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Application Research On The Damage Detection Of The Coplanar Electrode Capacitor In The Composite Adhesive Structure

Posted on:2017-03-11Degree:MasterType:Thesis
Country:ChinaCandidate:Y JinFull Text:PDF
GTID:2272330503982702Subject:Instrumentation engineering
Abstract/Summary:PDF Full Text Request
With the development of aerospace and aircraft industry, the thermal insulation composite material on the surface of the aircraft is more and more attention.The bonding quality of thermal insulation composite material on the surface of aircraft is directly related to the operation safety of the aircraft.At present, the bonding of the composite material mainly depends on the manual operation, and the quality of the adhesive is detected and judged by the artificial experience.However, this method can not accurately determine the bonding effect and the defect of the bonding structure, so as to constitute a hidden danger to the safe operation of the aircraft.With surface electrode capacitive lossless detection method is proposed for inhomogeneous, porous, non- conductive heat insulation type composite adhesive structure quality. And the method to detect structural bonding defect location and area.The following is the main research content of this paper.Firstly, the non destructive testing method of the thermal insulation composite material is investigated, and the feasibility of the method of the same electrode capacitance is determined.Secondly, building inspection system, the establishment of scan- Analysis of the integration of the detection platform, and to achieve the requirements of real-time detection.Thirdly, making the measured sample, setting defects at different locations and different areas in the sample on the adhesive layer.A prototype simulation model by ANSYS software, provides the theoretical foundation for this method.At last, through a large number of experiments, the experimental data of the defect detection of the bonding structure was initially obtained, and the experimental data were pretreated by the mean value method and the min max normalization method;A probabilistic neural network is trained on the preprocessed data, in order to achieve the purpose of intelligent system;finally, the two-dimensional curve can be drawn by MATLAB, which can indicate the position and area of the defect of the bonding structure.
Keywords/Search Tags:Heat Insulation Composite, Nondestructive Testing, Coplanar Electrode Capacitor, Probabilistic Neural Networks
PDF Full Text Request
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