Real-time simulation of neural network classifications from characteristics emitted by acoustic emission during horizontal single grit scratch tests
- Submitting institution
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Liverpool John Moores University
- Unit of assessment
- 12 - Engineering
- Output identifier
- 1979
- Type
- D - Journal article
- DOI
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10.1007/s10845-014-0883-x
- Title of journal
- JOURNAL OF INTELLIGENT MANUFACTURING
- Article number
- -
- First page
- 507
- Volume
- 27
- Issue
- 3
- ISSN
- 0956-5515
- Open access status
- Out of scope for open access requirements
- Month of publication
- February
- 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
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1
- Research group(s)
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C - GERI
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The research uncovered fundamental features of acoustic emission-associated material removal with a high confidence of classification accuracy, and facilitated a Simulink model as a potential control system for mapping the micro and macro mechanics seen in grinding operations. This supported a successful project at Rolls-Royce “Research into vibration assisted grinding of advanced materials” (£100k, 2014-2015, D. Novovic, donka.novovic@rolls-royce.com). The work attracted interest from the research community in Spain and Australia, leading to international collaboration (Spanish Ministry of Education, Culture and Sport grant “José Castillejo Stays Abroad for the Mobility of Young Doctors”, €100k; Endeavour Executive Fellowships, $AUD 120k).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -