The Decision-Making for Fault Diagnosis Based on Consistent Approximation Space

Abstract:

Article Preview

Due to vary kinds of factors, test results for a weapon system may be incomplete and hard to make decisions for fault diagnosis. Aimed at the problem of the weapon system inconsistent decision-making for fault diagnosis, introduced the method of consistent approximation space. Firstly the definition of inconsistent decision-making information system was brought forward, and then the consistent approximation space was formed. Attribute reduction for the consistent approximation space and an approach for rule amalgamation were also presented. Finally, a case was used to prove this method; the result shows that the method of consistent approximation space can solve the inconsistent decision-making for fault diagnosis problems effectively.

Info:

Periodical:

Advanced Materials Research (Volumes 591-593)

Edited by:

Liangchi Zhang, Chunliang Zhang, Jeng-Haur Horng and Zichen Chen

Pages:

1739-1742

DOI:

10.4028/www.scientific.net/AMR.591-593.1739

Citation:

L. Chen et al., "The Decision-Making for Fault Diagnosis Based on Consistent Approximation Space", Advanced Materials Research, Vols. 591-593, pp. 1739-1742, 2012

Online since:

November 2012

Export:

Price:

$35.00

[1] Ziarko W, Variable precision rough set model, J. Journal of Computer and System Science. 46 (1993) 39-59.

DOI: 10.1016/0022-0000(93)90048-2

[2] P Lv, Fault diagnosis of gear based on variable precision rough set, J. Journal of North China Electric Power University. 37 (2010) 99-102.

[3] W P Ding, J D Wang, Z J Guan, Concept lattice mining a algorithm using rough entropy with variable precision thresholding and co-evolution, J. Journal of PLA University of science and Technology(Natural Science Edition). 12 (2011) 25-30.

[4] S Y Cheng, Z Y Suo, H WU et al, Aero2engine fault diagnosis based on consistent approximative denoted space, J. Journal of Aerospace Power. 24 (2009) 1644-1648.

[5] W X Zhang, G F Qiu, Uncertain decision making based on rough sets. first ed. Tsinghua university press, Beijing (2006).

[6] Czyzewski A, Speaker-Independent Recognition of Isolated Words Using Rough Sets, J. Information Sciences. 104 (1998) 3-14.

DOI: 10.1016/s0020-0255(97)00072-8

[7] Slowinski R, Stefanowski J, Greco S et al, Rough set based processing of inconsistent information in decision analysis, J. Control Cybernet. 29 (2000) 379-404.

[8] Mi J S, Leung Y, Wu W Z, Approaches to knowledge reduction based on variable precision rough set model, J. Information Science. 159 (2004) 255-272.

DOI: 10.1016/j.ins.2003.07.004

In order to see related information, you need to Login.