Rolling element bearing diagnosis based on probability box theory

DOI10.1016/J.APM.2019.10.068zbMath1481.94163OpenAlexW2984270427WikidataQ126836714 ScholiaQ126836714MaRDI QIDQ1989019

Yi Du, Hong Tang, Hong-Liang Dai

Publication date: 24 April 2020

Published in: Applied Mathematical Modelling (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.apm.2019.10.068

zbMATH Keywords

feature extractionrolling element bearingcompound fault detectionprobability box theory

Mathematics Subject Classification ID

Applications of statistics in engineering and industry; control charts (62P30) Foundations and philosophical topics in statistics (62A01) Fault detection; testing in circuits and networks (94C12)

Related Items (2)

Mechanical characteristics and nonlinear dynamic response analysis of rotor-bearing-coupling system ⋮ A wavelet neural network informed by time-domain signal preprocessing for bearing remaining useful life prediction

Cites Work

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• Modeling of the safe region based on support vector data description for health assessment of wheelset bearings
• Local defect modelling and nonlinear dynamic analysis for the inter-shaft bearing in a dual-rotor system
• Possibility theory, probability theory and multiple-valued logics: a clarification

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