Application of BP neural network in fast location of fault dictionary

Fault dictionary method is a kind of very practical fault diagnosis method. But large scale and complex circuits, the fault dictionary is huge, and the speed of fault searching affects the efficiency of real-time diagnosing. In this paper, a new method that the faults are classed and many son fault dictionaries are built with BP nerve networks organize the search index is introduced. This method using the BP nerve network´s ability that could accurately describe the relation between input data and corresponding goal organizes the index in a multilayer binary tree with many BP nerve networks. Through this index, the seeking scope is reduced greatly, the searching speed is raised, and the efficiency of real-time diagnosing is improved.