In order to meet the requirements of high coverage rate and high precision in large-size three-dimensional profile measurement, an intelligent network planning method considering the measurement coverage rate and three-dimensional uncertainty is proposed. Combined with the requirements of the visual measurement, the discretization geometry model of visual measurement network is determined, the decision variables of network planning are established, and two concepts of the visual measurement network coverage rate and the three-dimensional uncertainty of the target are also given. The multi-visual network is realized accurately by the analysis of several constraint conditions of camera position and globally searching on decision variables through multi-objective genetic algorithm. Simulation of the propeller main structural model is conducted. It is concluded that the coverage rate of measurement network can reach 99.72%, and the three-dimensional uncertainty can converge to 0.0326 mm. The effectiveness and feasibility of the strategy are verified through single vision multi-station measurement experiment.