Details
| Original language | English |
|---|---|
| Journal | Production Engineering |
| Publication status | Published - 20 Jun 2024 |
Abstract
Monitoring of grinding wheel wear is a crucial task to ensure adequate quality of the manufactured workpiece. While external sensors, such as acoustic emission sensors, are commonly used for this task, the use of internal control signals has been neglected. Consequently, the extent to which degree these signals can be utilized to monitor the grinding process remains uncertain. Therefore, this work focuses on monitoring grinding wheel wear based on internal control signals in the case of surface grinding of 100Cr6. It is shown, that the novel approach can estimate tool life volume with a R² value of 0.98. The results are compared to models using force measurements of a dynamometer as well as sensor fusion approaches relying on both signal sources. Despite its low resolution in the frequency domain, drive signals can be used for grinding wheel wear monitoring. Nevertheless, dynamometer measurements enable more accurate estimations with a R² value of 0.99. The differences have to be considered when scheduling the grinding wheels redressing based on the estimated tool life volume.
Keywords
- Grinding, Tool condition monitoring, Tool wear
ASJC Scopus subject areas
- Engineering(all)
- Mechanical Engineering
- Engineering(all)
- Industrial and Manufacturing Engineering
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In: Production Engineering, 20.06.2024.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Condition monitoring of grinding wheels
T2 - Potential of internal control signals
AU - Denkena, B.
AU - Klemme, H.
AU - Stoppel, D.
N1 - Publisher Copyright: © The Author(s) 2024.
PY - 2024/6/20
Y1 - 2024/6/20
N2 - Monitoring of grinding wheel wear is a crucial task to ensure adequate quality of the manufactured workpiece. While external sensors, such as acoustic emission sensors, are commonly used for this task, the use of internal control signals has been neglected. Consequently, the extent to which degree these signals can be utilized to monitor the grinding process remains uncertain. Therefore, this work focuses on monitoring grinding wheel wear based on internal control signals in the case of surface grinding of 100Cr6. It is shown, that the novel approach can estimate tool life volume with a R² value of 0.98. The results are compared to models using force measurements of a dynamometer as well as sensor fusion approaches relying on both signal sources. Despite its low resolution in the frequency domain, drive signals can be used for grinding wheel wear monitoring. Nevertheless, dynamometer measurements enable more accurate estimations with a R² value of 0.99. The differences have to be considered when scheduling the grinding wheels redressing based on the estimated tool life volume.
AB - Monitoring of grinding wheel wear is a crucial task to ensure adequate quality of the manufactured workpiece. While external sensors, such as acoustic emission sensors, are commonly used for this task, the use of internal control signals has been neglected. Consequently, the extent to which degree these signals can be utilized to monitor the grinding process remains uncertain. Therefore, this work focuses on monitoring grinding wheel wear based on internal control signals in the case of surface grinding of 100Cr6. It is shown, that the novel approach can estimate tool life volume with a R² value of 0.98. The results are compared to models using force measurements of a dynamometer as well as sensor fusion approaches relying on both signal sources. Despite its low resolution in the frequency domain, drive signals can be used for grinding wheel wear monitoring. Nevertheless, dynamometer measurements enable more accurate estimations with a R² value of 0.99. The differences have to be considered when scheduling the grinding wheels redressing based on the estimated tool life volume.
KW - Grinding
KW - Tool condition monitoring
KW - Tool wear
UR - http://www.scopus.com/inward/record.url?scp=85196361344&partnerID=8YFLogxK
U2 - 10.1007/s11740-024-01295-x
DO - 10.1007/s11740-024-01295-x
M3 - Article
AN - SCOPUS:85196361344
JO - Production Engineering
JF - Production Engineering
SN - 0944-6524
ER -