's novel indicator, based on principal component analysis (PCA) and segmentation methods, is obtained by processing the time domain features. The SPE indicator, which effectively tracks bearings degradation, is used to develop a fuzzy inference system (FIS) by the clustering method. For illustration, a benchmark data set is used in this paper. The results show that the novel indicator SPE presented in this paper promises to predict the bearings RUL for maintenance decisions by an early warning.
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https://hal.univ-lorraine.fr/hal-03089950
Contributor : Kondo Adjallah <>
Submitted on : Tuesday, December 29, 2020 - 4:53:20 AM
Last modification on : Wednesday, December 30, 2020 - 3:07:37 AM

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  • HAL Id : hal-03089950, version 1

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Fei Huang, Alexandre Sava, Kondo H. Adjallah, Zhouhang Wang. Remaining useful life estimation for bearings based on segmented projection error and fuzzy inference system. ICMEM'2017 the 6th International Conference on Mechanical Engineering and Mechanics, Dec 2017, Metz, France. ⟨hal-03089950⟩

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