Experimental Validation of LS-SVM Based Fault Identification in Analog Circuits Using Frequency Features
Analog circuits have been widely used in diverse fields such as avionics, telecommunications, healthcare, and more. Detection and identification of soft faults in analog circuits subjected to component variation within standard tolerance range is critical for the development of reliable electronic systems, and thus forms the primary focus of this paper. In this paper, we have experimentally demonstrated a reliable and accurate (99 %) fault diagnostic framework consisting of a sweep signal generator, spectral estimator and a least squares-support vector machine. The proposed method is completely automated and can be extended for testing other analog circuits whose performances are mainly determined by their frequency characteristics.
KeywordsSupport Vector Machine Power Spectral Density Fault Diagnosis Little Square Support Vector Machine Analog Circuit
The authors would like to thank the more than 100 companies and organizations that support research activities at the Prognostics and Health Management Group within the Center for Advanced Life Cycle Engineering at the University of Maryland annually.
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