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Dynamic Modelling and Experimental Analysis of an Offshore Crane Payload Positioning System with a Parallel Cable-Driven Method Cover

Dynamic Modelling and Experimental Analysis of an Offshore Crane Payload Positioning System with a Parallel Cable-Driven Method

Open Access
|Jun 2024

Abstract

The violent swinging motion of a payload imposes significant safety problems for the operation of offshore ship-mounted cranes (offshore cranes). We therefore propose a stable experimental hoisting platform for an offshore crane payload positioning system with a parallel cable-driven method (PP-PCDM), and an adaptive cable-drive anti-swing tension (ACAT) control method based on the PP-PCDM is developed to resolve the problem of swinging of the payload by limiting its spatial position. The PP-PCDM enables synchronous tracking of the movement of the payload when the crane is working. When the payload deviates from a stable state due to an external disturbance, the anti-swing cables are immediately retracted or released based on the feedback signal. The spatial position of the payload is then limited by adjusting the length and tension of the parallel cables until the payload appears stationary from the perspective of the ship’s deck. Operational safety and efficiency is substantially improved, and the proposed PP-PCDM structure and ACAT control method can be applied to a variety of different types of cranes. The results of simulations and physical experiments show that the anti-swing effect exceeds 89.86%. The PP-PCDM enables excellent performance of synchronous tracking and hoisting assistance, and ensures that the rated lifting weight of the offshore crane is not affected.

DOI: https://doi.org/10.2478/pomr-2024-0019 | Journal eISSN: 2083-7429 | Journal ISSN: 1233-2585
Language: English
Page range: 29 - 45
Published on: Jun 22, 2024
Published by: Gdansk University of Technology
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2024 Zhaopeng Ren, Zhe Huang, Tingqi Zhao, Shenghai Wang, Yuqing Sun, Haiquan Chen, Nan Fang, published by Gdansk University of Technology
This work is licensed under the Creative Commons Attribution 4.0 License.