풍력발전기 상태 감시를 위한 SaaS 클라우드 인프라 내 데이터 처리 알고리즘 개선 연구
Study on Enhancement of Data Processing Algorithm in SaaS Cloud Infrastructure to Monitor Wind Turbine Condition
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초록
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.
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.
참고문헌 (7)
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- Sheng, S., "Wind turbine gearbox reliability database, condition monitoring, and O&M research update", Proceedings of GRC Annual Meeting (2015)
- 손은국, "1.5 MW 풍력 터빈 소음 측정 및 저주파 소음 특성 분석", 신재생에너지, 14(4), pp.4~13 (2018), 한국신·재생에너지학회[DOI]
- "Wind in the Cloud? How the Digital Wind Farm Will Make Wind Power 20 Percent More Efficient" (2018)[URL]
- Tchakoua, P., "Wind turbine condition monitoring : State-of-the-art review, new trends, and future challenges", Energies, 7(4), pp.2595~2630 (2014)
- 이광세, "풍력발전기 증속기 상태를 감시하기 위한 SaaS 클라우드 인프라 개발", 한국산학기술학회논문지, 19(9), pp.316~325 (2018), 한국산학기술학회[DOI]
- "ISO standard 10816-21, Mechanical vibration-Evaluation of machine vibration by measurements on non-rotating parts-Part 21: Horizontal axis wind turbines with gearbox", ~ (2015)