Staff profile

Prof. Christopher Crabtree is the Director of Education and 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.

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

• EPSRC HOME Offshore Archive
• EPSRC New Partnership in Offshore Wind

• 2019: Solid State Transformers for Offshore Wind Turbines(£25803.45 from Engineering and Physical Sciences Research Council)
• 2017: A New Partnership in Offshore Wind(£767499.35 from Engineering and Physical Sciences Research Council)
• 2017: Holistic Operation and Maintenance for Energy from Offshore Wind Farms(£311164.00 from )
• 2017: Novel Data Integration Techniques for Enhanced Wind Turbine Conditioning Monitor(£94743.00 from Engineering and Physical Sciences Research Council)
• 2016: IAA-DEMONSTRATION RELIABILITY TEST FACILITY FOR WIND TURBINE POWER ELECTRONICS(£33676.05 from Epsrc)
• 2014: EPSRC Supergen Wind Hub(£224262.00 from Epsrc)
• 2014: IAA - WIND TURBINE OIL CONDITION MONITORING(£4434.28 from Epsrc)
• 2014: IAA: SUPERGEN WIND ENERGY TECHNOLOGIES(£20188.01 from Epsrc)

Authored book

• Tavner, Peter J, Ran, Li & Crabtree, Christopher J (2020). Condition Monitoring of Rotating Electrical Machines. The Institution of Engineering and Technology.

Chapter in book

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

Conference Paper

• Pina-Gongora, Diana C, Kazemtabrizi, B & Crabtree, Christopher (2022), Performance comparison of Probabilistic and Artificial Neural Network Models for Long-sequence Generation of Wind Speed Forecasts, 21st Wind and Solar Integration Workshop. The Hague, Netherlands, IET.
• Li, Xiangyu, Dao, Cuong D., Kazemtabrizi, B. & Crabtree, Christopher J. (2020), Optimisation of Large Offshore Wind Farm Layout Considering Reliability and Wake Effect, 12: ASME Turbo Expo 2020. London, ASME (American Society of Mechanical Engineers).
• Dao, Cuong D., Kazemtabrizi, Behzad & Crabtree, Christopher J. (2019), Impacts of Reliability on Operational Performance and Cost of Energy Evaluation of Multimegawatt, Far-offshore Wind Turbines, Volume 3: Structures, Safety, and Reliability: ASME 38th International Conference on Ocean, Offshore & Arctic Engineering (OMAE) 2019. Glasgow, UK, American Society of Mechanical Engineers.
• Dao, Cuong D., Kazemtabrizi, Behzad & Crabtree, Christopher J. (2019), Modelling the Effects of Reliability and Maintenance on Levelised Cost of Wind Energy, ASME Turbo Expo 2019. Phoenix, AZ, USA.
• Thompson, A., Kazemtabrizi, B., Crabtree, C. J., 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, 15th IET International conference on AC and DC Power Transmission. Coventry, UK, IET.
• Zappalá, D., Crabtree, C.J. & Hogg, S. (2018), Investigating wind turbine dynamic transient loads using contactless shaft torque measurements, IET Renewable Power Generation Conference 2018. Technical University of Denmark (DTU), Copenhagen, Denmark.
• Brigham, K., Zappalá, D., Crabtree, C.J. & Donaghy-Spargo, C. (2018), Automated Fault Detection in Wind Turbine Induction Generators with Rotor Electrical Asymmetry, International Conference on Power Electronics, Machines and Drives. Liverpool, UK.
• Smith, C.J., Zappalá, D., Crabtree,C.J., Lapiedra, J. & Mulholland, B. (2018), Power Converter Junction Temperature Measurement using Infra-red Sensor, International Conference on Power Electronics, Machines and Drives. Liverpool, UK.
• Zappalá, D., Crabtree, C.J., Smith, C.J., Lapiedra, J. & Mulholland, B. (2017), Converter Reliability in Wind Turbines today – Onshore & Offshore, HUSUM Wind 2017. Husum, Germany.
• Smith, C.J., Crabtree, C.J. & Matthews, P.C. (2015), Evaluation of Synthetic Wind Speed Time Series for Reliability Analysis of Offshore Wind Farms, European Wind Energy Association 2015. Paris, France, European Wind Energy Association, Paris.
• Smith, C.J., Wadge, G.N., Crabtree, C.J. & Matthews, P.C. (2015), Characterisation of Electrical Loading Experienced by a Nacelle Power Converter, European Wind Energy Association 2015. Paris, France, European Wind Energy Association, Paris.
• Smith, C.J., Crabtree, C.J. & Matthews, P.C. (2015), Experimental Set-up for Applying Wind Turbine Operating Profiles to the Nacelle Power Converter, 11th EAWE PhD Seminar. Stuttgart, Germany, EAWE.
• Secker, M., Crabtree, C.J. & Zappalá, D. (2015), Wind Turbine Non-Intrusive Torque Monitoring, European Wind Energy Conference, Scientific Track. Paris, France, European Wind Energy Association.
• Smith, C.J., Crabtree, C.J., Matthews, P.C. & Kazemtabrizi, B. (2014), Modelling and Evaluation of Wind Speed Time Series for Reliability Analysis of Offshore Wind Farms, 10th PhD Seminar on Wind Energy in Europe, EAWE. Orléans, France, EAWE, Orléans, 159-162.
• Zappalá, D., Crabtree, C.J., Vilchis-Rodriguez, D.S., Tavner, P.J., Djurović, S. & Smith, A.C. (2014), Advanced Algorithms for Automatic Wind Turbine Generator Fault Detection and Diagnosis, European Wind Energy Conference, Scientific Track. Barcelona, Spain, European Wind Energy Association.
• Ahmad, T., Smith, C.J., Matthews, P.C., Crabtree, C.J. & Kazemtabrizi, B. (2014), Determining the Wind Speed Distribution within a Wind Farm considering Site Wind Characteristics and Wake Effects, 10th PhD Seminar on Wind Energy in Europe, EAWE. Orléans, France, EAWE, 131-134.
• Zappalá, D., Tavner, P.J., Crabtree, C.J. & Sheng, S. (2013), Sideband Algorithm for Automatic Wind Turbine Gearbox Fault Detection and Diagnosis, European Wind Energy Conference, Scientific Track. Vienna, Austria, European Wind Energy Association.
• Vilchis-Rodriguez, D., Djurovic, S., Smith, A. C. & Crabtree, C. J. (2012), Wind Turbine Induction Generator Fault Frequency Tracking by Reference Frame Transformation, 6th IET International Conference on Power Electronics, Machines and Drives. Bristol, Bristol.
• Zappalá, D., Tavner, P.J. & Crabtree, C.J. (2012), Gear Fault Detection Automation Using WindCon Frequency Tracking, European Wind Energy Conference, Scientific Track. Copenhagen, Denmark, European Wind Energy Association.
• Crabtree, C. J. (2012), Operational and Reliability Analysis of Offshore Wind Farms, European Wind Energy Association Annual Event. Copenhagen, Copenhagen.
• Crabtree, C.J. & Tavner, P.J. (2011), Condition Monitoring Algorithm Suited to Wind Turbine Use, IET Renewable Power Generation. Edinburgh, UK, Edinburgh.
• Djurovic, S., Crabtree, C.J., Smith, A.C. & Tavner, P.J. (2011), Influence of DFIG Rotor Fault Severity on Stator Current and Power Spectral Content, European Wind Energy Association. Brussels, Belgium, Brussels, 300-303.
• Feng, Y., Qiu, Y., Crabtree, C.J., Long, H. & Tavner, P.J. (2011), Use of SCADA and CMS Signals for Failure Detection and Diagnosis of a Wind Turbine Gearbox, European Wind Energy Association. Brussels, Belgium, Brussels, 17-19.
• Crabtree, C.J., Feng, Y. & Tavner, P.J. (2010), Detecting Incipient Gearbox Failure in Wind Turbines: A New Signal Analysis Method for Online Condition Monitoring, European Wind Energy Conference. Warsaw, Poland, Warsaw.
• Crabtree, C.J., Djurovic, S., Tavner, P.J. & Smith, A.C. (2010), Fault Frequency Tracking During Transient Operation of Wind Turbine Generators, 19th International Conference on Electrical Machines (ICEM). Rome, Italy, Rome.
• Crabtree, C.J., Djurovic, S., Tavner, P.J. & Smith, A.C. (2010), Condition Monitoring of a Wind Turbine DFIG by Current or Power Analysis, 5th IET International Conference on Power Electronics, Machines and Drives. Brighton, UK, Brighton.
• Yang, W, Tavner, P. J. & Crabtree, C. J. (2009), An Intelligent Approach to the Condition Monitoring of Large Scale Wind Turbines, European Wind Energy Conference, Scientific Track. Marseille, France, European Wind Energy Association, Marseille.
• Yang, W., Jiang, J., Tavner, P.J. & Crabtree, C.J. (2008), Monitoring Wind Turbine Condition by the Approach of Empirical Mode Decomposition, International Conference on Electrical Machines and Systems. 736-740.
• Yang, W., Tavner, P. J., Crabtree, C. J. & Wilkinson, M. (2008), Research on a Simple, Cheap but Globally Effective Condition Monitoring Technique for Wind Turbines, International Conference on Electrical Machines.

Doctoral Thesis

• Crabtree, C.J. (2011). Condition Monitoring Techniques for Wind Turbines. School of Engineering and Computing Sciences. Durham University. PhD.

Edited book

• Hogg, Simon & Crabtree, Christopher (2016). UK Wind Energy Technologies. Routledge.

Journal Article

• Dao, Cuong D., Kazemtabrizi, Behzad, Crabtree, Christopher J. & Tavner, Peter J. (2021). Integrated condition-based maintenance modelling and optimisation for offshore wind farms. Wind Energy 24(11): 1180-1198.
• Dao, Cuong D., Kazemtabrizi, Behzad & Crabtree, Christopher J. (2020). Offshore Wind Turbine Reliability and Operational Simulation under Uncertainties. Wind Energy 23(10): 1919-1938.
• Brigham, K., Zappalá, D., Crabtree, C.J. & Donaghy-Spargo, C. (2020). Simplified Automatic Fault Detection in Wind Turbine Induction Generators. Wind Energy 23(4): 1135-1144.
• 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: 107261.
• Dao, Cuong D., Kazemtabrizi, Behzad & Crabtree, Christopher J. (2019). Wind Turbine Reliability Data Review and Impacts on Levelised Cost of Energy. Wind Energy 22(12): 1848-1871.
• Meech, James, Crabtree, Christopher & Rácz, Zoltán (2019). Star Type Wireless Sensor Network for Future Distributed Structural Health Monitoring Applications. Inventions 4(1): 6.
• Smith, C.J., Zappalá, D., Crabtree, C.J., Lapiedra, J. & Mulholland, B. (2019). Power Converter Junction Temperature Measurement using Infra-red Sensors. The Journal of Engineering 2019(17): 4452-4456.
• Zappalá, D., Sarma, N., Djurović, S., Crabtree, C. J., Mohammad, A. & Tavner, P. J. (2019). Electrical & Mechanical Diagnostic Indicators of Wind Turbine Induction Generator Rotor Faults. Renewable Energy 131: 14-24.
• Zappalá, D., Bezziccheri, M., Crabtree, C.J. & Paone, N. (2018). Non-intrusive torque measurement for rotating shafts using optical sensing of zebra-tapes. Measurement Science and Technology 29(6): 065207.
• Ibrahim, Raed K., Watson, Simon J., Djurović, Siniša & Crabtree, Christopher J. (2018). An Effective Approach for Rotor Electrical Asymmetry Detection in Wind Turbine DFIGs. IEEE Transactions on Industrial Electronics 65(11): 8872-8881.
• Smith, C.J., Crabtree, C.J. & Matthews, P.C. (2017). Impact of wind conditions on thermal loading of PMSG wind turbine power converters. IET Power Electronics Special Issue: Power Electronics Converters for Marine Renewable Energy Applications 10(11): 1268-1278.
• Rieg, C. A., Smith, C. J. & Crabtree, C. J. (2016). Monitoring Wind Turbine Loading Using Power Converter Signals. Journal of Physics: Conference Series (JPCS) 749(1): 012018.
• Crabtree, C. J., Zappalá, D. & Hogg, S. I. (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.
• Zaggout, M. N., Tavner, P. J., Crabtree, C. J. & Ran, L. (2014). Detection of Rotor Electrical Asymmetry in Wind Turbine Doubly-Fed Induction Generators. IET Renewable Power Generation 8(8): 878-886.
• Zappalá, D., Tavner, P.J. Crabtree, C.J. & Sheng, S. (2014). Side-band algorithm for automatic wind turbine gearbox fault detection and diagnosis. IET Renewable Power Generation 8(4): 380-389.
• 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.
• Feng, Y., Qiu, Y., Crabtree, C. J., Long, H. & Tavner, P. J. (2012). Monitoring wind turbine gearboxes. Wind Energy 16(5): 728-740.
• Djurovic, S., Crabtree, C. J., Tavner, P. J. & Smith, A. C (2012). Condition Monitoring of Wind Turbine Induction Generators with Rotor Electrical Asymmetry. IET Renewable Power Generation 6(4): 207-216.
• Yang, W., Court, R., Tavner, P.J. & Crabtree, C.J. (2011). Bivariate Empirical Mode Decomposition and its Contribution to Wind Turbine Condition Monitoring. Journal of Sound and Vibration 330(15): 3766-3782.
• Yang, W., Tavner, P. J., Crabtree, C. J. & Wilkinson, M. (2010). Cost-effective condition monitoring for wind turbines. IEEE Transactions on Industrial Electronics 57(1): 263-271.
• Watson, S. J. Xiang, J. P., Yang, W. Tavner, P. J. & Crabtree, C. J. (2010). Condition monitoring of the power output of wind turbine generators using wavelets. IEEE Transactions on Energy Conversion 25(3): 715-721.

Newspaper/Magazine Article

• Feng, Y., Qiu, Y., Crabtree, C.J. & Tavner, P.J. (2011). Predicting gearbox failures in wind turbines. Modern Energy Review 3(2): 62-66.

Report

• Zappalá, D., Crabtree, C.J. & Hogg, S. (2018). Directory of UK Based Test and Demonstration Facilities for Wind Technologies. Department of Engineering. Durham, Durham University.
• Chen, B., Zappalá, D., Crabtree, C.J. & Tavner, P.J. (2014). Survey of Commercially Available SCADA Data Analysis Tools for Wind Turbine Health Monitoring. School of Engineering and Computing Sciences. Durham University School of Engineering and Computing Sciences.
• Crabtree, C.J., Zappalá, D. & Tavner, P.J. (2014). Survey of commercially available condition monitoring systems for wind turbines. School of Engineering and Computing Sciences. Durham University School of Engineering and Computing Sciences and the SUPERGEN Wind Energy Technologies Consortium.