| Autor: |
G.W. Eccleston, C.W. Baumgart, D. Beddingfield, H.O. Menlove, J.E. Smith, C.A. Rodriguez, J.A. Howell |
| Rok vydání: |
1995 |
| Předmět: |
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| DOI: |
10.2172/10105924 |
| Popis: |
For the past several years, the integration of containment and surveillance (C/S) with nondestructive assay (NDA) sensors for monitoring the movement of nuclear material has focused on the hardware and communications protocols in the transmission network. Little progress has been made in methods to utilize the combined C/S and NDA data for safeguards and to reduce the inspector time spent in nuclear facilities. One of the fundamental problems in the integration of the combined data is that the two methods operate in different dimensions. The C/S video data is spatial in nature; whereas, the NDA sensors provide radiation levels versus time data. The authors have introduced a new method to integrate spatial (digital video) with time (radiation monitoring) information. This technology is based on pattern recognition by neural networks, provides significant capability to analyze complex data, and has the ability to learn and adapt to changing situations. This technique has the potential of significantly reducing the frequency of inspection visits to key facilities without a loss of safeguards effectiveness. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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