Abstract
Power plant management relies on monitoring many signals that represent the technical parameters of the real plant. The use of neural networks (NN) is a novel approach that can help to produce decisions when integrated in a more general system. In this paper we introduce a NN module using an ART-MAP to discriminate different situations from the plant in order to prevent future malfunctions. A special process to generate of a complete training set has been designed. This process is developed in order to deal with the absence of data in abnormal plant situations. This module belongs to a more general system for predictive maintenance that has been implemented and incorporated in an hydroelectric plant.
This project has been supported by CDTI (belonging to Spanish Industry Ministery) and EEC (European Economic Comunity), reference number: PASO PC067.
Preview
Unable to display preview. Download preview PDF.
References
J.T. Evans, J.B. Gomm, D. Williams, P.J.G. Lisboa, “Online Modeling and Predictive Control using a Neural Network”, Proc. IASTED International Conference, Modeling, Simulation and Control in the Process Industry, pp 83–86, 1994.
R. Raghavan, B.H. Simon, “Advanced Plant Maintenance and Surveillance System for the Nuclear Power Plants of the Next Century”, Proc. 2nd ASME JSME Nuclear Engineering Joint Conference 1993, vol. 2, pp. 693–697, 1993.
A. Loskiewicz-Buczak, I.E. Alguindigue, R.E. Uhrig, “Vibration Analysis in Nuclear Power Plant Using Neural Networks”, Proc. 2nd ASME JSME Nuclear Engineering Joint Conference 1993, vol. 2, pp. 43–51, 1993.
H.G. Kim, S.S. Choi, K.S. Kang, S.H. Chang, “Development of an Online Expert System for Integrated Alarm Processing in Nuclear Power Plants”, Transactions of the American Nuclear Society, vol 71, pp. 121–123, 1994.
S. Yoshikawa, A. Saiki, D. Ugolini, K. Ozawa, “Nuclear Power Plant Monitoring and Fault Diagnosis Methods based on the Artificial Intelligence Technique”, Proc. SMORN VII, a Symposium on Nuclear Reactor Surveillance and Diagnostic, vol 1, pp. 4.9/1–9, 1995.
Yoh-Han Pao, Adaptive Pattern Recognition and Neural Networks, Addison-Wesley, 1989.
P.Isasi, J.M. Molina, A. Navia “Hidroelectric Power Plant Predictive Maintenance relying on Neural Network Acoustic Module”, Proc. International Conference on Neural Information Processing, ICONIP'96, pp. 1175–1180, 1996.
D. Yonghong, A. Van Cauwenberghe, “Use of Neural Networks for Non-linear Predictive Control”, Proc. 3rd European Control Conference, ECC'95, vol 3, pp. 2760–2765, 1995.
G.A. Carpenter, S. Grossberg, J. Reynolds, “ARTMAP: Supervised Real-Time Learning and Classification of Non-stationary Data by a Self-Organizing Neural Network”, Neural Networks, vol 4, pp. 565–588, 1991.
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1997 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Isasi-Viñuela, P., Molina-López, J.M., de Miguel, A.S. (1997). Unsupervised neural network for forecasting alarms in hydroelectric power plant. In: Mira, J., Moreno-Díaz, R., Cabestany, J. (eds) Biological and Artificial Computation: From Neuroscience to Technology. IWANN 1997. Lecture Notes in Computer Science, vol 1240. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0032590
Download citation
DOI: https://doi.org/10.1007/BFb0032590
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-63047-0
Online ISBN: 978-3-540-69074-0
eBook Packages: Springer Book Archive