Abstract:In order to improve the integrity, timeliness and standardization of the defect text of power grid equipment, and improve the defects management caused by incomplete defect data, such as extensive control mode, post control, incomplete data, incomplete defect elimination and incomplete defect analysis,the phenomenon of cardiopulmonary bypass existed in the defective data.Therefore, this paper proposes the development and application of a model for deep mining grid equipment defects cardiopulmonary bypass based on big data.With a large number of historical defect data as the carrier, based on TF-IDF algorithm to identify the huge historical defect data, extract the keywords belonging to the defect, through the defect keywords to screen out the work tickets belonging to the defect. Then Pair Letters Similarity algorithm and Jaro Winkler algorithm are used to match the defect work ticket with the existing defect data. Finally, the unmatched data is the defect cardiopulmonary bypass data.The test results show that the research model effectively improves the integrity of defect data, and has obvious advantages in the integrity of defect data and the timeliness of data filling.