Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | 2020 22nd European Conference on Power Electronics and Applications, EPE 2020 ECCE Europe |
| Herausgeber (Verlag) | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (elektronisch) | 9789075815368 |
| ISBN (Print) | 978-1-7281-9807-1 |
| Publikationsstatus | Veröffentlicht - 2020 |
| Veranstaltung | 22nd European Conference on Power Electronics and Applications, EPE 2020 ECCE Europe - Lyon, Frankreich Dauer: 7 Sept. 2020 → 11 Sept. 2020 |
Abstract
Temperature-Sensitive Electrical Parameters (TSEPs) are often discussed for on-line determination of the junction temperature of semiconductors, and as key parameters for condition monitoring. This paper focuses on the combination of several simultaneously captured TSEPs using Artificial Neural Networks (ANNs) to reduce cross-dependencies and improve accuracy.
ASJC Scopus Sachgebiete
- Energie (insg.)
- Energieanlagenbau und Kraftwerkstechnik
- Ingenieurwesen (insg.)
- Elektrotechnik und Elektronik
- Ingenieurwesen (insg.)
- Sicherheit, Risiko, Zuverlässigkeit und Qualität
- Mathematik (insg.)
- Steuerung und Optimierung
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2020 22nd European Conference on Power Electronics and Applications, EPE 2020 ECCE Europe. Institute of Electrical and Electronics Engineers Inc., 2020. 9215567.
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
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TY - GEN
T1 - Combining multiple temperature-sensitive electrical parameters using artificial neural networks
AU - Herwig, Daniel
AU - Brockhage, Torben
AU - Mertens, Axel
N1 - Funding Information: The project on which this report is based was funded by the German Federal Ministry of Education and Research under the funding code 16EMO0325. The authors are responsible for the content of this publication.
PY - 2020
Y1 - 2020
N2 - Temperature-Sensitive Electrical Parameters (TSEPs) are often discussed for on-line determination of the junction temperature of semiconductors, and as key parameters for condition monitoring. This paper focuses on the combination of several simultaneously captured TSEPs using Artificial Neural Networks (ANNs) to reduce cross-dependencies and improve accuracy.
AB - Temperature-Sensitive Electrical Parameters (TSEPs) are often discussed for on-line determination of the junction temperature of semiconductors, and as key parameters for condition monitoring. This paper focuses on the combination of several simultaneously captured TSEPs using Artificial Neural Networks (ANNs) to reduce cross-dependencies and improve accuracy.
KW - Circuits
KW - Component for measurements
KW - Data analysis
KW - Device modeling
KW - Estimation technique
KW - Hardware
KW - IGBT
KW - Industrial application
KW - Maintenance
KW - Measurement
KW - Neural network
KW - Reliability
KW - Thermal stress
UR - http://www.scopus.com/inward/record.url?scp=85094910845&partnerID=8YFLogxK
U2 - 10.23919/EPE20ECCEEurope43536.2020.9215567
DO - 10.23919/EPE20ECCEEurope43536.2020.9215567
M3 - Conference contribution
AN - SCOPUS:85094910845
SN - 978-1-7281-9807-1
BT - 2020 22nd European Conference on Power Electronics and Applications, EPE 2020 ECCE Europe
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 22nd European Conference on Power Electronics and Applications, EPE 2020 ECCE Europe
Y2 - 7 September 2020 through 11 September 2020
ER -