Title :
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
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;
Conference_Titel :
Natural Computation (ICNC), 2011 Seventh International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-9950-2
DOI :
10.1109/ICNC.2011.6022382
