Abstract: In order to overcome the deficiency of slower convergence speed and low accuracy of BP algorithm and BP neural network, a combination of Ant Colony optimization algorithm and BP neural network training was used and the validity of the method was verified. It was concluded that the identification of the defect location was shown more effective as compared with the defect size when the ant Colony neural network was used to identify concrete defects.