Improved ART1 Neural Network Based Condenser Fault Diagnosis

Abstract:

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Condenser is an essential equipment of steam turbine. It is valuable to diagnose the fault when monitor the condenser system. To overcome shortcomings of BP neural network in fault diagnosis, ART1 (adaptive resonance architecture 1) is used to diagnose the condenser fault. The ART1 Neural network studies the typical fault features data, and realizes fault diagnosis. The results indicate the improved ART1 neural network can diagnose the condenser system fault correctly, and overcome the shortcoming of the original training algorithm. Although this is an application based on condenser, the algorithm can be used to further industrial system.

Info:

Periodical:

Advanced Materials Research (Volumes 588-589)

Edited by:

Lawrence Lim

Pages:

1091-1094

Citation:

Q. Y. Xu and Y. Liang, "Improved ART1 Neural Network Based Condenser Fault Diagnosis", Advanced Materials Research, Vols. 588-589, pp. 1091-1094, 2012

Online since:

November 2012

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Price:

$38.00

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