Application of Bayesian Estimation to Structural Health Monitoring of Fatigue Cracks in Welded Steel Pipe
- Submitting institution
-
Brunel University London
- Unit of assessment
- 12 - Engineering
- Output identifier
- 275-193052-8468
- Type
- D - Journal article
- DOI
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10.1016/j.ymssp.2018.11.004
- Title of journal
- Mechanical Systems And Signal Processing
- Article number
- -
- First page
- 112
- Volume
- 121
- Issue
- -
- ISSN
- 0888-3270
- Open access status
- Compliant
- Month of publication
- November
- Year of publication
- 2018
- URL
-
http://bura.brunel.ac.uk/handle/2438/17069
- 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)
-
2 - Applied Mechanics & Structures
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The paper presents new results in SHM for fatigue monitoring of pipes using acoustic emission. A new cross-correlation coefficient was shown to be effective in evaluation of uncertainty arising from signals used for source detection. The effectiveness of this method was demonstrated on a full scale resonance test of a girth-welded steel pipe from healthy conditions to failure. The new coefficient was embedded in a Bayesian estimation loop showing very good performances in mitigating the risk of vibration induced fatigue failure.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -