resinSENSE - real-time, on-line monitoring of resin mix-ratio monitoring system

resinSENSE - 实时、在线监控树脂混合比监控系统

• 批准号: 10034050
• 金额: $ 24.75万
• 依托单位: TRIBOSONICS LTD
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=10034050
• 关键词: resinSENSE; real; time; line; monitoring

This project is to accelerate the development of novel and scalable technology to address a significant problem in the renewable energy sector; the need to better control resin mix-ratios in the production of wind turbine blades.Wind energy represents a key component of the UK's energy and decarbonisation mix, with UK wind production increasing by 715% from 2009 to 2020 (ONS, 2021). However, to continue increasing wind energy generation and enable "Net Zero" by 2050, the number of wind turbines manufactured per year needs to triple within the next decade (ORE Catapult). One barrier to this increased production is the need to make the manufacture of the turbine blades more efficient and less wasteful.Turbine blades take multiple days and many dozens of employees to manufacture a single blade, with an associated manufacturing cost running into many hundreds of thousands of pounds (CompositesWorld). Half of all defective blades produced are as a direct result of errors and inconsistencies of the resin mixture. Our innovation is to monitor the resin mix-ratios non-invasively and in-process using ultrasonic sensing to dramatically improve production throughput and reduce wastage. This is particularly relevant from a sustainability perspective, with the turbine blade being one of the few components of a wind turbine that cannot be easily recycled (Bloomberg Green). The technology solution developed during this project will also lead to improved traceability during the manufacturing process, allowing for the use of two-part resins in new markets, where the regulatory and quality assurance regimes currently limit their usage.This involves applying our sensing technology to characterise the resin in the mixing stage, before it is dispensed into the fibreglass mould, therefore avoiding the write-off of the blade. This project builds upon promising results obtained during a self-funded feasibility study, which demonstrated that it was possible to distinguish the mix-ratios of polyester resins down to levels of 0.1% using ultrasonic sensing. The project will be focused on designing and creating a measurement cell, improving the measurement algorithm, and embedding the algorithm onto a device for real-time measurement capabilities.The prototype sensing system, as well as providing a vital developmental feedback loop, will lead to increased confidence in the technology, accelerating commercialisation to solve this progress-limiting problem.

该项目旨在加速开发新颖且可扩展的技术，以解决可再生能源领域的一个重大问题；在风力涡轮机叶片的生产中需要更好地控制树脂混合比。风能是英国能源和脱碳组合的关键组成部分，从2009年到2020年，英国风能产量增长了715% （ONS, 2021）。然而，为了继续增加风能发电并在2050年实现“净零”，每年制造的风力涡轮机数量需要在未来十年内增加三倍（ORE Catapult）。增加产量的一个障碍是需要提高涡轮叶片的制造效率和减少浪费。涡轮叶片需要数天时间和数十名员工来制造单个叶片，相关的制造成本高达数十万英镑（CompositesWorld）。一半有缺陷的叶片是由于树脂混合物的错误和不一致直接造成的。我们的创新之处在于使用超声波传感技术无创地监测树脂混合比，从而显著提高生产吞吐量并减少浪费。从可持续发展的角度来看，这一点尤为重要，因为涡轮机叶片是风力涡轮机中为数不多的不能轻易回收的部件之一（彭博绿色）。在该项目中开发的技术解决方案还将改善制造过程中的可追溯性，允许在监管和质量保证制度目前限制其使用的新市场中使用双组分树脂。这涉及到在树脂被分配到玻璃纤维模具之前，在混合阶段应用我们的传感技术来表征树脂，因此避免了叶片的注销。该项目建立在一项自筹资金的可行性研究中获得的有希望的结果的基础上，该研究表明，利用超声波传感可以将聚酯树脂的混合比例区分到0.1%的水平。该项目将专注于设计和创建一个测量单元，改进测量算法，并将算法嵌入到实时测量能力的设备中。原型传感系统，以及提供一个重要的发展反馈回路，将增加对技术的信心，加速商业化，以解决这一限制进展的问题。