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Application of Teager–Kaiser Energy Operator in the Early Fault Diagnosis of Rolling Bearings

Rolling bearings are key components that support the rotation of motor shafts, operating with a quite high failure rate among all the motor components. Early bearing fault diagnosis has great significance to the operation security of motors. The main contribution of this paper is to illustrate Gauss...

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Autores principales: Shi, Xiangfu, Zhang, Zhen, Xia, Zhiling, Li, Binhua, Gu, Xin, Shi, Tingna
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9460047/
https://www.ncbi.nlm.nih.gov/pubmed/36081131
http://dx.doi.org/10.3390/s22176673
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author Shi, Xiangfu
Zhang, Zhen
Xia, Zhiling
Li, Binhua
Gu, Xin
Shi, Tingna
author_facet Shi, Xiangfu
Zhang, Zhen
Xia, Zhiling
Li, Binhua
Gu, Xin
Shi, Tingna
author_sort Shi, Xiangfu
collection PubMed
description Rolling bearings are key components that support the rotation of motor shafts, operating with a quite high failure rate among all the motor components. Early bearing fault diagnosis has great significance to the operation security of motors. The main contribution of this paper is to illustrate Gaussian white noise in bearing vibration signals seriously masks the weak fault characteristics in the diagnosis based on the Teager–Kaiser energy operator envelope, and to propose improved TKEO taking both accuracy and calculation speed into account. Improved TKEO can attenuate noise in consideration of computational efficiency while preserving information about the possible fault. The proposed method can be characterized as follows: a series of band-pass filters were set up to extract several component signals from the original vibration signals; then a denoised target signal including fault information was reconstructed by weighted summation of these component signals; finally, the Fourier spectrum of TKEO energy of the resulting target signal was used for bearing fault diagnosis. The improved TKEO was applied to a vibration signal dataset of run-to-failure rolling bearings and compared with two advanced diagnosis methods. The experimental results verify the effectiveness and superiority of the proposed method in early bearing fault detection.
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spelling pubmed-94600472022-09-10 Application of Teager–Kaiser Energy Operator in the Early Fault Diagnosis of Rolling Bearings Shi, Xiangfu Zhang, Zhen Xia, Zhiling Li, Binhua Gu, Xin Shi, Tingna Sensors (Basel) Article Rolling bearings are key components that support the rotation of motor shafts, operating with a quite high failure rate among all the motor components. Early bearing fault diagnosis has great significance to the operation security of motors. The main contribution of this paper is to illustrate Gaussian white noise in bearing vibration signals seriously masks the weak fault characteristics in the diagnosis based on the Teager–Kaiser energy operator envelope, and to propose improved TKEO taking both accuracy and calculation speed into account. Improved TKEO can attenuate noise in consideration of computational efficiency while preserving information about the possible fault. The proposed method can be characterized as follows: a series of band-pass filters were set up to extract several component signals from the original vibration signals; then a denoised target signal including fault information was reconstructed by weighted summation of these component signals; finally, the Fourier spectrum of TKEO energy of the resulting target signal was used for bearing fault diagnosis. The improved TKEO was applied to a vibration signal dataset of run-to-failure rolling bearings and compared with two advanced diagnosis methods. The experimental results verify the effectiveness and superiority of the proposed method in early bearing fault detection. MDPI 2022-09-03 /pmc/articles/PMC9460047/ /pubmed/36081131 http://dx.doi.org/10.3390/s22176673 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Shi, Xiangfu
Zhang, Zhen
Xia, Zhiling
Li, Binhua
Gu, Xin
Shi, Tingna
Application of Teager–Kaiser Energy Operator in the Early Fault Diagnosis of Rolling Bearings
title Application of Teager–Kaiser Energy Operator in the Early Fault Diagnosis of Rolling Bearings
title_full Application of Teager–Kaiser Energy Operator in the Early Fault Diagnosis of Rolling Bearings
title_fullStr Application of Teager–Kaiser Energy Operator in the Early Fault Diagnosis of Rolling Bearings
title_full_unstemmed Application of Teager–Kaiser Energy Operator in the Early Fault Diagnosis of Rolling Bearings
title_short Application of Teager–Kaiser Energy Operator in the Early Fault Diagnosis of Rolling Bearings
title_sort application of teager–kaiser energy operator in the early fault diagnosis of rolling bearings
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9460047/
https://www.ncbi.nlm.nih.gov/pubmed/36081131
http://dx.doi.org/10.3390/s22176673
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