Analysis of Occupational Exposure and Influencing Factors for 500kV Substation Personnel Based on Neural Networks

In recent years, with the continuous enhancement of China's economic strength, a large number of high-voltage substations have been put into operation in various provinces across the country, creating a highly complex electromagnetic environment. Therefore, it is crucial to establish a systematic and scientifically reasonable evaluation framework for the health hazards caused by the electromagnetic environment in substations. This paper develops a comprehensive evaluation model for the health hazards of substation workers based on the Fuzzy Analytic Hierarchy Process (FAHP). Through the study of relevant influencing factors, both single-factor and multi-factor analyses are conducted. The findings reveal that the occupational exposure of personnel in 500kV substations is quite severe, with the power frequency electric field being identified as a primary influencing factor. Employing a neural network algorithm to analyze the impact of electric field intensity on occupational exposure, the paper recommends addressing occupational exposure as a critical management concern.