Drone Swarm for Unmanned Inspection of Wind Turbines (Dr-SUIT): Battery Health Management, Hybrid Comms Systems and Operational Platform for Autonomous Offshore Windfarm Inspection

Airborne Robotics （AR）、Ocean Infinity （Ocean）和Bentley Telecom （Bentley）正与朴茨茅斯大学（UoP）合作，开发无人机群能力和用于海上风电场（OWF）自主检测的操作平台。该项目名为“Dr-Suit”，利用系统的系统方法，专注于建立无人机群的弹性和安全性，特别是在面临包括访问和环境危害，操作和维护（O&M）成本增加以及无人机电池寿命限制等挑战时。虽然无人机已用于WT检测，但无人机群部署提供了更大/进一步覆盖范围和减少检测时间的好处。由于无人机目前不是为标准使用的蜂群操作而设计的，Dr-SUIT将开发一种相互作用的算法，从而逐步将设计从单个飞行员控制无人机转变为单个飞行员控制多架无人机，并通过混合通信系统（4G, 5G，卫星）集成进行优化。5G网络将减少延迟，增加带宽大小和速度。利用卫星通信将覆盖范围扩大到通信行业和具有成本效益的回程服务。该混合系统将解决检测连续/大数据中继的延迟、冗余和带宽大小等问题，从而提高无人机对无人机、无人机对操作员和集群操作期间的传感性能。在计算整个运行所需的功率和飞行时间（考虑到飞行到200米以上的涡轮机和检查70-90米长的叶片）时，电池寿命是另一个问题。将开发一种具有预测分析功能的新型蜂群感知电池健康管理系统，以及更现实的无人机蜂群任务所需的电池充电/交换系统。一艘带有小型动力装置的驳船将被用作无人机充电/更换电池的平台，以便及时操作，并用于5G桅杆和卫星。考虑到无人机的性能、涡轮机位置和环境，实时检查调度和路由将被数学建模，这对蜂群的安全运行至关重要。优化的无人机群部署执行叶片检查的现场演示将结束该第二阶段项目。

Airborne Robotics (AR), Ocean Infinity (Ocean) and Bentley Telecom (Bentley) are working in partnership with the University of Portsmouth (UoP) to develop drone swarming capabilities and an operational platform for an autonomous inspection in offshore windfarms (OWF). Utilising a system-of-systems approach, the project entitled “Dr-Suit”, focuses to build in drone swarm resilience and safety especially when facing the challenges including access and environment hazards, increased Operations and Maintenance (O&M) costs, and drones’ battery life limitation. Although drones have been used for WT inspection, a drone swarm deployment offers benefits of larger/further coverage and reduced inspection time. Since drones are currently not designed for swarm operation at a standard use, Dr-SUIT will develop an algorithm to interplay, therefore progressively shift the design from a single pilot controlling a drone to a single pilot controlling multiple drones, optimised by the hybrid communication system (4G, 5G, satellite) integration. The 5G network will reduce the latency and increased bandwidth size and speed. The utilisation of satellite communications extends the coverage to the communication industries and cost-effective backhaul services. The hybrid system will address issues of latency, redundancy, and bandwidth size for detection’s continuous/big data relay, thus enhancing drone-to-drone, drone-to-operator and sensing performance during swarming operation. Battery life is another issue when calculating power and flight time required for an entire operation (accounting flying to above ~200m turbines and inspecting ~70-90m long blades). A novel swarm-aware battery health management system with predictive analytics will be developed along with a battery recharging/swapping system which is needed for more realistic drone swarming missions. A barge with a small power unit will be utilised as a platform for drones to recharge/swap batteries, for a timely operation, and for a 5G mast and satellite. Essential to the swarm safe operation, a real time inspection scheduling and routing will be mathematically modelled factoring drone’s performances, turbine positions, and environment. A live demonstration of an optimised drone swarm deployment performing blades inspection will conclude this Phase 2 project.