Research on intelligent classification of multi-attribute safety information and determination of operating environment

Abstract

To analyze the system safety through the field system operation data, especially the system operation information provided by the operators, and to obtain the environment scope of the safe operation of the system, the multi-attribute safety information intelligent mining method is adopted. The new definitions and methods of attribute circle classification are proposed. The improvement is using inner attribute polygon and outer attribute polygon to construct the object attribute area. Monte Carlo method is used to calculate the overlap area of the object attribute area, and define overlap and transform with similarity, which is calculated by the overlap degree and the distance between two points in multi-dimensional space. The object classification reasoning method and system adaptive environment analysis method is established. The improved similarity analysis method is more suitable for computer implementation and intelligent analysis. Based on the previous study, this paper also analyzes the similarity of operation safety evaluation given by 30 operators of an electrical system, and obtains the pair wise similarity. The results show that the algorithm classification results have good correspondence with the original data decision level, and the range of the system safe operation environment is obtained, which can lay a foundation for further study of intelligent classification and system safety operation environment optimization.