Gear Crack Detection Using Tooth Analysis

Abstract

Gear cracks are typically difficult to diagnose with sufficient warning time. Significant damage must he present before algorithms detect the damage. A new feature extraction and two new detection techniques are proposed. The time synchronous averaging concept was extended from revolution-based to tooth engagement-based. The detection techniques are based on statistical comparisons among the averages for the individual teeth. These techniques were applied to a series of three seeded fault crack propagation tests. These tests were conducted on aerospace quality spur gears in a test rig. The tests were conducted at speeds ranging from 2500 to 7500 revolutions per minute and torque from 184 to 228 percent of design load. The inability to detect these cracks with high confidence may be caused by the high loading required to initiate the cracks. The results indicate that these techniques do not currently produce an indication of damage that significantly exceeds experimental scatter.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 2002
Accession Number
ADA403009

Entities

People

  • Harry J. Decker

Organizations

  • United States Army Research Laboratory

Tags

Communities of Interest

  • Sensors
  • Space

DTIC Thesaurus Topics

  • Algorithms
  • Crack Propagation
  • Cracks
  • Data Analysis
  • Databases
  • Detection
  • Electronic Mail
  • Engineering
  • Extraction
  • Feature Extraction
  • Geometry
  • Materials
  • Military Research
  • Monitoring
  • Reliability
  • Revolutions
  • Space Sciences

Readers

  • Electrical Engineering
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  • Structural Health Monitoring of Composite Structures.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • Space