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Advanced algorithms to enhance signal to noise ratio of peel ply at the bondline of out-of-autoclave composite assemblies
LeMay, Gary S.
LeMay, Gary S.
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t16077_LeMay.pdf
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2016-12
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Electronic thesis
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Electronic dissertations
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Abstract
The objective of this thesis is to develop an algorithm (based on mathematical function menus) to improve the signal to noise ratio between constituents of similar acoustic impedance in bonded out-of-autoclave carbon fiber reinforced polymer assemblies. In particular, peel ply, a release fabric that may be trapped between the adhesive and the substrate during the manufacturing process. The assemblies consist of a pre-cured resin infused out-of-autoclave 3D woven fabric preform bonded to a pre-cured out-of-autoclave prepreg fabric substrate. Conventional ultrasonic nondestructive testing techniques and analysis software cannot consistently achieve signal to noise ratios that meet quantifiable rejection thresholds of accurately sized peel ply inserts at the bonded interface (i.e. bondline) of the aforementioned assemblies. To demonstrate the approach, ultrasonic pulse echo with full waveform capture was used to inspect a reference standard (i.e. representation of configuration and complexity of the part to be inspected) with peel ply inserts (sized according to minimum detectable requirements) placed between the film adhesive and the 3D woven fabric preform. The ultrasonic signal was produced by a 64 element array transducer with a central frequency of 2.8 Megahertz, utilizing a customary shoe and water bubbler. Waveform post-acquisition analysis with post processing software was used to analyze and enhance the signal response between the peel ply and the bondline resulting in the final algorithm. To verify the results, the signal to noise ratio of each insert was calculated for both the raw and processed data. As the measure of detectability, the method relies on principles of statistical measurement to provide an industry standard of 3:1 as the signal to noise response.
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Thesis (M.S.)--Wichita State University, College of Engineering, Dept. of Mechanical Engineering
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Wichita State University
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Copyright 2016 by Gary S. LeMay