View in EDS HTML Full Text PDF Full Text

Prediction and analysis of grinding force on grinding heads based on grain measurement statistics and single-grain grinding simulation.

Saved in:
Bibliographic Details
Title: Prediction and analysis of grinding force on grinding heads based on grain measurement statistics and single-grain grinding simulation.
Authors: Li, Baichun1 (AUTHOR), Li, Xiaokun1 (AUTHOR) 1286844926@qq.com, Hou, Shenghui1 (AUTHOR), Yang, Shangru1 (AUTHOR), Li, Zhi1 (AUTHOR), Qian, Junze1 (AUTHOR), He, Zhenpeng1 (AUTHOR)
Source: International Journal of Advanced Manufacturing Technology. May2024, Vol. 132 Issue 1/2, p513-532. 20p.
Subjects: Finite element method, Tangential force, Cephalometry, Statistical models, Prediction models
Abstract: 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. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Advanced Manufacturing Technology is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: egs
DbLabel: Engineering Source
An: 176584961
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Prediction and analysis of grinding force on grinding heads based on grain measurement statistics and single-grain grinding simulation.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Li%2C+Baichun%22">Li, Baichun</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Li%2C+Xiaokun%22">Li, Xiaokun</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> 1286844926@qq.com</i><br /><searchLink fieldCode="AR" term="%22Hou%2C+Shenghui%22">Hou, Shenghui</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Yang%2C+Shangru%22">Yang, Shangru</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Li%2C+Zhi%22">Li, Zhi</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Qian%2C+Junze%22">Qian, Junze</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22He%2C+Zhenpeng%22">He, Zhenpeng</searchLink><relatesTo>1</relatesTo> (AUTHOR)
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Advanced+Manufacturing+Technology%22">International Journal of Advanced Manufacturing Technology</searchLink>. May2024, Vol. 132 Issue 1/2, p513-532. 20p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Finite+element+method%22">Finite element method</searchLink><br /><searchLink fieldCode="DE" term="%22Tangential+force%22">Tangential force</searchLink><br /><searchLink fieldCode="DE" term="%22Cephalometry%22">Cephalometry</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+models%22">Statistical models</searchLink><br /><searchLink fieldCode="DE" term="%22Prediction+models%22">Prediction models</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: 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. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Advanced Manufacturing Technology is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=176584961
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1007/s00170-024-13370-9
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 20
        StartPage: 513
    Subjects:
      – SubjectFull: Finite element method
        Type: general
      – SubjectFull: Tangential force
        Type: general
      – SubjectFull: Cephalometry
        Type: general
      – SubjectFull: Statistical models
        Type: general
      – SubjectFull: Prediction models
        Type: general
    Titles:
      – TitleFull: Prediction and analysis of grinding force on grinding heads based on grain measurement statistics and single-grain grinding simulation.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Li, Baichun
      – PersonEntity:
          Name:
            NameFull: Li, Xiaokun
      – PersonEntity:
          Name:
            NameFull: Hou, Shenghui
      – PersonEntity:
          Name:
            NameFull: Yang, Shangru
      – PersonEntity:
          Name:
            NameFull: Li, Zhi
      – PersonEntity:
          Name:
            NameFull: Qian, Junze
      – PersonEntity:
          Name:
            NameFull: He, Zhenpeng
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 05
              Text: May2024
              Type: published
              Y: 2024
          Identifiers:
            – Type: issn-print
              Value: 02683768
          Numbering:
            – Type: volume
              Value: 132
            – Type: issue
              Value: 1/2
          Titles:
            – TitleFull: International Journal of Advanced Manufacturing Technology
              Type: main
ResultId 1