An approach to fault diagnosis of reciprocating compressor valves using Teager-Kaiser energy operator and deep belief networks
- Submitting institution
-
The University of Huddersfield
- Unit of assessment
- 12 - Engineering
- Output identifier
- 26
- Type
- D - Journal article
- DOI
-
10.1016/j.eswa.2013.12.026
- Title of journal
- Expert Systems with Applications
- Article number
- -
- First page
- 4113
- Volume
- 41
- Issue
- 9
- ISSN
- 0957-4174
- Open access status
- Out of scope for open access requirements
- Month of publication
- -
- Year of publication
- 2014
- 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
-
2
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper provided the first ever demonstration in the field of machinery condition assessment of the use of an approach combining the Teager-Kaiser energy operator with a deep belief network. The target was the condition assessment of reciprocating compressor valve failure (a common and problematic failure mode in industrial applications), and the results were extremely good. Since the publication of this highly cited work, there have been numerous further demonstrations of this approach in the field of condition monitoring, and to date this remains a well-frequented avenue of maintenance engineering research.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
