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Results for Fault detection

Publications & Outputs

  1. 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 article

  2. Fully unsupervised fault detection and identification based on recursive density estimation and self-evolving cloud-based classifier

    Costa, B. S. J., Angelov, P. & Guedes, L. A. 20/02/2015 In : Neurocomputing. 150, A, p. 289-303 15 p.

    Research output: Contribution to journalJournal article

  3. RDE with forgetting: an approximate solution for large values of k with an application to fault detection problems

    Bezerra, C. G., Costa, B., Guedes, L. A. & Angelov, P. 2015 Statistical learning and data sciences: Third International Symposium, SLDS 2015, Egham, UK, April 20-23, 2015, Proceedings. Gammerman, A., Vovk, V. & Papadopoulos, H. (eds.). Springer, p. 169-178 10 p. (Lecture Notes in Computer Science; vol. 9047)

    Research output: Contribution in Book/Report/ProceedingsPaper

  4. 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 article

  5. Real-time fault detection using recursive density estimation

    Costa, B. S. J., Angelov, P. & Guedes, L. A. 08/2014 In : Journal of Control, Automation and Electrical Systems. 25, 4, p. 428-437 10 p.

    Research output: Contribution to journalJournal article

  6. Acoustic emission for monitoring aircraft structures

    Holford, K. M., Pullin, R., Evans, S. L., Eaton, M. J., Hensman, J. & Worden, K. 05/2009 In : Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering. 223, 5, p. 525-532 8 p.

    Research output: Contribution to journalJournal article