Aiming at the problems of low artificial processing efficiency and low recognition rate of fuzzy image in the process of loading petrochemical dangerous goods, an intelligent repair and detection method of monitoring fuzzy image based on the combination of generative adversarial network (GAN), convolutional neural network (CNN) and extreme learning machine (ELM) is proposed. Firstly, using the deep learning network as the target detection framework, the fuzzy image is restored by using the zero sum game between the generator and the discriminator in the generative adversarial network to obtain a clear and complete job image. Secondly, using the ability of convolutional neural network to adaptively learn image features, the autonomous features of the repaired image are extracted. Finally, the extracted features are input into the extreme learning machine classifier for target recognition and classification to judge whether there are violations in the operation process. The experimental results show that the proposed method has fast image restoration speed, natural visual effect, high accuracy of target recognition and good generalization ability.