Feature Extraction from Engine's Data Based on Rough Sets Theory

Abstract:

Article Preview

The speed signal of engine contains abundant information. This paper introduces rough set theory for feature extraction from engine's speed signals, and proposes a method of mining useful information from a mass of data. The result shows that the discernibility matrix algorithm can be used to reduce attributes in decision table and eliminate unnecessary attributes, efficiently extracted the features for evaluating the technical condition of engine.

Info:

Periodical:

Edited by:

Jiuba Wen, Fuxiao Chen, Ye Han and Huixuan Zhang

Pages:

410-413

DOI:

10.4028/www.scientific.net/AMM.120.410

Citation:

F. Wang and L. X. Jia, "Feature Extraction from Engine's Data Based on Rough Sets Theory", Applied Mechanics and Materials, Vol. 120, pp. 410-413, 2012

Online since:

October 2011

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Price:

$35.00

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