Aiming at the problem of port mechanical balance beam,classification method of mechanical balance beam coating defects based on transfer learning was designed.The transfer learning based AlexNet model was proposed to fine-tune the weights of the original pre-trained model,and then replace the last fully connected layer(FCL)in the AlexNet model,and then use the target image dataset as the new input to fine-tune the weights of the model by back-propagation to achieve model migration.The experimental re sults showed that the success rate of classification with and without defects could reach more than 93%,the success rate of point-line surface defects classification reached more than 88%,and the accuracy rate for orange peel test reached more than 91%,which could meet the requirements of defect detection and classification.