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Title: Machine Vision Tests for Spent Fuel Scrap Characteristics

Abstract

The purpose of this work is to perform a feasibility test of a Machine Vision system for potential use at the Hanford K basins during spent nuclear fuel (SNF) operations. This report documents the testing performed to establish functionality of the system including quantitative assessment of results. Fauske and Associates, Inc., which has been intimately involved in development of the SNF safety basis, has teamed with Agris-Schoen Vision Systems, experts in robotics, tele-robotics, and Machine Vision, for this work.

Authors:
Publication Date:
Research Org.:
Fluor Hanford, Richland, WA (United States)
Sponsoring Org.:
ENVIRONMENTAL MANAGEMENT (US)
OSTI Identifier:
803042
Report Number(s):
SNF-6143, Rev.0
EDT-629022; TRN: US0300227
DOE Contract Number:  
AC06-96RL13200
Resource Type:
Technical Report
Resource Relation:
Other Information: PBD: 27 Apr 2000
Country of Publication:
United States
Language:
English
Subject:
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS; NUCLEAR FUELS; SAFETY; SCRAP; SPENT FUELS; TESTING; VISION; MACHINERY

Citation Formats

BERGER, W W. Machine Vision Tests for Spent Fuel Scrap Characteristics. United States: N. p., 2000. Web. doi:10.2172/803042.
BERGER, W W. Machine Vision Tests for Spent Fuel Scrap Characteristics. United States. https://doi.org/10.2172/803042
BERGER, W W. 2000. "Machine Vision Tests for Spent Fuel Scrap Characteristics". United States. https://doi.org/10.2172/803042. https://www.osti.gov/servlets/purl/803042.
@article{osti_803042,
title = {Machine Vision Tests for Spent Fuel Scrap Characteristics},
author = {BERGER, W W},
abstractNote = {The purpose of this work is to perform a feasibility test of a Machine Vision system for potential use at the Hanford K basins during spent nuclear fuel (SNF) operations. This report documents the testing performed to establish functionality of the system including quantitative assessment of results. Fauske and Associates, Inc., which has been intimately involved in development of the SNF safety basis, has teamed with Agris-Schoen Vision Systems, experts in robotics, tele-robotics, and Machine Vision, for this work.},
doi = {10.2172/803042},
url = {https://www.osti.gov/biblio/803042}, journal = {},
number = ,
volume = ,
place = {United States},
year = {Thu Apr 27 00:00:00 EDT 2000},
month = {Thu Apr 27 00:00:00 EDT 2000}
}