A New Method of Fault Diagnosis with Soft Set Theory

Xiao Lei Sun

doi:10.4028/www.scientific.net/AMR.383-390.7470

Paper Titles

Zero Internal Force Control for a Dual-Arm Space Robot
p.7449

The Influence on High-Speed Electrical Multiple Unit by Fluctuation of Traction Power System’s Voltage
p.7455

Steering Wheel Angle Pulse Input Simulation and Evaluation of a Car Based on ADAMS
p.7461

Design of Photovoltaic Generation Monitoring System Based on WinCC
p.7465

A New Method of Fault Diagnosis with Soft Set Theory
p.7470

Design of Random Combination System Based on Five Common Kinds of Mechanical Transmission
p.7475

Modeling and Analysis of a Turbidostat Model with Monod-Type Kinetics and State Feedback Control
p.7480

Circuit Model of Laser-Triggered Surface Flashover Switch in Vacuum Condition with Pulsed Voltage
p.7486

Detection of Electromagnetic Pulse Induced Hazard on Electroexplosive Device Based on Optical-Fiber Fluorescence
p.7492

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 383-390A New Method of Fault Diagnosis with Soft Set...

A New Method of Fault Diagnosis with Soft Set Theory

Abstract:

The soft set theory is a kind of new and effective tools to deal with the uncertainty. In this paper the principle and operations of the soft set theory was introduced briefly. The application in fault diagnosis was presented for the first time. An example was given to show this method valuable.

You might also be interested in these eBooks

Manufacturing Science and Technology, ICMST2011

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 383-390)

Pages:

7470-7474

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.383-390.7470

Citation:

Cite this paper

Online since:

November 2011

Authors:

Xiao Lei Sun

Keywords:

Fault Diagnosis, Fuzzy Set, Nonnumerical Information, Numerical Information, Soft Set

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] L.A. Zadeh, Fuzzy Set, Information and control, 1965(8): 338—353.

Google Scholar

[2] D. Molodtsov, Computers and mathematics with applications 1999, 37(7): 19—31.

Google Scholar

[3] D.A. Molodtsov, Stability of optimality principles; Nauka, Moscow(1987).

Google Scholar

[4] He xingui, Weighted Fuzzy logic and its applications. Proc, of the 12th Annual International Computer Software and Applications Conference, Chicago, Illinois, 1988: 485—489.

Google Scholar

[5] Wang Jiasheng et al, Probability with Application, Tianjin University Press, 1990. (In Chinese).

Google Scholar

[6] Gertler J J. Survey of model based failure detection and isolation in complex plants, IEEE Control Systems Magazine, 1988, 8(6): 3—11.

DOI: 10.1109/37.9163

Google Scholar

[7] Frank P M. Fault diagnosis in dynamic systems using analytical and knowledge-based redundancy: a survey. Automatica, 1990, 26 (3) : 459—474.

DOI: 10.1016/0005-1098(90)90018-d

Google Scholar

[8] Patton R J. Robustness issues in fault tolerant control. In: Proc. of International Conference on Fault Diagnosis, Toulouse, France, 1993. 3: 1081—1117.

Google Scholar