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Open Access research that better understands changing marine ecologies...

Strathprints makes available scholarly Open Access content by researchers in the Department of Mathematics & Statistics.

Mathematics & Statistics hosts the Marine Population Modelling group which is engaged in research into topics surrounding marine resource modelling and ecology. Recent work has included important developments in the population modelling of marine species.

Explore the Open Access research of Mathematics & Statistics. Or explore all of Strathclyde's Open Access research...

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Number of items: 9.

Turnbull, Alan and Carroll, James and McDonald, Alasdair (2022) A comparative analysis on the variability of temperature thresholds through time for wind turbine generators using normal behaviour modelling. Energies, 15 (14). 5298. ISSN 1996-1073

Turnbull, Alan and Mckinnon, Conor and Carroll, James and McDonald, Alasdair (2022) On the development of offshore wind turbine technology : an assessment of reliability rates and fault detection methods in a changing market. Energies, 15 (9). 3180. ISSN 1996-1073

Turnbull, Alan and Carroll, James (2021) Cost benefit of implementing advanced monitoring and predictive maintenance strategies for offshore wind farms. Energies, 14 (16). 4922. ISSN 1996-1073

Turnbull, Alan and Carroll, James and McDonald, Alasdair (2020) Combining SCADA and vibration data into a single anomaly detection model to predict wind turbine component failure. Wind Energy, 24 (3). pp. 197-211. ISSN 1095-4244

Mckinnon, Conor and Turnbull, Alan and Koukoura, Sofia and Carroll, James and McDonald, Alasdair (2020) Effect of time history on normal behaviour modelling using SCADA data to predict wind turbine failures. Energies, 13 (18). 4745. ISSN 1996-1073

Turnbull, Alan and Carroll, James and McDonald, Alasdair and Koukoura, Sofia (2019) Prediction of wind turbine generator failure using two-stage cluster-classification methodology. Wind Energy, 22 (11). pp. 1593-1602. ISSN 1095-4244

Hart, Edward and Turnbull, Alan and Feuchtwang, Julian and McMillan, David and Golysheva, Evgenia and Elliott, Robin (2019) Wind turbine main-bearing loading and wind field characteristics. Wind Energy, 22 (11). pp. 1534-1547. ISSN 1095-4244

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.

Hart, E and Turnbull, A and McMillan, D and Feuchtwang, J and Golysheva, E and Elliott, R (2017) Investigation of the relationship between main-bearing loads and wind field characteristics. Journal of Physics: Conference Series, 926. 012010. ISSN 1742-6588

This list was generated on Tue Jun 18 06:09:42 2024 BST.