Details
| Originalsprache | Englisch |
|---|---|
| Seitenumfang | 8 |
| Fachzeitschrift | Advanced engineering materials |
| Frühes Online-Datum | 14 Nov. 2024 |
| Publikationsstatus | Elektronisch veröffentlicht (E-Pub) - 14 Nov. 2024 |
Abstract
Hybrid components consist of multiple materials, enabling the material distribution to be tailored to locally varying loads during the use phase. By selectively applying materials with high strength and density only to areas of a component that will be subjected to high local loads, the overall weight can be reduced. Hybrid components are manufactured through joining, forming, and subsequent machining. Material defects such as cavities or cracks, which can occur during joining and forming, significantly reduce the component's lifetime. These defects can be detected by monitoring the process signals of the machine tool. However, unavoidable deviations in the axial position of the material transition zone cause temporal shifts in the signals, impairing the performance of established monitoring methods. To monitor material defects in hybrid workpieces, this article proposes a new anomaly detection method based on dynamic time-warping barycenter averaging that is robust against time shifts. For training, time series containing varying temporal shifts are used. The sensitivity and robustness of the new method when applied to hybrid workpieces are evaluated and compared to confidence limits that are common in industrial applications. Using the new method, over 97% of all material defects can be detected with no false alarms occurring.
ASJC Scopus Sachgebiete
- Werkstoffwissenschaften (insg.)
- Allgemeine Materialwissenschaften
- Physik und Astronomie (insg.)
- Physik der kondensierten Materie
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in: Advanced engineering materials, 14.11.2024.
Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review
}
TY - JOUR
T1 - Anomaly Detection Method for Hybrid Workpieces Using Dynamic Time Warping
AU - Denkena, Berend
AU - Bergmann, Benjamin
AU - Klemme, Heinrich
AU - Handrup, Miriam
N1 - Publisher Copyright: © 2024 The Author(s). Advanced Engineering Materials published by Wiley-VCH GmbH.
PY - 2024/11/14
Y1 - 2024/11/14
N2 - Hybrid components consist of multiple materials, enabling the material distribution to be tailored to locally varying loads during the use phase. By selectively applying materials with high strength and density only to areas of a component that will be subjected to high local loads, the overall weight can be reduced. Hybrid components are manufactured through joining, forming, and subsequent machining. Material defects such as cavities or cracks, which can occur during joining and forming, significantly reduce the component's lifetime. These defects can be detected by monitoring the process signals of the machine tool. However, unavoidable deviations in the axial position of the material transition zone cause temporal shifts in the signals, impairing the performance of established monitoring methods. To monitor material defects in hybrid workpieces, this article proposes a new anomaly detection method based on dynamic time-warping barycenter averaging that is robust against time shifts. For training, time series containing varying temporal shifts are used. The sensitivity and robustness of the new method when applied to hybrid workpieces are evaluated and compared to confidence limits that are common in industrial applications. Using the new method, over 97% of all material defects can be detected with no false alarms occurring.
AB - Hybrid components consist of multiple materials, enabling the material distribution to be tailored to locally varying loads during the use phase. By selectively applying materials with high strength and density only to areas of a component that will be subjected to high local loads, the overall weight can be reduced. Hybrid components are manufactured through joining, forming, and subsequent machining. Material defects such as cavities or cracks, which can occur during joining and forming, significantly reduce the component's lifetime. These defects can be detected by monitoring the process signals of the machine tool. However, unavoidable deviations in the axial position of the material transition zone cause temporal shifts in the signals, impairing the performance of established monitoring methods. To monitor material defects in hybrid workpieces, this article proposes a new anomaly detection method based on dynamic time-warping barycenter averaging that is robust against time shifts. For training, time series containing varying temporal shifts are used. The sensitivity and robustness of the new method when applied to hybrid workpieces are evaluated and compared to confidence limits that are common in industrial applications. Using the new method, over 97% of all material defects can be detected with no false alarms occurring.
KW - dynamic time warping
KW - hybrid components
KW - material transition zone
KW - process monitoring
KW - turning
UR - http://www.scopus.com/inward/record.url?scp=85208925188&partnerID=8YFLogxK
U2 - 10.1002/adem.202401388
DO - 10.1002/adem.202401388
M3 - Article
AN - SCOPUS:85208925188
JO - Advanced engineering materials
JF - Advanced engineering materials
SN - 1438-1656
ER -