A review: Challenges and opportunities for artificial intelligence and robotics in the offshore wind sector

Mitchell, Daniel; Blanche, Jamie; Harper, Sam; Lim, Theodore; Gupta, Ranjeetkumar; Zaki, Osama; Tang, Wenshuo; Robu, Valentin; Watson, Simon; Flynn, David

doi:10.1016/j.egyai.2022.100146

Cited by 47 publications

(23 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To prevent unexpected failures in the jacket structures, it is necessary to conduct real-time SHM. [14][15][16][17] Generally, the design life of an offshore wind turbine is 20 years, 18 and the life can be extended to a maximum of another 10 years by performing proper SHM. 19 The SHM often includes four objectives: damage identification, damage localization, damage quantification, and RUL estimation.…”

Section: Structure Health Monitoring Of Offshore Jacket Structuresmentioning

confidence: 99%

Condition-based structural health monitoring of offshore wind jacket structures: Opportunities, challenges, and perspectives

Leng

Gardoni

Wang

et al. 2023

Structural Health Monitoring

View full text Add to dashboard Cite

Structural health monitoring (SHM) has been recognized as a useful tool for safety management and risk reduction of offshore wind farms. In complex offshore environment, jacket structures of offshore wind turbines are prone to damages due to corrosion and fatigue. Effective SHM on jacket structures can substantially reduce their operation risk and costs. This work reviews the latest progress on the SHM of offshore wind jacket structures. The achievements in the structural damage identification, location, quantification, and remaining useful life (RUL) estimation are respectively introduced in detail, and existing challenges are discussed. Possible solutions to the challenges using the Digital Twin (DT) technology are put forward. The DT is able to mirror a real jacket structure into a virtual model, and Bayesian updating can refresh the virtual model parameters in real-time to keep consistency between virtual model and physical structure; then, just-in-time SHM can be carried out for jacket structures by performing damage detection, location, quantification, and RUL estimation using the virtual model. As a result, the DT may provide engineers and researchers a practicable tool for safety monitoring and risk reduction of fixed foundation offshore wind structures.

show abstract

Section: Structure Health Monitoring Of Offshore Jacket Structuresmentioning

confidence: 99%

Condition-based structural health monitoring of offshore wind jacket structures: Opportunities, challenges, and perspectives

Leng

Gardoni

Wang

et al. 2023

Structural Health Monitoring

View full text Add to dashboard Cite

show abstract

“…Reiman et al [75] also reviewed the ergonomics and other human factors in the context of the growing prevalence of industry 4.0 systems. Mitchell et al [76] reviewed the applications of robotics and artificial intelligence in wind infrastructure lifecycle management with special emphasis on offshore platforms. Forcina et al [77] reviewed how industry 4.0 technologies make modern factories safer for humans.…”

Section: A Related Reviewsmentioning

confidence: 99%

Robotics in Industry 4.0: A Bibliometric Analysis (2011-2022)

Sekhar

Shah²,

Iswanto

2022

Journal of Robotics and Control

View full text Add to dashboard Cite

Robotics forms an integral part of industry 4.0, the industrial revolution of the 21st century. This paper presents a bibliometric analysis of Web of Science (WoS) indexed publications addressing this emerging field from 2011 till June 2022. WoS research publications were firstly analysed along multiple verticals such as annual counts, types, publishing sources, research directions, researchers, organizations, and countries. Next, co-authorship collaborations among authors, organizations, and countries were discovered. This was followed by an analysis of co-occurring keywords related to robotics in industry 4.0. Finally, a detailed citation analysis was carried out to unearth citation linkages among authors, institutions, documents, nations, and journals. Latest trends, under-investigated topics, and future directions are also discussed. Primary results indicate that more than 3000 articles are being published annually in this emerging field, with a total of 18,893 documents published in WoS during the last decade. The 'IEEE Access', Chinese Academy of Science, Wang Y. (USA), and the USA emerged as the topmost productive journal, institution, author, and nation. Porpiglia Francesco (Italy), Chinese Academy Science and USA obtained the highest co-authorship total link strength (TLS); whereas Lee Chengkuo (Singapore), China, Chinese Academy Science, and the IEEE Access scored the highest citation TLS among authors, countries, organizations, and sources respectively. Machine learning (ML) emerged as the highest co-occurring keyword, followed by artificial intelligence (AI). Computer Science emerged as the most trending research domain, followed by general applications. In the future, ML and AI will advance more sophisticated robots in industry 4.0 systems.

show abstract

“…For Multi-Robot (MR) fleets operating in dangerous environments, such as discussed in this article for the nuclear sector, resilience and coordination of robots at a distance in a safe environment from a user interface by a human are identified as additional key challenges in the future [19]. The advancement of MRfleets represents a key opportunity to maximise the characteristics from a range of robots to improve IMR activities, productivity (due to the ability to complete tasks in parallel) and resilience in operations [14,20,21].…”

Section: Introductionmentioning

confidence: 99%

“…Within the current state-of-the-art for robots in nuclear environments, systems are deployed individually and evaluated under single use-case deployments via a sequence of events where in most examples, when safety is increased via robotics, efficiency decreases [10,11]. In addition, presently sectors such as defence [12], offshore (inclusive of both renewable and petrochemical domains) [13,14], healthcare [15], logistics [16] and agriculture [17] are also actively assessing the merits of deploying individual mobile robots. These evaluations aim to validate the accrued benefits of single-unit deployments.…”

Section: Introductionmentioning

confidence: 99%

“…A DT (digital twin) is a copy of a physical object, environment and system that is connected and shares operational and functional data [35]. These areas have had significant development in recent years where the state-of-theart has improved due to physical attributes of robotic platforms [14,36,37], processing in computing (e.g. Nvidia and Intel processors), digital modelling [38][39][40] and wireless connectivity including developments in the Internet of things [41,42].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Lessons learned: Symbiotic autonomous robot ecosystem for nuclear environments

Mitchell,

Emor Baniqued,

Zahid

et al. 2023

IET Cyber-Syst and Robotics

Self Cite

View full text Add to dashboard Cite

Nuclear facilities have a regulatory requirement to measure radiation levels within Post Operational Clean Out (POCO) around nuclear facilities each year, resulting in a trend towards robotic deployments to gain an improved understanding during nuclear decommissioning phases. The UK Nuclear Decommissioning Authority supports the view that human‐in‐the‐loop (HITL) robotic deployments are a solution to improve procedures and reduce risks within radiation characterisation of nuclear sites. The authors present a novel implementation of a Cyber‐Physical System (CPS) deployed in an analogue nuclear environment, comprised of a multi‐robot (MR) team coordinated by a HITL operator through a digital twin interface. The development of the CPS created efficient partnerships across systems including robots, digital systems and human. This was presented as a multi‐staged mission within an inspection scenario for the heterogeneous Symbiotic Multi‐Robot Fleet (SMuRF). Symbiotic interactions were achieved across the SMuRF where robots utilised automated collaborative governance to work together, where a single robot would face challenges in full characterisation of radiation. Key contributions include the demonstration of symbiotic autonomy and query‐based learning of an autonomous mission supporting scalable autonomy and autonomy as a service. The coordination of the CPS was a success and displayed further challenges and improvements related to future MR fleets.

show abstract

A review: Challenges and opportunities for artificial intelligence and robotics in the offshore wind sector

Cited by 47 publications

References 18 publications

Condition-based structural health monitoring of offshore wind jacket structures: Opportunities, challenges, and perspectives

Condition-based structural health monitoring of offshore wind jacket structures: Opportunities, challenges, and perspectives

Robotics in Industry 4.0: A Bibliometric Analysis (2011-2022)

Lessons learned: Symbiotic autonomous robot ecosystem for nuclear environments

Contact Info

Product

Resources

About