Soft computing approach to fault diagnosis of centrifugal pump
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- @Article{Sakthivel20121574,
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author = "N. R. Sakthivel and Binoy. B. Nair and V. Sugumaran",
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title = "Soft computing approach to fault diagnosis of
centrifugal pump",
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journal = "Applied Soft Computing",
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volume = "12",
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number = "5",
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pages = "1574--1581",
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year = "2012",
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ISSN = "1568-4946",
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DOI = "doi:10.1016/j.asoc.2011.12.009",
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URL = "http://www.sciencedirect.com/science/article/pii/S1568494611004935",
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keywords = "genetic algorithms, genetic programming, Centrifugal
pump, Gene expression programming, Fault diagnosis,
Statistical features, Decision tree algorithm, Support
vector machine, Proximal support vector machine",
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abstract = "Fault detection and isolation in rotating machinery is
very important from an industrial viewpoint as it can
help in maintenance activities and significantly reduce
the down-time of the machine, resulting in major cost
savings. Traditional methods have been found to be not
very accurate. Soft computing based methods are now
being increasingly employed for the purpose. The
proposed method is based on a genetic programming
technique which is known as gene expression programming
(GEP). GEP is somewhat a new member of the genetic
programming family. The main objective of this paper is
to compare the classification accuracy of the proposed
evolutionary computing based method with other pattern
classification approaches such as support vector
machine (SVM), Wavelet-GEP, and proximal support vector
machine (PSVM). For this purpose, six states viz.,
normal, bearing fault, impeller fault, seal fault,
impeller and bearing fault together, cavitation are
simulated on centrifugal pump. Decision tree algorithm
is used to select the features. The results obtained
using GEP is compared with the performance of
Wavelet-GEP, support vector machine (SVM) and proximal
support vector machine (PSVM) based classifiers. It is
observed that both GEP and SVM equally outperform the
other two classifiers (PSVM and Wavelet-GEP) considered
in the present study.",
- }
Genetic Programming entries for
N R Sakthivel
Binoy B Nair
V Sugumaran
Citations