In order to improve the accuracy of industrial CT defect detection,this paper presents a CT defect detec-tion method based on GA-BP neural network.Using genetic algorithm,the weights and thresholds of BP neural network were optimized,and an industrial CT defect detection model based on GA-BP neural network was estab-lished.Industrial CT images were used to compose the experimental data for simulation analysis,and the monitoring effect was compared with that of convolutional neural network and support vector machine.The results show that this method can reduce the number of false detection of GA-BP neural network model,the accuracy is up to 96.67％,and the effect is better,and it has good feasibility and practicability.
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