Flow noise identification using acoustic emission (AE) energy decomposition for sand monitoring in flow pipeline
- Submitting institution
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Robert Gordon University
- Unit of assessment
- 12 - Engineering
- Output identifier
- Steel_2
- Type
- D - Journal article
- DOI
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10.1016/j.apacoust.2017.10.016
- Title of journal
- Applied Acoustics
- Article number
- -
- First page
- 5-15
- Volume
- 131
- Issue
- -
- ISSN
- 0003-682X
- Open access status
- Compliant
- Month of publication
- -
- Year of publication
- 2017
- URL
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- Supplementary information
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- Request cross-referral to
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- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
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- Research group(s)
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- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This work is an output from a collaboration with Heriot Watt University with industrial funding from SMS Oilfield Ltd & CENSIS (Project no. 14-327) into sand monitoring applications. It developed an advanced signal processing technique to characterise noise/interference sources in pipeline flows for enhancing the monitoring of sand particle impacts in a multi-phase flow-loop which has significant industrial applications (e.g., sand monitoring during oil and gas production). The study underpinned the Sand Management Network (www.sandmanagement.com) actions plan in multi-phase flow and led to a new industrial collaboration with Halliburton and CNOOC International for solving sand deposition problems in pipelines.
- Author contribution statement
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- Non-English
- No
- English abstract
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