Fault Detection and Isolation for Wind Turbine Electric Pitch System

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

1 Citation (Scopus)

Resumé

This paper presents a model-based fault detection and isolation scheme applied on electric pitch system of wind turbines. Pitch system is one of the most critical components due to its effect on the operational safety and the dynamics of wind turbines. Faults in this system should be precisely detected to prevent failures and decrease downtime. To detect faults of electric pitch actuators and sensors, an extended kalman filter (EKF) based multiple model adaptive estimation (MMAE) designed to estimate the states of the system. The proposed method is demonstrated in case studies. The simulation results show that the proposed method detects different fault scenarios of wind turbines under the stochastic external condition.
OriginalsprogEngelsk
TitelProceedings of 2017 IEEE 12th International Conference on Power Electronics and Drive Systems (PEDS)
Antal sider6
ForlagIEEE Press
Publikationsdatodec. 2017
Sider618-623
ISBN (Elektronisk)978-1-5090-2364-6
DOI
StatusUdgivet - dec. 2017
Begivenhed2017 IEEE 12th International Conference on Power Electronics and Drive Systems (PEDS) - Honolulu, USA
Varighed: 12 dec. 201715 dec. 2017

Konference

Konference2017 IEEE 12th International Conference on Power Electronics and Drive Systems (PEDS)
LandUSA
ByHonolulu
Periode12/12/201715/12/2017
NavnIEEE International Conference on Power Electronics and Drive Systems
ISSN2164-5264

Fingerprint

Fault detection
Wind turbines
Electric actuators
Extended Kalman filters
Sensors

Citer dette

Zhu, J., Ma, K., Hajizadeh, A., N. Soltani, M., & Chen, Z. (2017). Fault Detection and Isolation for Wind Turbine Electric Pitch System. I Proceedings of 2017 IEEE 12th International Conference on Power Electronics and Drive Systems (PEDS) (s. 618-623). IEEE Press. IEEE International Conference on Power Electronics and Drive Systems https://doi.org/10.1109/PEDS.2017.8289226
Zhu, Jiangsheng ; Ma, Kuichao ; Hajizadeh, Amin ; N. Soltani, Mohsen ; Chen, Zhe. / Fault Detection and Isolation for Wind Turbine Electric Pitch System. Proceedings of 2017 IEEE 12th International Conference on Power Electronics and Drive Systems (PEDS). IEEE Press, 2017. s. 618-623 (IEEE International Conference on Power Electronics and Drive Systems).
@inproceedings{404562f0a0034bd9afe36e111cf55af2,
title = "Fault Detection and Isolation for Wind Turbine Electric Pitch System",
abstract = "This paper presents a model-based fault detection and isolation scheme applied on electric pitch system of wind turbines. Pitch system is one of the most critical components due to its effect on the operational safety and the dynamics of wind turbines. Faults in this system should be precisely detected to prevent failures and decrease downtime. To detect faults of electric pitch actuators and sensors, an extended kalman filter (EKF) based multiple model adaptive estimation (MMAE) designed to estimate the states of the system. The proposed method is demonstrated in case studies. The simulation results show that the proposed method detects different fault scenarios of wind turbines under the stochastic external condition.",
author = "Jiangsheng Zhu and Kuichao Ma and Amin Hajizadeh and {N. Soltani}, Mohsen and Zhe Chen",
year = "2017",
month = "12",
doi = "10.1109/PEDS.2017.8289226",
language = "English",
pages = "618--623",
booktitle = "Proceedings of 2017 IEEE 12th International Conference on Power Electronics and Drive Systems (PEDS)",
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}

Zhu, J, Ma, K, Hajizadeh, A, N. Soltani, M & Chen, Z 2017, Fault Detection and Isolation for Wind Turbine Electric Pitch System. i Proceedings of 2017 IEEE 12th International Conference on Power Electronics and Drive Systems (PEDS). IEEE Press, IEEE International Conference on Power Electronics and Drive Systems, s. 618-623, Honolulu, USA, 12/12/2017. https://doi.org/10.1109/PEDS.2017.8289226

Fault Detection and Isolation for Wind Turbine Electric Pitch System. / Zhu, Jiangsheng; Ma, Kuichao; Hajizadeh, Amin; N. Soltani, Mohsen; Chen, Zhe.

Proceedings of 2017 IEEE 12th International Conference on Power Electronics and Drive Systems (PEDS). IEEE Press, 2017. s. 618-623 (IEEE International Conference on Power Electronics and Drive Systems).

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

TY - GEN

T1 - Fault Detection and Isolation for Wind Turbine Electric Pitch System

AU - Zhu, Jiangsheng

AU - Ma, Kuichao

AU - Hajizadeh, Amin

AU - N. Soltani, Mohsen

AU - Chen, Zhe

PY - 2017/12

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N2 - This paper presents a model-based fault detection and isolation scheme applied on electric pitch system of wind turbines. Pitch system is one of the most critical components due to its effect on the operational safety and the dynamics of wind turbines. Faults in this system should be precisely detected to prevent failures and decrease downtime. To detect faults of electric pitch actuators and sensors, an extended kalman filter (EKF) based multiple model adaptive estimation (MMAE) designed to estimate the states of the system. The proposed method is demonstrated in case studies. The simulation results show that the proposed method detects different fault scenarios of wind turbines under the stochastic external condition.

AB - This paper presents a model-based fault detection and isolation scheme applied on electric pitch system of wind turbines. Pitch system is one of the most critical components due to its effect on the operational safety and the dynamics of wind turbines. Faults in this system should be precisely detected to prevent failures and decrease downtime. To detect faults of electric pitch actuators and sensors, an extended kalman filter (EKF) based multiple model adaptive estimation (MMAE) designed to estimate the states of the system. The proposed method is demonstrated in case studies. The simulation results show that the proposed method detects different fault scenarios of wind turbines under the stochastic external condition.

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DO - 10.1109/PEDS.2017.8289226

M3 - Article in proceeding

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BT - Proceedings of 2017 IEEE 12th International Conference on Power Electronics and Drive Systems (PEDS)

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Zhu J, Ma K, Hajizadeh A, N. Soltani M, Chen Z. Fault Detection and Isolation for Wind Turbine Electric Pitch System. I Proceedings of 2017 IEEE 12th International Conference on Power Electronics and Drive Systems (PEDS). IEEE Press. 2017. s. 618-623. (IEEE International Conference on Power Electronics and Drive Systems). https://doi.org/10.1109/PEDS.2017.8289226