On-line monitoring of instrument channel performance in nuclear power plant using PEANO

Progress in Nuclear Energy

Volumn 43, Issue 1-4 SPEC, 2003, Pages 83-89

  Fantoni, P F ^a   Hoffmann, M I ^a   Shankar, R ^b   Davis, E L ^c  

^a INSTITUTE FOR ENERGY TECHNOLOGY   (Norway)

^b Welding and Repair Technology Center   (United States)

^c Edan Engineering Corporation   (United States)

Author keywords

Artificial intelligence; Neuro fuzzy; On line monitoring; Signal validation

Indexed keywords

ARTIFICIAL INTELLIGENCE; CALIBRATION; COST EFFECTIVENESS; NUCLEAR POWER PLANTS; RADIATION;

OFF LINE TESTS; ON LINE MONITORING;

NUCLEAR ENERGY;

EID: 0037740731     PISSN: 01491970     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0149-1970(03)00017-9     Document Type: Article

References (14)

1. Bezdek JC (1981), Pattern Recognition with Fuzzy Objective Function Algorithms. Plenum Press, New York, NY.
2. EPRI (2000), On-Line Monitoring of Instrument Channel Performance, TR-104965-R1 NRC SER.
3. Fantoni P (1996), Neuro-Fuzzy Models Applied to Full Range Signal Validation in NPP. NPIC&HMIT'96, The Pennsylvania State Univ., PA.
4. Fantoni P (2000), A Neuro-Fuzzy Model Applied to Full Range Signal Validation of PWR Nuclear Power Plant Data. International Journal of General Systems, Vol. 29(2), pp 305-320.
5. Fantoni P, Figedy S, Racz A (1998), PEANO, A Toolbox for Real-Time Process Signal Validation and Estimation, HWR-515, OECD Halden Reactor Project (restricted).
6. Fantoni P, Mazzola A (1994), Applications of Autoassociative Neural Networks for Signal Validation in Accident Management, IAEA Specialist Meeting on Advanced Information Methods and Artificial Intelligence in Nuclear Power Plant Control Rooms. Halden, Norway.
7. Fantoni P Mazzola A (1995), Transient and Steady State Signal Validation in Nuclear Power Plants using Autoassociative Neural Networks and Pattern Recognition. SMORN VII, Avignon, France.
8. Fantoni P, Mazzola A (1996), A Pattern Recognition-Artificial Neural Networks Based Model for Signal Validation in Nuclear Power Plants. Annals of Nuclear Energy, Vol. 23, No.13, pp 1069-1076.
9. Fantoni P, Mazzola A (1996), Multiple Failure Signal Validation in Nuclear Power Plants using Artificial Neural Networks. Nuclear Technology, Vol. 113, No. 3, pp 368-374.
10. Fantoni P, Mazzola A (1996), Accuracy Estimate of Artificial Neural Networks Based Models for Industrial Applications. Artificial Intelligence in the Petroleum Industry. Symbolic and Computational Applications 2, Chapter 17, B Braunschweig & B Bremdal Editions.
11. Fantoni P, Renders J (1998), On-Line Performance Estimation and Condition Monitoring using Neuro-Fuzzy Techniques. Workshop on On-Line Fault Detection and Supervision in the Chemical Process Industries, Lyon, France.
12. Gustafson DE, Kessel W C (1979), Fuzzy Clustering with a Fuzzy Covariance Matrix. IEEE CDC, San Diego, CA.
13. Krishnapuram R, Keller J (1993), A Possibilistic Approach to Clustering. IEEE Transactions on Fuzzy Systems, Vol. 1, No. 2, pp 98-100.
14. Tou J.T., Gonzalez R.C. (1974), Pattern Recognition Principles, Addison Wesley Publishing Company, Reading, MA.