Intelligent monitoring method of running state of charging station based on multi-source data fusion

There is diversity in the type, scale, equipment suppliers, and other aspects of charging stations, so the monitoring requirements and technical requirements of different stations are not the same. At the same time, the running state of the charging station is affected by many factors, which makes it difficult to monitor. Therefore, an intelligent monitoring method based on multi-source data fusion is designed. With the fusion of charging station data, calculation of the reliability between data sources, and the degree of feature similarity after data fusion, the fusion process is designed. Based on this, the color correction algorithm based on K-L transformation is used to solve the color inconsistency and color distortion of the distorted video of the running state monitoring of the charging field. The multi-target tracking method based on a particle filter is adopted to obtain real-time information about the target and realize the intelligent monitoring of the running state of the charging field. The experimental results show that the background and the target of the charging vehicle in the surveillance video after processing by the proposed method are clear. The monitoring time is shorter, and the application effect is good.