Typical operation risk monitoring method for transformer substation based on twin network target tracking

The invention relates to a transformer substation typical operation risk monitoring method based on twin network target tracking. The method comprises the following steps: step 1, constructing a twin network SiamFC based on a full convolutional neural network; 2, constructing a single-person attitude tracker based on a twin network; 3, adopting a body posture estimation and tracking algorithm based on a twin network; 4, introducing a region candidate network to achieve the purpose of multi-scale detection; 5, detecting key point positions of the human body by adopting a posture estimation branch while tracking; 6, a single-person posture tracking task is completed; the method has the advantages that the template matching class tracking algorithm is adopted, the convolutional neural network is adopted to extract features, the feature maps are fused through cross correlation, and the similarity discrimination model is adopted. 本发明涉及基于孪生网络目标跟踪的变电站典型作业风险监测方法，所述的方法包括以下步骤：步骤1：构建基于全卷积神经网络的孪生网络SiamFC；步骤2：构建基于孪生网络的单人姿