New methods for statistical modeling and analysis of nondestructive evaluation data

dc.contributor.advisor William Q. Meeker Li, Ming
dc.contributor.department Statistics 2018-08-11T15:40:45.000 2020-06-30T02:36:13Z 2020-06-30T02:36:13Z Fri Jan 01 00:00:00 UTC 2010 2013-06-05 2010-01-01
dc.description.abstract <p>Statistical methods have a long history of applications in physical sciences and engineering for design of experiments and data analyses. In nondestructive evaluation (NDE) studies, standard statistical methods are described in Military Handbook 1823A as guidelines to analyze the experimental NDE data both in carefully controlled laboratory setup and field studies. However complicated data structures often demand non-traditional statistical approaches. In this dissertation, with the inspiration and needs from actual NDE data applications, we introduced several statistical methods for better description of the problem and more appropriate modeling of the data. We also discussed the potential applications of those statistical methods to other research areas.</p> <p>The dissertation is organized as following. First a brief background introduction and overview are presented at Chapter 1. Then the complementary risk noise-interference model is discussed in Chapter 2 to better describe the noise and signal relation. In Chapter 3, a direct application of the noise interference model to vibrothermography NDE experiment scalar data is presented. In Chapter 4, the matched filter technique is used to increase signal-to-noise ratio for sequence of image analysis. In Chapter 5, the physical model assisted probability of detection analyses are introduced where the underlying physical mechanism plays an important role in the data interpretation. In Chapter 6, a bivariate normal Bayesian approach is studied to efficiently handle missing information. Finally we summarize these recent NDE developments at Chapter 7.</p>
dc.format.mimetype application/pdf
dc.identifier archive/
dc.identifier.articleid 2556
dc.identifier.contextkey 2807754
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath etd/11513
dc.language.iso en
dc.source.bitstream archive/|||Fri Jan 14 18:52:11 UTC 2022
dc.subject.disciplines Statistics and Probability
dc.subject.keywords Applied statistics
dc.subject.keywords Image analysis
dc.subject.keywords Noise interference model
dc.subject.keywords Nondestructive evaluation
dc.subject.keywords Physical model assisted analysis
dc.subject.keywords Reliability
dc.title New methods for statistical modeling and analysis of nondestructive evaluation data
dc.type article
dc.type.genre dissertation
dspace.entity.type Publication
relation.isOrgUnitOfPublication 264904d9-9e66-4169-8e11-034e537ddbca dissertation Doctor of Philosophy
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