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The Global ETD Search service is a free service for researchers
to find electronic theses and dissertations. This service is
provided by the
Networked Digital Library of Theses and Dissertations.
Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
Search results
Showing 1 to 10 of 17 (0.015 seconds)| 1 |
Process analysis software for draw bending of small diameter thin walled tubesCritchley, Katherine January 2002 (has links)
No description available.
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Nonlinear dynamic process monitoring using kernel methodsSamuel, Raphael Tari January 2016 (has links)
The application of kernel methods in process monitoring is well established. How- ever, there is need to extend existing techniques using novel implementation strate- gies in order to improve process monitoring performance. For example, process monitoring using kernel principal component analysis (KPCA) have been reported. Nevertheless, the e ect of combining kernel density estimation (KDE)-based control limits with KPCA for nonlinear process monitoring has not been adequately investi- gated and documented. Therefore, process monitoring using KPCA and KDE-based control limits is carried out in this work. A new KPCA-KDE fault identi cation technique is also proposed. Furthermore, most process systems are complex and data collected from them have more than one characteristic. Therefore, three techniques are developed in this work to capture more than one process behaviour. These include the linear latent variable-CVA (LLV-CVA), kernel CVA using QR decomposition (KCVA-QRD) and kernel latent variable-CVA (KLV-CVA). LLV-CVA captures both linear and dynamic relations in the process variables. On the other hand, KCVA-QRD and KLV-CVA account for both nonlinearity and pro- cess dynamics. The CVA with kernel density estimation (CVA-KDE) technique reported does not address the nonlinear problem directly while the regular kernel CVA approach require regularisation of the constructed kernel data to avoid com- putational instability. However, this compromises process monitoring performance. The results of the work showed that KPCA-KDE is more robust and detected faults higher and earlier than the KPCA technique based on Gaussian assumption of process data. The nonlinear dynamic methods proposed also performed better than the aforementioned existing techniques without employing the ridge-type regularisation.
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Contrast transfer in bright field electron microscopy of amorphous specimensJenkins, W. K. January 1980 (has links)
No description available.
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Photometric observations of auroral oscillationsSingh, S. January 1980 (has links)
No description available.
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Assessing materials for use as outdoor insulationWatson, J. F. January 1980 (has links)
No description available.
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Design methods for production machinery companiesGouvinhas, Reidson Pereira January 1998 (has links)
No description available.
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Far infra-red spectroscopy at high pressuresShawyer, M. S. January 1980 (has links)
No description available.
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Raman spectroscopy from electrode surfacesPemble, M. E. January 1980 (has links)
No description available.
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Emissive mode operation of the scanning electron microscopeSanger, C. C. January 1980 (has links)
No description available.
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Mass flow measurement of solids in gravity conveyors using flow noise techniqueKwan, H. K. January 1981 (has links)
No description available.
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