As a frequent fault in distribution systems

line trip has accumulated a large number of filling texts

which are processed by manual methods. To overcome the disadvantiages of the inefficiency and subjectivity of manual methods

an intelligent mining method for a filling text of line trip of distribution system is proposed to automatically extract the fault phenomena and causes of a filling text

which provides the necessary conditions for the cause analysis of next line trip and the strategy of security control. In this method

the logical characteristics of the filling text narration of distribution system line trip are utilized

and a text extraction method of trip filling texts is proposed based on word segmentation

part-of-speech tagging

and syntactic structure parsing. Thereby

a two-stage text selection method is presented

in which the word vectorization model（word2 vec） is first used to perform the distributed representation of the filling text

then the filling text is filtered according to cosine similarity. After that

the character editing distance is further used for the second-stage filtering to determine the final results of text mining. The case analysis based on a distribution system in a province shows that the proposed text intelligent mining method can achieve an accuracy rate of more than 72%

the text processing efficiency is significantly improved

and it can initially meet the actual needs.