{"title":"基于晶粒测量统计和单晶粒磨削模拟的磨削头磨削力预测和分析","authors":"Baichun Li, Xiaokun Li, Shenghui Hou, Shangru Yang, Zhi Li, Junze Qian, Zhenpeng He","doi":"10.1007/s00170-024-13370-9","DOIUrl":null,"url":null,"abstract":"<p>Reliable prediction of the grinding force is essential for improving the grinding efficiency and service life of the grinding head. To better optimize and control the grinding process of the grinding head, this paper proposes a grinding force prediction method of the grinding head that combines surface measurement, statistical analysis, and finite element method (FEM). Firstly, a grinding head surface measurement system is constructed according to the principle of focused imaging. The distribution model of abrasive grains in terms of size, spacing, and protruding height has been established by measuring and counting the characteristics of abrasive grains on the surface of a real grinding head. Then, the undeformed chip thicknesses when the abrasive grains are cut are analyzed in depth, the material model of abrasive grains and workpiece is established, and the cutting process of abrasive grains with different characteristics on the surface of the grinding head is analyzed by finite element simulation. A single abrasive grain grinding force model is obtained. Finally, the grinding force prediction of the grinding head was realized by combining finite element simulation with grinding kinematics analysis. In addition, grinding experiments with different grinding parameters were conducted to verify the grinding force prediction model. The results show that the predicted grinding force of the grinding head is in good agreement with the experimental values. The average error of tangential grinding force is 7.42%, and the average error of normal grinding force is 9.77%. This indicates that the grinding force prediction method has good accuracy and reliability.</p>","PeriodicalId":50345,"journal":{"name":"International Journal of Advanced Manufacturing Technology","volume":"24 1","pages":""},"PeriodicalIF":2.9000,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Prediction and analysis of grinding force on grinding heads based on grain measurement statistics and single-grain grinding simulation\",\"authors\":\"Baichun Li, Xiaokun Li, Shenghui Hou, Shangru Yang, Zhi Li, Junze Qian, Zhenpeng He\",\"doi\":\"10.1007/s00170-024-13370-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Reliable prediction of the grinding force is essential for improving the grinding efficiency and service life of the grinding head. To better optimize and control the grinding process of the grinding head, this paper proposes a grinding force prediction method of the grinding head that combines surface measurement, statistical analysis, and finite element method (FEM). Firstly, a grinding head surface measurement system is constructed according to the principle of focused imaging. The distribution model of abrasive grains in terms of size, spacing, and protruding height has been established by measuring and counting the characteristics of abrasive grains on the surface of a real grinding head. Then, the undeformed chip thicknesses when the abrasive grains are cut are analyzed in depth, the material model of abrasive grains and workpiece is established, and the cutting process of abrasive grains with different characteristics on the surface of the grinding head is analyzed by finite element simulation. A single abrasive grain grinding force model is obtained. Finally, the grinding force prediction of the grinding head was realized by combining finite element simulation with grinding kinematics analysis. In addition, grinding experiments with different grinding parameters were conducted to verify the grinding force prediction model. The results show that the predicted grinding force of the grinding head is in good agreement with the experimental values. The average error of tangential grinding force is 7.42%, and the average error of normal grinding force is 9.77%. This indicates that the grinding force prediction method has good accuracy and reliability.</p>\",\"PeriodicalId\":50345,\"journal\":{\"name\":\"International Journal of Advanced Manufacturing Technology\",\"volume\":\"24 1\",\"pages\":\"\"},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2024-03-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Advanced Manufacturing Technology\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1007/s00170-024-13370-9\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Advanced Manufacturing Technology","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1007/s00170-024-13370-9","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
Prediction and analysis of grinding force on grinding heads based on grain measurement statistics and single-grain grinding simulation
Reliable prediction of the grinding force is essential for improving the grinding efficiency and service life of the grinding head. To better optimize and control the grinding process of the grinding head, this paper proposes a grinding force prediction method of the grinding head that combines surface measurement, statistical analysis, and finite element method (FEM). Firstly, a grinding head surface measurement system is constructed according to the principle of focused imaging. The distribution model of abrasive grains in terms of size, spacing, and protruding height has been established by measuring and counting the characteristics of abrasive grains on the surface of a real grinding head. Then, the undeformed chip thicknesses when the abrasive grains are cut are analyzed in depth, the material model of abrasive grains and workpiece is established, and the cutting process of abrasive grains with different characteristics on the surface of the grinding head is analyzed by finite element simulation. A single abrasive grain grinding force model is obtained. Finally, the grinding force prediction of the grinding head was realized by combining finite element simulation with grinding kinematics analysis. In addition, grinding experiments with different grinding parameters were conducted to verify the grinding force prediction model. The results show that the predicted grinding force of the grinding head is in good agreement with the experimental values. The average error of tangential grinding force is 7.42%, and the average error of normal grinding force is 9.77%. This indicates that the grinding force prediction method has good accuracy and reliability.
期刊介绍:
The International Journal of Advanced Manufacturing Technology bridges the gap between pure research journals and the more practical publications on advanced manufacturing and systems. It therefore provides an outstanding forum for papers covering applications-based research topics relevant to manufacturing processes, machines and process integration.