Title :
Research on Fault Diagnosis Approach of Analog Circuit Based on Neural Network
Author :
Meirong, Liu ; Yun, Li
Author_Institution :
Coll. of Electr. & Inf. Eng., Hunan Univ., Changsha
Abstract :
According to circuit decomposition technology and crossover tearing technology, a fast approach of module level fault diagnosis for analog circuit based on BPNN (back propagation neural network) is presented. Because the neural networks can create the fault dictionary, memorize and verify it simultaneously, computation time is drastically reduced. The new approach is based on parallel diagnosis, so fault modules can be located quickly and effectively. Two examples are given to illustrate the approach for both small and large-scale circuits.
Keywords :
analogue integrated circuits; backpropagation; fault diagnosis; neural chips; analog circuit; back propagation neural network; circuit decomposition; crossover tearing; fault diagnosis; fault dictionary; fault modules; large-scale circuit; parallel diagnosis; small-scale circuit; Analog circuits; Circuit faults; Circuit testing; Dictionaries; Educational technology; Fault diagnosis; Geoscience and remote sensing; Large-scale systems; Neural networks; Pattern recognition;
Conference_Titel :
Education Technology and Training, 2008. and 2008 International Workshop on Geoscience and Remote Sensing. ETT and GRS 2008. International Workshop on
Conference_Location :
Shanghai
Print_ISBN :
978-0-7695-3563-0
DOI :
10.1109/ETTandGRS.2008.353