Autonomous Wind-turbine Infrastructure Inspection

自主风力涡轮机基础设施检查

• 批准号: 102971
• 金额: $ 30.85万
• 依托单位: PERCEPTUAL ROBOTICS LIMITED
• 依托单位国家: 英国
• 项目类别: Feasibility Studies
• 财政年份: 2017
• 资助国家: 英国
• 起止时间: 2017 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=102971
• 关键词: Autonomous; Wind; turbine; Infrastructure; Inspection

Perceptual Robotics is working with the University of Bristol and industry partners to provide fully automated visual inspection of wind turbines using smart autonomous drone technology. One of the major concerns in investing in wind farm projects relates to maintaining turbine availability, which represents the risk of lower energy yields and lost production due to periods of turbine standstill and repair. Maintaining wind turbine reliability is essential for a wind farm to perform effectively and profitably. As a consequence with huge numbers of wind turbines worldwide (315,000+), frequent visual inspection is becoming ever more important. Current techniques using industrial rope access or piloted drones are costly, time-consuming and unable to deliver repeatable and consistent inspection. The aim of this project is to address these weaknesses by developing drone technology which is able to autonomously fulfil the entire inspection to reporting requirement, providing safe, robust, repeatable inspection, reducing costs and increasing trust and quality. Such an approach to inspections will contribute to reducing wind turbine down-time, deliver more affordable operational costs and improve the return on wind farm investment. The technology will include innovative algorithms in flight control and vision based defect detection, and will be developed within a platform independent architecture. It will yield a unique product with significant technology advantage over competitor systems and open up markets in the UK and overseas, further increasing UK expertise in renewable technology.

感知机器人公司正在与布里斯托尔大学和行业合作伙伴合作，使用智能自主无人机技术为风力涡轮机提供全自动视觉检查。投资风电场项目的主要问题之一是保持涡轮机的可用性，这意味着由于涡轮机停机和维修的时间段，存在能源产量降低和产量损失的风险。保持风力涡轮机的可靠性是风电场有效和有利可图运行的关键。因此，随着全球风力涡轮机数量的增加(315,000多台)，频繁的目视检查变得越来越重要。目前使用工业绳索通道或无人驾驶飞机的技术昂贵、耗时，而且无法提供可重复和一致的检查。该项目的目的是通过开发无人机技术来解决这些弱点，该技术能够自动完成整个检查，以满足报告要求，提供安全、可靠、可重复的检查，降低成本并提高信任和质量。这种检查方法将有助于减少风力涡轮机停机时间，提供更负担得起的运营成本，并提高风电场投资回报。该技术将包括飞行控制和基于视觉的缺陷检测的创新算法，并将在独立于平台的架构中开发。它将产生一种独特的产品，与竞争对手的系统相比具有显著的技术优势，并打开英国和海外的市场，进一步增加英国在可再生技术方面的专业知识。