Next generation predictive maintenance for wind turbine blade/hub/rotor through novel online condition monitoring/root cause analysis: MONTURWIND

为了缓解气候变化，到2050年，风能发电能力将增长10倍。不幸的是，风力涡轮机的运行和维护(O&M)成本是光伏和化石燃料发电厂的两倍，因为非常昂贵的计划外维修频率很高。问题的主要领域是涡轮机转子和传动系统的旋转部件，包括叶片、轮毂、低速轴、主转子轴承、变速箱和发电机。高额的起重机租用成本，甚至更昂贵的自升式船舶租赁成本(~GB 90k/天)增加了维修成本。WTs配备了状态监测(CM)系统来检测传动系统故障，但市场上或正在开发的系统没有监测叶片(玻璃/碳聚合物结构)、轮毂、低速轴，没有嵌入传感器或无损测试/检测技术。嵌入式传感器很难改装和维护。检查需要停机才能进行非破坏性测试或人工检查。光学和红外摄像机、机器人和无人机解决方案存在，但它们昂贵、笨重或可以检测到的故障类型有限。人工检查带来的健康和安全问题是由于塔楼攀爬和绳索接触工作造成的。该项目将开发一种全新的自动在线CM/根本原因分析系统，能够在没有嵌入传感器的情况下检测叶片/轮毂/轴的危险故障。技术以复杂的信号处理和人工智能为基础，可提供经济高效、易于翻新的解决方案。刀片式服务器/轴/集线器故障检测开启了42.3亿美元的市场商机。根据预计销售额，该行业将在五年内节省8.93亿GB，因为它实现了廉价的计划维修，而不是昂贵的更换，并通过根本原因检测/消除防止故障再次发生。系统销售将产生累积的PBIT GB 1050万(5年)、ROI 14.3和PBIT 3.78亿(10年)。

Wind energy capacity is set to grow tenfold by 2050 in order to mitigate climate change. Unfortunately, wind turbine (WT) operation and maintenance (O&M) cost is twice as high as photovoltaic and fossil fuel power plants due to high frequency of very expensive unplanned repairs.The major areas of issue are rotating components of turbine rotor and drivetrain including blades, hub, low-speed shaft, main rotor bearing, gearbox and generator. Repair costs are increased by high crane hire cost, or even more expensive jack-up vessel charter costs (~£90k/day) for offshore WTs.WTs are equipped with condition monitoring (CM) systems to detect drivetrain faults, however no system in the market or in development monitors blades (a glass / carbon polymer structure), and hub, low-speed shaft without embedded sensors or non-destructive testing / inspection techniques. Embedded sensors are difficult to retrofit and maintain. Inspection requires shutdown in order to carry out non-destructive testing or manual inspections. Optical and IR cameras, robotic and drone solutions exist but they are expensive, cumbersome or limited in types of faults that can be detected. Manual inspections present health and safety problems due to tower climbs and rope access work.The project will develop a radically novel automatic online CM / root cause analysis system capable of detecting blade / hub / shaft dangerous faults without embedded sensors. Technology is underpinned by sophisticated signal processing and AI to deliver a cost effective, easily retrofitted solution. Blade / shaft / hub fault detection unlocks access to a \>$4.23 billion market opportunity. Based on projected sales, the industry will save £893 million over five years by enabling inexpensive planned repairs rather than costly replacements and preventing fault re-occurrence by root cause detection / elimination. System sales will generate cumulative PBIT £10.5M (5 years), ROI 14.3 and PBIT 378M (10 years).