| Comparison of new anomaly detection technique for wind turbine condition monitoring using gearbox SCADA data C McKinnon, J Carroll, A McDonald, S Koukoura, D Infield, C Soraghan Energies 13 (19), 5152, 2020 | 48 | 2020 |
| Effect of time history on normal behaviour modelling using SCADA data to predict wind turbine failures C McKinnon, A Turnbull, S Koukoura, J Carroll, A McDonald Energies 13 (18), 4745, 2020 | 20 | 2020 |
| Investigation of isolation forest for wind turbine pitch system condition monitoring using SCADA data C McKinnon, J Carroll, A McDonald, S Koukoura, C Plumley Energies 14 (20), 6601, 2021 | 10 | 2021 |
| Investigation of anomaly detection technique for wind turbine pitch systems C McKinnon, J Carroll, A McDonald, S Koukoura, C Plumley IET Digital Library, 2021 | 5 | 2021 |
| Comparison of novel SCADA data cleaning technique for wind turbine electric pitch system C McKinnon, K Tartt, J Carroll, A McDonald, C Plumley, D Ferguson Journal of Physics: Conference Series 2151 (1), 012005, 2022 | 1 | 2022 |
| Comparison of anomaly detection techniques for wind turbine gearbox SCADA data: Wind Energy Science conference 2019 C Mckinnon, J Carroll, A McDonald, S Koukoura, C Soraghan | | 2019 |
| Machine learning in wind turbine O&M C Mckinnon, J Carroll, A McDonald, S Koukoura Future Wind and Marine, 2019 | | 2019 |
James CarrollUniversity of StrathclydeVerified email at strath.ac.uk
