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In order to timely and effectively detect and eliminate the fault of marine diesel turbocharging system, the distribution density SPREAD of generalized regression neural network (GRNN) was optimized and selected by fruit fly optimization algorithm (FOA) in this paper.A new method of fault diagnosis based on fly optimization algorithm and generalized regression neural network is proposed. Sample sets of a marine diesel engine were Collected.The same training samples were used to train GRNN optimized by FOA and RBF neural network respectively.The above two models were verified by the same test samples.The results show that compared with the fault diagnosis method of RBF neural network , the method of GRNN optimized by FOA is more accurate to identify the failure modes of the diesel engine turbocharging system.