关键词: 关键词：电力施工, 不安全行为, R3D模型, 云平台, 预警系统, 决策融合, 多源数据

Abstract:
 In order to reduce the occurrence of safety accidents and ensure the safety of power operators in the process of power grid construction， a behavior recognition model based on decision fusion of three dimensional residual convolutional neural network （R3D） models is proposed. First， the captured video dataset is subjected to data cleaning and enhancement； then， the corresponding R3D models are trained with the datasets collected from multiple angles； further， the multiple R3D models are fused at the decision level； finally， the possible violations or dangerous behaviors of power operators are warned in real-time by building a cloud platform. The experimental results show that the model has the advantages of high recognition accuracy and a low number of parameters， which proves that the behavior safety early warning method proposed in this paper can make early warning quickly and accurately and provide a safety guarantee for power grid construction.

Key words: Key words: power construction, unsafe behavior, R3D model, cloud platform, early warning system, decision fusion, multi-source data