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Hengyu Wu
Hainan Software Profession Institute

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Diagnosis Method for Analog Circuit Hard fault and Soft Fault Baoru Han; Jingbing Li; Hengyu Wu
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 9: September 2013
Publisher : Institute of Advanced Engineering and Science

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Abstract

Because the traditional BP neural network slow convergence speed, easily falling in local minimum and the learning process will appear oscillation phenomena. This paper introduces a tolerance analog circuit hard fault and soft fault diagnosis method based on adaptive learning rate and the additional momentum algorithm BP neural network. Firstly, tolerance analog circuit is simulated by OrCAD / Pspice circuit simulation software, accurately extracts fault waveform data by matlab program automatically. Secondly, using the adaptive learning rate and momentum BP algorithm to train neural network, and then applies it to analog circuit hard fault and soft fault diagnosis. With shorter training time, high precision and global convergence effectively reduces the misjudgment, missing, it can improve the accuracy of fault diagnosis and fast. DOI: http://dx.doi.org/10.11591/telkomnika.v11i9.3301 
Co-Authors Baoru Han Jingbing Li