In order to shorten the cathode design cycle, reduce design cost and improve forming accuracy for allmetal screw drill stator electrochemical machining (ECM), this paper proposed a precision forming cathode design method based on particle swarm optimization BP neural network (PSO-BP). The cathode design algorithm model of all-metal screw drill stator electrochemical machining was established, completed the three-side feed cathode design. By using self-developed large scale horizontal CNC electrochemical machining equipment, under the condition of voltage 19V, electrolyte 15%NaCl, electrolyte temperature 35 ± 1℃, electrolyte inlet pressure 1.6MPa, and feed speed 10mm/min, the stable and reliable electrochemical machining processing of the 4-meter length of 38CrMoAlA all-metal screw drill stator was completed. The contour forming accuracy is ± 0.03mm, and the surface roughness is Ra0.848µm. Research showed that it is an e cient and feasible method to design the electrochemical machining three-side feed cathode of all-metal screw drill stator using particle swarm optimization BP neural network.
Highlights► The structure of the inner hole of the all-metal screw drill is complicated and the precision is di cult to control, which brings great di culties to the manufacture.► In order to improve the quality of electrochemical machining, particle swarm optimization BP neural network was used to design the three-sided feed cathode for electrochemical machining.► The cathode design algorithm model of all-metal screw drill stator electrochemical machining was established, completed the three-side feed cathode design.► Using particle swarm optimization BP neural network to design cathode is an effective method to improve the accuracy of electrochemical machining.
