Autonomous Wind-turbine Infrastructure Inspection
Autonomous Wind-turbine Infrastructure Inspection
批准号:
102971
负责人:
金额:
$30.85万
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
项目状态:
已结题
起止时间:
2017 至 --
中文摘要
知觉机器人公司正在与布里斯托尔大学和行业合作伙伴合作,利用智能自主无人机技术对风力涡轮机进行全自动视觉检测。投资风力发电场项目的一个主要问题是保持涡轮机的可用性,这意味着由于涡轮机停滞和维修期间,能源产量降低和生产损失的风险。保持风力涡轮机的可靠性对于风力发电场有效运行和盈利至关重要。由于全球风力涡轮机数量庞大(超过315,000台),频繁的目视检查变得越来越重要。目前使用工业绳索或无人驾驶飞机的技术成本高,耗时长,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,该技术能够自主完成整个检查报告要求,提供安全,稳健,可重复的检查,降低成本,提高信任和质量。这种检查方法将有助于减少风力涡轮机的停机时间,提供更实惠的运营成本,提高风力发电场的投资回报。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内开发。它将产生一种独特的产品,比竞争对手的系统具有显著的技术优势,并在英国和海外打开市场,进一步提高英国在可再生能源技术方面的专业知识。
英文摘要
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.
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国内基金
海外基金
Development of a Linear Stochastic Model for Wind Field Reconstruction from Limited Measurement Data
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批准号:--
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项目类别:--
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资助金额:40万元
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批准年份:2020
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负责人:Vikrant Gupta
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依托单位: