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Volume 45 Issue 1
Mar.  2025
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Article Navigation >  Diamond & Abrasives Engineering  > 2025  >  45(1): 1-11
XU Xinyu, HE Xiansong, CHEN Zhaojie, ZHANG Jingying, YANG Linfeng, XIE Jin. Stability and process control of single-diamond grinding based on clustering of processing morphology data[J]. Diamond & Abrasives Engineering, 2025, 45(1): 1-11. doi: 10.13394/j.cnki.jgszz.2024.0013
Citation: XU Xinyu, HE Xiansong, CHEN Zhaojie, ZHANG Jingying, YANG Linfeng, XIE Jin. Stability and process control of single-diamond grinding based on clustering of processing morphology data[J]. Diamond & Abrasives Engineering, 2025, 45(1): 1-11. doi: 10.13394/j.cnki.jgszz.2024.0013
shu

Stability and process control of single-diamond grinding based on clustering of processing morphology data

doi: 10.13394/j.cnki.jgszz.2024.0013

  • School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou 510640, China

More Information
  • Received Date: 2024-01-16
  • Accepted Date: 2024-04-01
  • Rev Recd Date: 2024-03-29
    • Available Online: 2024-04-10
    Abstract
  •   Objectives  In the precision grinding process of hard mold steel workpieces, the subtle changes in machining depth can significantly cause dynamic changes in the magnitude and the direction of grinding forces, which directly lead to unstable machining conditions and affect machining accuracy and surface quality. To this end, the data clustering analysis is used to analyze the machining morphology data of the workpiece, and the stable single-point grinding of the workpiece is achieved through process control.   Methods  Using large particle diamond single-point grinding for hard mold steel, the dynamic characteristics and the stability of the grinding process are analyzed based on the morphology characteristics of the diamond processing surface. The influences of the process parameters on diamond processing efficiency and surface quality are explored to achieve high-efficiency and high-quality diamond grinding. Firstly, the dynamic modeling of the single point diamond grinding system is carried out, and the grinding vibration signal is measured by an accelerometer. The working mode analysis is performed to solve the natural frequency and the damping ratio of the machining system. Then, using a laser confocal microscope to obtain surface waviness and surface roughness data under different processing conditions, the feed depth and the wheel speed are correlated with the data clustering under stable conditions, and matched with the blade diagram area under stable grinding conditions to fit the stiffness and the grinding force coefficients of the processing system. A real-time control area for feed depth and the wheel speed during the stable grinding process is constructed. Finally, the machining efficiency and the quality of the mold steel are verified and analyzed through grinding experiments.   Results  The modal analysis of the grinding process and the clustering matching of the machined surface morphology features can map the machining process parameters in the stable domain of the grinding process. The working mode analysis method is applied to the stability analysis of single-point diamond grinding die steel, and the natural frequency and the damping ratio of the process system can be obtained under the working state. The natural frequency of the single-point diamond grinding die steel process system is fn = 363 Hz, and the damping ratio ξ = 0.027. The clustering analysis method is applied to the machining state classification, and the machining surface can be divided into stable machining and unstable machining according to the internal relationship between the surface waviness Wa and surface roughness Ra data. The surface morphologies of the two types of machining are obviously different. The surface of the stable processing state is smooth and flat, while the surface of the unstable processing state has a large area of plastic deformation and a large number of burrs. The surface machining quality of single-point diamond grinding die steel differs greatly under stable and unstable machining conditions. The average surface waviness Wa of single-point diamond grinding mold steel in the stable processing state is 0.635 μm, and the average surface roughness Ra is 0.143 μm. The average surface waviness Wa in the unstable state is 1.203 μm, and the average surface roughness Ra is 0.267 μm, which is about twice that of the stable state. The experimental points after clustering analysis are matched to the relevant areas on the grinding stability lobe diagram, and the experimental verification is carried out to obtain the system stiffness coefficient k = 7 × 106 N/m and the grinding force coefficient km' = 3 × 1015 N/m3 of the single-point diamond grinding die steel process system.   Conclusions  In the stable processing state, the single-point diamond grinding die steel can achieve a greater material removal rate while ensuring the surface quality as much as possible, thus improving the processing efficiency. In the case of the same amount of material removal, the surface roughness Ra of the stable region processing state is reduced by 74% on average compared with that of the unstable region processing state, which realizes the high-efficiency and the high-surface-quality machining of high-hardness metal materials.

     

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