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Title: Three neural network based sensor systems for environmental monitoring

Conference ·
OSTI ID:10165746

Compact, portable systems capable of quickly identifying contaminants in the field are of great importance when monitoring the environment. One of the missions of the Pacific Northwest Laboratory is to examine and develop new technologies for environmental restoration and waste management at the Hanford Site. In this paper, three prototype sensing systems are discussed. These prototypes are composed of sensing elements, data acquisition system, computer, and neural network implemented in software, and are capable of automatically identifying contaminants. The first system employs an array of tin-oxide gas sensors and is used to identify chemical vapors. The second system employs an array of optical sensors and is used to identify the composition of chemical dyes in liquids. The third system contains a portable gamma-ray spectrometer and is used to identify radioactive isotopes. In these systems, the neural network is used to identify the composition of the sensed contaminant. With a neural network, the intense computation takes place during the training process. Once the network is trained, operation consists of propagating the data through the network. Since the computation involved during operation consists of vector-matrix multiplication and application of look-up tables unknown samples can be rapidly identified in the field.

Research Organization:
Pacific Northwest Lab., Richland, WA (United States)
Sponsoring Organization:
USDOE, Washington, DC (United States)
DOE Contract Number:
AC06-76RL01830; FG06-89ER75522
OSTI ID:
10165746
Report Number(s):
PNL-SA-24175; CONF-9405197-1; ON: DE94014557; BR: 820201000/KE0103000; TRN: 94:014590
Resource Relation:
Conference: Electro @/94 international conference,Boston, MA (United States),10-12 May 1994; Other Information: PBD: May 1994
Country of Publication:
United States
Language:
English