Staff profile

Prof. Christopher Crabtree is the Professor of Wind Energy Systems in the Department of Engineering.

Having received the MEng in Engineering from the University of Durham in 2007, he began a PhD in the then School of Engineering and Computing Sciences at Durham, graduating in 2011 with a thesis on condition monitoring techniques for wind turbines. He briefly held a postdoctoral research post in Durham before joining the academic staff. 

Christopher’s research focuses on operation and maintenance aspects of wind energy, onshore and offshore, with the aim of improving reliability, raising availability and reducing the cost of energy from wind. His primary research areas are: (i) development of condition monitoring techniques, (ii) power conversion system reliability, (iii) performance analysis of wind energy systems, and (iv) high-frequency thermal monitoring for power electronics.

He also has interests in the movement of church bell towers during full-circle change ringing, with early work focused on Durham Cathedral.

Christopher has held a number of departmental roles including Director of Education (2019-2023), Chair of the PGT Board of Examiners and Programme Director for the MSc in New and Renewable Energy. He has led major educational initiatives for the Department and continues to be actively involved in the administrative and operational life of the Department.

Research

Christopher’s research began from the development of condition monitoring algorithms for wind turbines using electrical signals as an alternative to conventional vibration-based monitoring systems. His major interest is now in the development of targeted monitoring systems, including algorithms and sensor systems, for energy systems. Wind turbine drive trains form the core of his work with thermal monitoring of power electronic converters being added in recent years. His work is supported by both research council and industrial funding and has included impact acceleration projects with Cummins and Anecto. Amongst other industrial partners, he works closely with Ørsted, supervising two Ørsted-funded PhD students, as well as the Offshore Renewable Energy Catapult. He was part of the EPSRC SUPERGEN Wind consortium from 2007 and sat on the Management Board for the £3M EPSRC HOME-Offshore project (EP/P009743/1). He is currently co-investigator of the £7.6M EPSRC New Partnership in Offshore Wind (EP/R004900/1), working closely with Siemens-Gamesa Renewable Energy and Ørsted.

Teaching

Christopher currently teaches courses in electrostatics, electromagnetism and electrical energy conversion. He coordinates MSc group design projects and has previously taught modelling of dynamic systems and design, and supervised industrial projects.

Administrative Roles

Prof. Crabtree is the Director of Education for the Department of Engineering, leading the development and operation of the Department's undergraduate and taught postgraduate programmes. He has held a number of administrative roles including Chair of the Board of Examiners (Taught Postgraduate), MSc Programme Director, electrical teaching laboratory leader and electrical lab health and safety representative. He currently manages the electrical machines research laboratory.

• Offshore wind turbines and farms
• Condition monitoring
• Reliability of electrical machines and drives
• Electrical machines
• Sensors and monitoring algorithms
• Optical torque monitoring
• High-frequency temperature sensing
• Church bell ringing and tower movement

Authored book

• Tavner, P. J., Ran, L., & Crabtree, C. J. (2020). Condition Monitoring of Rotating Electrical Machines. (3rd ed.). Institution of Engineering and Technology (IET)

Chapter in book

• Zappalá, D., Crabtree, C., & Tavner, P. (2016). Reliability and condition monitoring. In S. Hogg, & C. Crabtree (Eds.), UK Wind Energy Technologies (76-136). Routledge

Conference Paper

• Saxena, I., Kazemtabrizi, B., Troffaes, M., & Crabtree, C. (in press). Data-driven Infrastructure Planning for Offshore Wind Farms.
• Pina-Gongora, D. C., Kazemtabrizi, B., & Crabtree, C. (2022). Performance comparison of Probabilistic and Artificial Neural Network Models for Long-sequence Generation of Wind Speed Forecasts. . https://doi.org/10.1049/icp.2022.2777
• Li, X., Dao, C. D., Kazemtabrizi, B., & Crabtree, C. J. (2020). Optimisation of Large Offshore Wind Farm Layout Considering Reliability and Wake Effect. . https://doi.org/10.1115/gt2020-15495
• Dao, C. D., Kazemtabrizi, B., & Crabtree, C. J. (2019). Impacts of Reliability on Operational Performance and Cost of Energy Evaluation of Multimegawatt, Far-offshore Wind Turbines. In Conference Proceedings: ASME 38th International Conference on Ocean, Offshore & Arctic Engineering (OMAE2019-95561, V003T02A072). https://doi.org/10.1115/omae2019-95561
• Thompson, A., Kazemtabrizi, B., Crabtree, C., Dao, C., Dinmohamdi, F., & Flynn, D. (2019). Reliability and Economic Evaluation of High Voltage Direct Current interconnectors for large-scale renewable energy integration and transmission. In 15th IET International Conference on AC and DC Power Transmission (ACDC 2019). https://doi.org/10.1049/cp.2019.0010
• Dao, C. D., Kazemtabrizi, B., & Crabtree, C. J. (2019). Modelling the Effects of Reliability and Maintenance on Levelised Cost of Wind Energy. . https://doi.org/10.1115/gt2019-90015
• Zappalá, D., Crabtree, C., & Hogg, S. (2018). Investigating wind turbine dynamic transient loads using contactless shaft torque measurements.
• Secker, M., Crabtree, C., & Zappalá, D. (2015). Wind Turbine Non-Intrusive Torque Monitoring. In S. Aubrun, S. Aubrun, & J. Mann (Eds.), European Wind Energy Association Annual Conference and Exhibition 2015, EWEA 2015 - Scientific Proceedings (126-130)
• Smith, C., Crabtree, C., & Matthews, P. (2015). Evaluation of Synthetic Wind Speed Time Series for Reliability Analysis of Offshore Wind Farms.
• Smith, C., Wadge, G., Crabtree, C., & Matthews, P. (2015). Characterisation of Electrical Loading Experienced by a Nacelle Power Converter.
• Smith, C., Crabtree, C., & Matthews, P. (2015). Experimental Set-up for Applying Wind Turbine Operating Profiles to the Nacelle Power Converter.
• Smith, C., Crabtree, C., Matthews, P., & Kazemtabrizi, B. (2014). Modelling and Evaluation of Wind Speed Time Series for Reliability Analysis of Offshore Wind Farms.
• Ahmad, T., Smith, C., Matthews, P., Crabtree, C., & Kazemtabrizi, B. (2014). Determining the Wind Speed Distribution within a Wind Farm considering Site Wind Characteristics and Wake Effects.
• Zappalá, D., Crabtree, C., Vilchis-Rodriguez, D., Tavner, P., Djurović, S., & Smith, A. (2014). Advanced Algorithms for Automatic Wind Turbine Generator Fault Detection and Diagnosis.
• Zappalá, D., Tavner, P., Crabtree, C., & Sheng, S. (2013). Sideband Algorithm for Automatic Wind Turbine Gearbox Fault Detection and Diagnosis.
• Crabtree, C. (2012). Operational and Reliability Analysis of Offshore Wind Farms.
• Vilchis-Rodriguez, D., Djurovic, S., Smith, A., & Crabtree, C. (2012). Wind Turbine Induction Generator Fault Frequency Tracking by Reference Frame Transformation.
• Zappalá, D., Tavner, P., & Crabtree, C. (2012). Gear Fault Detection Automation Using WindCon Frequency Tracking.
• Feng, Y., Qiu, Y., Crabtree, C., Long, H., & Tavner, P. (2011). Use of SCADA and CMS Signals for Failure Detection and Diagnosis of a Wind Turbine Gearbox.
• Crabtree, C., & Tavner, P. (2011). Condition Monitoring Algorithm Suited to Wind Turbine Use.
• Djurovic, S., Crabtree, C., Smith, A., & Tavner, P. (2011). Influence of DFIG Rotor Fault Severity on Stator Current and Power Spectral Content.
• Crabtree, C., Djurovic, S., Tavner, P., & Smith, A. (2010). Condition Monitoring of a Wind Turbine DFIG by Current or Power Analysis.
• Crabtree, C., Feng, Y., & Tavner, P. (2010). Detecting Incipient Gearbox Failure in Wind Turbines: A New Signal Analysis Method for Online Condition Monitoring.
• Crabtree, C., Djurovic, S., Tavner, P., & Smith, A. (2010). Fault Frequency Tracking During Transient Operation of Wind Turbine Generators.
• Large Scale Wind Turbines.
• Yang, W., Tavner, P., Crabtree, C., & Wilkinson, M. (2008). Research on a Simple, Cheap but Globally Effective Condition Monitoring Technique for Wind Turbines.
• Yang, W., Jiang, J., Tavner, P., & Crabtree, C. (2008). Monitoring Wind Turbine Condition by the Approach of Empirical Mode Decomposition.

Doctoral Thesis

• Crabtree, C. (2011). Condition Monitoring Techniques for Wind Turbines. (Thesis). School of Engineering and Computing Sciences, Durham University. Retrieved from https://durham-repository.worktribe.com/output/1618611

Edited book

• Hogg, S., & Crabtree, C. (Eds.). (2016). UK Wind Energy Technologies. Routledge

Journal Article

• Alsaadi, S., Crabtree, C. J., Matthews, P. C., & Shahbazi, M. (2024). Understanding wind turbine power converter reliability under realistic wind conditions. IET Power Electronics, https://doi.org/10.1049/pel2.12670
• Stone, E., Giani, S., Zappalá, D., & Crabtree, C. (2023). Convolutional neural network framework for wind turbine electromechanical fault detection. Wind Energy, https://doi.org/10.1002/we.2857
• Dao, C. D., Kazemtabrizi, B., Crabtree, C. J., & Tavner, P. J. (2021). Integrated condition-based maintenance modelling and optimisation for offshore wind farms. Wind Energy, 24(11), 1180-1198. https://doi.org/10.1002/we.2625
• Dao, C. D., Kazemtabrizi, B., & Crabtree, C. J. (2020). Offshore Wind Turbine Reliability and Operational Simulation under Uncertainties. Wind Energy, 23(10), 1919-1938. https://doi.org/10.1002/we.2526
• Brigham, K., Zappalá, D., Crabtree, C., & Donaghy-Spargo, C. (2020). Simplified Automatic Fault Detection in Wind Turbine Induction Generators. Wind Energy, 23(4), 1135-1144. https://doi.org/10.1002/we.2478
• Zhang, G., Zappalá, D., Crabtree, C., Donaghy-Spargo, C., Hogg, S., & Duffy, A. (2020). Validation of a non-contact technique for torque measurements in wind turbines using an enhanced transient FSV approach. Measurement, 151, Article 107261. https://doi.org/10.1016/j.measurement.2019.107261
• Dao, C. D., Kazemtabrizi, B., & Crabtree, C. J. (2019). Wind Turbine Reliability Data Review and Impacts on Levelised Cost of Energy. Wind Energy, 22(12), 1848-1871. https://doi.org/10.1002/we.2404
• Smith, C., Zappalá, D., Crabtree, C., Lapiedra, J., & Mulholland, B. (2019). Power Converter Junction Temperature Measurement using Infra-red Sensors. Journal of Engineering, 2019(17), 4452-4456. https://doi.org/10.1049/joe.2018.8098
• Meech, J., Crabtree, C., & Rácz, Z. (2019). Star Type Wireless Sensor Network for Future Distributed Structural Health Monitoring Applications. Inventions, 4(1), Article 6. https://doi.org/10.3390/inventions4010006
• Zappalá, D., Sarma, N., Djurović, S., Crabtree, C., Mohammad, A., & Tavner, P. (2019). Electrical & Mechanical Diagnostic Indicators of Wind Turbine Induction Generator Rotor Faults. Renewable Energy, 131, 14-24. https://doi.org/10.1016/j.renene.2018.06.098
• Ibrahim, R. K., Watson, S. J., Djurović, S., & Crabtree, C. J. (2018). An Effective Approach for Rotor Electrical Asymmetry Detection in Wind Turbine DFIGs. IEEE Transactions on Industrial Electronics, 65(11), 8872-8881. https://doi.org/10.1109/tie.2018.2811373
• Zappalá, D., Bezziccheri, M., Crabtree, C., & Paone, N. (2018). Non-intrusive torque measurement for rotating shafts using optical sensing of zebra-tapes. Measurement Science and Technology, 29(6), Article 065207. https://doi.org/10.1088/1361-6501/aab74a
• Smith, C., Crabtree, C., & Matthews, P. (2017). Impact of wind conditions on thermal loading of PMSG wind turbine power converters. IET Power Electronics, 10(11), 1268-1278. https://doi.org/10.1049/iet-pel.2016.0802
• Rieg, C., Smith, C., & Crabtree, C. (2016). Monitoring Wind Turbine Loading Using Power Converter Signals. Journal of Physics: Conference Series, 749(1), Article 012018. https://doi.org/10.1088/1742-6596/749/1/012018
• Crabtree, C., Zappalá, D., & Hogg, S. (2015). Wind Energy: UK Experiences and Offshore Operational Challenges. Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy, 229(7), 727-746. https://doi.org/10.1177/0957650915597560
• Zaggout, M., Tavner, P., Crabtree, C., & Ran, L. (2014). Detection of Rotor Electrical Asymmetry in Wind Turbine Doubly-Fed Induction Generators. IET Renewable Power Generation, 8(8), 878-886. https://doi.org/10.1049/iet-rpg.2013.0324
• Yang, W., Tavner, P. J., Crabtree, C. J., Feng, Y., & Qiu, Y. (2014). Wind turbine condition monitoring : technical and commercial challenges. Wind Energy, 17(5), 673-693. https://doi.org/10.1002/we.1508
• Zappalá, D., Tavner, P., Crabtree, C., & Sheng, S. (2014). Side-band algorithm for automatic wind turbine gearbox fault detection and diagnosis. IET Renewable Power Generation, 8(4), 380-389. https://doi.org/10.1049/iet-rpg.2013.0177
• Djurovic, S., Crabtree, C., Tavner, P., & Smith, A. (2012). Condition Monitoring of Wind Turbine Induction Generators with Rotor Electrical Asymmetry. IET Renewable Power Generation, 6(4), 207-216. https://doi.org/10.1049/iet-rpg.2011.0168
• Feng, Y., Qiu, Y., Crabtree, C., Long, H., & Tavner, P. (2012). Monitoring wind turbine gearboxes. Wind Energy, 16(5), 728-740. https://doi.org/10.1002/we.1521
• Yang, W., Court, R., Tavner, P., & Crabtree, C. (2011). Bivariate Empirical Mode Decomposition and its Contribution to Wind Turbine Condition Monitoring. Journal of Sound and Vibration, 330(15), 3766-3782. https://doi.org/10.1016/j.jsv.2011.02.027
• Watson, S., Xiang, J., Yang, W., Tavner, P., & Crabtree, C. (2010). Condition monitoring of the power output of wind turbine generators using wavelets. IEEE Transactions on Energy Conversion, 25(3), 715-721. https://doi.org/10.1109/tec.2010.2040083
• Yang, W., Tavner, P., Crabtree, C., & Wilkinson, M. (2010). Cost-effective condition monitoring for wind turbines. IEEE Transactions on Industrial Electronics, 57(1), 263-271. https://doi.org/10.1109/tie.2009.2032202

Other (Print)

• Feng, Y., Qiu, Y., Crabtree, C., & Tavner, P. (2011). Predicting gearbox failures in wind turbines

Presentation

• Smith, C., Zappalá, D., Crabtree, C., Lapiedra, J., & Mulholland, B. (2018, April). Power Converter Junction Temperature Measurement using Infra-red Sensor. Paper presented at International Conference on Power Electronics, Machines and Drives, Liverpool, UK
• Brigham, K., Zappalá, D., Crabtree, C., & Donaghy-Spargo, C. (2018, April). Automated Fault Detection in Wind Turbine Induction Generators with Rotor Electrical Asymmetry. Paper presented at International Conference on Power Electronics, Machines and Drives, Liverpool, UK
• Zappalá, D., Crabtree, C., Smith, C., Lapiedra, J., & Mulholland, B. (2017, September). Converter Reliability in Wind Turbines today – Onshore & Offshore. Paper presented at HUSUM Wind 2017, Husum, Germany

Report

• Zappalá, D., Crabtree, C., & Hogg, S. (2018). Directory of UK Based Test and Demonstration Facilities for Wind Technologies. [No known commissioning body]
• Chen, B., Zappalá, D., Crabtree, C., & Tavner, P. (2014). Survey of Commercially Available SCADA Data Analysis Tools for Wind Turbine Health Monitoring. [No known commissioning body]
• Crabtree, C., Zappalá, D., & Tavner, P. (2014). Survey of commercially available condition monitoring systems for wind turbines. UK EPSRC SUPERGEN Wind Energy Technologies programme