Gear Damage Detection Using Oil Debris Analysis

TITLE AND SUBTITLE:
Gear Damage Detection Using Oil Debris Analysis

AUTHOR(S):
Paula J. Dempsey

REPORT DATE:
September 2001

FUNDING NUMBERS:
WU-712-30-13-00

PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES):
National Aeronautics and Space Administration
John H. Glenn Research Center at Lewis Field
Cleveland, Ohio 44135-3191

PERFORMING ORGANIZATION REPORT NUMBER:
E-12789

SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES):
National Aeronautics and Space Administration
Washington, DC 20546-0001

REPORT TYPE AND DATES COVERED:
Technical Memorandum

SPONSORING/MONITORING AGENCY REPORT NUMBER:
NASA TM-2001-210936

SUPPLEMENTARY NOTES:
Prepared for the 14th International Congress and Exhibition on Condition Monitoring and Diagnostic Engineering Management cosponsored by The University of Manchester, COMADEM International, Society for Machinery Failure Prevention Technology, Holroyd Instruments, University of Tennessee, and STLE, Manchester, United Kingdom, September 4-6, 2001. Responsible person, Paula J. Dempsey, organization code 5950, 216-433-3398.

ABSTRACT:
The purpose of this paper was to verify, when using an oil debris sensor, that accumulated mass predicts gear pitting damage and to identify a method to set threshold limits for damaged gears. Oil debris data was collected from 8 experiments with no damage and 8 with pitting damage in the NASA Glenn Spur Gear Fatigue Rig. Oil debris feature analysis was performed on this data. Video images of damage progression were also collected from 6 of the experiments with pitting damage. During each test, data from an oil debris sensor was monitored and recorded for the occurrence of pitting damage. The data measured from the oil debris sensor during experiments with damage and with no damage was used to identify membership functions to build a simple fuzzy logic model. Using fuzzy logic techniques and the oil debris data, threshold limits were defined that discriminate between stages of pitting wear. Results indicate accumulated mass combined with fuzzy logic analysis techniques is a good predictor of pitting damage on spur gears.

SUBJECT TERMS:
Gears; Transmissions; Oil debris sensor; Damage detection;
Damage assessment; Health monitoring; Pitting fatigue

NUMBER OF PAGES:
16

PDF AVAILABLE FROM URL:
2001/TM-2001-210936.pdf
( 602 KB )

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