风电齿轮箱在随机风载下的疲劳损伤计算模型

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振动与冲击 ›› 2018, Vol. 37 ›› Issue (11) : 115-123.

论文

向东 1 ，蒋李 1，沈银华 1，韦尧中 1

作者信息 +

Fatigue damage calculation model for wind turbine gearboxes under random wind loads

XIANG Dong 1 JIANG Li 1 SHEN Yin-hua 1 WEI Yao-zhong 1

Author information +

文章历史 +

摘要

疲劳寿命是风电齿轮箱一个非常重要的性能，本文在风机整体分析、齿轮箱动力学分析和齿轮疲劳损伤分析的基础上提出了风电齿轮箱在随机风载下的疲劳损伤计算模型，其中风机整体分析用于获取齿轮箱在随机风载下的输入扭矩和输出转速，齿轮箱动力学分析是根据输入扭矩和输出转速计算各个齿轮之间的动态啮合力以及转速，齿轮疲劳损伤分析是将齿轮动态啮合力转化为弯曲和接触应力载荷块，依据线性损伤累计理论计算各齿轮的弯曲和接触疲劳损伤。在讨论部分，本文利用提出的疲劳损伤计算模型计算了在平均风速为11.5m/s和18m/s，湍流密度为14%的风况下，各齿轮的弯曲疲劳和接触疲劳损伤，找到了各级齿轮中最危险的齿轮，对风电齿轮箱排错具有指导意义。

Abstract

Fatigue life is an important performance for wind turbine gearboxes. A fatigue damage calculation model for wind turbine gearboxes was proposed under random wind loads based on wind turbine global analysis, gearbox dynamic analysis and gear fatigue damage analysis. Firstly, the wind turbine global analysis was done to calculate a gearbox’s input torque and output rotating speed under random wind loads. Then, based on the acquired input torque and output rotating speed, each gear’s dynamic contact force and rotating speed were calculated with the gearbox dynamic analysis. Finally, the gear fatigue damage analysis was done, gear’s contact force was converted into loads causing gear’s bending and contact stresses, according to Miner linear damage accumulation theory, each gear’s bending and contact fatigue damages were calculated. In the discussion part, each gear’s bending fatigue damage and contact fatigue damage were calculated using the proposed model under wind conditions with the mean wind of 11.5m/s and 18m/s, and the turbulence density of 14%. The most dangerous one in all gears was found. The study results were meaningful for detecting wind turbine gearboxes’ failure sources.

导出引用

向东 1,蒋李 1，沈银华 1，韦尧中 1. 风电齿轮箱在随机风载下的疲劳损伤计算模型[J]. 振动与冲击, 2018, 37(11): 115-123

XIANG Dong 1 JIANG Li 1 SHEN Yin-hua 1 WEI Yao-zhong 1. Fatigue damage calculation model for wind turbine gearboxes under random wind loads[J]. Journal of Vibration and Shock, 2018, 37(11): 115-123

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