journal article·2014-10

A descriptive model of wear evolution in rolling bearings

Idriss El-Thalji, Erkki Jantunen

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Abstract

Rolling contact wear is a complex phenomenon that might involve different wear mechanisms (adhesive, abrasive, fatigue and corrosive) and different stress concentration mechanisms (asperity, dent, debris, inclusions, etc.). The interactions among these mechanisms might accelerate or decelerate the overall wear progress. Therefore, it is complicated to model and monitor the fluctuations of wear progress. The current descriptive models are either describing individual physical phenomena within rolling contact wear or describing a specific stage of wear progress. Thus, the interactions among different wear mechanisms and the transition events among different stages of wear progress are not sufficiently addressed. Therefore, the purpose of this paper is to propose a descriptive model of the wear evolution process in rolling bearings over the whole lifetime. The descriptive model utilises a wide range of empirical findings in the literature to describe the wear interactions and evolution in the five-stage scenario: running-in, steady-state, defect initiation, defect propagation, and damage growth. The new descriptive model provides the most probable scenario of wear evolution in rolling bearings, which is useful for modelling and monitoring the wear progress. It illustrates the wear evolution stages, the involved wear mechanisms in each stage, the interaction among wear mechanisms in each stage, the surface topology changes and the influencing factors within each stage. For design, condition monitoring and prognosis purposes, these aspects are significantly important to understand, model, test and monitor the wear evolution process.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Mechanical stress and fatigue analysis · Gear and Bearing Dynamics Analysis · Tribology and Wear Analysis

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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