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Results for Condition monitoring

Publications & Outputs

  1. Efficient Data Reduction at the Edge of Industrial Internet of Things for PMSM Bearing Fault Diagnosis

    Wang, X., Lu, S., Huang, W., Wanga, Q., Zhang, S. & Xia, M., 1/03/2021, In: IEEE Transactions on Instrumentation and Measurement. 70, 12 p., 3508612.

    Research output: Contribution to journalJournal articlepeer-review

  2. Enhanced feature extraction method for motor fault diagnosis using low-quality vibration data from wireless sensor networks

    Shu, Q., Lu, S., Xia, M., Ding, J., Niu, J. & Liu, Y., 15/01/2020, In: Measurement Science and Technology. 31, 4, 17 p., 045016.

    Research output: Contribution to journalJournal articlepeer-review

  3. Data-driven condition monitoring approaches to improving power output of wind turbines

    Qian, P., Ma, X., Zhang, D. & Wang, J., 1/08/2019, In: IEEE Transactions on Industrial Electronics. 66, 8, p. 6012 - 6020 9 p.

    Research output: Contribution to journalJournal articlepeer-review

  4. 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

  5. Wind turbine fault detection and identification through PCA-based optimal variable selection

    Wang, Y., Ma, X. & Qian, P., 10/2018, In: IEEE Transactions on Sustainable Energy. 9, 4, p. 1627-1635 9 p.

    Research output: Contribution to journalJournal articlepeer-review

  6. 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 journalJournal articlepeer-review

  7. 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 journalJournal articlepeer-review

  8. 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/ISSNConference contribution/Paperpeer-review

  9. 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 journalJournal articlepeer-review

  10. 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 journalJournal articlepeer-review

  11. A novel condition monitoring and real-time simulation system for wind turbines

    Ma, X. & Cross, P., 4/02/2013, Proceedings of EWEA 2013 - European Wind Energy Conference & Exhibition. Vienna: EWEA, 9 p.

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

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