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- W1982316574 abstract "Maintenance is an important issue for aerospace systems, since they are in service beyond their designed lifetime.This requires scheduled inspections and damage repair before failure. Research is in progress to develop a structuralhealth monitoring system (SHMS) to improve this maintenance routine. Ultrasonic testing, utilizing a system ofpiezoelectric actuators and sensors, is a promising concept Measured wave signals are compared with signals forpreviously scanned states. Changes to the signal could be the result of damage to the component. This paper focuseson analyzing the differences of states, using artificial neural networks. Neural network analysis has the potential ofcreating a SHMS of greater ability and processing. Experiments were performed on a thin, flat aluminum panel.Ultrasonic actuators and sensors were installed and a baseline scan was performed on the undamaged panel.Simulated damage was introduced in specific areas, and scans were conducted for several damaged states. Neuralnetworks were created to assess the changing conditions of the panel. The system was later tested on a lap jointspecimen to confirm the abilities of the neural network. This form of analysis performed well at locating andquantifying areas of change within the structure. The neural network performance indicated that it has a role in theSHMS of aerospace structures." @default.
- W1982316574 created "2016-06-24" @default.
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- W1982316574 date "2009-03-26" @default.
- W1982316574 modified "2023-09-23" @default.
- W1982316574 title "Neural network approach of active ultrasonic signals for structural health monitoring analysis" @default.
- W1982316574 doi "https://doi.org/10.1117/12.815503" @default.
- W1982316574 hasPublicationYear "2009" @default.
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