Spiral Bevel Gear Damage Detection Using Decision Fusion Analysis

Abstract

A diagnostic tool for detecting damage to spiral bevel gears was developed. Two different monitoring technologies, oil debris analysis and vibration, were integrated using data fusion into a health monitoring system for detecting surface fatigue pitting damage on gears. This integrated system showed improved detection and decision-making capabilities as compared to using individual monitoring technologies. This diagnostic tool was evaluated by collecting vibration and oil debris data from fatigue tests performed in the NASA Glenn Spiral Bevel Gear Fatigue Rigs. Data was collected during experiments performed in this test rig when pitting damage occurred. Results show that combining the vibration and oil debris measurement technologies improves the detection of pitting damage on spiral bevel gears.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2002
Accession Number
ADA411722

Entities

People

  • Abdollah A. Afjeh
  • Paula J. Dempsey
  • Robert F. Handschuh

Organizations

  • National Aeronautics and Space Administration

Tags

Communities of Interest

  • Human Systems
  • Sensors

DTIC Thesaurus Topics

  • Damage Detection
  • Data Fusion
  • Databases
  • Detection
  • Detectors
  • Electronic Mail
  • Fatigue Tests (Mechanics)
  • Fuzzy Logic
  • Fuzzy Sets
  • Gears
  • Measurement
  • Military Research
  • Monitoring
  • Space Sciences
  • Spiral Bevel Gears
  • Standards
  • Test Facilities

Readers

  • Computer Vision.
  • Structural Health Monitoring of Composite Structures.
  • Tribology (the study of the boundary interaction between sliding surfaces, lubrication, wear and friction).