Effective grasping of aerospace electrical connectors is a prerequisite for completing on-orbit assembly tasks，and the set of effective grasping points is limited by the assembly tasks.In this paper，we propose an on-orbit assembly-oriented electrical connector grasping method，which learns the grasping experience from the robot in a simulated environment，and evaluates the grasping quality by detecting the correlation between the grasping position and the assembly task during the grasping-assembly process.In addition，this paper preliminarily takes into account the effect of the electrical connector's tail-end cable on the grasping through the design of the position distribution of the grasping points.Then a grasping network is used to train the grasping point cloud collection to obtain the grasping codebook，which can generate effective grasping points on the one hand，and enhance the demonstrability of effective grasping points through the established surface contact heat map on the other hand.At the same time，this paper proposes a non-uniform normalised object coordinate space representation to establish a dense mapping relationship in 3D space to migrate the effective grasping points to the same class of instances.Simulation results show that 94.1% of the gripping point sets generated based on the method proposed in this paper are effectively used for subsequent assembly tasks.