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• W2568703550 abstract "In view of the fact that the integration of ICs is becoming higher and accessible testing nodes are getting less, circuit testing is becoming more and more difficult. A multidimensional feature fault diagnosis method based on principal component analysis is proposed in this paper. On the basis of analyzing the fault feature of analog circuits, the fault diagnosis method of multiple fault features takes advantage of principal components analysis to get the correlation of fault and its feature. Thus, it can reduce the complexity of the fault diagnosis. Further more, considering the effect of the device tolerance on the circuit output performance, the fault pattern recognition algorithm is used to identify fault categories. An electronic system platform is built to verify the fault diagnosis method. The results show that the multidimensional feature fault diagnosis algorithm for analog circuits based on principal components analysis has a better performance in fault separation and fault identification." @default.
• W2568703550 created "2017-01-13" @default.
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• W2568703550 date "2016-10-01" @default.
• W2568703550 modified "2023-09-22" @default.
• W2568703550 title "A multidimensional features fault diagnosis method for analog circuits" @default.
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• W2568703550 doi "https://doi.org/10.1109/iecon.2016.7793374" @default.
• W2568703550 hasPublicationYear "2016" @default.
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