Abstract: The fault information of trucks in open-pit mines is obtained mainly by manual collection method,due to the poor ability of intelligent fault diagnosis.With low levels of standardization of fault information and procedure of fault management,the fault analysis work cannot be conducted deeply.Considering above-mentioned problem,a new fault analysis method based on natural language processing technology is proposed.The initial feature vectors are obtained firstly by pretreating fault text information,the vector space model is used to gather statistics on pretreatment result,and the initial feature vectors are obtained;then,the principal component analysis algorithm is adopted to descend dimension of initial feature vectors to establish the fault feature spatial model;finally,the fault mining model is trained by using these feature vectors,so as to analyze and mining the fault information of the truck in open-pit mine.The rationality of the mining and analyzing method proposed in this paper is verified based on the practical data of mines,and it is further indicated that it can provide a new and effective approach for analyzing and managing the fault information of trucks in open-pit mines.

Key words: Open-pit mine, Fault management, Natural language processing, Data mining