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Results for Wind turbine

Publications & Outputs

  1. A Nonlinear Wind Turbine Wake Expansion Model Considering Atmospheric Stability and Ground Effects

    Han, X., Wang, T., Ma, X., Xu, C., Fu, S., Zhang, J., Xue, F. & Cheng, Z., 8/09/2024, In: Energies. 17, 24 p., 4503.

    Research output: Contribution to Journal/MagazineJournal articlepeer-review

  2. Condition monitoring of wind turbine using novel deep learning method and dynamic kernel principal components Mahalanobis distance

    Chen, W., Zhou, H., Cheng, L., Liu, J. & Xia, M., 31/10/2023, In: Engineering Applications of Artificial Intelligence. 125, 106757.

    Research output: Contribution to Journal/MagazineJournal articlepeer-review

  3. Investigations on offshore wind turbine inflow modelling using numerical weather prediction coupled with local-scale computational fluid dynamics

    Castorrini, A., Gentile, S., Geraldi, E. & Bonfiglioli, A., 31/01/2023, In: Renewable and Sustainable Energy Reviews. 171, 113008.

    Research output: Contribution to Journal/MagazineJournal articlepeer-review

  4. Condition monitoring of wind turbines based on spatial-temporal feature aggregation networks

    Zhan, J., Wu, C., Yang, C., Miao, Q., Wang, S. & Ma, X., 1/11/2022, In: Renewable Energy. 200, p. 751-766 16 p.

    Research output: Contribution to Journal/MagazineJournal articlepeer-review

  5. Abnormal vibration detection of wind turbine based on temporal convolution network and multivariate coefficient of variation

    Zhan, J., Wu, C., Ma, X., Yang, C., Miao, Q. & Wang, S., 15/07/2022, In: Mechanical Systems and Signal Processing. 174, 15 p., 109082.

    Research output: Contribution to Journal/MagazineJournal articlepeer-review

  6. A hybrid LSTM-KLD approach to condition monitoring of operational wind turbines

    Wu, Y. & Ma, X., 31/01/2022, In: Renewable Energy. 181, p. 554-566 13 p.

    Research output: Contribution to Journal/MagazineJournal articlepeer-review

  7. Kullback-Leibler divergence based wind turbine fault feature extraction

    Wu, Y. & Ma, X., 1/07/2019, 24th International Conference on Automation & Computing. IEEE, p. 507-512 6 p.

    Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

  8. 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/MagazineJournal articlepeer-review

  9. Nonlinear system identification for model-based condition monitoring of wind turbines

    Cross, P. & Ma, X., 11/2014, In: Renewable Energy. 71, p. 166-175 10 p.

    Research output: Contribution to Journal/MagazineJournal articlepeer-review

  10. Improved control of individual blade pitch for wind turbines

    Zhang, D., Cross, P., Ma, X. & Li, W., 15/08/2013, In: Sensors and Actuators A: Physical. 198, p. 8-14 7 p.

    Research output: Contribution to Journal/MagazineJournal articlepeer-review