Intelligent Load Monitoring in Beam Structures

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dc.contributor.advisor Kara Peters, Committee Member en_US
dc.contributor.advisor F. G. Yuan, Committee Chair en_US
dc.contributor.advisor Fen Wu, Committee Member en_US
dc.contributor.author Li, Junping en_US
dc.date.accessioned 2010-04-02T17:59:47Z
dc.date.available 2010-04-02T17:59:47Z
dc.date.issued 2003-11-24 en_US
dc.identifier.other etd-10312002-213658 en_US
dc.identifier.uri http://www.lib.ncsu.edu/resolver/1840.16/969
dc.description.abstract A robust approach for identifying impact load location and impact force history in beam structures is presented in this thesis. Beam strain transients propagating from the impact site can be inverted to yield the impact location and force history. Solving the inverse problem consists of three parts: a transient wave model, an impact location determination, and then an impact history identification. The classical Euler-Bernoulli beam theory (EBT) is used to obtain the dynamic models of a simply-supported beam. The simulated measured strain data are utilized from the transient wave model derived from finite element method and state variable approach. A wavelet analysis using Gabor basis function is employed to determine the impact load location from strain measurements resulting from a pair of sensors which are located on the opposite side of the impact site. The information on traveling dispersive waves is described by the time-frequency representation of the transient strain data analyzed using wavelet transform. A Radial Basis Function network (RBFN) is then employed to efficiently reconstruct the impact load history from a single strain sensor. The back-propagation algorithm in conjunction with Levenberg-Marquardt method is adopted to update the parameters of RBFN by minimizing the difference between model prediction and the sensor measurements, where the transient wave model is embedded in the RBFN to guide and speed up the training process. The effect of noise on the identification of impact site and loading history is also investigated in detail. Several examples demonstrate the effectiveness of the approach. en_US
dc.rights I hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to NC State University or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report. en_US
dc.subject Load Monitoring en_US
dc.subject Radial Basis Function Networks (RBFN) en_US
dc.subject Wavelet Transform en_US
dc.title Intelligent Load Monitoring in Beam Structures en_US
dc.degree.name MS en_US
dc.degree.level thesis en_US
dc.degree.discipline Mechanical Engineering en_US


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