单颗磨粒磨削机理与数据融合驱动的磨削过程建模分析

doi:10.3901/JME.2023.07.200

机械工程学报 ›› 2023, Vol. 59 ›› Issue (7): 200-215.doi: 10.3901/JME.2023.07.200

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单颗磨粒磨削机理与数据融合驱动的磨削过程建模分析

吕黎曙¹, 邓朝晖², 岳文辉^1,3, 万林林^1,3, 刘涛⁴

1. 湖南科技大学机电工程学院湘潭 411201;
2. 华侨大学制造工程研究院厦门 361021;
3. 湖南科技大学难加工材料高效精密加工湖南省重点实验室湘潭 411201;
4. 湖南工业大学机械工程学院株洲 412007

收稿日期:2022-06-17 修回日期:2022-12-28 出版日期:2023-04-05 发布日期:2023-06-16
通讯作者: 吕黎曙(通信作者),男,1991年出生,博士。主要研究方向为高效精密绿色制造。E-mail:ldlylls@163.com
作者简介:邓朝晖,男,1968年出生,博士,教授,博士研究生导师。主要研究方向为磨削加工与磨削智能化。E-mail:edeng0080@vip.sina.com;岳文辉,男,1965年出生,博士,教授,博士研究生导师。主要研究方向为绿色制造与再制造。E-mail:whyue@hnust.edu.cn;万林林,男,1984年出生,博士,副教授,博士研究生导师。主要研究方向为加工过程智能决策与工艺数据库。E-mail:lynn8486@163.com;刘涛,男,1990年出生,博士。主要研究方向为高效精密磨削。E-mail:ddyxxt1@163.com
基金资助:
国家自然科学基金-浙江两化融合联合基金(U1809221)、湖南省创新型省份建设专项(2020GK2003)和湖南省教育厅科学研究(22B0483)

Modeling Analysis of Grinding Process Driven by Single Grain Grinding Mechanism and Data Fusion

Lü Lishu¹, DENG Zhaohui², YUE Wenhui^1,3, WAN Linlin^1,3, LIU Tao⁴

1. College of Mechanical and Electrical Engineering, Hunan University of Science and Technology, Xiangtan 411201;
2. Institute of Manufacturing Engineering, Huaqiao University, Xiamen 361021;
3. Hunan Provincial Key Laboratory of High Efficient and Precision Machining of Difficult-to-Cut Materials, Hunan University of Science and Technology, Xiangtan 411201;
4. School of Mechanical Engineering, Hunan University of Technology, Zhuzhou 412007

Received:2022-06-17 Revised:2022-12-28 Online:2023-04-05 Published:2023-06-16

摘要/Abstract

摘要： 实现磨削过程的精准预测对于实现我国节能减排的目标具有重要意义。针对现有磨削能耗研究无法准确表征出磨削能量流动情况和未考虑能耗动态变化数据等问题，提出一种基于单颗磨粒磨削机理与数据融合驱动的磨削过程建模分析方法。建立了考虑磨粒的尺寸、位置、角度、出刃高度的砂轮表面形貌模型，推导了磨粒与工件材料接触分析情况的数学表述模型，探讨了基于不同磨粒形状的磨削力与能耗模型的建立方法；在此基础上，建立了零件磨削机理与数据分析相融合的动态自学习能耗预测模型。实验结果表明融合模型的相对误差平均值为3.630 7%，不仅可以揭示磨削过程能量的生成和演变机制，更能够实现对磨削结果的精准预测。

关键词: 单颗磨粒, 磨削, 机理与数据融合, 磨削力, 磨削能耗

Abstract: Accurate prediction of the grinding process is of great significance to achieve the goal of energy conservation and emission reduction in China. In view of the problems that the existing grinding energy consumption research cannot accurately characterize the grinding energy flow and the dynamic change data of energy consumption are not considered, a modelling analysis method of grinding process driven by single grain grinding mechanism and data fusion is proposed. The surface topography model of the grinding wheel considering the size, position, angle, and edge height of the grain is established. The mathematical expression model of the contact analysis between grains and workpiece material is deduced, and the establishment method of grinding force and energy consumption based on different abrasive grain shapes is discussed. On this basis, a dynamic self-learning and energy consumption prediction model integrating grinding mechanism and data analysis is established. The experimental results show that the average relative error of the fusion model is 3.630 7%, which can not only reveal the generation and evolution mechanism of energy in the grinding process, but also achieve accurate prediction of the grinding results.

Key words: single grain, grinding, mechanism and data fusion, grinding force, grinding energy consumption

中图分类号:

TG156

吕黎曙, 邓朝晖, 岳文辉, 万林林, 刘涛. 单颗磨粒磨削机理与数据融合驱动的磨削过程建模分析[J]. 机械工程学报, 2023, 59(7): 200-215.

Lü Lishu, DENG Zhaohui, YUE Wenhui, WAN Linlin, LIU Tao. Modeling Analysis of Grinding Process Driven by Single Grain Grinding Mechanism and Data Fusion[J]. Journal of Mechanical Engineering, 2023, 59(7): 200-215.

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单颗磨粒磨削机理与数据融合驱动的磨削过程建模分析

Modeling Analysis of Grinding Process Driven by Single Grain Grinding Mechanism and Data Fusion

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