Dataset with four years of condition monitoring technical language annotations from paper machine industries in northern Sweden
SND-ID: 2023-257. Version: 1. DOI: https://doi.org/10.5878/hafd-ms27
Associated documentation
Citation
Creator/Principal investigator(s)
Karl Löwenmark
- Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering
Fredrik Sandin
- Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering
Marcus Liwicki
- Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering
Stephan Schnabel
- SKF (Sweden)
Research principal
Luleå University of Technology
- Department of Computer Science, Electrical and Space Engineering
Principal's reference number
2019-02533
Description
Data can be accessed in Python with:
import pandas as pd
annotations_df = pd.read_pickle("Technical_Language_Annotations.pkl")
annotation_contents = annotations_df['noteComment']
annotation_titles = annotations_df['title']
Data contains personal data
Yes
Type of personal data
Signed annotations are preserved in the raw data. As a result, the dataset contains pseudonymised personal data.
Language
Responsible department/unit
Department of Computer Science, Electrical and Space Engineering
Contributor(s)
Håkan Sirkka - Smurfit Kappa
Per-Erik Larsson - SKF (Sweden)
Pär-Erik Martinsson - Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering
Peter Wikström - SCA Munksund
Kjell Lundberg - Smurfit Kappa
... Show more..Håkan Sirkka - Smurfit Kappa
Per-Erik Larsson - SKF (Sweden)
Pär-Erik Martinsson - Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering
Peter Wikström - SCA Munksund
Kjell Lundberg - Smurfit Kappa
Smurfit Kappa
SKF (Sweden)
Svenska Cellulosa (Sweden)
RISE Research Institutes of Sweden
Funding
-
Funding agency:
VINNOVA
- Funding agency's reference number: 2019-02533
- Project name on the application: Kunskapsintegrering för klassificering av maskinskador
- Funding information: https://www.vinnova.se/p/kunskapsintegrering-for-klassificering-av-maskinskador/
Research area
Language technology (computational linguistics) (Standard för svensk indelning av forskningsämnen 2011)
Keywords
Paper machines, Condition monitoring, Language technology, Signal processing, Paper industry, Fault detection, Natural language processing, Technical language processing, Natural language processing, Prognostics and health management, Intelligent fault diagnosis, Technical language supervision
Löwenmark, K., Taal, C., Nivre, J., Liwicki, M., & Sandin, F. (2022). Processing of Condition Monitoring Annotations with BERT and Technical Language Substitution: A Case Study. In Proceedings of the 7th European Conference of the Prognostics and Health Management Society 2022 (pp. 306–314).
DOI:
https://doi.org/10.36001/phme.2022.v7i1.3356
URN:
urn:nbn:se:ltu:diva-95407
SwePub:
oai:DiVA.org:ltu-95407
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