UAV's for Quantitative Non-Destructive Inspection

本研究主要围绕定量无损检测(NDT)技术在无人机发电工业资产检测中的应用展开。在当前延长核电设施运行寿命的趋势和发展日益可再生的国家能源组合的趋势下，显然需要加强视察能力。例如，在风力涡轮机的情况下，传统的检查方法，即工程师在必要时应用其他技术之前爬上涡轮轴并目测工厂，正在看到无人机及其操作员部分取代。因此，本研究打算在对相关研究领域的最新技术进行深入审查后，展示更严格的无损检测技术的开发和应用到检查过程中。目的和目标：1.光学启发无人机定位，消除了物理手动控制和上升的需要，从而提高了操作员检查大量地理上分散的资产的能力，并减少了相关的个人安全担忧。无损检测驱动的无人机平台建模和控制理论，用于优化3D空间的表面探测速度或覆盖范围，以及相关硬件开发；3.用于优化位置不变部署的无损检测传感器设计和实现4.图像分析技术，包括同步定位和映射(SLAM)或缺陷分类，用于检测结构故障的超声波换能器专用，包括涡轮叶片中的复合材料分层，或其他类似工作。因此，该奖学金的最终目标是在EDF能源可再生能源部和国家核实验室的支持下，通过为期四年的iCASE博士资助，加强航空无损检测领域的工程科学。

This research studentship is focussed around the application of quantitative Non-Destructive Testing (NDT) techniques to power generation industrial asset inspection by way of Unmanned Aerial Vehicles (UAVs). Within the current trend of operating lifespan extension for nuclear power generation facilities and the development of an increasingly renewable national energy portfolio, there is an appreciable need for enhanced inspection capability. For example in the case of wind turbines, the traditional inspection method, whereby an engineer would climb the turbine shaft and visually inspect the plant before applying other techniques as necessary, is seeing partial replacement by UAVs and their operators. This research therefore intends to demonstrate the development and application of more rigorous NDT techniques to the inspection process following an in depth-review of the state of the art in related fields of study. Aims & Objectives:1. Optical inspired UAV positioning eliminating the need for physical manual control and ascension, thereby increasing the ability of the operator to inspect numerous geographically diffuse assets and reducing the associated personal safety concerns.2. NDT Driven UAV platform modelling and control theory for optimised surface exploration speed or coverage in 3D space and relevant hardware development, 3. NDT Sensor design and implementation for optimised position invariant deployment 4. Image analysis techniques including Simultaneous Localisation and Mapping (SLAM) or defect classification, ultrasonic transducer appropriation for detection of structural faults including composite material delamination in turbine blades, or other similar works. Thus, the ultimate goal of the studentship is to enhance engineering science within the field of airborne NDT through an iCASE PhD funding period of four years, supported by the EDF Energy renewables department and National Nuclear Laboratory.