STTR Phase I: Enhancing wind-energy industry competitiveness using self-powered blade monitoring sensors

STTR 第一阶段：利用自供电叶片监测传感器增强风能行业竞争力

• 批准号: 2131373
• 负责人: Pranay Kohli
• 金额: $ 25.6万
• 依托单位: ACTIVECHARGE LLC
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-10-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2131373&HistoricalAwards=false
• 关键词: STTR; Phase; Enhancing; wind; energy

The broader impact/commercial potential of this Small Business Technology Transfer (STTR) project seeks to provide an integrated monitoring solution for wind turbine blades. Continuous and reliable monitoring within the blade has been a challenge, primarily due to the lack of reliable energy for the wireless sensor (e.g., batteries need to be replaced and can be expensive and logistically difficult to replace inside the blade and power lines inside the blade are hard to install and require frequent maintenance). The proposed solution seeks to overcome current technical challenges by providing a long-lasting, maintenance-free, self-powered, integrated solution for wind turbine blade monitoring and analytics. If successfully commercialized, the solution can be deployed for autonomous sensing and smart maintenance scheduling based on big data analysis. This project may contribute to significantly and permanently reducing existing blade monitoring costs, decreasing downtime for manual monitoring and battery changes and reducing catastrophic failures with better monitoring information. By reducing the operational costs, the solution may make large-scale wind energy more competitive, reducing the world’s dependence on environmentally-harmful sources of energy. In addition, the technology may reduce the risk of injury to humans as compared to current operational processes, making wind energy safer to operate. This STTR Phase I project proposes to develop an integrated, self-powering sensor node for wind turbine blade monitoring by overcoming the following technical hurdles: lack of reliable energy for the sensor/transmitter system deep inside the blade, logistical challenges to replacing batteries inside the blade for a large number of sensors at different intervals, and difficulites with long wire-runs inside the blade as those are hard to install and require frequent maintenance. To handle these technical hurdles, this project aims to prototype an integrated, self-powered, wireless sensor node and perform field tests. This project plans to: (1) develop a mechanism for the harvester module that reliably produces electrical voltage and power regardless of the blade rotational speed, (2) develop a power management circuit with autonomous sleep/wakeup and without impedance tracking to increase charging efficiency, and (3) perform indoor and in-field test for verification of power harvesting and data transmission performance. This technolology seeks to address the fundamental weaknesses of vibration energy harvesters while integrating various components (e.g., energy harvester, sensor, transmitter, receiver, and analytics software) for an optimized solution.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该小型企业技术转让 (STTR) 项目旨在为风力涡轮机叶片提供集成监控解决方案，具有更广泛的影响/商业潜力，叶片内的连续可靠监控一直是一项挑战，主要是由于叶片缺乏可靠的能源。无线传感器（例如，电池需要更换，并且在刀片内部更换电池可能很昂贵并且在逻辑上很困难，并且刀片内部的电源线很难安装并且需要频繁维护）。所提出的解决方案旨在通过提供一种解决方案来克服当前的技术挑战。持久，用于风力涡轮机叶片监测和分析的免维护、自供电、集成解决方案如果成功商业化，该解决方案可用于基于大数据分析的自主传感和智能维护调度。叶片监控成本，减少手动监控和电池更换的停机时间，并通过更好的监控信息减少灾难性故障。通过降低运营成本，该解决方案可以使大规模风能更具竞争力，减少世界对环境有害能源的依赖。此外，该技术还可以与当前的运行流程相比，降低了对人体造成伤害的风险，使风能运行更安全。该 STTR 第一阶段项目建议通过克服以下技术障碍，开发一种用于风力涡轮机叶片监测的集成式自供电传感器节点： 缺乏。叶片深处的传感器/发射器系统的能量消耗，以不同的时间间隔为大量传感器更换叶片内的电池的后勤挑战，以及叶片内长电线的困难，因为这些难以安装并且需要频繁来处理这些。为了克服技术障碍，该项目旨在制作一个集成的、自供电的无线传感器节点原型并进行现场测试。该项目计划：（1）开发一种用于收割机模块的机制，无论叶片如何旋转，该机制都能可靠地产生电压和功率。该技术旨在解决以下问题：(2) 开发具有自主睡眠/唤醒功能且无需阻抗跟踪的电源管理电路，以提高充电效率；(3) 进行室内和现场测试以验证电力收集和数据传输性能。振动的根本弱点能量采集器，同时集成各种组件（例如能量采集器、传感器、发射器、接收器和分析软件）以获得优化的解决方案。该奖项是 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查进行评估，被认为值得支持标准。