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Kevin Leahy
Kevin Leahy
PhD Researcher, IERG, UCC
Verified email at umail.ucc.ie - Homepage
Title
Cited by
Cited by
Year
An industrial big data pipeline for data-driven analytics maintenance applications in large-scale smart manufacturing facilities
P O’Donovan, K Leahy, K Bruton, DTJ O’Sullivan
Journal of Big Data 2 (1), 1-26, 2015
2492015
Big data in manufacturing: a systematic mapping study
P O’donovan, K Leahy, K Bruton, DTJ O’Sullivan
Journal of Big Data 2 (1), 1-22, 2015
1972015
Diagnosing wind turbine faults using machine learning techniques applied to operational data
K Leahy, RL Hu, IC Konstantakopoulos, CJ Spanos, AM Agogino
2016 ieee international conference on prognostics and health management …, 2016
932016
A comparison of fog and cloud computing cyber-physical interfaces for Industry 4.0 real-time embedded machine learning engineering applications
P O’Donovan, C Gallagher, K Leahy, DTJ O’Sullivan
Computers in industry 110, 12-35, 2019
742019
Diagnosing and predictingwind turbine faults from SCADA data using support vector machines
K Leahy, RL Hu, IC Konstantakopoulos, CJ Spanos, AM Agogino, ...
International Journal of Prognostics and Health Management 9 (1), 2018
562018
The suitability of machine learning to minimise uncertainty in the measurement and verification of energy savings
CV Gallagher, K Bruton, K Leahy, DTJ O’Sullivan
Energy and Buildings 158, 647-655, 2018
382018
A robust prescriptive framework and performance metric for diagnosing and predicting wind turbine faults based on SCADA and alarms data with case study
K Leahy, C Gallagher, P O’Donovan, K Bruton, DTJ O’Sullivan
Energies 11 (7), 1738, 2018
352018
Development and application of a machine learning supported methodology for measurement and verification (M&V) 2.0
CV Gallagher, K Leahy, P O’Donovan, K Bruton, DTJ O’Sullivan
Energy and Buildings 167, 8-22, 2018
322018
Automatically identifying and predicting unplanned wind turbine stoppages using scada and alarms system data: Case study and results
K Leahy, C Gallagher, K Bruton, P O’Donovan, DTJ O’Sullivan
Journal of Physics: Conference Series 926 (1), 012011, 2017
282017
Using domain knowledge features for wind turbine diagnostics
RL Hu, K Leahy, IC Konstantakopoulos, DM Auslander, CJ Spanos, ...
2016 15th IEEE International Conference on Machine Learning and Applications …, 2016
242016
Issues with data quality for wind turbine condition monitoring and reliability analyses
K Leahy, C Gallagher, P O’Donovan, DTJ O’Sullivan
Energies 12 (2), 201, 2019
212019
Cluster analysis of wind turbine alarms for characterising and classifying stoppages
K Leahy, C Gallagher, P O'Donovan, DTJ O'Sullivan
IET Renewable Power Generation 12 (10), 1146-1154, 2018
112018
IntelliMaV: A cloud computing measurement and verification 2.0 application for automated, near real-time energy savings quantification and performance deviation detection
CV Gallagher, K Leahy, P O’Donovan, K Bruton, DTJ O’Sullivan
Energy and Buildings 185, 26-38, 2019
92019
From M&V to M&T: An artificial intelligence-based framework for real-time performance verification of demand-side energy savings
CV Gallagher, P O’Donovan, K Leahy, K Bruton, DTJ O’Sullivan
2018 International Conference on Smart Energy Systems and Technologies (SEST …, 2018
42018
A data pipeline for PHM data-driven analytics in large-scale smart manufacturing facilities
PO Donovan, K Leahy, DO Cusack, K Bruton, DTJ O’Sullivan
Annual conference of the prognostics and health management society 6, 1-10, 2015
42015
Implementing the Green Batch: A case study: Continuous statistical evaluation to achieve the most energy efficient and reliable process
K Leahy, K Bruton, D O'Sullivan
Proceedings of the 2014 IEEE Emerging Technology and Factory Automation …, 2014
12014
Industrial Big Data Pipeline for Wind Turbine PHM in a Large Manufacturing Facility
K Leahy, C Gallagher, P O’Donovan, DTJ O’Sullivan
International Journal of Prognostics and Health Management 10 (1), 1-4, 2019
2019
Data analytics for fault prediction and diagnosis in wind turbines
K Leahy
University College Cork, 2018
2018
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