A multi-robot platform for the autonomous operation and maintenance of offshore wind farms

With the increasing scale of offshore wind farm development, maintaining farms efficiently and safely becomes a necessity. The length of turbine downtime and the logistics for human technician transfer make up a significant proportion of the operation and maintenance (O&M) costs. To reduce such costs, future O&M infrastructures will increasingly rely on offshore autonomous robotic solutions that are capable of co-managing wind farms with human operators located onshore. In particular, unmanned aerial vehicles, autonomous surface vessels and crawling robots are expected to play important roles not only to bring down costs but also to significantly reduce the health and safety risks by assisting (or replacing) human operators in performing the most hazardous tasks. This paper portrays a visionary view in which heterogeneous robotic assets, underpinned by AI agent technology, coordinate their behavior to autonomously inspect, maintain and repair offshore wind farms over long periods of time and unstable weather conditions. They cooperate with onshore human operators, who supervise the mission at a distance, via the use of shared deliberation techniques. We highlight several challenging research directions in this context and offer ambitious ideas to tackle them as well as initial solutions

Autonomous wind turbine inspection using a quadrotor

There has been explosive growth of wind farm installations in recent years due to the fact that wind energy is gaining worldwide popularity. However, the maintenance of these offshore or onshore wind turbines, especially in remote areas, remains a challenging task. In this work, vision-based autonomous wind turbine inspection using a quadrotor is designed based on realistic assumptions. Both simulation and Hardware-In-the-Loop (HIL) testing results have shown the effectiveness of the proposed approach

Maintenance Management of Wind Turbines

“Maintenance Management of Wind Turbines” considers the main concepts and the state-of-the-art, as well as advances and case studies on this topic. Maintenance is a critical variable in industry in order to reach competitiveness. It is the most important variable, together with operations, in the wind energy industry. Therefore, the correct management of corrective, predictive and preventive politics in any wind turbine is required. The content also considers original research works that focus on content that is complementary to other sub-disciplines, such as economics, finance, marketing, decision and risk analysis, engineering, etc., in the maintenance management of wind turbines. This book focuses on real case studies. These case studies concern topics such as failure detection and diagnosis, fault trees and subdisciplines (e.g., FMECA, FMEA, etc.) Most of them link these topics with financial, schedule, resources, downtimes, etc., in order to increase productivity, profitability, maintainability, reliability, safety, availability, and reduce costs and downtime, etc., in a wind turbine. Advances in mathematics, models, computational techniques, dynamic analysis, etc., are employed in analytics in maintenance management in this book. Finally, the book considers computational techniques, dynamic analysis, probabilistic methods, and mathematical optimization techniques that are expertly blended to support the analysis of multi-criteria decision-making problems with defined constraints and requirements

Design and Development of a Mobile Climbing Robot for Wind Turbine Inspection

Wind turbines (WT) have become an essential renewable energy source as the contribution of WT farms has reached megawatts scale. However, wind turbine blades (WTB) are subjected to failure due to many loading effects such as aerodynamic, gravity and centrifugal loads and operation in harsh environments such as ultraviolet (UV) radiation, ice, hail, temperature variation, dirt, and salt. As a result, the blades suffer different types of damage. Consequently, a periodic inspection process is required to detect and repair defects before a catastrophic failure happens. This thesis presents a literature review of wall climbing robots to identify the most appropriate locomotion and adhesion method to use for a WT climbing machine that can take a large payload of non-destructive testing (NDT) sensors up to a blade and deploy them with scanning arms. A review of wind turbine blade construction, various loading effects on blades and types of damage in blades is followed by a review of the NDT techniques used for inspecting WTB. The above review determines the design requirements to achieve the aim of the current research which is to design a low-cost and reliable mobile robot which will be able to climb the WT tower and subsequently scan the blade surface to perform the inspection using various sensors to identify and classify damages. This robot system should be able to access all the critical areas of the blade structure in a stable and secure way. It should be stable enough to allow the various test sensors to scan the blade structure in the shortest possible time. The thesis describes the development of a tower climbing robot that uses magnetic adhesion to adhere to the WT. As a preliminary study, a simulation model is developed using COMSOL Multiphysics to simulate the magnetic adhesion force while climbing the tower. A test rig is designed and fabricated to measure the magnetic adhesion force experimentally to validate the simulation model. The response surface methodology (RSM) using Box-Behnken design (BBD) is used to design and perform experiments to optimise different independent variables i.e. air gap, the distance between magnets in an array and backplate (yoke) thickness that affect the magnetic adhesion force. A scaled-down prototype magnetic adhesion climbing robot has been designed and constructed for wind turbine blade inspection. The robot is 0.29 m long with two 1.0 m long arms, weighs 10.0 kg and can carry a maximum 2.0 kg payload of NDT sensors. Optimum design of a magnetic adhesion mechanism has been developed for the climbing robot prototype that maximises the magnetic adhesion force. The robot is equipped with two arms that can be extended by one meter to come close to the blade for inspection. Each arm is equipped with a gripper that can hold an inspection tool of weight up to one kilogram. A scaled-down wind turbine has been modelled using SolidWorks and a portion of it constructed to experimentally test the scaled-down climbing robot. To scale up the robot prototype for operation on a normal sized wind turbine, a 100 m tall wind turbine with three 76 m long blades has been modelled and the prototype robot scaled up based on these dimensions. The scaled-up robot is 3.0 m long, weighs 1135 kg and has two 10 m long arms. Static stress analysis and flow simulation have been carried out to check the durability of the scaled-up robot while climbing the wind turbine tower. The procedure for scaling up the adhesion mechanism to achieve equilibrium of the robot has been introduced based on the reaction force concluded from the static stress and flow simulation study. As a result, the maximum payload that each arm can carry has been calculated for both the scaled-down prototype (1 kg) and the scaled-up design (50 kg). This concludes the utility and robustness of the wall climbing robot as a robotic solution for wind turbine blade inspection

Multifunctional arm for telerobotic wind turbine blade repair

Within the Multi-Platform Inspection, Maintenance and Repair in Extreme Environments (MIMRee) project, a lightweight and multifunctional robotic repair arm is created for wind turbine blades. The design features a toolbox at the base of the arm housing multiple end-effector tools and an autonomous end-effector tool-changer. The arm communicates commands and data via internet with a bespoke user interface enabling human-in-the-loop operation and overriding of autonomous repair actions. This paper outlines our approach in design, development, testing and control of the robotic repair system. The functionalities of the arm include cleaning, sanding, and filler material deposition and forming, each using a bespoke end-effector tool closely replicating the relevant manual repair process. The experimental results confirm the effectiveness of our approach indicating a maximum end-effector position error of 3 mm, a maximum tool switching time of 8 seconds, and a maximum arm’s weight of 1.8 kg. This presents around 84% weight reduction compared with existing technologies used for the same purpose. Our standalone design enables modular integration into a wide range of mobile platform types used in industrial operations

Self-engineering – Technological Challenges

Engineered products are becoming more complex and need longer lifetime availability; there is a need for new approaches in maintaining, repairing and overhaul (MRO). This paper presents the concept of self-engineering; the aim is to preserve the functions of a product or system and extend its lifetime and automate MRO processes. New developments in self-healing materials, self-reconfiguring electronics and robotics, which are already or could be self-engineering systems, are reviewed. Biological healing and repair mechanisms are discussed as a potential source of inspiration for new self-engineering systems. Examples of biological self-engineering are presented. Key technological challenges and research questions which need to be addressed in future self-engineering research are discussed throughout

Collaborative Unmanned Vehicles for Inspection, Maintenance, and Repairs of Offshore Wind Turbines

Operations and maintenance of Offshore Wind Turbines (OWTs) are challenging, with manual operators constantly exposed to hazardous environments. Due to the high task complexity associated with the OWT, the transition to unmanned solutions remains stagnant. Efforts toward unmanned operations have been observed using Unmanned Aerial Vehicles (UAVs) and Unmanned Underwater Vehicles (UUVs) but are limited mostly to visual inspections only. Collaboration strategies between unmanned vehicles have introduced several opportunities that would enable unmanned operations for the OWT maintenance and repair activities. There have been many papers and reviews on collaborative UVs. However, most of the past papers reviewed collaborative UVs for surveillance purposes, search and rescue missions, and agricultural activities. This review aims to present the current capabilities of Unmanned Vehicles (UVs) used in OWT for Inspection, Maintenance, and Repair (IMR) operations. Strategies to implement collaborative UVs for complex tasks and their associated challenges are discussed together with the strategies to solve localization and navigation issues, prolong operation time, and establish effective communication within the OWT IMR operations. This paper also briefly discusses the potential failure modes for collaborative approaches and possible redundancy strategies to manage them. The collaborative strategies discussed herein will be of use to researchers and technology providers in identifying significant gaps that have hindered the implementation of full unmanned systems which have significant impacts towards the net zero strategy.</jats:p

Dynamic digital shearography for on-board robotic non-destructive testing of wind turbine blades

Structural integrity plays a critical role in development of infrastructural construction and support facilities. During the lifespan of most large-scale equipment, condition monitoring and periodic inspection is indispensable for ensuring structural health and evaluation of service condition. Wind turbine blades are the most important component of wind turbines and demands regular inspection to detect defects, which often occur underneath a blade surface. Current methods used to inspect wind turbine blades include to send NDT operators to climb the tower for on-site inspection of the blades’ surface or to dismantle the blades for inspection on the ground. These approaches are time-consuming, costly and pose risks of injury to human inspectors. Thus, it is necessary to develop a technological method for wind turbine blade on-site inspection of wind turbine blades. Digital shearography based on laser interferometry has demonstrated its prominent capability for inspecting composite material which is the main material used in the construction of wind turbine blades. Shearography is a ramification of holography interferometry and is more efficient to be used as a non-destructive testing (NDT) technique owing to its improved robustness and sensitivity to surface displacement. Robotic climbers, on the other hand, have recently drawn significant interest in NDT applications to replace human inspectors in extreme conditions. Thus, this thesis presents investigations into the development of a robotic NDT method using digital shearography for on-site inspection of wind turbine blades. The development of the shearography unit with correlation fringe pattern acquisition and the integration of this unit with the robotic climber adhering to wind turbine blades using vacuum generators are described in this thesis. The successful conduction of the indoor and outdoor trails for the integrated system verifies that shearography holds the ability to be used as an NDT tool for on-site wind turbine blade inspection, and that the climbing robot is able to access most areas of a wind turbine blade and stabilise itself to remove the impact on the shearography of the high frequencies from the climber’s vacuum motor and the low frequencies from the blade swing. Temporal phase shift shearography, and the fast phase map acquisition methods with less steps are evaluated in the thesis. Experiments are performed in lab with phase maps obtained using different algorithms. Apart from the conventional 4 steps and 3 steps phase shift algorithms, the modified 4+1 and 3+1 temporal phase shifting algorithms are developed for more suitability of semi-dynamic inspection by firstly calculating the correlation fringes and followed by the phase map calculations. The results of these modified methods are compared with the conventional 4 steps and 3 steps methods and are shown with equal qualities. Moreover, the reduced steps of phase shifting, i.e., 2+1 phase shifting methods are conducted for semi-dynamic phase map acquisition. It is found that the temporal phase shifting methods are not suitable for dynamic wind turbine blade inspection, however, the fast semi-dynamic temporal phase shift algorithms are able to produce phase maps with lower clarity. Pixelated spatial phase shift shearography is developed to remedy the limitation of temporal phase shift techniques. It adopts a micro-polarization sensor in the complementary metal oxide semiconductor (CMOS) camera, two linear polarizers, and a quarter waveplate as a new arrangement of optical path to replace the piezoelectric transducer stepper as the phase stepper. Three algorithms are introduced based on this novel developed system. Additionally, the site of view is enlarged for upgrading of the system. The development of the pixelated spatial phase shift shearography has mitigated the static processing limitation on temporal phase shift shearography, which caters for the demands of on-site NDT operation. At the same time, it remedies the current real-time shearography system which is not able to produce phase distributions for further quantitative analysis. The new developed pixelated spatial phase shift shearography system is thus more suitable for WTB on board inspection than both conventional and less-steps temporal phase shift shearography system. The field of view enlargement optimisation in the new developed spatial phase shift system indirectly reduces the distance for the inspection process and meanwhile enlarges the site of view, which consequently reduces the weight and structural complexity of the robotic-shearography integration system. The research addresses and resolves the difficulty of on-board wind turbine blade inspection with a novel robotic NDT approach using digital shearography. The approach is significant for real world industrial applications. Moreover, through the temporal and spatial phase shift evaluation, the research proves the feasibility of dynamically obtaining phase maps by the shearography system for further quantitative analysis without using temporal phase shift devices

Multi-Robot Coverage Path Planning for Inspection of Offshore Wind Farms: A Review

Offshore wind turbine (OWT) inspection research is receiving increasing interest as the sector grows worldwide. Wind farms are far from emergency services and experience extreme weather and winds. This hazardous environment lends itself to unmanned approaches, reducing human exposure to risk. Increasing automation in inspections can reduce human effort and financial costs. Despite the benefits, research on automating inspection is sparse. This work proposes that OWT inspection can be described as a multi-robot coverage path planning problem. Reviews of multi-robot coverage exist, but to the best of our knowledge, none captures the domain-specific aspects of an OWT inspection. In this paper, we present a review on the current state of the art of multi-robot coverage to identify gaps in research relating to coverage for OWT inspection. To perform a qualitative study, the PICo (population, intervention, and context) framework was used. The retrieved works are analysed according to three aspects of coverage approaches: environmental modelling, decision making, and coordination. Based on the reviewed studies and the conducted analysis, candidate approaches are proposed for the structural coverage of an OWT. Future research should involve the adaptation of voxel-based ray-tracing pose generation to UAVs and exploration, applying semantic labels to tasks to facilitate heterogeneous coverage and semantic online task decomposition to identify the coverage target during the run time.</jats:p

Teleoperated, In Situ Repair of an Aeroengine: Overcoming the Internet Latency Hurdle

There is a substantial financial incentive for in situ repair of industrial assets. However, the need for highly trained mechanics to travel to the location of a repair often results in inconveniently long downtimes. The emergence of robots capable of replicating human interventions on industrial equipment can be coupled with remote-control strategies to reduce the response time from several days to a few hours