Enhanced Phase Demodulation for Vibration-based Fault Detection of Wind Turbine Drivetrain

Mohamed A.A. Ismail; Ayman Abdallah

doi:10.1109/PHM-BEIJING63284.2024.10874532

Enhanced Phase Demodulation for Vibration-based Fault Detection of Wind Turbine Drivetrain

Mohamed A.A. Ismail^*, Ayman Abdallah

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Vibration-based fault detection plays a vital role in monitoring rotary machinery systems such as aircraft Propulsion systems and wind turbines. Detecting their failures early is crucial for ensuring their safety and reliability. One of the main challenges is identifying system faults using non-stationary vibration measurements caused by variable-speed operation. In many cases operating speed has high fluctuations (>±10%) that limit the fault detection performance. In this paper, we introduce an improved method for extracting speed profile from a vibration signal utilizing a geometric feature within a rotating machinery system such as gearboxes, actuators and ball-screws. The performance of the enhanced method has been successfully validated using international benchmarking datasets for wind turbine gearboxes.

Original language	English
Title of host publication	15th Global Reliability and Prognostics and Health Management Conference, PHM-Beijing 2024
Editors	Huimin Wang, Steven Li
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798350354010
DOIs	https://doi.org/10.1109/PHM-BEIJING63284.2024.10874532
State	Published - 2024
Event	15th IEEE Global Reliability and Prognostics and Health Management Conference, PHM-Beijing 2024 - Beijing, China Duration: 11 Oct 2024 → 13 Oct 2024

Publication series

Name	15th Global Reliability and Prognostics and Health Management Conference, PHM-Beijing 2024

Conference

Conference	15th IEEE Global Reliability and Prognostics and Health Management Conference, PHM-Beijing 2024
Country/Territory	China
City	Beijing
Period	11/10/24 → 13/10/24

Bibliographical note

Publisher Copyright:
© 2024 IEEE.

Keywords

Wind turbines
order-tracking
planetary gearbox
sensorless fault diagnosis
vibration-based diagnosis

ASJC Scopus subject areas

Artificial Intelligence
Computer Networks and Communications
Information Systems and Management
Health Informatics
Health Policy
Health(social science)
Computer Vision and Pattern Recognition
Safety, Risk, Reliability and Quality

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/PHM-BEIJING63284.2024.10874532

Cite this

Ismail, M. A. A., & Abdallah, A. (2024). Enhanced Phase Demodulation for Vibration-based Fault Detection of Wind Turbine Drivetrain. In H. Wang, & S. Li (Eds.), 15th Global Reliability and Prognostics and Health Management Conference, PHM-Beijing 2024 (15th Global Reliability and Prognostics and Health Management Conference, PHM-Beijing 2024). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/PHM-BEIJING63284.2024.10874532

Ismail, Mohamed A.A. ; Abdallah, Ayman. / Enhanced Phase Demodulation for Vibration-based Fault Detection of Wind Turbine Drivetrain. 15th Global Reliability and Prognostics and Health Management Conference, PHM-Beijing 2024. editor / Huimin Wang ; Steven Li. Institute of Electrical and Electronics Engineers Inc., 2024. (15th Global Reliability and Prognostics and Health Management Conference, PHM-Beijing 2024).

@inproceedings{022c8caedd8d4c1390d75227bc90777a,

title = "Enhanced Phase Demodulation for Vibration-based Fault Detection of Wind Turbine Drivetrain",

abstract = "Vibration-based fault detection plays a vital role in monitoring rotary machinery systems such as aircraft Propulsion systems and wind turbines. Detecting their failures early is crucial for ensuring their safety and reliability. One of the main challenges is identifying system faults using non-stationary vibration measurements caused by variable-speed operation. In many cases operating speed has high fluctuations (>±10%) that limit the fault detection performance. In this paper, we introduce an improved method for extracting speed profile from a vibration signal utilizing a geometric feature within a rotating machinery system such as gearboxes, actuators and ball-screws. The performance of the enhanced method has been successfully validated using international benchmarking datasets for wind turbine gearboxes.",

keywords = "Wind turbines, order-tracking, planetary gearbox, sensorless fault diagnosis, vibration-based diagnosis",

author = "Ismail, {Mohamed A.A.} and Ayman Abdallah",

note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 15th IEEE Global Reliability and Prognostics and Health Management Conference, PHM-Beijing 2024 ; Conference date: 11-10-2024 Through 13-10-2024",

year = "2024",

doi = "10.1109/PHM-BEIJING63284.2024.10874532",

language = "English",

series = "15th Global Reliability and Prognostics and Health Management Conference, PHM-Beijing 2024",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

editor = "Huimin Wang and Steven Li",

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address = "United States",

}

Ismail, MAA & Abdallah, A 2024, Enhanced Phase Demodulation for Vibration-based Fault Detection of Wind Turbine Drivetrain. in H Wang & S Li (eds), 15th Global Reliability and Prognostics and Health Management Conference, PHM-Beijing 2024. 15th Global Reliability and Prognostics and Health Management Conference, PHM-Beijing 2024, Institute of Electrical and Electronics Engineers Inc., 15th IEEE Global Reliability and Prognostics and Health Management Conference, PHM-Beijing 2024, Beijing, China, 11/10/24. https://doi.org/10.1109/PHM-BEIJING63284.2024.10874532

Enhanced Phase Demodulation for Vibration-based Fault Detection of Wind Turbine Drivetrain. / Ismail, Mohamed A.A.; Abdallah, Ayman.
15th Global Reliability and Prognostics and Health Management Conference, PHM-Beijing 2024. ed. / Huimin Wang; Steven Li. Institute of Electrical and Electronics Engineers Inc., 2024. (15th Global Reliability and Prognostics and Health Management Conference, PHM-Beijing 2024).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Enhanced Phase Demodulation for Vibration-based Fault Detection of Wind Turbine Drivetrain

AU - Ismail, Mohamed A.A.

AU - Abdallah, Ayman

PY - 2024

Y1 - 2024

N2 - Vibration-based fault detection plays a vital role in monitoring rotary machinery systems such as aircraft Propulsion systems and wind turbines. Detecting their failures early is crucial for ensuring their safety and reliability. One of the main challenges is identifying system faults using non-stationary vibration measurements caused by variable-speed operation. In many cases operating speed has high fluctuations (>±10%) that limit the fault detection performance. In this paper, we introduce an improved method for extracting speed profile from a vibration signal utilizing a geometric feature within a rotating machinery system such as gearboxes, actuators and ball-screws. The performance of the enhanced method has been successfully validated using international benchmarking datasets for wind turbine gearboxes.

AB - Vibration-based fault detection plays a vital role in monitoring rotary machinery systems such as aircraft Propulsion systems and wind turbines. Detecting their failures early is crucial for ensuring their safety and reliability. One of the main challenges is identifying system faults using non-stationary vibration measurements caused by variable-speed operation. In many cases operating speed has high fluctuations (>±10%) that limit the fault detection performance. In this paper, we introduce an improved method for extracting speed profile from a vibration signal utilizing a geometric feature within a rotating machinery system such as gearboxes, actuators and ball-screws. The performance of the enhanced method has been successfully validated using international benchmarking datasets for wind turbine gearboxes.

KW - Wind turbines

KW - order-tracking

KW - planetary gearbox

KW - sensorless fault diagnosis

KW - vibration-based diagnosis

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M3 - Conference contribution

AN - SCOPUS:85219651457

T3 - 15th Global Reliability and Prognostics and Health Management Conference, PHM-Beijing 2024

BT - 15th Global Reliability and Prognostics and Health Management Conference, PHM-Beijing 2024

A2 - Wang, Huimin

A2 - Li, Steven

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 15th IEEE Global Reliability and Prognostics and Health Management Conference, PHM-Beijing 2024

Y2 - 11 October 2024 through 13 October 2024

ER -

Ismail MAA , Abdallah A. Enhanced Phase Demodulation for Vibration-based Fault Detection of Wind Turbine Drivetrain. In Wang H, Li S, editors, 15th Global Reliability and Prognostics and Health Management Conference, PHM-Beijing 2024. Institute of Electrical and Electronics Engineers Inc. 2024. (15th Global Reliability and Prognostics and Health Management Conference, PHM-Beijing 2024). doi: 10.1109/PHM-BEIJING63284.2024.10874532

Enhanced Phase Demodulation for Vibration-based Fault Detection of Wind Turbine Drivetrain

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

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Cite this