Vibration-based wind turbine planetary gearbox fault diagnosis using spectral averaging
Vibration-based wind turbine planetary gearbox fault diagnosis using spectral averaging
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DOI：
10.1002/we.1940
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发表时间：
2016-09
期刊：
影响因子：
4.1
通讯作者：
Jae Yoon;D. He;B. V. Hecke;Thomas J. Nostrand;Junda Zhu;Eric Bechhoefer
中科院分区：
文献类型：
--
作者：
Jae Yoon;D. He;B. V. Hecke;Thomas J. Nostrand;Junda Zhu;Eric Bechhoefer
行星齿轮箱（PGB）广泛用于风力涡轮机的传动系统中。任何PGB故障都可能导致风力涡轮机的严重故障或重大损失。因此，PGB故障诊断对于减少停机时间和维护成本，提高风力发电机组的安全性、可靠性和使用寿命具有重要意义。风能行业目前利用振动分析作为PGB状态监测和故障诊断的标准方法。其中，振动分离被认为是成熟的振动分析技术之一。然而，在文献中报道的振动分离技术的缺点包括：潜在的太阳轮故障诊断的限制，多个传感器和大量的数据要求，以及易受外部噪声。本文提出了一种基于单振动传感器谱平均的PGB故障诊断新方法。它结合了包络技术、Welch的谱平均技术和基于数据挖掘的故障分类器。利用该方法，提取风力涡轮机PGB的振动故障特征作为故障诊断的状态指标，并将状态指标作为故障分类器的输入，进行PGB故障诊断。该方法验证了一组种子本地故障的所有齿轮：太阳齿轮，行星齿轮，齿圈。实验结果表明，该方法具有良好的PGB故障诊断性能。版权所有© 2015约翰威利父子有限公司.
Planetary gearboxes (PGBs) are widely used in the drivetrain of wind turbines. Any PGB failure could lead to a significant breakdown or major loss of a wind turbine. Therefore, PGB fault diagnosis is very important for reducing the downtime and maintenance cost and improving the safety, reliability, and lifespan of wind turbines. The wind energy industry currently utilizes vibratory analysis as a standard method for PGB condition monitoring and fault diagnosis. Among them, the vibration separation is considered as one of the well‐established vibratory analysis techniques. However, the drawbacks of the vibration separation technique as reported in the literature include the following: potential sun gear fault diagnosis limitation, multiple sensors and large data requirement, and vulnerability to external noise. This paper presents a new method using a single vibration sensor for PGB fault diagnosis using spectral averaging. It combines the techniques of enveloping, Welch's spectral averaging, and data mining‐based fault classifiers. Using the presented approach, vibration fault features for wind turbine PGB are extracted as condition indicators for fault diagnosis and condition indicators are used as inputs to fault classifiers for PGB fault diagnosis. The method is validated on a set of seeded localized faults on all gears: sun gear, planetary gear, and ring gear. The results have shown a promising PGB fault diagnosis performance with the presented method. Copyright © 2015 John Wiley & Sons, Ltd.