Before the year 2000: Artificial neural networks may set the standard
The use of artifical neural networks (ANNs) for monitoring of equipment and components in nuclear power plants could be commonplace before the turn of the century. Within five years, the relative inexpensiveness of neural networks could usher in a technology that will be used to detect incipient faults in machinery and increase effectiveness of maintenance scheduling. Working since November 1992 with the Electric Power Research Institute on research and development of the technology, SynEx and another Virginia-based company, A&T, Inc., will later this year demonstrate prototype ANN systems at Consolidated Edison Company and New York State Electric Gas fossil fuel power plants. (Fossil fuel plants were chosen for the project because of easier access, as opposed to the security measures in place at nuclear facilities.) The demonstration will utilize sensors and the neural network systems to detect abnormal equipment behavior, sending signals back to centralized monitoring boards located in each plant`s control room. The cost of the project, including research and development, will reach $1 million. However, the cost of installing a neural network at a nuclear plant within the next five years, according to Birdsall, could be as low as $10,000 to $15,000, with hopes of reducing the expenditure to just $5000.
- OSTI ID:
- 486235
- Journal Information:
- Nuclear News, Vol. 37, Issue 9; Other Information: PBD: Jul 1994
- Country of Publication:
- United States
- Language:
- English
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