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PEANO and On-Line Monitoring Techniques for Calibration Reduction of Process Instrumentation in Power Plants
On-line monitoring evaluates instrument channel performance by assessing its consistency with other plant indications. Industry and EPRI [1]...
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Hidden Markov Model Based Transient Identification in NPPs
In this chapter, a transient identification based on a hidden Markov model (HMM) has been suggested and evaluated experimentally for the...
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Regulatory Treatment of On-Line Surveillance and Diagnostic Systems
For almost two decades, various university and national laboratory research groups have been develo** surveillance and diagnostic techniques for...
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Overview of Recent KFKI AEKI Activities in the Field of Plant Surveillance and Diagnostics
Application of noise diagnostics techniques for the regular surveillance of the four VVER-440/213 type reactors of the Paks NPP (Hungary) has long...
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Application of Neuro-Fuzzy Logic for Early Detection and Diagnostics in Gas Plants and Combustion Chambers at ENEA
This chapter presents the work done in collaboration between ENEA and the OECD Halden Reactor Project (HRP), which resulted in the application of HRP...
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Expert System-Based Implementation of Failure Detection
In light of the need to improve MMIS of NPPs, the advanced I&C research team of KAERI has embarked on develo** an Alarm and Diagnosis-Integrated...
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Development of Advanced Core Noise Monitoring System for a Boiling Water Reactor
For an efficient nuclear power plant operation, advanced core design is very important. However, advances in design may result in approaching...
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Failure Detection Using a Fuzzy Neural Network with an Automatic Input Selection Algorithm
It is well known that the performance of fuzzy neural networks applied to sensor monitoring strongly depends on the selection of inputs. In their...
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Regularization of Ill-Posed Surveillance and Diagnostic Measurements
Most data-based predictive modeling techniques have an inherent weakness in that they may give unstable or inconsistent results when the predictor...
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A Possibilistic Approach for Transient Identification with “Don’t Know” Response Capability Optimized by Genetic Algorithm
This work describes a possibilistic approach for transient identification based on the minimum centroids set method, proposed in previous work,...
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A Hybrid Fuzzy-Fractal Approach for Time Series Analysis and Prediction and Its Applications to Plant Monitoring
We describe in this paper a new hybrid fuzzy-fractal approach for plant monitoring. We use the concept of the fractal dimension to measure the...
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A New Approach for Transient Identification with “Don’t Know” Response Using Neural Networks
In the last years, many different approaches based on neural network (NN) have been proposed for transient identification in nuclear power plants...
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Optimized Maintenance and Management of Ageing of Critical Equipment in Nuclear Power Plants
New power generation economics and politics in the 2000 decade, recent interest in nuclear power plant life extension, and challenges from other...
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Detection of Incipient Signal or Process Faults in a Co-Generation Plant Using the Plant ECM System
A 161 megawatt co-generation plant operated by the US Steel Corporation is highly instrumented, providing real-time monitoring of turbine,...
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ALADDIN: Event Recognition & Fault Diagnosis for Process & Machine Condition Monitoring
Many industrial processes are characterized by long periods of steady-state operation, intercalated by occasional shorter periods of a more dynamic...
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Analysis of Selected Structures for Model-Based Measuring Methods Using Fuzzy Logic
Monitoring and diagnosis of safety-related technical processes in nuclear engineering can be improved with the help of intelligent methods of signal...
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A Possibilistic Approach to Target Classification
This chapter describes an alternative to the Bayesian approach to target classification that is based on possibility theory. A possibilistic...
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Controlling Neutron Power of a TRIGA Mark III Research Nuclear Reactor with Fuzzy Adaptation of the Set of Output Membership Functions
A fuzzy method is developed to obtain the set of output membership functions (SOMF) to be used in the defuzzification process of a typical fuzzy rule...
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Continued Fractions in Time Series Forecsting
Through their ergodic properties, continued fractions provide a fascinating example of a dynamical system whose properties we attempt to encode in a...
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Regularization Methods for Inferential Sensing in Nuclear Power Plants
Inferential sensing is the use of information related to a plant parameter to infer its actual value. The most common method of inferential sensing...