基于区间划分的风电齿轮箱在线故障预警方法

针对大型风电机组运行工况复杂多变,依靠恒定的润滑油温度值作为齿轮箱故障预警值容易不报的问题,提出了基于运行区间划分的风电机组齿轮箱在线故障预警方法。该方法通过划分不同的运行区间,对不同运行区间根据高斯模型分别设定阈值。将实时数据代入相应运行区间判定是否异常,再利用移动窗口计算异常率作为触发齿轮箱故障预警的指标。该方法用于某1.5 MW风电机组齿轮箱故障的分析,结果表明,该方法能够准确地反映故障的发展趋势,可实现齿轮箱故障的早期预警,避免故障向更严重的方向发展,降低风电机组运行和维修成本。

An Online Fault Early Warning Method for Wind Turbine Gearbox Based on Operational Condition Division

Aiming at the problem that the operational condition of large size wind turbines is complex and relying on constant lubricating oil temperature as gearbox fault early warning values is not easy to report, an online fault early warning method for wind turbine gearbox based on operational condition division was proposed. By dividing different operation conditions, this method respectively sets threshold for different operation conditions according to the Gaussian Model. The proposed approach takes the real-time data into the corresponding operational condition to determine whether the data is abnormal, and uses moving window to calculate the abnormal rate as an indicator to trigger gearbox fault early warning. The method is used for a 1.5 MW wind turbine gearbox fault analysis, the re- sults show that the method can accurately reflect the development trend of fault, achieve gearbox fault early warn- ing, avoid the failure to develop in the direction of more serious, and decrease the wind turbine operation and maintenance cost.