-
摘要: 硬质模具钢的磨削过程因加工深度变化会引起磨削力变化,导致加工状态不稳定。因此,采用大颗粒金刚石的单点磨削,基于加工表面的形貌特征分析磨削过程的动态特性及稳定性,探究工艺参数与加工效率和表面质量的作用机制,旨在实现高效率高质量的磨削加工。首先,对单点金刚石磨削系统进行动力学建模,再采用加速度传感器测量磨削振动信号并进行工作模态分析,求解加工系统的固有频率和阻尼比。然后,基于加工表面波纹度和粗糙度的特征化数据,关联进给深度和砂轮转速对加工稳定状态进行数字化聚类分析,与磨削稳定性的叶瓣图区域匹配,拟合出加工系统刚度和磨削力系数,构建进给深度和砂轮转速实时可控的磨削过程稳定性。最后,通过模具钢的磨削实验进行验证,分析加工效率和质量。结果表明:磨削过程的模态分析与加工表面形貌特征的聚类匹配能够映射磨削过程稳定域的加工工艺参数。在磨削稳定域内,采用更大材料去除率可以将平均表面波纹度从1.203 μm下降到0.635 μm,平均表面粗糙度从0.267 μm下降到0.143 μm。而且,在相同材料的去除量下,稳定域加工的表面粗糙度平均能够下降74%。因此,在加工过程中依据加工表面特征化的磨削稳定域实时调整进给深度和砂轮转速,可以同时提高加工质量和效率。Abstract: The grinding process of hardened mold steel can result in variations in grinding forces due to changes in machining depth, leading to unstable machining conditions. Therefore, utilizing single-point grinding with large-grain diamond, based on the analysis of the surface morphology characteristics of the machining surface, the dynamic properties and stability of the grinding process are investigated. The aim is to explore the mechanism of the effect of process parameters on machining efficiency and surface quality, with the goal of achieving high-efficiency and high-quality grinding. Firstly, the single-point diamond grinding system is dynamically modeled, and then the grinding vibration signals are measured using an accelerometer for modal analysis of the working system. The natural frequency and damping ratio of the machining system are solved. Next, based on the characterization data of surface waviness and roughness, a digital clustering analysis is performed to correlate the feed depth and wheel speed with the stable machining state. This is matched with the stability lobes diagram of grinding to fit the stiffness of the machining system and the coefficient of grinding force. Thus, a real-time controllable grinding process stability is established by controlling the feed depth and wheel speed. Finally, the grinding experiments on mold steel are conducted to validate and analyze the machining efficiency and quality. The results demonstrate that the modal analysis of the grinding process, along with the clustering matching of the surface morphology characteristics, can effectively map the machining process parameters within the stable domain of the grinding process. Within the stable domain of grinding, using a higher material removal rate can reduce the average surface waviness from 1.203 μm to 0.635 μm, and the average surface roughness from 0.267 μm to 0.143 μm. Moreover, under the same material removal amount, the average surface roughness of stable domain grinding can be reduced by 74% compared to unstable domain grinding. Therefore, by adjusting the feed depth and wheel speed in real-time based on the characterized stable domain of grinding during the machining process, it is possible to simultaneously improve the machining quality and efficiency.
-
Key words:
- single point diamond /
- grinding stability /
- cluster analysis /
- surface quality /
- roughness
点击查看大图
计量
- 文章访问数: 260
- HTML全文浏览量: 88
- 被引次数: 0