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Condition monitoring of spar-type floating wind turbine drivetrain using statistical fault diagnosis

机译：基于统计故障诊断的翼梁式浮动风力发电机组传动系统状态监测

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摘要

Operation and maintenance costs are significant for large-scale wind turbines and particularly so for offshore. A well-organized operation and maintenance strategy is vital to ensure the reliability, availability, and cost-effectiveness of a system. The ability to detect, isolate, estimate, and perform prognoses on component degradation could become essential to reduce unplanned maintenance and downtime. Failures in gearbox components are in focus since they account for a large share of wind turbine downtime. This study considers detection and estimation of wear in the downwind main-shaft bearing of a 5-MW spar-type floating turbine. Using a high-fidelity gearbox model, we show how the downwind main bearing and nacelle axial accelerations can be used to evaluate the condition of the bearing. The paper shows how relative acceleration can be evaluated using statistical change-detection methods to perform a reliable estimation of wear of the bearing. It is shown in the paper that the amplitude distribution of the residual accelerations follows a t-distribution and a change-detection test is designed for the specific changes we observe when the main bearing becomes worn. The generalized likelihood ratio test is extended to fit the particular distribution encountered in this problem, and closed-form expressions are derived for shape and scale parameter estimation, which are indicators for wear and extent of wear in the bearing. The results in this paper show how the proposed approach can detect and estimate wear in the bearing according to desired probabilities of detection and false alarm.
机译：对于大型风力涡轮机，特别是对于海上风力涡轮机而言，其运营和维护成本意义重大。井井有条的运维策略对于确保系统的可靠性，可用性和成本效益至关重要。检测，隔离，估计和执行组件降级的能力对于减少计划外的维护和停机时间至关重要。变速箱组件的故障非常重要，因为它们占了风力涡轮机停机时间的很大一部分。本研究考虑了对5 MW翼梁式浮动涡轮机顺风主轴轴承的磨损的检测和估计。使用高保真齿轮箱模型，我们展示了如何利用顺风主轴承和机舱轴向加速度来评估轴承的状况。本文显示了如何使用统计变化检测方法评估相对加速度，以执行轴承磨损的可靠估计。本文显示，残余加速度的幅度分布遵循t分布，并且针对主轴承磨损时观察到的特定变化设计了变化检测测试。扩展了广义似然比检验以适合该问题遇到的特定分布，并导出了用于形状和比例参数估计的闭合形式表达式，这些表达式是轴承磨损和磨损程度的指标。本文的结果说明了该方法如何根据所需的检测概率和虚警概率来检测和估计轴承的磨损。

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  • 来源
    《Wind Energy》 |2018年第7期|575-589|共15页
  • 作者

    Ghane Mahdi; Nejad Amir Rasekhi; Blanke Mogens; Gao Zhen; Moan Torgeir;

  • 作者单位

    Norwegian Univ Sci & Technol, Dept Marine Technol, Ctr Ships & Ocean Struct, NO-7491 Trondheim, Norway;

    Norwegian Univ Sci & Technol, Dept Marine Technol, Ctr Ships & Ocean Struct, NO-7491 Trondheim, Norway;

    Norwegian Univ Sci & Technol, Dept Marine Technol, Ctr Autonomous Marine Operat & Syst, NO-7491 Trondheim, Norway;

    Norwegian Univ Sci & Technol, Dept Marine Technol, Ctr Ships & Ocean Struct, NO-7491 Trondheim, Norway;

    Norwegian Univ Sci & Technol, Dept Marine Technol, Ctr Ships & Ocean Struct, NO-7491 Trondheim, Norway;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    condition monitoring; fault detection; floating wind turbine; main bearing; statistical change detection; wind turbine gearbox;

    机译：状态监测;故障检测;浮动风力发电机;主轴承;统计变化检测;风力发电机齿轮箱;

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