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Steven M. Shepard

Publications -  21
Citations -  1596

Steven M. Shepard is an academic researcher. The author has contributed to research in topics: Thermography & Nondestructive testing. The author has an hindex of 17, co-authored 21 publications receiving 1471 citations.

Papers
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Journal ArticleDOI

Reconstruction and enhancement of active thermographic image sequences

TL;DR: In this paper, the authors proposed a deterministic active thermographic response is deterministic, to the extent that the postexcitation time evolution for a defect-free sample can be accurately predicted using a simple one-dimensional model.
Proceedings ArticleDOI

Advances in pulsed thermography

TL;DR: In this article, the authors developed an alternative approach to analysis of pulsed thermographic data, based on developing a parametric equation for the time history of each pixel, which provides increased spatial and temporal resolution, and significantly extends the range of defect depths and sample configurations.
Patent

System for generating thermographic images using thermographic signal reconstruction

TL;DR: In this paper, a method for compiling thermographic data including obtaining data indicative of a monotonically changing characteristic of a specimen, sequencing the data or a surrogate of the data into a plurality of groups, categorizing, within each group, the frequency distribution of an attribute of the attributes or attributes of said surrogate data, and compiling, from one or more groups, a collection of two or more of the frequency distributions.
Journal ArticleDOI

Non-destructive testing of structural composites and adhesively bonded composite joints: pulsed thermography

TL;DR: In this paper, an advanced thermal non-destructive test (NDT) method, pulsed thermography, was evaluated for its capability to assess joint quality in an adhesively bonded composite pickup truck box.
Proceedings ArticleDOI

Enhancement and reconstruction of thermographic NDT data

TL;DR: The concept of Thermographic Signal Reconstruction (TSR) is introduced as a means of enhancing defect to background contrast while reducing the amount of data that must be stored by an order of magnitude, and the mechanisms for the resulting performance improvements are considered.