摘要：In order to improve the accuracy rate of aero-engne gas-path fault diagnosis based on BP neural network,this research uses the genetic algorithm to optimize the initial weights and thresholds of BP neural networkin their solution space, retrains the results by gradient descent algorithm and uses the optimized network to testifythe fault samples. The result shows that GA-BP network has a higher precision and converges faster, and its convergencec u r e is smoother than that of the common BP network. This work can put forward new ideas and methodsfor aero-engine fault diagnosis and has a certain research value.

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