Characterization of Fault Size in Bearings

Abstract

Bearings are important components in rotating machines. An initial small damage in the bearing may cause a fast degradation, which may lead to the machine breakdown. The health condition of bearings can be monitored using proven vibro-acoustic methods effective for detecting bearing faults. However, the existing bearing health indicators do not provide a reliable estimation of the fault characteristics, such as fault size and fault location. As a result, the ability to assess the severity of the bearing damage and to make maintenance decisions is limited. The presented study is a part of an ongoing research on bearing prognostics, aimed to improve the understanding of the effects of fault size on the bearing dynamics. The research methodology combines dynamic modeling of the faulty bearing with experimental validation and confirmation of model simulations.

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Document Details

Document Type
Technical Report
Publication Date
Dec 23, 2014
Accession Number
AD1002400

Entities

People

  • Gideon Kogan
  • Jacob Bortman
  • Matan Mendelovich
  • Mor Battat
  • Renata Klein
  • Yitschak Sanders

Organizations

  • Ben-Gurion University of the Negev

Tags

Communities of Interest

  • Biomedical
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Acoustic Emissions
  • Ball Bearings
  • Bearings
  • Data Acquisition
  • Data Analysis
  • Detectors
  • Dynamic Response
  • Dynamics
  • Engineering
  • Experimental Data
  • Frequency
  • Indicators
  • Manufacturing Engineering
  • Mechanical Engineering
  • Sidebands
  • Simulations
  • Vibration

Fields of Study

  • Engineering

Readers

  • Parallel and Distributed Computing.
  • Theoretical Analysis.
  • Tribology (the study of the boundary interaction between sliding surfaces, lubrication, wear and friction).