|
Activity Number:
|
27
- SDNS Speed Session
|
|
Type:
|
Contributed
|
|
Date/Time:
|
Sunday, August 8, 2021 : 1:30 PM to 3:20 PM
|
|
Sponsor:
|
Section on Statistics in Defense and National Security
|
|
Abstract #318311
|
|
|
Title:
|
Identification and Quantification of Potential Crack Features on Hazardous Material Container Surfaces Using Wide Angle Measurement Intensity Data
|
|
Author(s):
|
James G. Wendelberger*
|
|
Companies:
|
Los Alamos National Laboratory
|
|
Keywords:
|
|
|
Abstract:
|
Data is acquired by destructive analysis of a hazardous material stainless steel container. The acquisition is with a Wide Angle Measurement System (WAMS) resulting in WAMS binary data files. These binary files are translated to image intensity input data for a Matlab program. The Matlab program is used to detect potential crack features on the images by an image feature identification algorithm. The image feature identification algorithm identifies contiguous elongated features of similar intensity. It links features with similar orientation and proximity together to estimate a potential crack feature. These potential crack features are then ranked based upon their relationship to the expected number of intensity pixels that may have occurred randomly in the feature region. A user may then either probe identified features of interest on the intensity image by a simple mouse click or examine features based upon the potential feature crack rank. The final step is to determine classification and misclassification probabilities by comparison to higher resolution data measured with a laser confocal microscope (LCM).
|
Authors who are presenting talks have a * after their name.
Back to the full JSM 2021 program
|
