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何怡刚

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期刊论文

CLASS-BASED NEURAL NETWORK METHOD FOR FAULT LOCATION OF LARGE-SCALE ANALOGUE CIRCUITS

何怡刚Yigang He Yanghong Tan and Yichuang Sun

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摘要/描述

A new method for fault diagnosis of large-scale analogue circuits based on the class concept is developed in this paper. A large analogue circuit is decomposed into blocks/sub-circuits and the nodes between the blocks are classified into three classes. Only those sub-circuits related to the faulty class need to be, treated. Node classification reduces the scope of search for faults, thus reduced after-test time.' The proposed method is more suitable for real-time testing and can deal with both hard and soft faults. Tolerance effects are taken into account in the method. The class-based fault diagnosis principle and neural network based method are described in some details. Two non-trivial circuit examples are presented, showing that the proposed method is feasible.

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