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）正在与朴茨茅斯（UoP）合作，开发无人机群集能力和海上风电场（OWF）自主检查的操作平台。该项目名为“Dr-Suit”，采用系统中系统的方法，重点是建立无人机群的弹性和安全性，特别是在面临挑战时，包括进入和环境危害，增加运营和维护（O&M）成本，以及无人机的电池寿命限制。 虽然无人机已用于WT检查，但无人机群部署提供了更大/更远的覆盖范围和减少检查时间的好处。由于无人机目前不是为标准用途的群体操作而设计的，因此Dr-SUIT将开发一种相互作用的算法，从而逐步将设计从单一飞行员控制无人机转变为单一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。卫星通信的使用将覆盖范围扩大到通信行业和具有成本效益的回程服务。该混合系统将解决延迟、冗余和带宽大小等问题，用于检测连续/大数据中继，从而增强无人机到无人机、无人机到操作员和群集操作期间的感知性能。 在计算整个操作所需的功率和飞行时间时，电池寿命是另一个问题（计算飞行到200米以上的涡轮机和检查70- 90米长的叶片）。一种具有预测分析功能的新型集群感知电池健康管理系统将与电池充电/交换系统沿着开发，这是更现实的无人机集群任务所需的。一艘带有小型动力装置的驳船将被用作无人机充电/交换电池的平台，以便及时操作，以及5G桅杆和卫星。对于群安全操作至关重要的是，将对真实的时间检查调度和路由进行数学建模，以考虑无人机的性能、涡轮机位置和环境。一个优化的无人机群部署执行叶片检查的现场演示将结束这个第二阶段项目。

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.