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For the complexity, uncertainty, ambiguity grab correction system, this paper proposed fuzzy neural network based fault tree as a method for grab correction system fault diagnosis. The method extracted fault diagnosis input and output variables of grab correction system by using fault tree knowledge. It introduced the concept of fuzz logic, used fuzzy membership functions to describe the degree of failures. It used Levenberg-Marquardt algorithm to train the neural network system, got a better performance in inference speed and fault-tolerant. The experiments verify the effectiveness of fault diagnosis grab correction system based on fuzzy neural network. [ABSTRACT FROM AUTHOR]