Abstract: In order to optimize the camera stations in dynamic photogrammetry for large wind turbine blades, an optimization method of photogrammetric network based on improved genetic algorithm for mutation operation was used. A measurement error model was established based on error propagation in the 3-D reconstruction process by front intersecting ray bundles. Taking the standard deviations of the spatial coordinate measurement error as the goal of network optimization, while considering the constraint conditions caused by the wind turbine blade geometry and the actual environment, a simulation experiment was performed to obtain the optimal camera stations. The results show that, in the simulation experiment, the wind turbine with blade length of 40m was taken as the measuring object, the standard deviation of the spatial coordinate measurement errors of the optimal stations is 2.7mm. Real data experiments are conducted on a wind turbine model with 3.5m blade length. The relative measurement error of the optimal station is 0.009%, and the maximum error is 0.617mm. This study provides reference for the network optimization of photogrammetry of wind turbine blades.