This research investigates the feasibility of implementing an in-flight fatigue crack monitoring system in an airplane to identify fatigue crack growth. An acoustic emission data acquisition system coupled with a Kohonen self organizing map neural network were used to perform the analysis.
Fatigue cracking was responsible for ripping the top of a fuselage off an Aloha Airlines Boeing 737-200 as it carried passengers over the Pacific Ocean, killing some aboard. This tragedy is perhaps a precursor of problems to come, as our nation’s aircraft age. These planes experience fatigue as they perform their daily routine of ferrying passengers from location to location. Fatigue can initiate cracking within the aircraft’s structure and at least damage a small expendable part of the plane, or at most damage a vital part of the airplane leading to disaster as happened to the Aloha Airlines flight.
In an attempt to curb this sort of devastation, this research involves the development of an in-flight fatigue crack monitoring system. Such a system would have the ability to identify possible crack sources before the crack would have the chance to cause significant damage. Advantages of this type of system would be first, an obvious safety cushion, and second, lower maintenance costs because routine parts replacement and inspection could be minimized.
","abstract_html":"<p>This research investigates the feasibility of implementing an in-flight fatigue crack monitoring system in an airplane to identify fatigue crack growth. An acoustic emission data acquisition system coupled with a Kohonen self organizing map neural network were used to perform the analysis.</p> <p>Fatigue cracking was responsible for ripping the top of a fuselage off an Aloha Airlines Boeing 737-200 as it carried passengers over the Pacific Ocean, killing some aboard. This tragedy is perhaps a precursor of problems to come, as our nation’s aircraft age. These planes experience fatigue as they perform their daily routine of ferrying passengers from location to location. Fatigue can initiate cracking within the aircraft’s structure and at least damage a small expendable part of the plane, or at most damage a vital part of the airplane leading to disaster as happened to the Aloha Airlines flight.</p> <p>In an attempt to curb this sort of devastation, this research involves the development of an in-flight fatigue crack monitoring system. Such a system would have the ability to identify possible crack sources before the crack would have the chance to cause significant damage. Advantages of this type of system would be first, an obvious safety cushion, and second, lower maintenance costs because routine parts replacement and inspection could be minimized.</p>","abstract_has_math":false,"creators":["Vaughn, Samuel Gordon, III"],"institution":null,"degree_name":"Master of Science in Aerospace Engineering","degree_level":"Thesis - Open Access","degree_discipline":"Aerospace Engineering","degree_department":null,"school":null,"contributors":["Eric v. K. Hill","Frank J. Radosta","Charles W. Bishop"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":1998,"date_issued":"1998-08-01T07:00:00Z","date_published":"1998-08-01T07:00:00Z","updated_at":"2026-07-27T19:25:23Z","subjects":["fatigue","cracks","aircraft engine","cowling","Boeing 737-200","Aerospace Engineering","Aviation"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://commons.erau.edu/db-theses/222","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Eric v. K. Hill","Frank J. Radosta","Charles W. Bishop"]},{"key":"dc:creator","label":"Author","values":["Vaughn, Samuel Gordon, III"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["Aerospace Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis - Open Access"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science in Aerospace Engineering"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["fatigue","cracks","aircraft engine","cowling","Boeing 737-200","Aerospace Engineering","Aviation"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://commons.erau.edu/db-theses/222"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This research investigates the feasibility of implementing an in-flight fatigue crack monitoring system in an airplane to identify fatigue crack growth. An acoustic emission data acquisition system coupled with a Kohonen self organizing map neural network were used to perform the analysis.
Fatigue cracking was responsible for ripping the top of a fuselage off an Aloha Airlines Boeing 737-200 as it carried passengers over the Pacific Ocean, killing some aboard. This tragedy is perhaps a precursor of problems to come, as our nation’s aircraft age. These planes experience fatigue as they perform their daily routine of ferrying passengers from location to location. Fatigue can initiate cracking within the aircraft’s structure and at least damage a small expendable part of the plane, or at most damage a vital part of the airplane leading to disaster as happened to the Aloha Airlines flight.
In an attempt to curb this sort of devastation, this research involves the development of an in-flight fatigue crack monitoring system. Such a system would have the ability to identify possible crack sources before the crack would have the chance to cause significant damage. Advantages of this type of system would be first, an obvious safety cushion, and second, lower maintenance costs because routine parts replacement and inspection could be minimized.
"]},{"key":"dc:title","label":"Title","values":["In-Flight Fatigue Crack Monitoring of an Aircraft Engine Cowling"]}]}],"canonical_facts":{"dc:contributor":["Eric v. K. Hill","Frank J. Radosta","Charles W. Bishop"],"dc:creator":["Vaughn, Samuel Gordon, III"],"dc:description.abstract":["This research investigates the feasibility of implementing an in-flight fatigue crack monitoring system in an airplane to identify fatigue crack growth. An acoustic emission data acquisition system coupled with a Kohonen self organizing map neural network were used to perform the analysis.
Fatigue cracking was responsible for ripping the top of a fuselage off an Aloha Airlines Boeing 737-200 as it carried passengers over the Pacific Ocean, killing some aboard. This tragedy is perhaps a precursor of problems to come, as our nation’s aircraft age. These planes experience fatigue as they perform their daily routine of ferrying passengers from location to location. Fatigue can initiate cracking within the aircraft’s structure and at least damage a small expendable part of the plane, or at most damage a vital part of the airplane leading to disaster as happened to the Aloha Airlines flight.
In an attempt to curb this sort of devastation, this research involves the development of an in-flight fatigue crack monitoring system. Such a system would have the ability to identify possible crack sources before the crack would have the chance to cause significant damage. Advantages of this type of system would be first, an obvious safety cushion, and second, lower maintenance costs because routine parts replacement and inspection could be minimized.
"],"dc:identifier":["https://commons.erau.edu/db-theses/222"],"dc:subject":["fatigue","cracks","aircraft engine","cowling","Boeing 737-200","Aerospace Engineering","Aviation"],"dc:title":["In-Flight Fatigue Crack Monitoring of an Aircraft Engine Cowling"],"thesis:degree_discipline":["Aerospace Engineering"],"thesis:degree_level":["Thesis - Open Access"],"thesis:degree_name":["Master of Science in Aerospace Engineering"]},"updated_at":"2026-07-27T19:25:23Z"}