Fuel injection nozzles are a key component of electronic injection engines, and their inner surface roughness affects the performance of the nozzles and restricts the working efficiency of the engine. Therefore, the polishing technology for a nozzle’s inner surface is particularly important. At present, abrasive flow polishing technology is commonly used to treat the inner surfaces of the nozzles. This study investigated the magnetic particles in the abrasive flow working medium. Due to the external magnetic field, magnetic particles are affected by the magnetic field force and change the polishing performance of the abrasive flow working medium. Through a numerical analysis and contrast experimental research, we can see that the choice of different grinding grain sizes, kinematic viscosity, magnetic field intensity, and process parameters, such as inlet pressure, with magnetic particles in a solid–liquid two-phase abrasive flow for polishing, can effectively improve the quality of the injection nozzle’s inner surface. The study also reveals that the influence of the nozzle’s inner surface polishing quality is significant and creates a mechanism for process parameters.

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Polygonal helical curved tube is the main form of rifling barrel, which surface quality determines the shooting accuracy of gun. Abrasive flow machining (AFM) technology can significantly improve its inner surface quality. In order to study the influence of AFM technical parameters on the inner surface quality of polygonal helical curved tube, orthogonal experimental design (OED) was used as the research method in this paper. By means of analysis of variance (ANOVA) of experimental data, the degree of influence of inlet pressure, abrasive concentration, abrasive particle size and machining time on the inner surface quality of polygonal helical curved tube was determined, and the optimal combination of process parameters was obtained. Under the optimal process parameters, the surface roughness Ra value in the inlet area of polygonal helical curved tube was reduced to 0.098 µm. The surface quality was significantly improved. Based on the regression analysis of experimental data, the quality prediction model of polygonal helical curved tube roughness by AFM was established to realize the effective prediction of surface quality after machining. The fitting value calculated by the model with optimal process parameters is close to the experimental value, which proves the accuracy and validity of the prediction model.