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Novel early warning fault detection for wind-turbine-based DG systems

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

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Novel early warning fault detection for wind-turbine-based DG systems. / Ma, Xiandong.
Proceedings of 2011 2nd IEEE PES International Conference and Exhibition on Innovative Smart Grid Technologies (ISGT Europe): 5-7 Dec. 2011, Manchester, UK. IEEE, 2012. p. 1-6.

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

Harvard

Ma, X 2012, Novel early warning fault detection for wind-turbine-based DG systems. in Proceedings of 2011 2nd IEEE PES International Conference and Exhibition on Innovative Smart Grid Technologies (ISGT Europe): 5-7 Dec. 2011, Manchester, UK. IEEE, pp. 1-6. https://doi.org/10.1109/ISGTEurope.2011.6162772

APA

Ma, X. (2012). Novel early warning fault detection for wind-turbine-based DG systems. In Proceedings of 2011 2nd IEEE PES International Conference and Exhibition on Innovative Smart Grid Technologies (ISGT Europe): 5-7 Dec. 2011, Manchester, UK (pp. 1-6). IEEE. https://doi.org/10.1109/ISGTEurope.2011.6162772

Vancouver

Ma X. Novel early warning fault detection for wind-turbine-based DG systems. In Proceedings of 2011 2nd IEEE PES International Conference and Exhibition on Innovative Smart Grid Technologies (ISGT Europe): 5-7 Dec. 2011, Manchester, UK. IEEE. 2012. p. 1-6 doi: 10.1109/ISGTEurope.2011.6162772

Author

Ma, Xiandong. / Novel early warning fault detection for wind-turbine-based DG systems. Proceedings of 2011 2nd IEEE PES International Conference and Exhibition on Innovative Smart Grid Technologies (ISGT Europe): 5-7 Dec. 2011, Manchester, UK. IEEE, 2012. pp. 1-6

Bibtex

@inproceedings{ba958d0d2815469587d7f2ea1a3f055b,
title = "Novel early warning fault detection for wind-turbine-based DG systems",
abstract = "This paper will study condition monitoring signals of a distributed generation (DG) system not only due to the mechanical and electrical faults inside the wind turbines but also due to the grid system fluctuations. A novel feature extraction and characterisation method based on singularity detection of the monitoring data will be presented, aiming to identify the abnormal events and fault conditions as early as possible. The algorithm used to calculate Lipschitz values is given in the paper and efficient processing and storage of monitoring data is also discussed. The preliminary research has produced promising results.",
keywords = "Condition monitoring, distributed generation , wind turbine , Lipschitz exponent , feature extraction , data mining and fusion",
author = "Xiandong Ma",
year = "2012",
month = mar,
day = "5",
doi = "10.1109/ISGTEurope.2011.6162772",
language = "English",
isbn = "978-1-4577-1422-1",
pages = "1--6",
booktitle = "Proceedings of 2011 2nd IEEE PES International Conference and Exhibition on Innovative Smart Grid Technologies (ISGT Europe)",
publisher = "IEEE",

}

RIS

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T1 - Novel early warning fault detection for wind-turbine-based DG systems

AU - Ma, Xiandong

PY - 2012/3/5

Y1 - 2012/3/5

N2 - This paper will study condition monitoring signals of a distributed generation (DG) system not only due to the mechanical and electrical faults inside the wind turbines but also due to the grid system fluctuations. A novel feature extraction and characterisation method based on singularity detection of the monitoring data will be presented, aiming to identify the abnormal events and fault conditions as early as possible. The algorithm used to calculate Lipschitz values is given in the paper and efficient processing and storage of monitoring data is also discussed. The preliminary research has produced promising results.

AB - This paper will study condition monitoring signals of a distributed generation (DG) system not only due to the mechanical and electrical faults inside the wind turbines but also due to the grid system fluctuations. A novel feature extraction and characterisation method based on singularity detection of the monitoring data will be presented, aiming to identify the abnormal events and fault conditions as early as possible. The algorithm used to calculate Lipschitz values is given in the paper and efficient processing and storage of monitoring data is also discussed. The preliminary research has produced promising results.

KW - Condition monitoring

KW - distributed generation

KW - wind turbine

KW - Lipschitz exponent

KW - feature extraction

KW - data mining and fusion

U2 - 10.1109/ISGTEurope.2011.6162772

DO - 10.1109/ISGTEurope.2011.6162772

M3 - Conference contribution/Paper

SN - 978-1-4577-1422-1

SP - 1

EP - 6

BT - Proceedings of 2011 2nd IEEE PES International Conference and Exhibition on Innovative Smart Grid Technologies (ISGT Europe)

PB - IEEE

ER -