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In the field of weapon equipment maintenance and technical support, there are many problems, such as complex failure modes and complicated analysis and location, which affect the efficiency of equipment maintenance to a certain extent. In order to solve the above problems, a fault analysis method based on artificial neural network is designed on the typical platform of a portable air defense missile launching mechanism of the Army. The application of neural network in the field of equipment technical support is studied. This method is based on BP neural network and uses historical maintenance data to determine the forward and backward propagation matrix of the network. In the later stage, some measures are taken to optimize the classification accuracy. The whole method is implemented in Python environment. Experiments show that this method has high speed, high efficiency and accuracy over 96% when locating the fault of launching mechanism. Therefore, this method has high classification accuracy for fault mode analysis under the influence of various fault phenomena, and can satisfy the rapid analysis and location of fault mode in equipment maintenance, and has strong versatility.