Research on Automatic Mapping Technology of Substation Monitoring System Based on Decision Tree Algorithm

Aiming at the status quo of substation monitoring system with large number of graphics, high cost of drawing labor, and difficulty of manual adjustment after drawing, this paper proposes a method to analyze the mapping behavior of monitoring system based on a large amount of monitoring system interval mapping data accumulated in different regions in the engineering practice, establishes a self-learning corrective mechanism by combining with the analysis of the mapping behavior, and adopts the decision tree algorithm to train and learn the model and generate the training model based on the trained model and combined with the automatic mapping technology. The decision tree algorithm is used to train and learn the model of each region and generate the training model. Based on the trained model and combined with the automatic mapping technology, the interval maps of the monitoring system are automatically generated according to the characteristics of the region and the behavioral characteristics, and the actual engineering test proves that the method researched in this paper has the effect of enhancing the automation application of the automatic mapping of the monitoring system, which greatly reduces the workload of the onsite engineers, and at the same time, the training and selection of the model do not affect the implementation of on-site engineering. At the same time, the model training and selection are carried out under the condition of not affecting the implementation of on-site engineering, which improves the efficiency of engineering production under the condition of meeting the accuracy and practicality, and solves the problem of drawing interval diagrams for substation monitoring system under the huge data and differentiated needs of users.