---
_id: '64826'
author:
- first_name: Max
full_name: Kelber, Max
id: '70188'
last_name: Kelber
- first_name: Steffen
full_name: Brück, Steffen
last_name: Brück
- first_name: Nishant
full_name: Bhardwaj, Nishant
last_name: Bhardwaj
- first_name: Osarenren Kennedy
full_name: Aimiyekagbon, Osarenren Kennedy
id: '9557'
last_name: Aimiyekagbon
- first_name: Rolf
full_name: Naumann, Rolf
last_name: Naumann
- first_name: Walter
full_name: Sextro, Walter
id: '21220'
last_name: Sextro
citation:
ama: 'Kelber M, Brück S, Bhardwaj N, Aimiyekagbon OK, Naumann R, Sextro W. Methodik
zur Untersuchung der Fahrwerksparameter von Schienenfahrzeugen auf Basis optischer
Schwingungsmessungen an einer ortsfesten Messstelle. In: Hochschule für Technik
und Wirtschaft Dresden, Fakultät Maschinenbau, ed. Tagungsband Rad-Schiene-Tagung
2026. DVV Media Group GmbH - Eurailpress; 2026:206 – 208.'
apa: Kelber, M., Brück, S., Bhardwaj, N., Aimiyekagbon, O. K., Naumann, R., &
Sextro, W. (2026). Methodik zur Untersuchung der Fahrwerksparameter von Schienenfahrzeugen
auf Basis optischer Schwingungsmessungen an einer ortsfesten Messstelle. In Hochschule
für Technik und Wirtschaft Dresden, Fakultät Maschinenbau (Ed.), Tagungsband
Rad-Schiene-Tagung 2026 (pp. 206 – 208). DVV Media Group GmbH - Eurailpress.
bibtex: '@inproceedings{Kelber_Brück_Bhardwaj_Aimiyekagbon_Naumann_Sextro_2026,
place={Hamburg}, title={Methodik zur Untersuchung der Fahrwerksparameter von Schienenfahrzeugen
auf Basis optischer Schwingungsmessungen an einer ortsfesten Messstelle}, booktitle={Tagungsband
Rad-Schiene-Tagung 2026}, publisher={DVV Media Group GmbH - Eurailpress}, author={Kelber,
Max and Brück, Steffen and Bhardwaj, Nishant and Aimiyekagbon, Osarenren Kennedy
and Naumann, Rolf and Sextro, Walter}, editor={Hochschule für Technik und Wirtschaft
Dresden, Fakultät Maschinenbau}, year={2026}, pages={206 – 208} }'
chicago: 'Kelber, Max, Steffen Brück, Nishant Bhardwaj, Osarenren Kennedy Aimiyekagbon,
Rolf Naumann, and Walter Sextro. “Methodik zur Untersuchung der Fahrwerksparameter
von Schienenfahrzeugen auf Basis optischer Schwingungsmessungen an einer ortsfesten
Messstelle.” In Tagungsband Rad-Schiene-Tagung 2026, edited by Hochschule
für Technik und Wirtschaft Dresden, Fakultät Maschinenbau, 206 – 208. Hamburg:
DVV Media Group GmbH - Eurailpress, 2026.'
ieee: M. Kelber, S. Brück, N. Bhardwaj, O. K. Aimiyekagbon, R. Naumann, and W. Sextro,
“Methodik zur Untersuchung der Fahrwerksparameter von Schienenfahrzeugen auf Basis
optischer Schwingungsmessungen an einer ortsfesten Messstelle,” in Tagungsband
Rad-Schiene-Tagung 2026, Dresden, 2026, pp. 206 – 208.
mla: Kelber, Max, et al. “Methodik zur Untersuchung der Fahrwerksparameter von Schienenfahrzeugen
auf Basis optischer Schwingungsmessungen an einer ortsfesten Messstelle.” Tagungsband
Rad-Schiene-Tagung 2026, edited by Hochschule für Technik und Wirtschaft Dresden,
Fakultät Maschinenbau, DVV Media Group GmbH - Eurailpress, 2026, pp. 206 – 208.
short: 'M. Kelber, S. Brück, N. Bhardwaj, O.K. Aimiyekagbon, R. Naumann, W. Sextro,
in: Hochschule für Technik und Wirtschaft Dresden, Fakultät Maschinenbau (Ed.),
Tagungsband Rad-Schiene-Tagung 2026, DVV Media Group GmbH - Eurailpress, Hamburg,
2026, pp. 206 – 208.'
conference:
end_date: 2026-03-06
location: Dresden
name: 21. Internationale Schienenfahrzeugtagung Dresden 4.-6. März 2026
start_date: 2026-03-04
corporate_editor:
- Hochschule für Technik und Wirtschaft Dresden, Fakultät Maschinenbau
date_created: 2026-03-04T10:26:27Z
date_updated: 2026-03-04T10:38:28Z
department:
- _id: '151'
language:
- iso: ger
page: 206 – 208
place: Hamburg
popular_science: '1'
project:
- _id: '1355'
name: enableATO – Automatisierter Bahnverkehr als Backbone für eine nachhaltige,
vernetzte Mobilität im ländlichen Raum
publication: Tagungsband Rad-Schiene-Tagung 2026
publication_identifier:
isbn:
- 978-3-96892-332-1
publication_status: published
publisher: DVV Media Group GmbH - Eurailpress
status: public
title: Methodik zur Untersuchung der Fahrwerksparameter von Schienenfahrzeugen auf
Basis optischer Schwingungsmessungen an einer ortsfesten Messstelle
type: conference
user_id: '70188'
year: '2026'
...
---
_id: '64787'
abstract:
- lang: eng
text: This study proposes a fault diagnostics methodology that addresses the challenges
posed by highly imbalanced datasets typical of railway applications, where faulty
conditions constitute the minority class. Fault diagnostics is performed from
the component level upward, considering each sensor’s proximity to its respective
critical component. Advanced signal analysis, feature engineering, and automated
data-driven model generation techniques were explored to achieve comprehensive
diagnostics, such that the model development process accounts for variations in
the operating conditions and differing levels of information availability. The
proposed methodology is evaluated on datasets from the MONOCAB, for scenarios
with limited faulty instances and on the Beijing 2024 IEEE PHM Conference data
challenge, which focused on fault diagnostics of railway systems under various
fault modes and operating conditions.
article_number: '1'
author:
- first_name: Osarenren Kennedy
full_name: Aimiyekagbon, Osarenren Kennedy
id: '9557'
last_name: Aimiyekagbon
- first_name: Alexander
full_name: Löwen, Alexander
id: '47233'
last_name: Löwen
- first_name: Raphael
full_name: Hanselle, Raphael
last_name: Hanselle
- first_name: Thomas
full_name: Rief, Thomas
last_name: Rief
- first_name: Maximilian
full_name: Beck, Maximilian
last_name: Beck
- first_name: Walter
full_name: Sextro, Walter
id: '21220'
last_name: Sextro
citation:
ama: 'Aimiyekagbon OK, Löwen A, Hanselle R, Rief T, Beck M, Sextro W. Multilevel
fault diagnostics for railway applications using limited historical data. In:
PHM Society Asia-Pacific Conference. Vol 5. ; 2025. doi:10.36001/phmap.2025.v5i1.4449'
apa: Aimiyekagbon, O. K., Löwen, A., Hanselle, R., Rief, T., Beck, M., & Sextro,
W. (2025). Multilevel fault diagnostics for railway applications using limited
historical data. PHM Society Asia-Pacific Conference, 5, Article
1. https://doi.org/10.36001/phmap.2025.v5i1.4449
bibtex: '@inproceedings{Aimiyekagbon_Löwen_Hanselle_Rief_Beck_Sextro_2025, title={Multilevel
fault diagnostics for railway applications using limited historical data}, volume={5},
DOI={10.36001/phmap.2025.v5i1.4449},
number={1}, booktitle={PHM Society Asia-Pacific Conference}, author={Aimiyekagbon,
Osarenren Kennedy and Löwen, Alexander and Hanselle, Raphael and Rief, Thomas
and Beck, Maximilian and Sextro, Walter}, year={2025} }'
chicago: Aimiyekagbon, Osarenren Kennedy, Alexander Löwen, Raphael Hanselle, Thomas
Rief, Maximilian Beck, and Walter Sextro. “Multilevel Fault Diagnostics for Railway
Applications Using Limited Historical Data.” In PHM Society Asia-Pacific Conference,
Vol. 5, 2025. https://doi.org/10.36001/phmap.2025.v5i1.4449.
ieee: 'O. K. Aimiyekagbon, A. Löwen, R. Hanselle, T. Rief, M. Beck, and W. Sextro,
“Multilevel fault diagnostics for railway applications using limited historical
data,” in PHM Society Asia-Pacific Conference, 2025, vol. 5, doi: 10.36001/phmap.2025.v5i1.4449.'
mla: Aimiyekagbon, Osarenren Kennedy, et al. “Multilevel Fault Diagnostics for Railway
Applications Using Limited Historical Data.” PHM Society Asia-Pacific Conference,
vol. 5, 1, 2025, doi:10.36001/phmap.2025.v5i1.4449.
short: 'O.K. Aimiyekagbon, A. Löwen, R. Hanselle, T. Rief, M. Beck, W. Sextro, in:
PHM Society Asia-Pacific Conference, 2025.'
date_created: 2026-02-27T20:41:54Z
date_updated: 2026-02-27T20:46:44Z
department:
- _id: '151'
doi: 10.36001/phmap.2025.v5i1.4449
intvolume: ' 5'
keyword:
- MONOCAB
- Beijing Data Challenge
- Diagnostics of railway systems
language:
- iso: eng
project:
- _id: '1355'
name: enableATO – Automatisierter Bahnverkehr als Backbone für eine nachhaltige,
vernetzte Mobilität im ländlichen Raum
publication: PHM Society Asia-Pacific Conference
publication_status: published
quality_controlled: '1'
status: public
title: Multilevel fault diagnostics for railway applications using limited historical
data
type: conference
user_id: '9557'
volume: 5
year: '2025'
...
---
_id: '63193'
abstract:
- lang: eng
text: The integration of data-driven models and specifically machine learning for
conditon monitoring and predictive maintenance into companies, especially small
and medium-sized enterprises, offers significant opportunities in reducing costs,
operating more sustainably, and maintaining long-term competitiveness. However,
many small and medium-sized enterprises lack the necessary resources and expertise
to derive knowledge from data and integrate their own machine learning based solutions.
To address this challenge, a framework is presented that enables the automated
generation of data-driven models with a particular focus on condition monitoring
and predictive maintenance, but applicable to other use cases as well. Using a
dataset from the 2022 data challenge of the prognostics and health management
society, it is demonstrated that the framework can generate high-performing models,
achieving F1-scores up to 0.998, exemplarily for a classification task.
author:
- first_name: Alexander
full_name: Löwen, Alexander
id: '47233'
last_name: Löwen
- first_name: Dennis
full_name: Quirin, Dennis
last_name: Quirin
- first_name: Marc
full_name: Hesse, Marc
last_name: Hesse
- first_name: Osarenren Kennedy
full_name: Aimiyekagbon, Osarenren Kennedy
id: '9557'
last_name: Aimiyekagbon
- first_name: Walter
full_name: Sextro, Walter
id: '21220'
last_name: Sextro
citation:
ama: 'Löwen A, Quirin D, Hesse M, Aimiyekagbon OK, Sextro W. Facilitating the Automated
Generation of Data-Driven Models for the Diagnostics and Prognostics of Technical
Systems. In: 2025 IEEE 30th International Conference on Emerging Technologies
and Factory Automation (ETFA). IEEE; 2025. doi:10.1109/etfa65518.2025.11205799'
apa: Löwen, A., Quirin, D., Hesse, M., Aimiyekagbon, O. K., & Sextro, W. (2025).
Facilitating the Automated Generation of Data-Driven Models for the Diagnostics
and Prognostics of Technical Systems. 2025 IEEE 30th International Conference
on Emerging Technologies and Factory Automation (ETFA). 2025 IEEE 30th International
Conference on Emerging Technologies and Factory Automation (ETFA), Porto. https://doi.org/10.1109/etfa65518.2025.11205799
bibtex: '@inproceedings{Löwen_Quirin_Hesse_Aimiyekagbon_Sextro_2025, title={Facilitating
the Automated Generation of Data-Driven Models for the Diagnostics and Prognostics
of Technical Systems}, DOI={10.1109/etfa65518.2025.11205799},
booktitle={2025 IEEE 30th International Conference on Emerging Technologies and
Factory Automation (ETFA)}, publisher={IEEE}, author={Löwen, Alexander and Quirin,
Dennis and Hesse, Marc and Aimiyekagbon, Osarenren Kennedy and Sextro, Walter},
year={2025} }'
chicago: Löwen, Alexander, Dennis Quirin, Marc Hesse, Osarenren Kennedy Aimiyekagbon,
and Walter Sextro. “Facilitating the Automated Generation of Data-Driven Models
for the Diagnostics and Prognostics of Technical Systems.” In 2025 IEEE 30th
International Conference on Emerging Technologies and Factory Automation (ETFA).
IEEE, 2025. https://doi.org/10.1109/etfa65518.2025.11205799.
ieee: 'A. Löwen, D. Quirin, M. Hesse, O. K. Aimiyekagbon, and W. Sextro, “Facilitating
the Automated Generation of Data-Driven Models for the Diagnostics and Prognostics
of Technical Systems,” presented at the 2025 IEEE 30th International Conference
on Emerging Technologies and Factory Automation (ETFA), Porto, 2025, doi: 10.1109/etfa65518.2025.11205799.'
mla: Löwen, Alexander, et al. “Facilitating the Automated Generation of Data-Driven
Models for the Diagnostics and Prognostics of Technical Systems.” 2025 IEEE
30th International Conference on Emerging Technologies and Factory Automation
(ETFA), IEEE, 2025, doi:10.1109/etfa65518.2025.11205799.
short: 'A. Löwen, D. Quirin, M. Hesse, O.K. Aimiyekagbon, W. Sextro, in: 2025 IEEE
30th International Conference on Emerging Technologies and Factory Automation
(ETFA), IEEE, 2025.'
conference:
location: Porto
name: 2025 IEEE 30th International Conference on Emerging Technologies and Factory
Automation (ETFA)
date_created: 2025-12-18T09:07:38Z
date_updated: 2025-12-18T09:12:48Z
department:
- _id: '151'
doi: 10.1109/etfa65518.2025.11205799
language:
- iso: eng
project:
- _id: '1483'
name: Industrie 4.0 Ökosystem für den automatisierten Einsatz von datengetriebenen
Services (I4.0AutoServ)
publication: 2025 IEEE 30th International Conference on Emerging Technologies and
Factory Automation (ETFA)
publication_status: published
publisher: IEEE
related_material:
link:
- relation: confirmation
url: https://ieeexplore.ieee.org/document/11205799
status: public
title: Facilitating the Automated Generation of Data-Driven Models for the Diagnostics
and Prognostics of Technical Systems
type: conference
user_id: '47233'
year: '2025'
...
---
_id: '51518'
abstract:
- lang: eng
text: In applications of piezoelectric actuators and sensors, the dependability
and particularly the reliability throughout their lifetime are vital to manufacturers
and end-users and are enabled through condition-monitoring approaches. Existing
approaches often utilize impedance measurements over a range of frequencies or
velocity measurements and require additional equipment or sensors, such as a laser
Doppler vibrometer. Furthermore, the non-negligible effects of varying operating
conditions are often unconsidered. To minimize the need for additional sensors
while maintaining the dependability of piezoelectric bending actuators irrespective
of varying operating conditions, an online diagnostics approach is proposed. To
this end, time- and frequency-domain features are extracted from monitored current
signals to reflect hairline crack development in bending actuators. For validation
of applicability, the presented analysis method was evaluated on piezoelectric
bending actuators subjected to accelerated lifetime tests at varying voltage amplitudes
and under external damping conditions. In the presence of a crack and due to a
diminished stiffness, the resonance frequency decreases and the root-mean-square
amplitude of the current signal simultaneously abruptly drops during the lifetime
tests. Furthermore, the piezoelectric crack surfaces clapping is reflected in
higher harmonics of the current signal. Thus, time-domain features and harmonics
of the current signals are sufficient to diagnose hairline cracks in the actuators.
article_number: '521'
article_type: original
author:
- first_name: Osarenren Kennedy
full_name: Aimiyekagbon, Osarenren Kennedy
id: '9557'
last_name: Aimiyekagbon
- first_name: Amelie
full_name: Bender, Amelie
id: '54290'
last_name: Bender
- first_name: Tobias
full_name: Hemsel, Tobias
id: '210'
last_name: Hemsel
- first_name: Walter
full_name: Sextro, Walter
id: '21220'
last_name: Sextro
citation:
ama: Aimiyekagbon OK, Bender A, Hemsel T, Sextro W. Diagnostics of Piezoelectric
Bending Actuators Subjected to Varying Operating Conditions. Electronics.
2024;13(3). doi:10.3390/electronics13030521
apa: Aimiyekagbon, O. K., Bender, A., Hemsel, T., & Sextro, W. (2024). Diagnostics
of Piezoelectric Bending Actuators Subjected to Varying Operating Conditions.
Electronics, 13(3), Article 521. https://doi.org/10.3390/electronics13030521
bibtex: '@article{Aimiyekagbon_Bender_Hemsel_Sextro_2024, title={Diagnostics of
Piezoelectric Bending Actuators Subjected to Varying Operating Conditions}, volume={13},
DOI={10.3390/electronics13030521},
number={3521}, journal={Electronics}, publisher={MDPI AG}, author={Aimiyekagbon,
Osarenren Kennedy and Bender, Amelie and Hemsel, Tobias and Sextro, Walter}, year={2024}
}'
chicago: Aimiyekagbon, Osarenren Kennedy, Amelie Bender, Tobias Hemsel, and Walter
Sextro. “Diagnostics of Piezoelectric Bending Actuators Subjected to Varying Operating
Conditions.” Electronics 13, no. 3 (2024). https://doi.org/10.3390/electronics13030521.
ieee: 'O. K. Aimiyekagbon, A. Bender, T. Hemsel, and W. Sextro, “Diagnostics of
Piezoelectric Bending Actuators Subjected to Varying Operating Conditions,” Electronics,
vol. 13, no. 3, Art. no. 521, 2024, doi: 10.3390/electronics13030521.'
mla: Aimiyekagbon, Osarenren Kennedy, et al. “Diagnostics of Piezoelectric Bending
Actuators Subjected to Varying Operating Conditions.” Electronics, vol.
13, no. 3, 521, MDPI AG, 2024, doi:10.3390/electronics13030521.
short: O.K. Aimiyekagbon, A. Bender, T. Hemsel, W. Sextro, Electronics 13 (2024).
date_created: 2024-02-20T06:46:43Z
date_updated: 2024-03-15T16:15:56Z
department:
- _id: '151'
doi: 10.3390/electronics13030521
funded_apc: '1'
intvolume: ' 13'
issue: '3'
keyword:
- piezoelectric transducer
- self-sensing
- fault detection
- diagnostics
- hairline crack
- condition monitoring
language:
- iso: eng
publication: Electronics
publication_identifier:
issn:
- 2079-9292
publication_status: published
publisher: MDPI AG
quality_controlled: '1'
status: public
title: Diagnostics of Piezoelectric Bending Actuators Subjected to Varying Operating
Conditions
type: journal_article
user_id: '9557'
volume: 13
year: '2024'
...
---
_id: '55336'
abstract:
- lang: eng
text: "Predicting the remaining useful life of technical \r\nsystems has gained
significant attention in recent years due to \r\nincreasing demands for extending
the lifespan of degrading system \r\ncomponents. Therefore, already used systems
are retrofitted by \r\nintegrating sensors to monitor their performance and \r\nfunctionality,
enabling accurate diagnosis of their condition and \r\nprediction of their remaining
useful life. One of the main \r\nchallenges in this field is identified in the
missing data from the \r\ntime where the retrofitted system has already run but
without \r\nbeing monitored by sensors. In this paper, a novel approach for \r\nthe
combined diagnostics and prognostics of retrofitted systems is \r\nproposed. The
methodology aims to provide an accurate diagnosis \r\nof the system’s health state
and estimation of the remaining useful \r\nlife by a combination of a machine
learning and expert knowledge. \r\nTo evaluate the effectiveness of the proposed
methodology, a case \r\nstudy involving a retrofitted system in an industrial
setting is \r\nselected and applied. It is demonstrated that the approach \r\neffectively
diagnose the current system’s health state and \r\naccurately predict its remaining
useful life, thereby enabling \r\npredictive maintenance and decision-making.
Overall, our \r\nresearch contributes to advancing the field of condition \r\nmonitoring
for retrofitted systems by providing a comprehensive \r\nmethodology that addresses
the challenge of missing data."
author:
- first_name: Amelie
full_name: Bender, Amelie
id: '54290'
last_name: Bender
- first_name: Osarenren Kennedy
full_name: Aimiyekagbon, Osarenren Kennedy
id: '9557'
last_name: Aimiyekagbon
- first_name: Walter
full_name: Sextro, Walter
id: '21220'
last_name: Sextro
citation:
ama: 'Bender A, Aimiyekagbon OK, Sextro W. Diagnostics and Prognostics for Retrofitted
Systems: A Comprehensive Approach for Enhanced System Health Assessment. In: Proceedings
of the 2024 Prognostics and System Health Management Conference (PHM). IEEE
Computer Society; 2024. doi:10.1109/PHM61473.2024.00038'
apa: 'Bender, A., Aimiyekagbon, O. K., & Sextro, W. (2024). Diagnostics and
Prognostics for Retrofitted Systems: A Comprehensive Approach for Enhanced System
Health Assessment. Proceedings of the 2024 Prognostics and System Health Management
Conference (PHM). 2024 Prognostics and System Health Management Conference
(PHM), Stockholm, Schweden. https://doi.org/10.1109/PHM61473.2024.00038'
bibtex: '@inproceedings{Bender_Aimiyekagbon_Sextro_2024, title={Diagnostics and
Prognostics for Retrofitted Systems: A Comprehensive Approach for Enhanced System
Health Assessment}, DOI={10.1109/PHM61473.2024.00038},
booktitle={Proceedings of the 2024 Prognostics and System Health Management Conference
(PHM)}, publisher={IEEE Computer Society}, author={Bender, Amelie and Aimiyekagbon,
Osarenren Kennedy and Sextro, Walter}, year={2024} }'
chicago: 'Bender, Amelie, Osarenren Kennedy Aimiyekagbon, and Walter Sextro. “Diagnostics
and Prognostics for Retrofitted Systems: A Comprehensive Approach for Enhanced
System Health Assessment.” In Proceedings of the 2024 Prognostics and System
Health Management Conference (PHM). IEEE Computer Society, 2024. https://doi.org/10.1109/PHM61473.2024.00038.'
ieee: 'A. Bender, O. K. Aimiyekagbon, and W. Sextro, “Diagnostics and Prognostics
for Retrofitted Systems: A Comprehensive Approach for Enhanced System Health Assessment,”
presented at the 2024 Prognostics and System Health Management Conference (PHM),
Stockholm, Schweden, 2024, doi: 10.1109/PHM61473.2024.00038.'
mla: 'Bender, Amelie, et al. “Diagnostics and Prognostics for Retrofitted Systems:
A Comprehensive Approach for Enhanced System Health Assessment.” Proceedings
of the 2024 Prognostics and System Health Management Conference (PHM), IEEE
Computer Society, 2024, doi:10.1109/PHM61473.2024.00038.'
short: 'A. Bender, O.K. Aimiyekagbon, W. Sextro, in: Proceedings of the 2024 Prognostics
and System Health Management Conference (PHM), IEEE Computer Society, 2024.'
conference:
end_date: 2024-05-31
location: Stockholm, Schweden
name: 2024 Prognostics and System Health Management Conference (PHM)
start_date: 2024-05-28
date_created: 2024-07-22T09:27:57Z
date_updated: 2024-07-22T09:29:26Z
department:
- _id: '151'
doi: 10.1109/PHM61473.2024.00038
keyword:
- retrofit
- diagnosis
- prognostics
- RUL prediction
- missing data
- ball bearings
language:
- iso: eng
publication: Proceedings of the 2024 Prognostics and System Health Management Conference
(PHM)
publication_identifier:
isbn:
- 979-8-3503-6058-5
publisher: IEEE Computer Society
quality_controlled: '1'
status: public
title: 'Diagnostics and Prognostics for Retrofitted Systems: A Comprehensive Approach
for Enhanced System Health Assessment'
type: conference
user_id: '54290'
year: '2024'
...
---
_id: '55631'
abstract:
- lang: eng
text: This paper investigates the remaining useful lifetime (RUL) estimation of
bearings under dynamic, i.e., time-varying, operating conditions (OC). Unlike
conventional studies that assume constant OC in bearing accelerated life tests,
we introduce a dataset with time-varying OC during run-to-failure experiments,
simulating real-world scenarios. We explore data-driven approaches to identify
the transition point from a healthy to an unhealthy state and estimate the RUL.
Additionally, we examine strategies for integrating OC information to enhance
RUL estimations. These methodologies are evaluated through numerical experiments
using various machine learning algorithms.
article_number: '9'
author:
- first_name: Alireza
full_name: Javanmardi, Alireza
last_name: Javanmardi
- first_name: Osarenren Kennedy
full_name: Aimiyekagbon, Osarenren Kennedy
id: '9557'
last_name: Aimiyekagbon
- first_name: Amelie
full_name: Bender, Amelie
id: '54290'
last_name: Bender
- first_name: James Kuria
full_name: Kimotho, James Kuria
last_name: Kimotho
- first_name: Walter
full_name: Sextro, Walter
id: '21220'
last_name: Sextro
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Javanmardi A, Aimiyekagbon OK, Bender A, Kimotho JK, Sextro W, Hüllermeier
E. Remaining Useful Lifetime Estimation of Bearings Operating under Time-Varying
Conditions. In: PHM Society European Conference. Vol 8. PHM Society; 2024.
doi:10.36001/phme.2024.v8i1.4101'
apa: Javanmardi, A., Aimiyekagbon, O. K., Bender, A., Kimotho, J. K., Sextro, W.,
& Hüllermeier, E. (2024). Remaining Useful Lifetime Estimation of Bearings
Operating under Time-Varying Conditions. PHM Society European Conference,
8(1), Article 9. https://doi.org/10.36001/phme.2024.v8i1.4101
bibtex: '@inproceedings{Javanmardi_Aimiyekagbon_Bender_Kimotho_Sextro_Hüllermeier_2024,
title={Remaining Useful Lifetime Estimation of Bearings Operating under Time-Varying
Conditions}, volume={8}, DOI={10.36001/phme.2024.v8i1.4101},
number={19}, booktitle={PHM Society European Conference}, publisher={PHM Society},
author={Javanmardi, Alireza and Aimiyekagbon, Osarenren Kennedy and Bender, Amelie
and Kimotho, James Kuria and Sextro, Walter and Hüllermeier, Eyke}, year={2024}
}'
chicago: Javanmardi, Alireza, Osarenren Kennedy Aimiyekagbon, Amelie Bender, James
Kuria Kimotho, Walter Sextro, and Eyke Hüllermeier. “Remaining Useful Lifetime
Estimation of Bearings Operating under Time-Varying Conditions.” In PHM Society
European Conference, Vol. 8. PHM Society, 2024. https://doi.org/10.36001/phme.2024.v8i1.4101.
ieee: 'A. Javanmardi, O. K. Aimiyekagbon, A. Bender, J. K. Kimotho, W. Sextro, and
E. Hüllermeier, “Remaining Useful Lifetime Estimation of Bearings Operating under
Time-Varying Conditions,” in PHM Society European Conference, Prague, Czech
Republic, 2024, vol. 8, no. 1, doi: 10.36001/phme.2024.v8i1.4101.'
mla: Javanmardi, Alireza, et al. “Remaining Useful Lifetime Estimation of Bearings
Operating under Time-Varying Conditions.” PHM Society European Conference,
vol. 8, no. 1, 9, PHM Society, 2024, doi:10.36001/phme.2024.v8i1.4101.
short: 'A. Javanmardi, O.K. Aimiyekagbon, A. Bender, J.K. Kimotho, W. Sextro, E.
Hüllermeier, in: PHM Society European Conference, PHM Society, 2024.'
conference:
end_date: 2024-07-05
location: Prague, Czech Republic
name: 8th European Conference of the Prognostics and Health Management Society 2024
start_date: 2024-07-03
date_created: 2024-08-19T07:41:32Z
date_updated: 2025-02-10T10:37:52Z
department:
- _id: '151'
doi: 10.36001/phme.2024.v8i1.4101
intvolume: ' 8'
issue: '1'
language:
- iso: eng
publication: PHM Society European Conference
publication_identifier:
isbn:
- 978-1-936263-40-0
publication_status: published
publisher: PHM Society
quality_controlled: '1'
status: public
title: Remaining Useful Lifetime Estimation of Bearings Operating under Time-Varying
Conditions
type: conference
user_id: '9557'
volume: 8
year: '2024'
...
---
_id: '47116'
abstract:
- lang: eng
text: This paper presents a comprehensive study on diagnosing a spacecraft propulsion
system utilizing data provided by the Prognostics and Health Management (PHM)
society, specifically obtained as part of the Asia-Pacific PHM conference’s data
challenge 2023. The objective of the challenge is to identify and diagnose known
faults as well as unknown anomalies in the spacecraft’s propulsion system, which
is critical for ensuring the spacecraft’s proper functionality and safety. To
address this challenge, the proposed method follows a systematic approach of feature
extraction, feature selection, and model development. The models employed in this
study are kMeans clustering and decision trees combined to ensembles, enriched
with expert knowledge. With the method presented, our team was capable of reaching
high accuracy in identifying anomalies as well as diagnosing faults, resulting
in attaining the seventh place with a score of 93.08 %.
author:
- first_name: Osarenren Kennedy
full_name: Aimiyekagbon, Osarenren Kennedy
id: '9557'
last_name: Aimiyekagbon
- first_name: Alexander
full_name: Löwen, Alexander
id: '47233'
last_name: Löwen
- first_name: Amelie
full_name: Bender, Amelie
id: '54290'
last_name: Bender
- first_name: Lars
full_name: Muth, Lars
id: '77313'
last_name: Muth
orcid: 0000-0002-2938-5616
- first_name: Walter
full_name: Sextro, Walter
id: '21220'
last_name: Sextro
citation:
ama: 'Aimiyekagbon OK, Löwen A, Bender A, Muth L, Sextro W. Expert-Informed Hierarchical
Diagnostics of Multiple Fault Modes of a Spacecraft Propulsion System. In: Proceedings
of the Asia Pacific Conference of the PHM Society 2023 . Vol 4. ; 2023. doi:10.36001/phmap.2023.v4i1.3596'
apa: Aimiyekagbon, O. K., Löwen, A., Bender, A., Muth, L., & Sextro, W. (2023).
Expert-Informed Hierarchical Diagnostics of Multiple Fault Modes of a Spacecraft
Propulsion System. Proceedings of the Asia Pacific Conference of the PHM Society
2023 , 4(1). https://doi.org/10.36001/phmap.2023.v4i1.3596
bibtex: '@inproceedings{Aimiyekagbon_Löwen_Bender_Muth_Sextro_2023, title={Expert-Informed
Hierarchical Diagnostics of Multiple Fault Modes of a Spacecraft Propulsion System},
volume={4}, DOI={10.36001/phmap.2023.v4i1.3596},
number={1}, booktitle={Proceedings of the Asia Pacific Conference of the PHM Society
2023 }, author={Aimiyekagbon, Osarenren Kennedy and Löwen, Alexander and Bender,
Amelie and Muth, Lars and Sextro, Walter}, year={2023} }'
chicago: Aimiyekagbon, Osarenren Kennedy, Alexander Löwen, Amelie Bender, Lars Muth,
and Walter Sextro. “Expert-Informed Hierarchical Diagnostics of Multiple Fault
Modes of a Spacecraft Propulsion System.” In Proceedings of the Asia Pacific
Conference of the PHM Society 2023 , Vol. 4, 2023. https://doi.org/10.36001/phmap.2023.v4i1.3596.
ieee: 'O. K. Aimiyekagbon, A. Löwen, A. Bender, L. Muth, and W. Sextro, “Expert-Informed
Hierarchical Diagnostics of Multiple Fault Modes of a Spacecraft Propulsion System,”
in Proceedings of the Asia Pacific Conference of the PHM Society 2023 ,
2023, vol. 4, no. 1, doi: 10.36001/phmap.2023.v4i1.3596.'
mla: Aimiyekagbon, Osarenren Kennedy, et al. “Expert-Informed Hierarchical Diagnostics
of Multiple Fault Modes of a Spacecraft Propulsion System.” Proceedings of
the Asia Pacific Conference of the PHM Society 2023 , vol. 4, no. 1, 2023,
doi:10.36001/phmap.2023.v4i1.3596.
short: 'O.K. Aimiyekagbon, A. Löwen, A. Bender, L. Muth, W. Sextro, in: Proceedings
of the Asia Pacific Conference of the PHM Society 2023 , 2023.'
date_created: 2023-09-18T07:52:32Z
date_updated: 2024-08-19T07:39:12Z
department:
- _id: '151'
doi: 10.36001/phmap.2023.v4i1.3596
intvolume: ' 4'
issue: '1'
keyword:
- PHM
- Fault Diagnostics
- Multiple Fault Modes
- Expert-Informed Diagnostics
- Anomaly Detection
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.papers.phmsociety.org/index.php/phmap/article/view/3596
oa: '1'
publication: 'Proceedings of the Asia Pacific Conference of the PHM Society 2023 '
quality_controlled: '1'
status: public
title: Expert-Informed Hierarchical Diagnostics of Multiple Fault Modes of a Spacecraft
Propulsion System
type: conference
user_id: '9557'
volume: 4
year: '2023'
...
---
_id: '47159'
author:
- first_name: Osarenren Kennedy
full_name: Aimiyekagbon, Osarenren Kennedy
id: '9557'
last_name: Aimiyekagbon
- first_name: Amelie
full_name: Bender, Amelie
id: '54290'
last_name: Bender
- first_name: Walter
full_name: Sextro, Walter
id: '21220'
last_name: Sextro
citation:
ama: Aimiyekagbon OK, Bender A, Sextro W. On the applicability of time series features
as health indicators for technical systems operating under varying conditions.
Condition Monitor. 2022:5-10.
apa: Aimiyekagbon, O. K., Bender, A., & Sextro, W. (2022). On the applicability
of time series features as health indicators for technical systems operating under
varying conditions. Condition Monitor, 425, 5–10.
bibtex: '@article{Aimiyekagbon_Bender_Sextro_2022, title={On the applicability of
time series features as health indicators for technical systems operating under
varying conditions}, number={425}, journal={ Condition Monitor}, author={Aimiyekagbon,
Osarenren Kennedy and Bender, Amelie and Sextro, Walter}, year={2022}, pages={5–10}
}'
chicago: Aimiyekagbon, Osarenren Kennedy, Amelie Bender, and Walter Sextro. “On
the Applicability of Time Series Features as Health Indicators for Technical Systems
Operating under Varying Conditions.” Condition Monitor, 2022.
ieee: O. K. Aimiyekagbon, A. Bender, and W. Sextro, “On the applicability of time
series features as health indicators for technical systems operating under varying
conditions,” Condition Monitor, no. 425, pp. 5–10, 2022.
mla: Aimiyekagbon, Osarenren Kennedy, et al. “On the Applicability of Time Series
Features as Health Indicators for Technical Systems Operating under Varying Conditions.”
Condition Monitor, no. 425, 2022, pp. 5–10.
short: O.K. Aimiyekagbon, A. Bender, W. Sextro, Condition Monitor (2022) 5–10.
date_created: 2023-09-22T09:25:48Z
date_updated: 2023-09-22T09:29:51Z
department:
- _id: '151'
issue: '425'
language:
- iso: eng
page: 5 - 10
publication: ' Condition Monitor'
publication_date: 2022-08
publication_identifier:
issn:
- 0268-8050
publication_status: published
status: public
title: On the applicability of time series features as health indicators for technical
systems operating under varying conditions
type: newspaper_article
user_id: '9557'
year: '2022'
...
---
_id: '27652'
abstract:
- lang: ger
text: "Aufgrund der Fortschritte der Digitalisierung finden Systeme zur Zustandsüberwachung
vermehrt Einsatz in der Industrie, um durch eine zustandsbasierte oder eine prädiktive
Instandhaltung Vorteile, wie eine verbesserte Zuverlässigkeit und geringere Kosten
zu erzielen. Dabei beruhen Zustandsüberwachungssysteme auf den folgenden Bausteinen:
Sensorik, Datenvorverarbeitung, Merkmalsextraktion und -auswahl, Diagnose bzw.
Prognose sowie einer Entscheidungsfindung basierend auf den Ergebnissen. Jeder
dieser Bausteine erfordert individuelle Einstellungen, um ein geeignetes Zustandsüberwachungssystem
für die jeweilige Anwendung zu entwickeln. Eine offene Fragestellung im Bereich
der Zustandsüberwachung ergibt sich aufgrund der Unsicherheit der Zukunft, die
sich in den zukünftigen Betriebs- und Umgebungsbedingungen zeigt. Diese Unsicherheit
gilt es in allen Bausteinen zu berücksichtigen.\r\nDieser Beitrag konzentriert
sich auf den Baustein Merkmalsextraktion und -selektion, mit dem Ziel anhand geeigneter
Merkmale eine Prognose der nutzbaren Restlebensdauer mit hoher Genauigkeit realisieren
zu können. Daher werden geeignete Merkmale aus dem Zeitbereich und daraus abgeleitete
Zustandsindikatoren für die Restlebensdauerprognose von technischen Systemen vorgestellt.
Dabei sind Zustandsindikatoren Kenngrößen zur Beobachtung des Zustands der kritischen
Systemkomponenten. Anhand dreier Anwendungsbeispiele wird ihre Eignung evaluiert.
Dabei werden Daten aus Lebensdauerversuchen unter instationären Betriebs- und
Umgebungsbedingungen ausgewertet. Die auftretenden Unsicherheiten der Zukunft
werden somit berücksichtigt. Die Beispielsysteme beruhen auf Gummi-Metall-Elementen
und Wälzlagern. Aus den generierten Ergebnissen lässt sich schließen, dass die
Zustandsindikatoren aus der betrachteten Zeitreihen-Toolbox auch unter unbekannten
Betriebs- und Umgebungsbedingungen robust sind.\r\n"
- lang: eng
text: "Due to the advances in digitalization, condition monitoring systems have
found numerous applications in the industry due to benefits such as improved reliability
and lowered costs through condition-based or predictive maintenance. Condition
monitoring systems typically involve elements, such as data acquisition via suitable
sensors, data preprocessing, feature extraction and selection, diagnostics, prognostics
and (maintenance) decisions based on diagnosis or prognosis. For the application-specific
development of a suitable condition monitoring system, each of these elements
requires individual settings. Due to the uncertainty of the future, an open question
arises in the condition monitoring field, which is reflected in unknown future
operating and environmental conditions. This uncertainty needs consideration in
all elements of a condition monitoring system.\r\nThis article focuses on feature
extraction and selection, building on the hypothesis that the remaining useful
life of a technical system can be predicted with high accuracy utilizing suitable
features. In this article, health indicators derived from time-domain features
that permit the monitoring of the health of critical system components are presented
for predicting the remaining useful life of technical systems. Three distinct
application examples based on rubber-metal elements and rolling-element bearings
are evaluated to validate the suitability of the presented methods. Experimental
data from accelerated lifetime tests conducted under non-stationary operating
and environmental conditions are considered to take possible future uncertainties
into account. It can be concluded from the acquired results that health indicators
derived from the presented time series toolbox are robust to varying operating
and environmental conditions.\r\n"
author:
- first_name: Osarenren Kennedy
full_name: Aimiyekagbon, Osarenren Kennedy
id: '9557'
last_name: Aimiyekagbon
- first_name: Amelie
full_name: Bender, Amelie
id: '54290'
last_name: Bender
- first_name: Walter
full_name: Sextro, Walter
id: '21220'
last_name: Sextro
citation:
ama: 'Aimiyekagbon OK, Bender A, Sextro W. Extraktion und Selektion geeigneter Merkmale
für die Restlebensdauerprognose von technischen Systemen trotz aleatorischen Unsicherheiten
. In: VDI-Berichte 2391. VDI Verlag GmbH; 2021:197-210.'
apa: Aimiyekagbon, O. K., Bender, A., & Sextro, W. (2021). Extraktion und Selektion
geeigneter Merkmale für die Restlebensdauerprognose von technischen Systemen trotz
aleatorischen Unsicherheiten . VDI-Berichte 2391, 197–210.
bibtex: '@inproceedings{Aimiyekagbon_Bender_Sextro_2021, place={Düsseldorf}, title={Extraktion
und Selektion geeigneter Merkmale für die Restlebensdauerprognose von technischen
Systemen trotz aleatorischen Unsicherheiten }, booktitle={VDI-Berichte 2391},
publisher={VDI Verlag GmbH}, author={Aimiyekagbon, Osarenren Kennedy and Bender,
Amelie and Sextro, Walter}, year={2021}, pages={197–210} }'
chicago: 'Aimiyekagbon, Osarenren Kennedy, Amelie Bender, and Walter Sextro. “Extraktion
und Selektion geeigneter Merkmale für die Restlebensdauerprognose von technischen
Systemen trotz aleatorischen Unsicherheiten .” In VDI-Berichte 2391, 197–210.
Düsseldorf: VDI Verlag GmbH, 2021.'
ieee: O. K. Aimiyekagbon, A. Bender, and W. Sextro, “Extraktion und Selektion geeigneter
Merkmale für die Restlebensdauerprognose von technischen Systemen trotz aleatorischen
Unsicherheiten ,” in VDI-Berichte 2391, Würzburg, 2021, pp. 197–210.
mla: Aimiyekagbon, Osarenren Kennedy, et al. “Extraktion und Selektion geeigneter
Merkmale für die Restlebensdauerprognose von technischen Systemen trotz aleatorischen
Unsicherheiten .” VDI-Berichte 2391, VDI Verlag GmbH, 2021, pp. 197–210.
short: 'O.K. Aimiyekagbon, A. Bender, W. Sextro, in: VDI-Berichte 2391, VDI Verlag
GmbH, Düsseldorf, 2021, pp. 197–210.'
conference:
end_date: 2021-11-17
location: Würzburg
name: '3. VDI-Fachtagung '
start_date: 2021-11-16
date_created: 2021-11-22T07:42:44Z
date_updated: 2022-01-06T06:57:43Z
department:
- _id: '151'
keyword:
- run-to-failure
- rubber-metal element
- bearing prognostics
- non-stationary operating conditions
- varying operating conditions
- feature extraction
- feature selection
language:
- iso: ger
page: 197 - 210
place: Düsseldorf
publication: VDI-Berichte 2391
publication_identifier:
isbn:
- 978-3-18-092391-8
issn:
- '0083-5560 '
publication_status: published
publisher: VDI Verlag GmbH
status: public
title: 'Extraktion und Selektion geeigneter Merkmale für die Restlebensdauerprognose
von technischen Systemen trotz aleatorischen Unsicherheiten '
type: conference
user_id: '9557'
year: '2021'
...
---
_id: '22507'
abstract:
- lang: eng
text: Several methods, including order analysis, wavelet analysis and empirical
mode decomposition have been proposed and successfully employed for the health
state estimation of technical systems operating under varying conditions. However,
where information such as the speed of rotating machinery, component specifications
or other domain-specific information is unavailable, such methods are often infeasible.
Thus, this paper investigates the application of classical time-domain features,
features from the medical field and novel features from the highly comparative
time-series analysis (HCTSA) package, for the health state estimation of rotating
machinery operating under varying conditions. Furthermore, several feature selection
methods are investigated to identify features as viable health indicators for
the diagnostics and prognostics of technical systems. As a case study, the presented
methods are evaluated on real-world and experimentally acquired vibration data
of bearings operating under varying speed. The results show that the selected
features can successfully be employed as health indicators for technical systems
operating under varying conditions.
author:
- first_name: Osarenren Kennedy
full_name: Aimiyekagbon, Osarenren Kennedy
id: '9557'
last_name: Aimiyekagbon
- first_name: Amelie
full_name: Bender, Amelie
id: '54290'
last_name: Bender
- first_name: Walter
full_name: Sextro, Walter
id: '21220'
last_name: Sextro
citation:
ama: 'Aimiyekagbon OK, Bender A, Sextro W. On the applicability of time series features
as health indicators for technical systems operating under varying conditions.
In: Proceedings of the Seventeenth International Conference on Condition Monitoring
and Asset Management (CM 2021).'
apa: Aimiyekagbon, O. K., Bender, A., & Sextro, W. (n.d.). On the applicability
of time series features as health indicators for technical systems operating under
varying conditions. Proceedings of the Seventeenth International Conference
on Condition Monitoring and Asset Management (CM 2021). Seventeenth International
Conference on Condition Monitoring and Asset Management (CM 2021).
bibtex: '@inproceedings{Aimiyekagbon_Bender_Sextro, title={On the applicability
of time series features as health indicators for technical systems operating under
varying conditions}, booktitle={Proceedings of the Seventeenth International Conference
on Condition Monitoring and Asset Management (CM 2021)}, author={Aimiyekagbon,
Osarenren Kennedy and Bender, Amelie and Sextro, Walter} }'
chicago: Aimiyekagbon, Osarenren Kennedy, Amelie Bender, and Walter Sextro. “On
the Applicability of Time Series Features as Health Indicators for Technical Systems
Operating under Varying Conditions.” In Proceedings of the Seventeenth International
Conference on Condition Monitoring and Asset Management (CM 2021), n.d.
ieee: O. K. Aimiyekagbon, A. Bender, and W. Sextro, “On the applicability of time
series features as health indicators for technical systems operating under varying
conditions,” presented at the Seventeenth International Conference on Condition
Monitoring and Asset Management (CM 2021).
mla: Aimiyekagbon, Osarenren Kennedy, et al. “On the Applicability of Time Series
Features as Health Indicators for Technical Systems Operating under Varying Conditions.”
Proceedings of the Seventeenth International Conference on Condition Monitoring
and Asset Management (CM 2021).
short: 'O.K. Aimiyekagbon, A. Bender, W. Sextro, in: Proceedings of the Seventeenth
International Conference on Condition Monitoring and Asset Management (CM 2021),
n.d.'
conference:
end_date: 2021-06-18
name: Seventeenth International Conference on Condition Monitoring and Asset Management
(CM 2021)
start_date: 2021-06-14
date_created: 2021-06-23T05:24:39Z
date_updated: 2023-09-22T08:10:34Z
ddc:
- '620'
department:
- _id: '151'
file:
- access_level: open_access
content_type: application/pdf
creator: kennedy
date_created: 2021-06-23T06:43:44Z
date_updated: 2021-06-23T06:50:07Z
description: 'This is a post-print version of the article presented at the Seventeenth
International Con-ference on Condition Monitoring and Asset Management (CM 2021).
The event websiteis available at: https://www.bindt.org/events/CM-2021/ and the
abstract is available at:https://www.bindt.org/events/CM-2021/abstract-9a7/.'
file_id: '22508'
file_name: Aimiyekagbon_et_al_2021_On_the_applicability_of_time_series_features_as_health_indicators_postPrint.pdf
file_size: 1875572
relation: main_file
title: On the applicability of time series features as health indicators for technical
systems operating under varying conditions
file_date_updated: 2021-06-23T06:50:07Z
has_accepted_license: '1'
keyword:
- Wind turbine diagnostics
- bearing diagnostics
- non-stationary operating conditions
- varying operating conditions
- feature extraction
- feature selection
- fault detection
- failure detection
language:
- iso: eng
oa: '1'
publication: Proceedings of the Seventeenth International Conference on Condition
Monitoring and Asset Management (CM 2021)
publication_status: inpress
quality_controlled: '1'
status: public
title: On the applicability of time series features as health indicators for technical
systems operating under varying conditions
type: conference
user_id: '9557'
year: '2021'
...
---
_id: '27111'
abstract:
- lang: eng
text: In the industry 4.0 era, there is a growing need to transform unstructured
data acquired by a multitude of sources into information and subsequently into
knowledge to improve the quality of manufactured products, to boost production,
for predictive maintenance, etc. Data-driven approaches, such as machine learning
techniques, are typically employed to model the underlying relationship from data.
However, an increase in model accuracy with state-of-the-art methods, such as
deep convolutional neural networks, results in less interpretability and transparency.
Due to the ease of implementation, interpretation and transparency to both domain
experts and non-experts, a rule-based method is proposed in this paper, for prognostics
and health management (PHM) and specifically for diagnostics. The proposed method
utilizes the most relevant sensor signals acquired via feature extraction and
selection techniques and expert knowledge. As a case study, the presented method
is evaluated on data from a real-world quality control set-up provided by the
European prognostics and health management society (PHME) at the conference’s
2021 data challenge. With the proposed method, our team took the third place,
capable of successfully diagnosing different fault modes, irrespective of varying
conditions.
author:
- first_name: Osarenren Kennedy
full_name: Aimiyekagbon, Osarenren Kennedy
id: '9557'
last_name: Aimiyekagbon
- first_name: Lars
full_name: Muth, Lars
id: '77313'
last_name: Muth
orcid: 0000-0002-2938-5616
- first_name: Meike Claudia
full_name: Wohlleben, Meike Claudia
id: '43991'
last_name: Wohlleben
orcid: 0009-0009-9767-7168
- first_name: Amelie
full_name: Bender, Amelie
id: '54290'
last_name: Bender
- first_name: Walter
full_name: Sextro, Walter
id: '21220'
last_name: Sextro
citation:
ama: 'Aimiyekagbon OK, Muth L, Wohlleben MC, Bender A, Sextro W. Rule-based Diagnostics
of a Production Line. In: Do P, King S, Fink O, eds. Proceedings of the European
Conference of the PHM Society 2021. Vol 6. ; 2021:527-536. doi:10.36001/phme.2021.v6i1.3042'
apa: Aimiyekagbon, O. K., Muth, L., Wohlleben, M. C., Bender, A., & Sextro,
W. (2021). Rule-based Diagnostics of a Production Line. In P. Do, S. King, &
O. Fink (Eds.), Proceedings of the European Conference of the PHM Society 2021
(Vol. 6, Issue 1, pp. 527–536). https://doi.org/10.36001/phme.2021.v6i1.3042
bibtex: '@inproceedings{Aimiyekagbon_Muth_Wohlleben_Bender_Sextro_2021, title={Rule-based
Diagnostics of a Production Line}, volume={6}, DOI={10.36001/phme.2021.v6i1.3042},
number={1}, booktitle={Proceedings of the European Conference of the PHM Society
2021}, author={Aimiyekagbon, Osarenren Kennedy and Muth, Lars and Wohlleben, Meike
Claudia and Bender, Amelie and Sextro, Walter}, editor={Do, Phuc and King, Steve
and Fink, Olga}, year={2021}, pages={527–536} }'
chicago: Aimiyekagbon, Osarenren Kennedy, Lars Muth, Meike Claudia Wohlleben, Amelie
Bender, and Walter Sextro. “Rule-Based Diagnostics of a Production Line.” In Proceedings
of the European Conference of the PHM Society 2021, edited by Phuc Do, Steve
King, and Olga Fink, 6:527–36, 2021. https://doi.org/10.36001/phme.2021.v6i1.3042.
ieee: 'O. K. Aimiyekagbon, L. Muth, M. C. Wohlleben, A. Bender, and W. Sextro, “Rule-based
Diagnostics of a Production Line,” in Proceedings of the European Conference
of the PHM Society 2021, 2021, vol. 6, no. 1, pp. 527–536, doi: 10.36001/phme.2021.v6i1.3042.'
mla: Aimiyekagbon, Osarenren Kennedy, et al. “Rule-Based Diagnostics of a Production
Line.” Proceedings of the European Conference of the PHM Society 2021,
edited by Phuc Do et al., vol. 6, no. 1, 2021, pp. 527–36, doi:10.36001/phme.2021.v6i1.3042.
short: 'O.K. Aimiyekagbon, L. Muth, M.C. Wohlleben, A. Bender, W. Sextro, in: P.
Do, S. King, O. Fink (Eds.), Proceedings of the European Conference of the PHM
Society 2021, 2021, pp. 527–536.'
conference:
name: PHM Society European Conference
date_created: 2021-11-03T12:26:39Z
date_updated: 2023-09-22T09:13:01Z
department:
- _id: '151'
doi: 10.36001/phme.2021.v6i1.3042
editor:
- first_name: Phuc
full_name: Do, Phuc
last_name: Do
- first_name: Steve
full_name: King, Steve
last_name: King
- first_name: Olga
full_name: Fink, Olga
last_name: Fink
intvolume: ' 6'
issue: '1'
keyword:
- PHME 2021
- Feature Selection Classification
- Feature Selection Clustering
- Interpretable Model
- Transparent Model
- Industry 4.0
- Real-World Diagnostics
- Quality Control
- Predictive Maintenance
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://papers.phmsociety.org/index.php/phme/article/download/3042/1812
oa: '1'
page: 527-536
publication: Proceedings of the European Conference of the PHM Society 2021
publication_status: published
quality_controlled: '1'
status: public
title: Rule-based Diagnostics of a Production Line
type: conference
user_id: '9557'
volume: 6
year: '2021'
...
---
_id: '17810'
abstract:
- lang: eng
text: In all fields, the significance of a reliable and accurate predictive model
is almost unquantifiable. With deep domain knowledge, models derived from first
principles typically outperforms other models in terms of reliability and accuracy.
When it may become a cumbersome or an unachievable task to build or validate such
models of complex (non-linear) systems, machine learning techniques are employed
to build predictive models. However, the accuracy of such techniques is not only
dependent on the hyper-parameters of the chosen algorithm, but also on the amount
and quality of data. This paper investigates the application of classical time
series forecasting approaches for the reliable prognostics of technical systems,
where black box machine learning techniques might not successfully be employed
given insufficient amount of data and where first principles models are infeasible
due to lack of domain specific data. Forecasting by analogy, forecasting by analytical
function fitting, an exponential smoothing forecasting method and the long short-term
memory (LSTM) are evaluated and compared against the ground truth data. As a case
study, the methods are applied to predict future crack lengths of riveted aluminium
plates under cyclic loading. The performance of the predictive models is evaluated
based on error metrics leading to a proposal of when to apply which forecasting
approach.
author:
- first_name: Osarenren Kennedy
full_name: Aimiyekagbon, Osarenren Kennedy
id: '9557'
last_name: Aimiyekagbon
- first_name: Amelie
full_name: Bender, Amelie
id: '54290'
last_name: Bender
- first_name: Walter
full_name: Sextro, Walter
id: '21220'
last_name: Sextro
citation:
ama: 'Aimiyekagbon OK, Bender A, Sextro W. Evaluation of time series forecasting
approaches for the reliable crack length prediction of riveted aluminium plates
given insufficient data. In: PHM Society European Conference. Vol 5. ;
2020.'
apa: Aimiyekagbon, O. K., Bender, A., & Sextro, W. (2020). Evaluation of time
series forecasting approaches for the reliable crack length prediction of riveted
aluminium plates given insufficient data. PHM Society European Conference,
5(1).
bibtex: '@inproceedings{Aimiyekagbon_Bender_Sextro_2020, title={Evaluation of time
series forecasting approaches for the reliable crack length prediction of riveted
aluminium plates given insufficient data}, volume={5}, number={1}, booktitle={PHM
Society European Conference}, author={Aimiyekagbon, Osarenren Kennedy and Bender,
Amelie and Sextro, Walter}, year={2020} }'
chicago: Aimiyekagbon, Osarenren Kennedy, Amelie Bender, and Walter Sextro. “Evaluation
of Time Series Forecasting Approaches for the Reliable Crack Length Prediction
of Riveted Aluminium Plates given Insufficient Data.” In PHM Society European
Conference, Vol. 5, 2020.
ieee: O. K. Aimiyekagbon, A. Bender, and W. Sextro, “Evaluation of time series forecasting
approaches for the reliable crack length prediction of riveted aluminium plates
given insufficient data,” in PHM Society European Conference, 2020, vol.
5, no. 1.
mla: Aimiyekagbon, Osarenren Kennedy, et al. “Evaluation of Time Series Forecasting
Approaches for the Reliable Crack Length Prediction of Riveted Aluminium Plates
given Insufficient Data.” PHM Society European Conference, vol. 5, no.
1, 2020.
short: 'O.K. Aimiyekagbon, A. Bender, W. Sextro, in: PHM Society European Conference,
2020.'
date_created: 2020-08-11T13:32:40Z
date_updated: 2023-09-22T09:13:16Z
department:
- _id: '151'
intvolume: ' 5'
issue: '1'
keyword:
- PHM 2019
- crack propagation
- forecasting
- unevenly spaced time series
- step ahead prediction
- short time series
language:
- iso: eng
publication: PHM Society European Conference
quality_controlled: '1'
status: public
title: Evaluation of time series forecasting approaches for the reliable crack length
prediction of riveted aluminium plates given insufficient data
type: conference
user_id: '9557'
volume: 5
year: '2020'
...