Similarity matching algorithm of equipment fault diagnosis based on CBR

Abstract

In view of the lack of semantic information description in commonly-used knowledge representation modes such as framework and object-oriented mode, the domain ontology of electronic protective equipment fault diagnosis is designed by analyzing and summarizing the characteristics of the equipment fault cases. Considering that the traditional VSM (vector space model) ignores the role of the position of document entries and structural elements in describing the semantic correlation between features, K-NN (K-nearest neighbor) similarity matching algorithm based on SVSM (semantic vector space model) is proposed by making full use of the advantages of ontology in semantic knowledge representation. For electronic protective equipment fault diagnosis algorithm based on CBR (case based reasoning), a detailed description is given and its feasibility and advantage in performance is proved through experiment.