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Evaluation Method of the Band Saw Blade Wear State Based on Current Signals.

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Title: Evaluation Method of the Band Saw Blade Wear State Based on Current Signals.
Authors: Li, Dongliang1,2 (AUTHOR), Chen, Bing2 (AUTHOR) chenbing@hnust.edu.cn, Fu, Jiahao1 (AUTHOR), Liu, Zihao1,2 (AUTHOR), Liu, Junchang1 (AUTHOR), Ou, Wenchu1 (AUTHOR), Liu, Guoyue2 (AUTHOR)
Source: Materials (1996-1944). May2026, Vol. 19 Issue 9, p1853. 24p.
Subjects: Band saws, Condition-based maintenance, Statistical correlation, Cutting tools
Abstract: The band saw blade is distinguished by its multi-point and flexible cutting capability when sawing materials. Its wear form is significantly more intricate than that of traditional cutting tools, such as the lathe tool and the milling cutter. Preliminary experimental observations suggest a close correlation between the wear of band saw blades and the motor current of the driving wheel. Therefore, this study evaluates the wear condition of band saw blades using current signals. A mathematical correlation model was established between the driving wheel motor current signals and the load on the band saw. A comprehensive experimental study was conducted on the band saw blade, encompassing the entire lifecycle of sawing operations. The average wear width of the tooth tip was utilized as an indicator of tooth wear, and an investigation was conducted into the correlation between the driving wheel motor current signals and the wear state. The findings indicated that the driving wheel motor current signals could be utilized to assess the blade wear state with high precision, which would facilitate proactive maintenance and replacement strategies to optimize band saw performance and service life. [ABSTRACT FROM AUTHOR]
Copyright of Materials (1996-1944) is the property of MDPI 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.)
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Header DbId: egs
DbLabel: Engineering Source
An: 193715659
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PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Evaluation Method of the Band Saw Blade Wear State Based on Current Signals.
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  Data: <searchLink fieldCode="AR" term="%22Li%2C+Dongliang%22">Li, Dongliang</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Chen%2C+Bing%22">Chen, Bing</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> chenbing@hnust.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Fu%2C+Jiahao%22">Fu, Jiahao</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Liu%2C+Zihao%22">Liu, Zihao</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Liu%2C+Junchang%22">Liu, Junchang</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ou%2C+Wenchu%22">Ou, Wenchu</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Liu%2C+Guoyue%22">Liu, Guoyue</searchLink><relatesTo>2</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Materials+%281996-1944%29%22">Materials (1996-1944)</searchLink>. May2026, Vol. 19 Issue 9, p1853. 24p.
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  Data: <searchLink fieldCode="DE" term="%22Band+saws%22">Band saws</searchLink><br /><searchLink fieldCode="DE" term="%22Condition-based+maintenance%22">Condition-based maintenance</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+correlation%22">Statistical correlation</searchLink><br /><searchLink fieldCode="DE" term="%22Cutting+tools%22">Cutting tools</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: The band saw blade is distinguished by its multi-point and flexible cutting capability when sawing materials. Its wear form is significantly more intricate than that of traditional cutting tools, such as the lathe tool and the milling cutter. Preliminary experimental observations suggest a close correlation between the wear of band saw blades and the motor current of the driving wheel. Therefore, this study evaluates the wear condition of band saw blades using current signals. A mathematical correlation model was established between the driving wheel motor current signals and the load on the band saw. A comprehensive experimental study was conducted on the band saw blade, encompassing the entire lifecycle of sawing operations. The average wear width of the tooth tip was utilized as an indicator of tooth wear, and an investigation was conducted into the correlation between the driving wheel motor current signals and the wear state. The findings indicated that the driving wheel motor current signals could be utilized to assess the blade wear state with high precision, which would facilitate proactive maintenance and replacement strategies to optimize band saw performance and service life. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Materials (1996-1944) is the property of MDPI 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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      – Type: doi
        Value: 10.3390/ma19091853
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      – Code: eng
        Text: English
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      Pagination:
        PageCount: 24
        StartPage: 1853
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      – SubjectFull: Band saws
        Type: general
      – SubjectFull: Condition-based maintenance
        Type: general
      – SubjectFull: Statistical correlation
        Type: general
      – SubjectFull: Cutting tools
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    Titles:
      – TitleFull: Evaluation Method of the Band Saw Blade Wear State Based on Current Signals.
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            NameFull: Li, Dongliang
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            NameFull: Chen, Bing
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            NameFull: Fu, Jiahao
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            NameFull: Liu, Zihao
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            NameFull: Liu, Junchang
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            NameFull: Ou, Wenchu
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            NameFull: Liu, Guoyue
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            – D: 01
              M: 05
              Text: May2026
              Type: published
              Y: 2026
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              Value: 19
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              Value: 9
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            – TitleFull: Materials (1996-1944)
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