Picture of barbed wire fence

Open Access research that is addressing youth & criminal justice...

Advancing our understanding of crime and criminal justice, including youth justice, is a key area of research enquiry by researchers based at the Scottish Centre for Crime & Justice (SCCJR) and the Centre for Youth & Criminal Justice (CYCJ), within the School of Social Work & Social Policy.

SCCJR seeks to advance this understanding through theoretical, empirical and applied research, working with communities and policy makers, while simulatneously fostering a national criminological research capacity. Specialisms include the role of violence, drugs and alcohol in crime and the criminal justice system. Meanwhile, CYCJ remains dedicated to supporting improvements in youth justice, contributing to better lives for individuals, families and communities. Research here focuses on improving youth justice practice, policy and research.

Explore some of the Open Access research from SCCJR and CYCJ. Or explore all of Strathclyde's Open Access research...

Browse by Author or creator

Up a level
Export as [feed] Atom [feed] RSS 1.0 [feed] RSS 2.0
Group by: Publication Date | Item type | No Grouping
Jump to: 2019 | 2018 | 2017
Number of items: 10.

2019

Mckinnon, C. and Carroll, J. and McDonald, A. and Koukoura, S. and Soraghan, C. (2019) Comparison of anomaly detection techniques for wind turbine gearbox SCADA data. In: Wind Energy Science conference 2019, 2019-06-17 - 2019-06-20, University College Cork.

Koukoura, Sofia and Carroll, James and McDonald, Alasdair (2019) On the use of AI based vibration condition monitoring of wind turbine gearboxes. Journal of Physics: Conference Series, 1222 (1). 012045. ISSN 1742-6588

Mckinnon, Conor and Carroll, James and McDonald, Alasdair and Koukoura, Sofia (2019) Machine learning in wind turbine O&M. In: Future Wind and Marine, 2019-03-07, University of Strathclyde.

2018

Carroll, James and Koukoura, Sofia and McDonald, Alasdair and Weiss, Stephan and McArthur, Stephen (2018) Wind turbine gearbox failure and remaining useful life prediction using machine learning techniques. Wind Energy. ISSN 1095-4244

Koukoura, S and Carroll, J and McDonald, A and Weiss, S (2018) Wind turbine gearbox planet bearing failure prediction using vibration data. Journal of Physics: Conference Series, 1104. 012016. ISSN 1742-6596

Turnbull, A. and Carroll, J. and Koukoura, S. and McDonald, A. (2018) Prediction of wind turbine generator bearing failure through analysis of high frequency vibration data and the application of support vector machine algorithms. In: The 7th International Conference on Renewable Power Generation, 2018-08-26 - 2018-09-27, DTU, Lyngby.

Koukoura, Sofia and Carroll, James and McDonald, Alasdair (2018) An insight into wind turbine planet bearing fault prediction using SCADA data. Proceedings of the European Conference of the PHM Society, 4 (1).

Artigao, Estefania and Koukoura, Sofia and Honrubia-Escribano, Andrés and Carroll, James and McDonald, Alasdair and Gómez-Lázaro, Emilio (2018) Current signature and vibration analyses to diagnose an in-service wind turbine drive train. Energies, 11 (4). ISSN 1996-1073

2017

Koukoura, Sofia and Carroll, James and Weiss, Stepha and McDonald, Alasdair; (2017) Wind turbine gearbox vibration signal signature and fault development through time. In: 25th European Signal Processing Conference, EUSIPCO 2017. IEEE, GRC, pp. 1380-1384. ISBN 9780992862671

Koukoura, Sofia and Carroll, James and McDonald, Alasdair (2017) Wind turbine intelligent gear fault identification. In: Annual Conference of the PHM Society, 2017-10-02 - 2017-10-05.

This list was generated on Thu Jun 4 23:01:30 2020 BST.