Dynamic model assisted fault diagnostics of wind turbine gearbox

风力发电机齿轮箱动态模型辅助故障诊断

• 批准号: LP230100456
• 负责人: A/Prof JC Ji
• 金额: $ 25.4万
• 依托单位: University of Technology Sydney
• 依托单位国家: 澳大利亚
• 项目类别: Linkage Projects
• 财政年份: 2024
• 资助国家: 澳大利亚
• 起止时间: 2024-01-01 至 2026-12-31
• 项目状态: 未结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/LP230100456
• 关键词: Dynamic; model; assisted; fault; diagnostics

This project aims to develop novel condition monitoring methodologies for the gearbox of large horizontal-axis wind turbines which are widely installed in wind farms for generating renewable energy. This project expects to generate a new diagnostic framework by integrating dynamic model assisted simulations and digital twin-based approaches. Expected outcomes of this project include new vibration-based methods for fault diagnostics and predictions of the remaining useful life of turbine gearboxes. This should provide significant benefits to the Australian Wind Industry by ensuring reliable operation of wind turbines, reducing turbine downtime and reducing operation and maintenance costs; ultimately lowering the cost of energy from wind.

该项目旨在为大型水平轴风力涡轮机的齿轮箱开发新的状态监测方法，这些涡轮机广泛安装在风力发电场中，用于产生可再生能源。该项目希望通过集成动态模型辅助仿真和基于数字孪生的方法来生成一个新的诊断框架。该项目的预期成果包括新的基于振动的故障诊断方法和涡轮齿轮箱剩余使用寿命的预测。这将通过确保风力涡轮机的可靠运行，减少涡轮机停机时间，降低运行和维护成本，为澳大利亚风能行业带来重大利益；最终降低风能的成本。