A REAL TIME COAL CONTENT ORE GRADE (C2OG) SENSOR

Swanson, Dr. Rand

National Energy Technology Laboratory (U.S.)

关键词: Titanium;    01 Coal, Lignite, And Peat;    Coal;    Targets;    Algorithms;   

DOI  :  10.2172/804933
RP-ID  :  FC26-01NT41057--05
RP-ID  :  FC26-01NT41057
RP-ID  :  804933

美国|英语

来源: UNT Digital Library

【 摘 要 】

This fifth quarterly technical report discusses the progress made on a machine vision technique for determining coal content and ore grades. Recent work has been devoted to implementing new hardware and examining defects in titanium sponge, a new application for the machine vision system. With the improvements in hardware and software, the data collection is much improved. Early results from data taken on titanium sponge defects indicate that some defects will be relatively easy to identify, but others will be much more difficult. Consequently, additional work is required with software algorithms for target recognition. Ongoing work will be divided into several fronts, which include data collection and analysis, improving the target recognition capabilities, and improving the electronic interface.