The analysis of radar fault cause text is helpful to locate the fault location， facilitate equipment maintenance and analyze equipment performance. Knowledge extraction， representation and management of radar fault cause text using knowledge graph technology can effectively improve the utilization efficiency of the text， quickly locate the fault location and analyze the equipment performance in time. On the basis of summarizing the characteristics of radar equipment fault cause text， radar equipment fault cause knowledge graph is constructed by a method combines both the scheme layer and the data layer. The scheme layer of the knowledge graph in the top-down style is designed， which defines the knowledge framework， the concept types， and the relationships between the concepts of the knowledge graph. For the text characteristics， the data layer of knowledge map is constructed in the bottom-up style： in order to solve the problems of small sample size and compound words entity recognition， entity naming recognition is carried out by Att-AlBERT-BiGRU-CRF model. The ALBERT-BiGRU-Att model is used for relationship extraction. Experiments show the effectiveness of the above extraction method. Based on the entities and relationship， the knowledge graph of radar fault causes is constructed.