Fault Localization of Analog Circuit with Small Sample Using SVM and AIS Methods

Abstract:

Both Support Vector Machines (SVM) and Artificial Immune Systems (AIS) are by far effective on faults localization of analogue circuits for small samples. In this paper, both a selective SVM ensemble based on clustering Algorithm and a new AIS based on real-valued NS (RNS) algorithm are applied to the fault diagnosis and their effects are evaluated. The fault diagnosis experiments on a continuous-time state-variable filter circuit show that the fault diagnosis method based the AIS can obtain high fault localization rate of 95% when only one group samples acted as the training samples and the other method can obtain fault localization rate of 85% when 400 group samples acted as the training samples. So, AIS is a more effective method to fault diagnosis with small samples.

• Periodical: Applied Mechanics and Materials (Volumes 325-326)
• Pages: 893-898
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.325-326.893
• Online since: June 2013
• Authors: Xiong Xue Wu, Chao You Guo
• Keywords: Analog Circuit, Artificial Immune Systems (AIS), Fault Diagnosis, Small Samples, Support Vector Machine (SVM)

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