Paper
10 April 2008 Active ultrasonic joint integrity adjudication for real-time structural health monitoring
Author Affiliations +
Abstract
The Operationally Responsive Space (ORS) strategy hinges, in part, on realizing technologies which can facilitate the rapid deployment of satellites. Presently, preflight qualification testing and vehicle integration processes are time consumptive and pose as two significant hurdles which must be overcome to effectively enhance US space asset deployment responsiveness. There is a growing demand for innovative embedded Structural Health Monitoring (SHM) technologies which can be seamlessly incorporated onto payload hardware and function in parallel with satellite construction to mitigate lengthy preflight checkout procedures. In this effort our work is focused on the development of a joint connectivity monitoring algorithm which can detect, locate, and assess preload in bolted joint assemblies. Our technology leverages inexpensive, lightweight, flexible thin-film macro-fiber composite (MFC) sensor/actuators with a novel online, data-driven signal processing algorithm. This algorithm inherently relies upon Chaotic Guided Ultrasonic Waves (CGUW) and a novel cross-prediction error classification technique. The efficacy of the monitoring algorithm is evaluated through a series of numerical simulations and experimentally in two test configurations. We conclude with a discussion surrounding further development of this approach into a commercial product as a real-time flight readiness indicator.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Erik H. Clayton, Matthew B. Kennel, Timothy R. Fasel, Michael D. Todd, Mark C. Stabb, and Brandon J. Arritt "Active ultrasonic joint integrity adjudication for real-time structural health monitoring", Proc. SPIE 6935, Health Monitoring of Structural and Biological Systems 2008, 69350M (10 April 2008); https://doi.org/10.1117/12.776347
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Cited by 11 scholarly publications.
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KEYWORDS
Autoregressive models

Structural health monitoring

Ultrasonics

Microsoft Foundation Class Library

Algorithm development

Data modeling

Signal processing

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