A GAFCM Clustering Analysis Model for Diesel Engine Faulty Diagnosis

Abstract:

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A general fuzzy clustering analysis theory method is introduced at first, then a GAFCM algorithm and its implement steps are given. The diagnosis types of the test samples are judged by getting across the most of the Euclid pressing close degree choosing approximately principle. Practice proves that this method can be used to diagnose the diesel engine vibration faulty.

Info:

Periodical:

Advanced Materials Research (Volumes 199-200)

Edited by:

Jianmin Zeng, Zhengyi Jiang, Taosen Li, Daoguo Yang and Yun-Hae Kim

Pages:

745-748

DOI:

10.4028/www.scientific.net/AMR.199-200.745

Citation:

X. G. Chen "A GAFCM Clustering Analysis Model for Diesel Engine Faulty Diagnosis", Advanced Materials Research, Vols. 199-200, pp. 745-748, 2011

Online since:

February 2011

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Price:

$35.00

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