Modeling and prediction method for inherent energy consumption of CNC machine tool spindle systems.
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| Title: | Modeling and prediction method for inherent energy consumption of CNC machine tool spindle systems. |
|---|---|
| Authors: | Wang, Xuanyi1,2 (AUTHOR), Wu, Hongyi2 (AUTHOR), Yang, Junshou2 (AUTHOR), Deng, Xiaolei2 (AUTHOR) dxl@zju.edu.cn, Piao, Zhongyu1 (AUTHOR), Yao, Xinhua3 (AUTHOR) |
| Source: | Journal of Mechanical Science & Technology. Jul2025, Vol. 39 Issue 7, p4129-4145. 17p. |
| Subjects: | Numerical control of machine tools, Spindles (Machine tools), Bond graphs, Power transmission, Energy consumption |
| Abstract: | The existing machine tool energy consumption (EC) modeling mainly focuses on the total EC or cutting EC of the machine tool, while limited research exists on modeling the inherent EC of mechanical drive components in the spindle system. Therefore, this study adopts bond graph (BG) theory, and under comprehensive consideration of the influence of multiple rotational speeds, a BG model of a belt-type spindle system is established. Then, the output power of the system and the EC characteristics of the key components are obtained through derivation and simulation calculation. The output power of the EC model is used to predict the start-up EC through the peak power mapping method. The feasibility and practicability of the model are verified through experiments. The adjusted R2 value of the damping coefficient of the pulley reaches 0.9998. Experimental results show that the average relative errors of the BG model and the start-up EC prediction model are 2.29 % and 5.94 %, respectively, and the minimum relative errors are 0.34 % and 0.9 %, respectively. The model proposed in this paper provides theoretical support and a new evaluation index for the optimal design of spindle systems. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Mechanical Science & 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 |
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| Header | DbId: egs DbLabel: Engineering Source An: 186466876 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Modeling and prediction method for inherent energy consumption of CNC machine tool spindle systems. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Wang%2C+Xuanyi%22">Wang, Xuanyi</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wu%2C+Hongyi%22">Wu, Hongyi</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Yang%2C+Junshou%22">Yang, Junshou</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Deng%2C+Xiaolei%22">Deng, Xiaolei</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> dxl@zju.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Piao%2C+Zhongyu%22">Piao, Zhongyu</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Yao%2C+Xinhua%22">Yao, Xinhua</searchLink><relatesTo>3</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Journal+of+Mechanical+Science+%26+Technology%22">Journal of Mechanical Science & Technology</searchLink>. Jul2025, Vol. 39 Issue 7, p4129-4145. 17p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Numerical+control+of+machine+tools%22">Numerical control of machine tools</searchLink><br /><searchLink fieldCode="DE" term="%22Spindles+%28Machine+tools%29%22">Spindles (Machine tools)</searchLink><br /><searchLink fieldCode="DE" term="%22Bond+graphs%22">Bond graphs</searchLink><br /><searchLink fieldCode="DE" term="%22Power+transmission%22">Power transmission</searchLink><br /><searchLink fieldCode="DE" term="%22Energy+consumption%22">Energy consumption</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The existing machine tool energy consumption (EC) modeling mainly focuses on the total EC or cutting EC of the machine tool, while limited research exists on modeling the inherent EC of mechanical drive components in the spindle system. Therefore, this study adopts bond graph (BG) theory, and under comprehensive consideration of the influence of multiple rotational speeds, a BG model of a belt-type spindle system is established. Then, the output power of the system and the EC characteristics of the key components are obtained through derivation and simulation calculation. The output power of the EC model is used to predict the start-up EC through the peak power mapping method. The feasibility and practicability of the model are verified through experiments. The adjusted R2 value of the damping coefficient of the pulley reaches 0.9998. Experimental results show that the average relative errors of the BG model and the start-up EC prediction model are 2.29 % and 5.94 %, respectively, and the minimum relative errors are 0.34 % and 0.9 %, respectively. The model proposed in this paper provides theoretical support and a new evaluation index for the optimal design of spindle systems. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Journal of Mechanical Science & 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.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s12206-025-0635-1 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 17 StartPage: 4129 Subjects: – SubjectFull: Numerical control of machine tools Type: general – SubjectFull: Spindles (Machine tools) Type: general – SubjectFull: Bond graphs Type: general – SubjectFull: Power transmission Type: general – SubjectFull: Energy consumption Type: general Titles: – TitleFull: Modeling and prediction method for inherent energy consumption of CNC machine tool spindle systems. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Wang, Xuanyi – PersonEntity: Name: NameFull: Wu, Hongyi – PersonEntity: Name: NameFull: Yang, Junshou – PersonEntity: Name: NameFull: Deng, Xiaolei – PersonEntity: Name: NameFull: Piao, Zhongyu – PersonEntity: Name: NameFull: Yao, Xinhua IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 07 Text: Jul2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 1738494X Numbering: – Type: volume Value: 39 – Type: issue Value: 7 Titles: – TitleFull: Journal of Mechanical Science & Technology Type: main |
| ResultId | 1 |
