Polishing inner wall of crossed deep micropores using magnetic microabrasive jet technology
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摘要: 针对交叉深孔内壁常规光整加工尺寸受限、加工不均匀、质量差等问题，结合磨料射流去除函数稳定、自适应性强等特点，用磁性微磨料射流技术对交叉深孔内壁进行光整加工以提高其质量。通过动态磁场下的磁性微磨料聚焦技术，采用有限元法和离散元法耦合对不同参数下的磁性微磨料射流抛光交叉深孔内壁过程进行模拟，分析不同参数下的流场分布、侵蚀速率、壁面剪切力作用规律。通过响应面法对射流靶距、射流压强及喷嘴直径3参数进行优化，以孔口、孔内壁面及孔交叉部分所受的壁面剪切力和侵蚀速率的综合影响为响应值，建立响应面方程，获得最佳参数组合并进行试验验证。结果表明：利用响应面法得到的最佳工艺参数组合是射流靶距为7.0 mm，射流压强为1.0 MPa，喷嘴直径为1.4 mm；在此组合参数下加工的交叉深孔内部相贯处毛刺等缺陷被有效去除，其内壁面孔附近的表面粗糙度Ra从0.49 μm降至0.13 μm，且孔口处有较好的倒圆效果。Abstract:
Objectives Precision micro through-hole parts are widely used. However, due to the limitations of manufacturing technology, precision parts with complex shapes, such as cross micro-holes, may have defects such as burrs, scratches, and nodules during the manufacturing process. In view of the problems of conventional finishing processing of cross deep micro-holes being limited by size, uneven processing, and poor quality, and combined with the characteristics of a stable removal function and strong adaptability of the abrasive jet, the magnetic micro-abrasive jet technology finishing processing method is proposed to improve the quality of the inner wall of cross deep micro-holes. Methods An independent magnetic abrasive jet device was used to carry out finishing tests on the cross deep micro-holes, and an electromagnetic device was used to generate a focusing magnetic force near the nozzle outlet. The magnetic abrasive was concentrated towards the center during the internal movement of the nozzle, alleviating the problem of rapid divergence of the magnetic abrasives with the jet after spraying and further improving the efficiency of finishing processing. A simulation mathematical model was established to explore the influence of different process parameters on the finishing effect. The finite element method and the discrete element method were coupled to simulate the polishing process of the inner wall of deep micro-holes by the magnetic micro-abrasive jet under different process parameters. The flow field distribution, the erosion rate, and the action law of wall shear force under different parameters were analyzed, and the key factors were identified. Finally, the response surface method was used to optimize the three factors of jet target distance, jet pressure, and nozzle diameter. The response surface equation was established and solved by taking the comprehensive influences of wall shear force and erosion rate on the orifice, the inner wall of the hole, and the cross part of the hole as the response value, and the optimal combination of process parameters was obtained and verified by the test. Results Adding a focusing magnetic field near the nozzle can effectively reduce the divergence of the abrasive after jet ejection, and further improve the efficiency and quality of magnetic abrasive ejection polishing of cross deep micro-holes. The simulation results show that the main parameters affecting micro-hole finishing are jet target distance, jet pressure, and nozzle diameter. By using the response surface method combined with experiments for parameter optimization, the optimal process parameter combination for magnetic micro-abrasive jet finishing of cross deep micro-hole inner walls is obtained, which includes a jet target distance of 7 mm, a jet pressure of 1.0 MPa, and a nozzle diameter of 1.4 mm. Under the optimal combination of process parameters, the inner wall quality of the cross deep micro-holes is significantly improved, the burrs at the cross-holes are completely removed, the wall roughness Ra is reduced from 0.49 μm to 0.13 μm, and the orifice has a good rounding effect. Conclusions By combining magnetic fields and abrasive jets, the magnetic micro-abrasive jet technology provides a new method for the finishing of cross deep micro-holes. Due to the ability of the magnetic abrasive micro-jet to achieve focused fixed-point machining, it has significant processing advantages in cross deep micro-hole finishing and deburring. By constructing a physical model of the machining process and using the simulation form of coupling the finite element method and the discrete element method, it is possible to more clearly simulate the motion of the abrasive and flow field in the abrasive water jet during the machining process, as well as the force situation of the workpiece being machined. In the finishing process of cross-hole parts, the nozzle diameter, pressure, and target distance have a direct impact on the finishing effect. However, parameter adjustment is required for finishing workpieces of different sizes and shapes. Finding suitable processing parameters will further improve the quality and efficiency of workpiece processing. -
图 5 磨料颗粒与流体的速度变化曲线
Figure 5. Velocity variation curves between abrasive particles and fluid
图 15 射流在空气中的速度变化云图及发散情况
Figure 15. Velocity change nephogram and divergence of jet in air
图 19 靶距和喷嘴直径的交互影响
Figure 19. Interactive effect of target distance and nozzle diameter
图 20 加工前后工件表面形貌及表面粗糙度
Figure 20. Surface morphology and surface roughness of workpiece before and after processing
表 1 研磨介质成分及参数
Table 1. Composition and parameters of grinding medium
成分 基本颗粒尺寸 D1 / $ \mathrm{\mu }\mathrm{m} $ 质量分数 ω / % α-Al2O3磁性磨料 50 5.0 悬浮剂 0.1 分散剂 0.3 纯净水 余量 
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表 2 不同射流压强下射流的最大速度和质量流率
Table 2. Maximum velocity and mass flow rate of jet under different jet pressures
压强 p' / MPa 射流最大速度 vmax / (m·s−1) 质量流率 M / (kg·s−1) 0.1 14.3 0.0205 0.4 29.0 0.0413 0.7 38.6 0.0548 1.0 46.2 0.0656 1.3 52.8 0.0749
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表 3 试验设计的因素及水平
Table 3. Factors and levels of experimental design
水平 因素 射流靶距 d / mm
A射流压强 p' / MPa
B喷嘴直径 D2 / mm
C−1 4.0 0.8 0.8 0 7.0 1.0 1.4 1 10.0 1.2 2.0
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表 4 响应面法计算结果
Table 4. Response surface method calculation results
因素 平方和 SS 自由度 df 均方值 MS F值 P值 模型 2.28 × 105 9 2.53 × 105 801.04 < 0.0001 A 2.73 × 105 1 2.73 × 105 861.83 < 0.0001 B 1.48 × 105 1 1.48 × 105 469.72 < 0.0001 C 2.04 × 105 1 2.04 × 105 644.33 < 0.0001 AB 716.71 1 716.71 2.26 0.1762 AC 6531.30 1 6531.30 20.62 0.0027 BC 13239.02 1 13239.02 41.80 0.0003 A2 1.28 × 105 1 1.28 × 105 406.57 < 0.0001 B2 6.46 × 105 1 6.46 × 105 2039.36 < 0.0001 C2 7.11 × 105 1 7.11 × 105 2247.39 < 0.0001 残差 2217.29 7 316.76 失拟量 2217.29 3 739.10 误差 0.00 4 0.01 总和 2.28 × 106 16
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