Remote intelligent fault diagnosis of analog circuit

Author

Qing Yang ; Yuanyuan Zhu ; Feng Wu

Author_Institution

Sch. of Inf. Sci. & Eng., Shenyang Ligong Univ., Shenyang, China

Volume

3

fYear

2011

fDate

26-28 July 2011

Firstpage

1677

Lastpage

1680

Abstract

A remote intelligent fault diagnosis approach of analog circuit based on probabilistic neural network (PNN) and virtual instrument technology, called RPNN, is proposed. Firstly, PNN is used to classify the faults. Then, remote fault diagnosis is realized by virtual instrument technology. Simulation results illustrate that RPNN is feasible to soft fault diagnosis in analog circuit. RPNN can provide an accepted degree of accuracy in fault classification under different soft fault conditions and can be operated remotely from another site connected to the server via the World Wide Web.

Keywords

analogue circuits; circuit analysis computing; fault diagnosis; neural nets; virtual instrumentation; analog circuit; probabilistic neural network; remote intelligent fault diagnosis; soft fault diagnosis; virtual instrument technology; Analog circuits; Browsers; Circuit faults; Computational modeling; Fault diagnosis; Probabilistic logic; Training; PNN; RPNN; analog circuit; fault diagnosis; remote LabVIEW;

fLanguage

English

Publisher

ieee

Conference_Titel

Natural Computation (ICNC), 2011 Seventh International Conference on

Conference_Location

Shanghai

ISSN

2157-9555

Print_ISBN

978-1-4244-9950-2

Type

conf

DOI

10.1109/ICNC.2011.6022382

Filename

6022382