Ventilator Fault Diagnosis Based on Fuzzy Theory

Author

Lou Guohuan ; Zhou Yuan

Author_Institution

Coll. of Comput. & Autom. Control, Hebei Polytech. Univ., Tangshan, China

fYear

2009

fDate

11-13 Dec. 2009

Firstpage

1

Lastpage

3

Abstract

Fault diagnosis has been the research hotspot in the industry fields. It has a practical significance to discuss the effective fault diagnosis methods. Aiming at the fuzzy and random features of the occurrence probabilities, this paper presents a hybrid method that combines the fault tree with fuzzy set theory.In this approach, fuzzy aggregation and defuzzification are adopted and this method is used in ventilator fault diagnosis. The research shows that this method is feasible and effective and can be applied to the other rotating machinery fault diagnosis.

Keywords

fault diagnosis; fault trees; fuzzy set theory; ventilation; defuzzification; fault tree; fuzzy aggregation; fuzzy set theory; fuzzy theory; industry field; occurrence probabilities; random features; rotating machinery fault diagnosis; ventilator fault diagnosis; Automatic control; Computer industry; Educational institutions; Failure analysis; Fault diagnosis; Fault trees; Fuzzy control; Fuzzy sets; Industrial control; Machinery;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-4507-3

Electronic_ISBN

978-1-4244-4507-3

Type

conf

DOI

10.1109/CISE.2009.5365808

Filename

5365808