Embry Riddle Aeronautical University
Detection of Fatigue Crack Growth in a Simulated Aircraft Fuselage
Abstract
dc:description.abstract<p>Acoustic emission (AE) nondestructive testing can detect fatigue cracks as they occur in complex structures. One use for AE has been in-flight detection of fatigue cracks in aircraft. The KC-135 aircraft were successfully monitored as early as 1979. The main problem with this and subsequent applications was an unfavorable signal to noise ratio, the key being to separate the small amplitude crack signals from the large amplitude ambient noise. This was accomplished here through the use of a Kohonen self-organizing map (SOM) neural network.</p> <p>In order to simulate a fuselage undergoing fatigue, a pressure vessel was constructed from a 0.040 inch thick 2024-T3 aluminum cylinder. The vessel contained a rivet line, a round hole with a notch filed in it to provide a stress concentration, and a repair patch and was cyclically pressurized from 20 to 80 psi in order to fatigue the aluminum and generate typical in-flight signals. During the test, AE sensors, powered by a data acquisition system, collected the AE parameter data from metal rubbing at the patch, rivet fretting at the rivet line, and fatigue crack propagation at the stress concentration. The SOM successfully separated the crack signals from the rivet and rubbing signals. A prototype system is currently being built by Martingale Research Corporation to provide aircraft with a real time in-flight fatigue crack growth monitoring capability.</p>
Degree
thesis:*- Name thesis:degree_name
- Master of Science in Aerospace Engineering
- Level thesis:degree_level
- Thesis - Open Access
- Discipline thesis:degree_discipline
- Aerospace Engineering
- Year
- 1996
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Marsden, Michael Lee
- Contributors dc:contributor
-
- Eric v. K. Hill
- Frank J. Radosta
- Christopher J. Raczkowski
Subjects
dc:subject × 7Identifiers
dc:identifier.*- Repository record dc:identifier
- https://commons.erau.edu/db-theses/133
- OAI identifier oai:identifier
- oai:commons.erau.edu:db-theses-1184