Adaptive System Based on Macro-Fiber Composite Transducers for Vibration Control and Noise Reduction in Wind Turbine Blades

基于粗纤维复合传感器的风力涡轮机叶片振动控制和降噪自适应系统

• 批准号: 1028365
• 负责人: Francesco Lanza di Scalea
• 金额: $ 34.91万
• 依托单位: University of California-San Diego
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-15 至 2014-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1028365&HistoricalAwards=false
• 关键词: Adaptive; System; Based; Macro; Fiber

Research Objectives and ApproachesThe objective of this research is to improve the performance of wind turbine blades for renewable energy generation by mitigating the blade vibrations, hence reducing the airborne noise and increasing the blade?s fatigue life.The approach is to integrate with the blade a distributed network of piezo-composite patches to mitigate low-frequency vibrations ( 100Hz) through active piezoelectric actuation and high-frequency vibrations (100 Hz) through passive shunt damping. Intellectual MeritVibrations in wind turbines result in both airborne noise affecting surrounding areas, and increased lifecycle cost of the turbine from structural fatigue. The project will complement existing "global" control of wind turbine blades by reducing vibrations at a more "local" scale using a distributed network of piezo-composite patches. Piezo-composite patches, compared to monolithic piezoelectric disks, offer increased durability, conformability to curved surfaces, and better compatibility with the composite blade material. The network will also provide a multi-scale vibration suppression capability that is unprecedented in wind turbines. Broader ImpactsWind currently accounts for 42% of the installed renewable power in the U.S. One of the Grand Challenges of the Department of Energy is to have 20% of the U.S. energy generated by wind by 2030. The proposed piezo-composite network will reduce airborne noise levels to surrounding areas and will increase the operating regime and the structural life of the blades. The project will also include the modification of an existing course at UCSD, international research cooperation, and outreach efforts to low-income 6-12 grade students.

研究目标和方法本研究的目的是通过减轻叶片振动，从而降低空气噪声，增加叶片的体积，从而提高用于可再生能源发电的风力涡轮机叶片的性能。S疲劳寿命。该方法是将压电复合贴片的分布式网络集成到叶片中，通过主动压电驱动来减轻低频振动（100Hz），通过被动分流阻尼来减轻高频振动（100Hz）。风力涡轮机的振动不仅会影响周围区域的空气噪声，还会增加涡轮机结构疲劳带来的生命周期成本。该项目将补充现有的风力涡轮机叶片的“全球”控制，通过使用压电复合片的分布式网络在更“局部”的范围内减少振动。与单片压电片相比，压电复合片提供了更高的耐用性，对曲面的适应性，以及与复合叶片材料更好的兼容性。该网络还将提供风力涡轮机中前所未有的多尺度振动抑制能力。更广泛的影响风能目前占美国可再生能源装机容量的42%。美国能源部面临的重大挑战之一是，到2030年，风能发电量将占美国总发电量的20%。拟用的压电复合材料网络将减少空气中对周围地区的噪音水平，并将增加叶片的运行状态和结构寿命。该项目还将包括对加州大学圣地亚哥分校现有课程的修改，国际研究合作，以及向低收入的6-12年级学生提供服务。