The invention discloses a
track circuit fault
cause analysis method based on text
record data mining, and belongs to the technical field of
track circuit fault diagnosis and analysis in a
railway signal system, and the method comprises the following steps: S1, collecting a
track circuit fault text, and
processing the track circuit fault text into a standardized fault text R; s2, semantic features and
word order features of the R are extracted and fused, and a
feature set S is output after optimization of an SMOTE
algorithm; s3, inputting the S into an FEML model, and outputting a large-class
label corresponding to the fault text through parameter optimization, parallel training of a base learner and integration of a meta learner; s4, in combination with the
weight value and a Dirichlet multi-term
hybrid model, extracting and outputting a fine-grained fault type and a cause thereof under the large-class
label; and S5, constructing a visual map by using Neo4j, and realizing association analysis through a Cyber
query language. According to the method, the analysis model and the visual
knowledge graph are constructed, fault causes are accurately mined, and the operation and maintenance efficiency is improved.