One of the essential works of the tunnel maintenance department is to inspect and maintain the electricity transmission system (ETS). Tunnel inspection with a mobile laser system (MLS) can automate the traditionally manual surveys. In this study, we proposed a step-wise method for automatically extracting ETS in MLS data. First, in the approximate extraction stage, we used edge-based and fitting-based segmentation algorithms to remove the ground and lining, respectively. Then, in the precise extraction stage, power transmission lines were accurately extracted at the object-level using a proposed spherical-stepping-cluster algorithm, and the supporting fixtures were extracted using density information and connection characteristics. The proposed method was validated through experiments on a batch of point cloud markings with ground-truth data and comparisons with existing methods. The average F-score for the datasets was 94.2 %, indicating that this research provides a new paradigm for extracting tunnel ETS.