A heterogeneous benchmark dataset for data analytics: multiphase flow facility case study
- Submitting institution
-
Imperial College of Science, Technology and Medicine
- Unit of assessment
- 12 - Engineering
- Output identifier
- 4573
- Type
- D - Journal article
- DOI
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10.1016/j.jprocont.2019.04.009
- Title of journal
- Journal of Process Control
- Article number
- -
- First page
- 41
- Volume
- 79
- Issue
- 1
- ISSN
- 0959-1524
- Open access status
- Compliant
- Month of publication
- May
- Year of publication
- 2019
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
5
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The benchmark dataset includes process measurements, alarm records, high-frequency ultrasonic flow and pressure measurements, operation logs and video recordings, and experimentally-induced faults. The article has been in the top-five most downloaded papers of the journal since publication. The dataset has been downloaded 1500 times since April 2019 (https://zenodo.org/record/1341583). The data are used industrially by Celonis in Munich and ABB for developing and validating algorithms for fault-detection and diagnosis (Celonis, contact: FoEREF@ic.ac.uk). ABB has funded a Chair of Autonomous Industrial Systems at Imperial for related work.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -