Recently, multiple wind turbine failure databases have reviewed that the pitch system is one of the subassemblies with the highest failure rates and largest contributors to the overall downtime. Therefore, there has been an increasing interest to provide remote health monitoring for wind turbine pitch system. While most of the research articles are discussing pitch actuation system (hydraulic or electric actuator) faults only, there is very limited research on pitch-bearing-defect detection. This article provides a remote and hardware-free solution to monitor multiaxis pitch-bearing health condition called pitch symmetrical-component analysis. It leverages readily available low-resolution (100 Hz) electrical measurements, mechanical measurements, and control signals from the existing pitch control platform, and innovatively applies symmetrical-component analysis in multiphase ac system to multiaxis pitch control system and introduces multiaxis pitch-bearing degradation trending curves. This hardware-free solution can be directly applied to the existing wind turbines and successfully give the wind farm operator an early warning before multiaxis pitch bearing fails. It has been proved to be accurate, low cost, and has minimum impacts on turbine normal operation, and has been validated by field data from several North America MW-scale wind farms. This approach turns out to be the first hardware-free (no additional hardware needed) method to remotely monitor and diagnose multiaxis wind turbine pitch-bearing condition.

中文翻译：

---

使用桨距对称分量分析对兆瓦级风力发电机中的桨距轴承缺陷进行远程监控和诊断


最近，多个风力涡轮机故障数据库审查表明，变桨系统是故障率最高且对整体停机时间影响最大​​的组件之一。因此，人们越来越关注为风力涡轮机变桨系统提供远程健康监测。虽然大多数研究文章仅讨论变桨驱动系统（液压或电动执行器）故障，但对变桨轴承缺陷检测的研究非常有限。本文提供了一种远程且无硬件的解决方案来监控多轴变桨轴承的健康状况，称为变桨对称分量分析。它利用现有变桨控制平台中现成的低分辨率 (100 Hz) 电气测量、机械测量和控制信号，创新地将多相交流系统中的对称分量分析应用于多轴变桨控制系统，并引入多轴变桨轴承退化趋势曲线。这种无硬件的解决方案可以直接应用于现有的风力涡轮机，并成功地在多轴变桨轴承发生故障之前向风电场运营商发出预警。事实证明该方法准确、成本低、对风机正常运行影响最小，并得到北美多个兆瓦级风电场的现场数据验证。这种方法被证明是第一个无硬件（不需要额外硬件）的方法来远程监控和诊断多轴风力涡轮机变桨轴承状况。