A performance degradation model and a real-time remaining useful life (RUL) prediction method are proposed on the basis of temperature characteristic parameters to determine the RUL of wind turbine bearings. First, using the moving average method, the relative temperature data of wind turbine bearings are smoothed, and the temperature trend data are obtained on the basis of the uncertainty of wind speed and wind direction that causes the temperature of wind turbine bearings to vary widely. Second, given that the degradation speed of bearings changes with operational time and uncertain external factors, the performance degradation model is established with the Wiener process. The parameters of this model are obtained through the maximum likelihood estimation method. Third, according to the failure principle of the first temperature monitoring value beyond the first warning threshold, the RUL prediction model for wind turbine bearings is established on the basis of an inverse Gaussian distribution. Finally, the performance degradation process and real-time RUL prediction are demonstrated by predicting the RUL of a practical rear bearing of a wind turbine generator. The comparison of the predicted RUL and actual RUL shows that the proposed model and prediction method are correct and effective.

中文翻译：

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基于维纳过程的风电机组轴承实时剩余使用寿命预测方法

提出了一种基于温度特性参数的性能退化模型和实时剩余使用寿命(RUL)预测方法，以确定风电机组轴承的RUL。首先，采用移动平均法，对风电机组轴承的相对温度数据进行平滑处理，根据导致风电机组轴承温度变化较大的风速风向的不确定性，得到温度趋势数据。其次，考虑到轴承的退化速度随运行时间和不确定的外部因素而变化，利用维纳过程建立了性能退化模型。该模型的参数是通过最大似然估计方法获得的。第三，根据第一温度监测值超出第一预警阈值的失效原理，建立了基于逆高斯分布的风电机组轴承RUL预测模型。最后，通过预测实际风力涡轮发电机后轴承的 RUL 来证明性能退化过程和实时 RUL 预测。预测的 RUL 与实际的 RUL 的比较表明，所提出的模型和预测方法是正确有效的。