New & Renewable Energy (신재생에너지)

Korean Society for New and Renewable Energy (한국신·재생에너지학회)
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Study on Enhancement of Data Processing Algorithm in SaaS Cloud Infrastructure to Monitor Wind Turbine Condition

풍력발전기 상태 감시를 위한 SaaS 클라우드 인프라 내 데이터 처리 알고리즘 개선 연구

  • Received : 2019.10.17
  • Accepted : 2020.01.21
  • Published : 2020.03.25
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Abstract

In this study, an SW for the analysis of the wind-turbine vibration characteristics was developed as an application of SaaS cloud infrastructure. A measurement system for power-performance, mechanical load, and gearbox vibration as type-test class was installed at a target MW-class wind turbine, and structural meta and raw data were then acquired into the cloud. Data processing algorithms were developed to provide cloud data to the SW. To operate the SW continuously, raw data was downloaded consistently based on the algorithms. During the SW test, an intermittent long time-delay occurred due to the communication load associated with frequent access to the cloud. To solve this, a compression service for the target raw data was developed in the cloud and more stable data processing was confirmed. Using the compression service, stable big data processing of wind turbines, including gearbox vibration analysis, is expected.

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References

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