Applying neural networks to optimize instrumentation performance
Conference
·
OSTI ID:79135
Well calibrated instrumentation is essential in providing meaningful information about the status of a plant. Signals from plant instrumentation frequently have inherent non-linearities, may be affected by environmental conditions and can therefore cause calibration difficulties for the people who maintain them. Two neural network approaches are described in this paper for improving the accuracy of a non-linear, temperature sensitive level probe ised in Expermental Breeder Reactor II (EBR-II) that was difficult to calibrate.
- Research Organization:
- Argonne National Lab., Idaho Falls, ID (United States)
- Sponsoring Organization:
- USDOE, Washington, DC (United States)
- DOE Contract Number:
- W-31109-ENG-38
- OSTI ID:
- 79135
- Report Number(s):
- ANL/IFR/CP--84089; CONF-950564--8; ON: DE95009466
- Country of Publication:
- United States
- Language:
- English
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