Neural network based model for fault diagnosis of pneumatic valve with dimensionality reduction

Authors:
P. Subbaraj;B. Kannapiran
Affiliations:
Sri Nandhanam College of Engineering and Technology, Vellore District, Tamilnadu, India;Department of Instrumentation & Control Engineering, Arulmigu Kalasalingam college of Engineering, Virudunagar District, Tamilnadu, India
Venue:
SEMCCO'11 Proceedings of the Second international conference on Swarm, Evolutionary, and Memetic Computing - Volume Part I
Year:
2011

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Abstract

Fault detection and diagnosis of pneumatic valve used in cooler water spray system in cement industry is of great practical significance and paramount importance for the continued operation of the plant. This paper presents the design and development of Artificial Neural Network (ANN) based model for the fault detection of pneumatic valve in cooler water spray system in cement industry. Principal component analysis (PCA) is applied to reduce the input dimension. The training and testing data required for the development of ANN is generated in a laboratory grade experimental setup. The performance of the developed model is compared with the network trained with the original variables without any dimensionality reduction. From the comparison it is observed that the classification performance of the neural network has been improved due to the application of PCA and the training time of the neural network is reduced.