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An Approach of Quantifying Gear Fatigue Life for Wind Turbine Gearboxes Using Supervisory Control and Data Acquisition Data

机译:利用监控和数据采集数据量化风力发电机齿轮箱齿轮疲劳寿命的一种方法

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Quantifying wind turbine (WT) gearbox fatigue life is a critical problem for preventive maintenance when unsolved. This paper proposes a practical approach that uses ten minutes’ average wind speed of Supervisory Control and Data Acquisition (SCADA) data to quantify a WT gearbox’s gear fatigue life. Wind turbulence impacts on gearbox fatigue are studied thoroughly. Short-term fatigue assessment for the gearbox is then performed using linear fatigue theory by considering WT responses under external and internal excitation. The results shows that for a three stage gearbox, the sun gear in the first stage and pinions in the 2nd and 3rd stage are the most vulnerable parts. High mean wind speed, especially above the rated range, leads to a high risk of gearbox fatigue damage. Increase of wind turbulence may not increase fatigue damage as long as a WT has an instant response to external excitation. An approach of using SCADA data recorded every ten minutes to quantify gearbox long-term damages is presented. The calculation results show that the approach effectively presents gears’ performance degradation by quantifying their fatigue damage. This is critical to improve WT reliability and meaningful for WT gearbox fatigue assessment theory. The result provides useful tools for future wind farm prognostic maintenance.
机译:量化风力涡轮机(WT)齿轮箱的疲劳寿命是未解决的预防性维护的关键问题。本文提出了一种实用的方法,该方法利用监督控制和数据采集(SCADA)数据的十分钟平均风速来量化WT变速箱的齿轮疲劳寿命。风湍流对变速箱疲劳的影响已得到深入研究。然后,通过考虑外部和内部激励下的WT响应,使用线性疲劳理论对齿轮箱进行短期疲劳评估。结果表明,对于三级变速箱,第一级的太阳轮以及第二级和第三级的小齿轮是最易损坏的部分。高平均风速,尤其是高于额定范围,会导致变速箱疲劳损坏的风险很高。只要WT对外部激励具有即时响应,风湍流的增加可能不会增加疲劳损伤。提出了一种使用每十分钟记录一次的SCADA数据来量化齿轮箱长期损坏的方法。计算结果表明,该方法通过量化齿轮的疲劳损伤有效地显示了齿轮的性能下降。这对于提高WT可靠性至关重要,对于WT变速箱疲劳评估理论具有重要意义。结果为将来的风电场预后维护提供了有用的工具。

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