When natural language processing (NLP) technology is applied to industrial internet, problems such as lack of data and imbalance of data are often encountered. In order to improve the accuracy and robustness of the model, text data augmentation was proposed to expand data. Data augmentation is widely used in computer vision. For example, the semantics of the image will not be changed if the image is rotated several degrees or converted to gray level. However, augmentation of text data in NLP is pretty rare. Data augmentation is a low-cost means to expand the amount of data and improve the effect of the model, which has a wide range of applications.