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Article:Artificial Neural Network Approach for Fault Detection in Pneumatic Valve in Cooler Water Spray System

by P. Subbaraj, B. Kannapiran
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 9 - Number 7
Year of Publication: 2010
Authors: P. Subbaraj, B. Kannapiran
10.5120/1395-1881

P. Subbaraj, B. Kannapiran . Article:Artificial Neural Network Approach for Fault Detection in Pneumatic Valve in Cooler Water Spray System. International Journal of Computer Applications. 9, 7 ( November 2010), 43-52. DOI=10.5120/1395-1881

@article{ 10.5120/1395-1881,
author = { P. Subbaraj, B. Kannapiran },
title = { Article:Artificial Neural Network Approach for Fault Detection in Pneumatic Valve in Cooler Water Spray System },
journal = { International Journal of Computer Applications },
issue_date = { November 2010 },
volume = { 9 },
number = { 7 },
month = { November },
year = { 2010 },
issn = { 0975-8887 },
pages = { 43-52 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume9/number7/1395-1881/ },
doi = { 10.5120/1395-1881 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:58:02.155571+05:30
%A P. Subbaraj
%A B. Kannapiran
%T Article:Artificial Neural Network Approach for Fault Detection in Pneumatic Valve in Cooler Water Spray System
%J International Journal of Computer Applications
%@ 0975-8887
%V 9
%N 7
%P 43-52
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The detection and diagnosis of faults in technical systems are of great practical significance and paramount importance for the safe operation of the plant. The early detection of fault can help avoid system shutdown, breakdown and even catastrophe involving human fatalities and material damage. Since the operator cannot monitor all variables simultaneously, an automated approach is needed for the real time monitoring and diagnosis of the system. This paper presents the design and development of artificial neural network based model for the fault detection of Pneumatic valve in cooler water spray system in cement industry. The network is developed to detect a totally nineteen faults. The training and testing data required to develop the neural network model were generated at different operating conditions by operating the pneumatic valve and by creating various faults in real time in a laboratory experimental model. The performance of the developed back propagation is found to be satisfactory for the real time fault diagnosis.

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Index Terms

Computer Science
Information Sciences

Keywords

Fault detection Neural networks Back propagation algorithm

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