Abstract: To address challenges in transformer handover testing such as incomplete risk identification and lack of systematic preventive measures during installation processes, this study conducts risk analysis and control technology research for handover testing. By establishing a hierarchical risk factor model covering the entire testing lifecycle, integrating fault tree analysis with fuzzy comprehensive evaluation methods, and designing an active prevention system incorporating environmental awareness and intelligent early warning mechanisms, the study achieves effective control of latent and sudden risks. Comparative experiments demonstrate that this technology outperforms traditional methods in both risk pre-control capabilities and first-pass testing rates, significantly enhancing the safety and reliability of transformer handover testing while demonstrating substantial engineering application value.