"AI-based actuator/sensor fault detection with low computational cost for industrial applications"
- Submitting institution
-
Cranfield University
- Unit of assessment
- 12 - Engineering
- Output identifier
- 22721506
- Type
- D - Journal article
- DOI
-
10.1109/TCST.2015.2422794
- Title of journal
- IEEE Transactions on Control Systems Technology
- Article number
- -
- First page
- 293
- Volume
- ="24"
- Issue
- ="1"
- ISSN
- 1063-6536
- Open access status
- Out of scope for open access requirements
- Month of publication
- May
- Year of publication
- 2015
- 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
-
3
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The research findings are being implemented by Precup in the field of neuro-fuzzy control applications (Dean of the Faculty of Automation and Computers, Politehnica University of Timisoara, Romania, Contact Details: Audit_file_22721506).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -