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© 2002

Power Plant Surveillance and Diagnostics

Applied Research with Artificial Intelligence

  • Da Ruan
  • Paolo F. Fantoni

Benefits

  • Edited book reporting recent results of AI research in power plant surveillance and diagnostics

  • High quality and applicability of the contributions through a thorough peer-reviewing process

  • Condition monitoring and early fault detection both provide efficient energy systems at lower costs

Book

Part of the Power Systems book series (POWSYS)

Table of contents

  1. Front Matter
    Pages i-xiii
  2. Tomas O. Carlsson, Ronald Wennersten
    Pages 75-90
  3. Jung-Taek Kim, Kee-Choon Kwon, In-Koo Hwang, Dong-Young Lee, Jung-Woon Lee, Sang-Jeong Lee
    Pages 107-120
  4. Michitsugu Mori, Shigeru Kanemoto, Mitsuhiro Enomoto, Shigeo Ebata
    Pages 175-192
  5. Man Gyun Na, Young Rok Sim, Kyung Ho Park, Belle R. Upadhyaya, Baofu Lu, Ke Zhao
    Pages 221-242
  6. Antônio C. de A. Mol, Aquilino S. Martinez, Roberto Schirru
    Pages 253-272
  7. Celso M. F. Lapa, Cláudio M. N. A. Pereira, P. F. Frutuoso e Melo
    Pages 273-285
  8. José Carlos S. de Almeida, Roberto Schirru, Cláudio M. N. A. Pereira
    Pages 287-297

About this book

Introduction

In little more than a decade, the availability of nuclear power plants in the United States and most European and Pacific Rim countries has increased dramatically­ from around 60% to about 90%. Such improvement is equivalent to adding approximately 30,000 MW e of new generating capacity in this period in the United States and perhaps an equal amount elsewhere. Some of this improvement has been due to longer fuel cycles-increases from 12 months to 18 or 24 months, but the major gains have been due to on-line maintenance and improved operation and planning by the utilities, accomplished primarily by training of plant operators and support personnel. However, there are emerging indications that the benefits of training are asymptotically approaching the limit beyond which it cannot improve availability and that plant personnel errors may also be approaching a comparable lower limit. Indeed, further improvement appears to be dependent upon the effective introduction and use of plant operational support systems. The Halden Reactor Project (HRP) historically has focused on plant operational support system, i. e. , such tools as COPMA (Computerized OPeration MAnuals), PEANO (Process Evaluation and Analysis by Neural Operators), TEMPO (ThErMal Performance and Optimization), PLASMA (PLAnt Safety Monitoring and Assessment system), and others.

Keywords

Bayesian network artificial intelligence artificial neural network cognition expert system fuzzy fuzzy logic genetic algorithm hidden Markov model modeling neural network

Editors and affiliations

  • Da Ruan
    • 1
  • Paolo F. Fantoni
    • 2
  1. 1.Belgian Nuclear Research Centre (SCK·CEN)MolBelgium
  2. 2.Institute for Energy (IFE)HaldenNorway

Bibliographic information

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