Vacuum switch cabinet is one of the most important equipments in power distribution system

so its state has significant influence on the safety of the distribution network and the power quality at customs side.However

the information for condition assessment of distribution switch cabinet is insufficient

and the assessment model is not dynamic. In this paper

a vacuum switch cabinet condition assessment model based on multi-source information fusion is proposed. This model includes such information as ultrasound values

TEV values

infrared temperature

vacuum degree

insulation resistance and mechanical parameters. The vacuum switch cabinet is divided into vacuum circuit breaker

buses

and outlet cable for condition assessment. The environment information

operation information and position information of the vacuum switch cabinet are also taken into consideration. Moreover

membership functions and proportional model are employed in the condition assessment. Then Bayes conditional probability model is used to predict the future condition of the vacuum switch cabinet. In addition

examples are given to prove the validity of the proposed vacuum switch cabinet condition assessment model. Compared with conventional probability calculation model

the proposed model shows better consistency with operation condition of electric power equipments.