Research On Methods Of Distribution Switch Cabinet Condition Assessment Based On Multi-source Information Fusion

Switch cabinet has some special characteristics such as closed constructed type, a huge quantity of installation, wide distribution, etc. Failure rate of switch cabinet is the highest in all main equipments in power distribution system. Serve as one of the most important equipments in power distribution system, switch cabinet plays the role to control and protect other electric power equipments, and is important to the safety and stability of power distribution system. The current domestic and foreign research in condition assessment of switch cabinet is still in its infancy. Therefore, basic safety information and scientific basis will be provided by a reasonable and accurate condition assessment method, and furthermore, contributions to safety and stability operation of the whole power distribution system will be made.Against the shortcomings of existed distribution switch cabinet condition assessment methods, according to the characteristics of the structure and installation feature of the switch cabinet, based on technology of multi-source information fusion, a condition assessment method is proposed in this paper. Firstly, key state of the switch cabinet is analyzed in the paper, according to importance of different characteristics, layered space model is established, which is served as the structural basis of characteristic information fusion. Then, the matter-element extenics theory is introduced to fuse the information and assess the current condition of switch cabinet. Meanwhile, traditional extenics is improved from two aspects:weight allocation and correlation calculation. Finally, based on history and current assessment results, dynamic Bayesian inference is used to predict the condition of switch cabinet in future, which provide a good basis for condition based maintenance.In the mean time, a practical example is used to illustrate the process of condition assessment, and the evaluation results of the proposed methods is compared with conventional extenics theory and the reality condition of the switch cabinet, which prove the validity of the methods; the past and present condition assessment results of a switch cabinet is fused via Bayesian network to predict its condition in future and is compared with the reality condition of the switch cabinet, result shows that the proposed method is effective.