Actions for High quality garbage [electronic resource] : A neural network plastic sorter in hardware and software

Email RIS file
Bookmark
Report an Issue

High quality garbage [electronic resource] : A neural network plastic sorter in hardware and software

Published
Washington, D.C. : United States. Dept. of Energy, 1993.
Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy.
Physical Description
5 pages : digital, PDF file
Additional Creators
Sandia National Laboratories, United States. Department of Energy, and United States. Department of Energy. Office of Scientific and Technical Information
Access Online

Availability

I Want It
I Want It

Finding items...

Restrictions on Access
Free-to-read Unrestricted online access
Summary
In order to produce pure polymer streams from post-consumer waste plastics, a quick, accurate and relatively inexpensive method of sorting needs to be implemented. This technology has been demonstrated by using near-infrared spectroscopy reflectance data and neural network classification techniques. Backpropagation neural network routines have been developed to run real-time sortings in the lab, using a laboratory-grade spectrometer. In addition, a new reflectance spectrometer has been developed which is fast enough for commercial use. Initial training and test sets taken with the laboratory instrument show that a network is capable of learning 100% when classifying 5 groups of plastic (HDPE and LDPE combined), and up to 100% when classifying 6 groups. Initial data sets from the new instrument have classified plastics into all seven groups with varying degrees of success. One of the initial networks has been implemented in hardware, for high speed computations, and thus rapid classification. Two neural accelerator systems have been evaluated, one based on the Intel 8017ONX chip, and another on the AT&T ANNA chip.
Report Numbers
E 1.99:sand--93-0521c
E 1.99: conf-9311101--2
conf-9311101--2
sand--93-0521c
Subject(s)
Other Subject(s)
Note
Published through SciTech Connect.
09/01/1993.
"sand--93-0521c"
" conf-9311101--2"
"DE93041143"
GOMAC 93: government microcircuit application conference,New Orleans, LA (United States),1-4 Nov 1993.
Alam, M.K.; Stanton, S.L.; Hebner, G.A.
Funding Information
AC04-76DP00789
View MARC record | catkey: 14078485