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Data Visualization for Statistical Analysis and Discovery in Container Surface Characterization at the Nano-Scale and Micro-Scale

Visualization is used for stainless steel container wall and lid cross section characterization. Two specific types of containers are examined: 3013 and SAVY. The container wall examined is from a sample of the inner container of a 3013 container. The inner lid cross section examined is from a SAVY container. Laser confocal microscope data and photographic data are used to determine features of the surfaces. The surface features are then characterized by various feature statistics, such as, maximum depth, area, eccentricity, and others. The purpose of this pilot study is to demonstrate the effectiveness of using the methodology to detect potential corrosion events on the inner container surfaces. The features are used to quantify these corrosion events. An automatic image analysis system uses this methodology to classify images for possible further human analysis by flagging possible corrosion events. A manual image analysis methodology is used to determine the amount of MnS on the SAVY container lid cross section. Visualization is an integral component of the analysis methodology.

Identiferoai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:32808
Date25 January 2019
CreatorsWendelberger, James George, Smith, Paul Herrick
Source SetsHochschulschriftenserver (HSSS) der SLUB Dresden
LanguageEnglish
Detected LanguageEnglish
Typedoc-type:conferenceObject, info:eu-repo/semantics/conferenceObject, doc-type:Text
Rightsinfo:eu-repo/semantics/openAccess
Relationurn:nbn:de:bsz:15-qucosa2-327974, qucosa:32797

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