In view of the limitations of the existing style transfer methods in the data enhancement of water meters.In this paper,we proposed an arbitrary style transfer algorithm based on large convolutional kernel(LKAST).Firstly,the large convolution kernel is used to extract the style features for the style images,and the high-level features of the style features are retained,and a new loss function is introduced to better preserve the content of the migration results. Finally,the effectiveness of the method was verified by two groups of controlled experiments.Experimental results show that the proposed method can simulate the water performance field environment while retaining enough content information,and the accuracy of the SSD object detection algorithm is increased by 6.84%and YOLOv5 by 6.56% under the premise of only changing the data augmentation algorithm.