Abstract: During long-term operation, high-voltage electrical equipment in hydropower stations is prone to insulation degradation and potential state-related hazards. Traditional data acquisition methods for preventive testing are often inefficient, produce fragmented data, and are difficult to manage uniformly. To address these issues, this paper investigates a data acquisition technology specifically tailored for preventive testing of high-voltage electrical equipment in hydropower stations. By designing a data acquisition system architecture, the study integrates automatic data collection based on communication protocol analysis with auxiliary acquisition methods utilizing image recognition, enabling unified data retrieval from both smart and legacy instruments. Additionally, a standardized data model is established, incorporating data validity verification and trend analysis mechanisms. Field application results from preventive testing of a main transformer at a hydropower station validate the engineering applicability of this technology in improving acquisition efficiency, enhancing data quality, and supporting electronic management.