Lifetime Prediction of Rolling Element Bearings using Adaptive Algorithms Based on their Vibration Trends, M.Sc. Thesis Sharif University of Technology ; Behzad, Mehdi (Supervisor)
Abstract
Rolling element bearings are the most widely used components in rotating machinery and so, estimation of their remaining useful lifetime in order to increase the reliability and availability of them is a critical issue in the field of condition monitoring of these machinery. Despite numerous researches which have tried to develop a model for precise prediction of rolling element bearings’ lifetime, there is no method which can predict their remaining lifetime exactly. The failure criterion in these components is the area of defect in their races and rolling elements. Consequently, an approach which can predict the defect area of these components is susceptible to prediction of their...
Cataloging briefLifetime Prediction of Rolling Element Bearings using Adaptive Algorithms Based on their Vibration Trends, M.Sc. Thesis Sharif University of Technology ; Behzad, Mehdi (Supervisor)
Abstract
Rolling element bearings are the most widely used components in rotating machinery and so, estimation of their remaining useful lifetime in order to increase the reliability and availability of them is a critical issue in the field of condition monitoring of these machinery. Despite numerous researches which have tried to develop a model for precise prediction of rolling element bearings’ lifetime, there is no method which can predict their remaining lifetime exactly. The failure criterion in these components is the area of defect in their races and rolling elements. Consequently, an approach which can predict the defect area of these components is susceptible to prediction of their...
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