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contributor authorRamasamy, Suresh K.
contributor authorRaja, Jayaraman
contributor authorBoudreau, Brian D.
date accessioned2017-05-09T01:01:45Z
date available2017-05-09T01:01:45Z
date issued2013
identifier issn2166-0468
identifier otherjmnm_1_1_011004.pdf
identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/152851
description abstractInterdisciplinary research efforts have started focusing on the development of multiscale models and development of designer multiscale surfaces exhibiting specific properties at different scales for a specific purpose. With the rapid evolution of these new engineered surfaces for microelectromechanical systems (MEMS), microfluidics, etc., there is a strong need for developing tools to measure and characterize these surfaces at different scales. In order to obtain all meaningful details of the surface at various required scales, one is left with the only option of measuring the surface using multiple technologies using a combination of instruments. The majority of hardwarebased approaches focus on the development of systems housing multiple technologies/capabilities into a single frame. These systems enable the user to obtain different surface maps using various technologies, but the user does not readily have the ability to combine all the obtained data into one single dataset. The effective approach toward multiscale measurement and characterization would be to use the individual measurement tools and finding a method to relate the individual coordinate systems and use an offline virtual tool to unify, manipulate, segment, merge, and retrieve data. Shape primitives and focusbased fusion strategies cannot be used as every data point in the data sets under consideration has to be treated as essentially at optimal focus. A multiscale data fusion strategy results in edge effects on nonplanar and high aspect ratio surfaces. An optimized fusion strategy, the “FWR method,â€‌ for the surface metrology domain is proposed where the subimages obtained from discrete wavelet frame (DWF) were separated into three regimes—form, waviness, and roughness—and fusion was not performed on subimages in the form regime. This approach effectively eliminates the edge effects. Individual datapointlevel fusion was successfully demonstrated on Fresnel microlens array surface data as a case study of a nondirectional engineered surface with high aspect ratio.
publisherThe American Society of Mechanical Engineers (ASME)
titleData Fusion Strategy for Multiscale Surface Measurements
typeJournal Paper
journal volume1
journal issue1
journal titleJournal of Micro and Nano
identifier doi10.1115/1.4023755
journal fristpage11004
journal lastpage11004
identifier eissn1932-619X
treeJournal of Micro and Nano-Manufacturing:;2013:;volume( 001 ):;issue: 001
contenttypeFulltext


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