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Dr Xiandong Ma

Senior Lecturer

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  1. 2016
  2. Published

    A condition monitoring system for an early warning of developing faults in wind turbine electrical systems

    Ma, X., Cross, P. & Qian, P., 1/12/2016, In: Insight – Non-Destructive Testing and Condition Monitoring. 58, 12, p. 663-670 8 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  3. Published

    Reducing sensor complexity for monitoring wind turbine performance using principal component analysis

    Wang, Y., Ma, X. & Joyce, M. J., 11/2016, In: Renewable Energy. 97, p. 444–456 13 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  4. Published

    Fault diagnosis in multi-machine power systems using the Derivative-free nonlinear Kalman Filter

    Rigatos, G., Siano, P., Wira, P. & Ma, X., 13/06/2016, Environmental, Energy, and Structural Monitoring Systems (EESMS), 2016 IEEE Workshop on. IEEE, 6 p.

    Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

  5. Published

    Simultaneous fault detection and sensor selection for condition monitoring of wind turbines

    Zhang, W. & Ma, X., 12/04/2016, In: Energies. 9, 4, 15 p., 280.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  6. 2015
  7. Published

    New software aims to improve fuel efficiency

    Ma, X. & Briddon, M., 25/09/2015, SAFETY4SEA.

    Research output: Contribution to specialist publication › Featured article

  8. Published

    New software aims to improve fuel efficiency, reduce unnecessary maintenance

    Ma, X. & Briddon, M., 25/09/2015, Ship & Bunker - The World's Most Read Publication for the Marine Fuels Industry.

    Research output: Contribution to specialist publication › Featured article

  9. Published

    University collaboration improves Mimic condition monitoring

    Ma, X. & Briddon, M., 23/09/2015, The Motorship Magazine - insight for marine technology professionals.

    Research output: Contribution to specialist publication › Featured article

  10. Published

    Condition monitoring of wind turbines based on extreme learning machine

    Qian, P., Ma, X. & Wang, Y., 12/09/2015, ICAC2015: Proceedings of the 21st International Conference on Automation and Computing. IEEE, p. 37-42 6 p.

    Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

  11. Published

    Fault ride-through analysis and protection of a 2-MW DFIG tidal current turbine

    Zhang, D., Chen, Y., Yang, J., Tan, M., Ma, X. & Li, W., 1/09/2015, In: Marine Technology Society Journal . 49, 5, p. 49-57 9 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  12. Published

    Model-based and fuzzy logic approaches to condition monitoring of operational wind turbines

    Cross, P. & Ma, X., 02/2015, In: International Journal of Automation and Computing. 12, 1, p. 25-34 10 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

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