针对现有的风电轴承健康状态评估方法需大量样本提取和模型训练、存在实现过程繁琐费时费力且泛化应用能力弱的问题,提出基于动态阈值的风电轴承健康状态评估方法。首先,考虑风的随机性和间歇性,利用风电轴承温度监测数据,引入劣化度概念,采用曲线拟合和机群聚类方法确定了劣化度的上、下限动态阈值;其次,通过健康状态评语集及其等级划分范围和劣化度计算,提出基于动态阈值的风电轴承健康状态评估方法;最后,以某风电机组的发电机后轴承超温故障为例,验证了所提评估方法可获得有效的风电轴承健康状态和及早获知故障征兆。
Abstract
To address the challenges faced by current wind turbine bearing health assessment methods, which involve extensive sample extraction, model training, and are therefore cumbersome, time-intensive, and labor-intensive with limited applicability, a method utilizing a dynamic threshold for assessing the health status of wind turbine bearings is introduced. Firstly, considering the randomness and intermittency of wind, the concept of deterioration degree is introduced by using the temperature monitoring data of wind turbine bearings, and the upper and lower dynamic thresholds of deterioration degree are determined by curve fitting and cluster clustering methods. Secondly, the health condition evaluation method of wind turbine bearings based on dynamic threshold is proposed by calculating the health status comment set and its grade division range and deterioration degree. Finally, taking the overtemperature fault of the rear bearing of a wind turbine as an example, it is verified that the proposed evaluation method can obtain the effective health conditions of the wind turbine bearing and obtain the fault symptom as soon as possible.
关键词
风力机 /
轴承 /
劣化度 /
状态评估 /
动态阈值 /
健康管理
Key words
wind turbines /
bearing /
deterioration /
condition evaluation /
dynamic threshold /
health management
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基金
国家电力投资集团有限公司统筹研发资助项目（TC2020FD05）
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