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An experimental study on the fault diagnosis of wind turbines through a condition monitoring system

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Abstract

To detect wind turbine faults at an early stage, an investigation into a practical maintenance and repair approach was carried out on Jeju Island, South Korea. A condition monitoring system was installed in each wind turbine nacelle to detect the vibration signals from the gearbox and the generator. The vibration signals were measured by strain gauges on the gearbox and the generator for a period of approximately one to two years. A time domain analysis to detect the components’ faults was performed, and a frequency domain analysis was conducted to find the location of the faults that occurred. Using the criteria of acceptance level for the root mean square suggested in Verein Deutscher Ingenieure standard 3834, it was determined whether or not the gearbox and the generator were operated normally. After a fault was detected by root mean square analysis, the fast fourier transform spectrum was analyzed and then compared with that suggested by the International Organization for Standardization standard 10816–21 and 13373–1. Repair work was then conducted on the defective parts of the components. The root mean square and the acceleration value of the normal, the warning and the abnormal conditions were compared with one another. As a result, cavitation might occur in the gear oil pump attached to the gearbox due to the high acceleration values observed for frequencies ranging from 5000 Hz to 11000 Hz. Additionally, the generator bearing at the non drive end was found to be broken because the defect frequency of the bearing was 88 Hz, which was derived from envelope spectrum analysis. The root mean square and the acceleration values for the gearbox and the generator decreased to values indicating normal operating conditions after the damage repair. The annual energy production increased by 1.8 % after the generator bearing repair.

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Authors and Affiliations

  1. Multidisciplinary Graduate School Program for Wind Energy, Jeju National University, 102 Jejudaehakro, Jeju, 63243, Korea

    Jinhyuk Son & Dongbum Kang

  2. Namjeju Thermal Power Plant Wind Farm Management Team, 521 Hankyeonghaeanro, Jeju, 63002, Korea

    Daewon Boo

  3. Faculty of Wind Energy Engineering, Graduate School, Jeju National University, 102 Jejudaehakro, Jeju, 63243, Korea

    Kyungnam Ko

Authors
  1. Jinhyuk Son
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  2. Dongbum Kang
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  3. Daewon Boo
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  4. Kyungnam Ko
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Corresponding author

Correspondence to Kyungnam Ko.

Additional information

Recommended by Associate Editor Daeil Kwon

Jinhyuk Son is a Ph.D. candidate of the Multidisciplinary Graduate School Program for Wind Energy in Jeju University, Republic of Korea. He holds a bachelor’s degree (2015) in New Material Engineering from Gyeongsang University and a master’s degree (2017) from the Faculty of Wind Energy Engineering, Graduate School, Jeju University. He has been studying on the condition monitoring system of wind turbines. In addition, he is interested in prediction for life time of wind turbine components.

Dongbum Kang is a Ph.D. candidate of the Multidisciplinary Graduate School Program for Wind Energy in Jeju University, Republic of Korea. He holds a bachelor’s degree (2009) in Physical education and a master’s degree (2015) from the Faculty of Wind Energy Engineering, Graduate School, Jeju University. He has been studying on wind resource assessment and the condition monitoring system of wind turbines.

Kyungnam Ko is an Associate Professor of the Faculty of Wind Energy Engineering, Graduate School, Jeju University, Republic of Korea. He earned a bachelor’s degree in Marine Engineering in 1993 and a master’s degree in Mechanical Engineering in 1995 at Jeju University. He then received his Ph.D. degree in Mechanical System Engineering in 2002 from Gunma University, Japan. He has been studying on wind resource assessment, wind farm design, condition monitoring system and power curves of wind turbines. Furthermore, his research interest includes economic feasibility analysis.

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Son, J., Kang, D., Boo, D. et al. An experimental study on the fault diagnosis of wind turbines through a condition monitoring system. J Mech Sci Technol 32, 5573–5582 (2018). https://doi.org/10.1007/s12206-018-1103-y

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  • DOI: https://doi.org/10.1007/s12206-018-1103-y

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