Abstract
Regular dry dock maintenance work on ship hulls is essential for maintaining the efficiency and sustainability of the shipping industry. Hydro blasting is one of the major processes of dry dock maintenance work, where human labor is extensively used. The conventional methods of maintenance work suffer from many shortcomings, and hence robotized solutions have been developed. This paper proposes a novel robotic system that can synthesize a benchmarking map for a previously blasted ship hull. A Self-Organizing Fuzzy logic (SOF) classifier has been developed to benchmark the blasting quality of a ship hull similar to blasting quality categorization done by human experts. Hornbill, a multipurpose inspection and maintenance robot intended for hydro blasting, benchmarking, and painting, has been developed by integrating the proposed SOF classifier. Moreover, an integrated system solution has been developed to improve dry dock maintenance of ship hulls. The proposed SOF classifier can achieve a mean accuracy of 0.9942 with an execution time of 8.42 µs. Realtime experimenting with the proposed robotic system has been conducted on a ship hull. This experiment confirms the ability of the proposed robotic system in synthesizing a benchmarking map that reveals the benchmarking quality of different areas of a previously blasted ship hull. This sort of a benchmarking map would be useful for ensuring the blasting quality as well as performing efficient spot wise reblasting before the painting. Therefore, the proposed robotic system could be utilized for improving the efficiency and quality of hydro blasting work on the ship hull maintenance industry.
Highlights
Routine dry dock maintenance on the outer hull of ships is essential for the efficient and sustainable operation of shipping [1,2]
The data set required for the training and testing was prepared by capturing images of blasted ship hulls through the robot’s camera
It can be concluded that the proposed benchmarking robotic system is capable of benchmarking the hydro blasting with adequate accuracy in realtime
Summary
Routine dry dock maintenance on the outer hull of ships is essential for the efficient and sustainable operation of shipping [1,2]. Many robots and devices have been developed for inspection and maintenance work of ship hulls to resolve the shortcoming of the conventional methods discussed above [9]. The scope of the work cited above is limited to the design and development of climbing robots or their adhesion mechanisms for inspection of ship hulls; the methods for automatic inspection and maintenance such as vision-based corrosion detection, are not discussed within the scope of the work. Much of the work is limited to the development of vision-based detection mechanisms for robots, and the ways for utilizing the detection outcomes as a fully integrated system for synthesizing a benchmarking map for an already blasted ship hull are not considered within the scopes.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
