Journal of Mechanical Science and Technology

, volume 26 , issue 2 , pages 601-608

Fault diagnosis of rotary kiln using SVM and binary ACO

Ouahab Kadri ¹

Leila Hayet Mouss ¹

Mohamed Djamel Mouss ¹

Hide authors affiliations Show authors affiliations: 1 affiliation

Laboratory of Automation & Production Engineering, University of Batna, Batna, Algeria |

Publication type: Journal Article

Publication date: 2012-02-13

Korean Society of Mechanical Engineers

Journal of Mechanical Science and Technology

scimago Q2

wos Q3

SJR: 0.418

CiteScore: 3.0

Impact factor: 1.7

ISSN: 1738494X, 19763824

DOI: 10.1007/s12206-011-1216-z

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Mechanical Engineering

Mechanics of Materials

Abstract

This paper proposes a novel hybrid algorithm for fault diagnosis of rotary kiln based on a binary ant colony (BACO) and support vector machine (SVM). The algorithm can find a subset selection which is attained through the elimination of the features that produce noise or are strictly correlated with other already selected features. The BACO algorithm can improve classification accuracy with an appropriate feature subset and optimal parameters of SVM. The proposed algorithm is easily implemented and because of use of a simple filter in that, its computational complexity is very low. The performance of the proposed algorithm is evaluated through two real Rotary Cement kiln datasets. The results show that our algorithm outperforms existing algorithms.

Found

1 citation

Ouahab Kadri

DSc in Engineering, professor

14 publications, 175 citations

h-index: 5

University of Batna 2

Research interests

Machine learning

Pattern Recognition

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Kadri O., Mouss L. H., Mouss M. D. Fault diagnosis of rotary kiln using SVM and binary ACO // Journal of Mechanical Science and Technology. 2012. Vol. 26. No. 2. pp. 601-608.

GOST all authors (up to 50) Copy

Kadri O., Mouss L. H., Mouss M. D. Fault diagnosis of rotary kiln using SVM and binary ACO // Journal of Mechanical Science and Technology. 2012. Vol. 26. No. 2. pp. 601-608.

RIS |

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RIS Copy

TY - JOUR

DO - 10.1007/s12206-011-1216-z

UR - https://doi.org/10.1007/s12206-011-1216-z

TI - Fault diagnosis of rotary kiln using SVM and binary ACO

T2 - Journal of Mechanical Science and Technology

AU - Kadri, Ouahab

AU - Mouss, Leila Hayet

AU - Mouss, Mohamed Djamel

PY - 2012

DA - 2012/02/13

PB - Korean Society of Mechanical Engineers

SP - 601-608

IS - 2

VL - 26

SN - 1738-494X

SN - 1976-3824

ER -

BibTex |

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BibTex (up to 50 authors) Copy

@article{2012_Kadri,

author = {Ouahab Kadri and Leila Hayet Mouss and Mohamed Djamel Mouss},

title = {Fault diagnosis of rotary kiln using SVM and binary ACO},

journal = {Journal of Mechanical Science and Technology},

year = {2012},

volume = {26},

publisher = {Korean Society of Mechanical Engineers},

month = {feb},

url = {https://doi.org/10.1007/s12206-011-1216-z},

number = {2},

pages = {601--608},

doi = {10.1007/s12206-011-1216-z}

}

MLA

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MLA Copy

Kadri, Ouahab, et al. “Fault diagnosis of rotary kiln using SVM and binary ACO.” Journal of Mechanical Science and Technology, vol. 26, no. 2, Feb. 2012, pp. 601-608. https://doi.org/10.1007/s12206-011-1216-z.