A REAL TIME COAL CONTENT ORE GRADE (C2OG) SENSOR | Zendy

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A REAL TIME COAL CONTENT ORE GRADE (C2OG) SENSOR

Author(s) -

Rand Swanson

Publication year - 2003

Publication title -

osti oai (u.s. department of energy office of scientific and technical information)

Language(s) - English

Resource type - Reports

DOI - 10.2172/821602

Subject(s) - software deployment , dolomite , coal , mining engineering , software , hyperspectral imaging , talc , engineering , computer science , geology , waste management , artificial intelligence , mineralogy , software engineering , operating system , paleontology

This eighth quarterly technical report discusses the progress made on a machine vision technique for determining coal content and preparations for Year-3 system deployment. Classification maps for coal have been generated and shown to two coal-mining executives. An application for licensing high-speed hyperspectral data analysis software from the Naval Research Laboratory (NRL) has been made. Both Western Energy and Stillwater Mining Company have offered platforms for Year-3 deployment. Barretts Minerals has expressed renewed interest in using Resonon's machine vision system for identifying dolomite in their talc ore and have agreed to provide samples to the Montana Tech team

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