As a place with extremely high safety protection factor,substations are often damaged.Although the current substations are equipped with various technical defense systems,the lack of correlation between the various systems results in a high rate of false alarms and false alarms.Protecting the safety of substations can be achieved by accurately identifying the attributes of objects in the alarm area,reducing the rate of false alarms and false alarms.Accurately identifying the attributes of objects is of great significance for the safety protection of substations.In response to such problems,this paper proposes a substation alarm area property recognition based on the SVM algorithm,which integrates multiple independent information of video,sound,radar and thermal imaging to obtain multi-dimensional information of the object,and adopts a combination of feature engineering and machine learning technology.The intrusion object recognition classification algorithm realizes the object recognition in the alarm area of the substation.Through experimental analysis,it is verified that the method proposed in this paper can accurately identify the attributes of objects and provide strong support and guarantee for the safety protection of substations..