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Gear Tooth Wear Detection Algorithm
NTRS Full-Text: Click to View  [PDF Size: 5.3 MB]
Author and Affiliation:
Delgado, Irebert R.(NASA Glenn Research Center, Cleveland, OH, United States)
Abstract: Vibration-based condition indicators continue to be developed for Health Usage Monitoring of rotorcraft gearboxes. Testing performed at NASA Glenn Research Center have shown correlations between specific condition indicators and specific types of gear wear. To speed up the detection and analysis of gear teeth, an image detection program based on the Viola-Jones algorithm was trained to automatically detect spiral bevel gear wear pitting. The detector was tested using a training set of gear wear pictures and a blind set of gear wear pictures. The detector accuracy for the training set was 75 percent while the accuracy for the blind set was 15 percent. Further improvements on the accuracy of the detector are required but preliminary results have shown its ability to automatically detect gear tooth wear. The trained detector would be used to quickly evaluate a set of gear or pinion pictures for pits, spalls, or abrasive wear. The results could then be used to correlate with vibration or oil debris data. In general, the program could be retrained to detect features of interest from pictures of a component taken over a period of time.
Publication Date: Jul 01, 2015
Document ID:
20170005246
(Acquired Jun 13, 2017)
Subject Category: AERONAUTICS (GENERAL)
Report/Patent Number: NASA/TM-2015-218830, E-19102
Document Type: Technical Report
Contract/Grant/Task Num: WBS 664817.02.03.02.03.02
Financial Sponsor: NASA Glenn Research Center; Cleveland, OH, United States
Organization Source: NASA Glenn Research Center; Cleveland, OH, United States
Description: 20p; In English
Distribution Limits: Unclassified; Publicly available; Unlimited
Rights: No Copyright
NASA Terms: GEAR TEETH; ALGORITHMS; WEAR; TRANSMISSIONS (MACHINE ELEMENTS); GEARS; VIBRATION; DETECTION; ROTARY WING AIRCRAFT; SPIRAL BEVEL GEARS; PITTING; ABRASION
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