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Robots for Marine Renewable Energy Plants Maintenance and Surveying

用于海洋可再生能源工厂维护和测量的机器人

基本信息

批准号：
2274493
负责人：
金额：
--
依托单位：
University of Edinburgh
依托单位国家：
英国
项目类别：
Studentship
财政年份：
2019
资助国家：
英国
起止时间：
2019 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=studentship-2274493
关键词：
Robots Marine Renewable Energy Plants

项目摘要

The purpose of my research is to investigate the design of autonomous vehicles for deployment in rough seas, delving into the underlying electronics and hardware design which is fundamental to the operation of the vehicle. I intend to conduct research which will assist in the drive to create underwater vehicles that can manoeuvre and operate in daunting environments where current technologies do not yet have the capabilities of successfully venturing, allowing maintenance to be carried out in a broader spectrum of conditions. With operations in offshore deep sea oil and gas extraction particularly becoming more complex, the need for automated vehicles for maintenance and inspection is growing substantially. My aim will be to develop new or adapt current technologies that can manage and counteract the disturbances the vehicle will see in the unpredictable subsea environment, therefore reducing the limitations of operations that current Remotely Operated Vehicles (ROV's) and Autonomous Underwater Vehicles (AUV's) are subject to. The capabilities of modern ROV's and AUV's are very much dependent on weather conditions; this is the problem I intend to tackle with my research and make substantial progress in developing solutions to widen the conditions these vehicles are capable of tackling. Approaches to the challenge could involve possibly adapting current integrated circuit designs for custom use, which could speed up the processing of information and possibly advance the predictive ability of the system; this would allow the vehicle to counteract disturbances more effectively. A mechanical based approach would be to obstruct the movement of the vehicle through restraints, allowing maintenance/inspection to be conducted with minimal disturbances in reference to position. Another control-based approach may involve sensing disturbances before they occur, by being able to predict accurately how the vehicle would be affected; this would be more complex as the sea is a naturally chaotic environment but using a combination of advanced sensors and machine learning it then a much more possible solution. This research is critical if the industry is to transition to fully automated inspection and maintenance of offshore technologies, which implies the reduction of cost of maintenance in the long term thus also implying lower cost per watt of energy produced; the need to place humans in extremely dangerous positions would also be removed therefore improving the safety of such operations.

我的研究目的是研究在波涛汹涌的海面上部署的自动驾驶车辆的设计，深入研究对车辆运行至关重要的底层电子和硬件设计。我打算进行研究，帮助创造能够在令人生畏的环境中操纵和操作的水下机器人，在这些环境中，目前的技术还不具备成功冒险的能力，允许在更广泛的条件下进行维护。随着近海深海石油和天然气开采作业变得特别复杂，对用于维护和检查的自动化车辆的需求大幅增长。我的目标将是开发新的或调整现有的技术，能够管理和抵消潜水器在不可预测的水下环境中将看到的干扰，从而减少目前的遥控潜水器(ROV)和自主水下潜航器(AUV)受到的操作限制。现代ROV和AUV的能力在很大程度上取决于天气条件；这是我打算通过我的研究解决的问题，并在开发解决方案方面取得实质性进展，以扩大这些车辆能够处理的条件。应对这一挑战的办法可能涉及调整目前的集成电路设计以供定制使用，这可以加快信息处理速度，并可能提高系统的预测能力；这将使车辆能够更有效地抵消干扰。一种基于机械的方法是通过约束来阻碍车辆的移动，以便在对位置的干扰最小的情况下进行维护/检查。另一种基于控制的方法可能涉及在干扰发生之前进行感知，方法是能够准确预测车辆将如何受到影响；这将更加复杂，因为海洋是一个自然混乱的环境，但使用先进传感器和机器学习的组合比使用更可能的解决方案更有可能。如果该行业要过渡到海上技术的全自动化检查和维护，这项研究是至关重要的，这意味着从长远来看，维护成本的降低，从而意味着每瓦特能源生产成本的降低；还将消除将人类置于极其危险的位置的必要性，从而提高此类作业的安全性。