Search Results (31)

The motion of ships in the ocean follows six degrees of freedom, and accurately measuring this motion is crucial for improving marine engineering operations. Among the six degree-of-freedom movement of ships, the change in ship heave freedom has the worst impact on offshore lifting operations. At present, the most common method for measuring heave displacement is by integrating heave acceleration twice. The heave motion of ships belongs to low-frequency motion, but the low-frequency band range is often easily overlooked. This paper first analyzes the wave spectrum to determine the dominant frequency range of ship heave motion under typical wind speeds, which is found to be between 0.22 Hz and 0.45 Hz. The accuracy of low-frequency ship heave displacement signals largely depends on the heave acceleration signal, and filtering acceleration signals in the low-frequency range is particularly difficult. To address this challenge, this paper proposes a low-frequency component filtering method for heave acceleration signal of marine ships, which effectively avoids the phase and peak-to-peak errors introduced by traditional filters. This method further improves the filtering performance of acceleration signals in the 0.2 Hz to 0.5 Hz low-frequency range and can provide the crane driver with a motion reference for the heave of the ship when the ship is performing lifting operations. Full article

This study investigates the dynamic behavior of an articulated boom offshore crane under various load application laws. The following steps were taken to perform numerical simulations using the finite-element method (FEM): Definition of the model’s geometry, materials, and boundary conditions. The modal analyses reveal significant resonance frequencies in the direction of load application (payload). The crane’s displacement, velocity, and acceleration responses are closely related to load application laws, specifically the time required to reach the structure’s full payload (epsilon). It is highly correlated with the dynamic factor (maximum acceleration multiplied by payload), which has a wide range of effects on the structure, including the effects of overstress, overturning, buckling, and so on. The main findings reveal a very strong exponential correlation, allowing the dynamic effect to be estimated as a function of epsilon time. This is a useful tool for increasing the safety and reliability of offshore lifting operations. Full article

Offshore cranes equipped with active motion compensation (AMC) systems play a vital role in marine engineering tasks such as offshore wind turbine maintenance, subsea operations, and dynamic load positioning under wave-induced disturbances. These systems rely on complex hydraulic actuators whose strongly nonlinear dynamics—often described by differential-algebraic equations (DAEs)—impose significant computational burdens, particularly in real-time applications like hardware-in-the-loop (HIL) simulation, digital twins, and model predictive control. To address this bottleneck, we propose a neural network-based surrogate model that approximates the actuator dynamics with high accuracy and low computational cost. By approximately reducing the original DAE model, we obtain a lower-dimensional ordinary differential equations (ODEs) representation, which serves as the foundation for training. The surrogate model includes three hidden layers, demonstrating strong fitting capabilities for the highly nonlinear characteristics of hydraulic systems. Bayesian regularization is adopted to train the surrogate model, effectively preventing overfitting. Simulation experiments verify that the surrogate model reduces the solving time by 95.33%, and the absolute pressure errors for chambers $p_1$ and $p_2$ are controlled within 0.1001 MPa and 0.0093 MPa, respectively. This efficient and scalable surrogate modeling framework possesses significant potential for integrating high-fidelity hydraulic actuator models into real-time digital and control systems for offshore applications. Full article

To address distributed mass payload (DMP) anti-swing control problems typified by offshore wind turbine blades, this paper adopts multi-body dynamics and rigid-flexible coupling modelling approaches. It derives the geometric constraints and static equilibrium equations for marine crane multipoint lifting of DMP, and establishes a dynamic coupling model considering ship roll and pitch environmental excitations. Then, under the maximum environmental excitation set in the experiment, the flexible cable parallel anti-swing system achieves swing suppression rates of 41.0% and 58.0% for the in-plane and out-of-plane angles of the DMP with regular geometric shape and mass distribution, respectively. For the DMP with irregular geometry and mass distribution, the suppression rates are 48.4% and 39.3% for the in-plane and out-of-plane angles, respectively. It is found that, after adjusting the lifting method and increasing the distance between the lifting points, the maximum in-plane angle of the payload decreases by 2.3%, while the out-of-plane angle maximum decreases by 52.0%. These results demonstrate the effectiveness of adjusting lifting methods in suppressing swing for irregular DMPs, thereby verifying the reliability and applicability of the flexible cable parallel anti-swing system and providing a reference for improving anti-swing performance and lifting efficiency in offshore DMP operations. Full article

Offshore cranes are widely used in important fields such as wind power construction and ship replenishment. However, large payloads such as wind turbine blades are hoisted by multiple steel wire ropes, which makes it difficult to directly control their movements; that is, the number of input degrees of freedom is less than that of the output degrees of freedom. In addition, compared with land cranes, offshore cranes are inevitably affected by waves, wind, etc. The transition from a fixed base to a dynamic base brings severe challenges to their oscillation suppression and precise positioning. At the same time, to improve operational efficiency, the hoisting operation of offshore cranes usually adopts velocity input control patterns that fit the habits of manual operation, and most of them are in the form of dual-axis linkage for pitch and hoisting. Therefore, this paper proposes a fast terminal sliding mode control method for double-pendulum offshore cranes with distributed-mass payloads (DMPs). First, a nonlinear dynamic model of offshore cranes considering DMPs is established, and a dynamic model based on acceleration input control patterns is acquired. Based on this, considering the variation in hoisting rope lengths, a novel adaptive control method is proposed. Finally, simulation results verify the effectiveness of the proposed method, and the robustness of the proposed method to DMP mass parameter uncertainty and disturbances is demonstrated. Full article

Dual marine lifting systems are complicated, fully actuated mechatronics systems with multi-input and multi-output capabilities. The anti-swing cooperative lifting control of dual marine lifting systems with dual ships’ sway, heave, and roll motions is still open. The uncertainty regarding system parameters makes the task of achieving stable performance more challenging. To adjust both the attitude and position of large distributed-mass payloads to their target positions, this paper presents a time-delay-based sliding mode-tracking controller for cooperative dual marine lifting systems impacted by sea wave disturbances. Firstly, a dynamic model of a dual marine lifting system is established by using Lagrange’s method. Then, a kinematic coupling-based cooperative trajectory planning strategy is proposed by analyzing the coupling relationship between the dual marine lifting system and dual ship motion. After that, an improved sliding mode tracking controller is proposed by using time-delay estimation technology, which estimates unknown system parameters online. The finite-time convergence of full-state variables is rigorously proven. Finally, the simulation results verify the designed controller in terms of anti-swing control performance. The hardware experiments revealed that the proposed controller significantly reduces the actuator positioning errors by 83.33% compared with existing control methods. Full article

To investigate the influencing factors on the operation of an offshore wind turbine installation ship, a neural network, as a machine-learning method, is built to predict and analyze the motion response of a floating derrick in the process of a lifting operation under an external environmental load. The numerical method for the double floating body, from the software SESAM/SIMA, is validated against the experiments. The numerical method is used to establish the floating derrick-lifting impeller model to obtain the motions of the ship and impeller and the coupling effect. Based on the numerical results, the BP neural network model is built to predict the ship’s operation. The results show that the BP neural network model for the floating derrick and impeller motion prediction is very feasible. Combined with the Rules for Lifting Appliances of Ships and Offshore Installations and the Noble Denton Guidelines for Marine Lifting Operations, the operation of the floating crane system can be determined based on the environmental parameters. Full article

The increasing demand for cost-effective floating offshore wind turbines (FOWTs) necessitates streamlined mass production and efficient assembly strategies. This research investigates the assembly and integration of 15 MW FOWT floaters, utilising a semi-submersible floater equipped with a 15 MW wind turbine. The infrastructure and existing port facilities of Taiwan are used as an example. The effectiveness of various assembly and integration strategies has been evaluated. The study outlines equipment and infrastructure requirements for on-quay floater and turbine assembly, comparing on-quay assembly to construction at remote locations and subsequent towing. Detailed analyses of port operations, crane specifications, and assembly procedures are presented, emphasising the critical role of crane selection and configuration. The findings indicate that on-quay assembly at one major port is feasible and cost-effective, provided that port infrastructure and operational logistics are optimised. This research offers insights and recommendations for implementing large-scale FOWT projects, contributing to advancing offshore wind energy deployment. Full article

The maintenance of the surface of steel structures is crucial for ensuring the quality of shipbuilding cranes. Various types of wall-climbing robots have been proposed for inspecting diverse structures, including ships and offshore installations. Given that these robots often operate in outdoor environments, their performance is significantly influenced by wind conditions. Consequently, understanding the impact of wind loads on these robots is essential for developing structurally sound designs. In this study, SolidWorks software was utilized to model both the wall-climbing robot and crane, while numerical simulations were conducted to investigate the aerodynamic performance of the magnetic wall-climbing inspection robot under wind load. Subsequently, a MATLAB program was developed to simulate both the time history and spectrum of wind speed affecting the wall-climbing inspection robot. The resulting wind speed time-history curve was analyzed using a time-history analysis method to simulate wind pressure effects. Finally, modal analysis was performed to determine the natural frequency and vibration modes of the frame in order to ensure dynamic stability for the robot. The analysis revealed that wind pressure predominantly concentrates on the front section of the vehicle body, with significant eddy currents observed on its windward side, leeward side, and top surface. Following optimization efforts on the robot’s structure resulted in a reduction in vortex formation; consequently, compared to pre-optimization conditions during pulsating wind simulations, there was a 99.19% decrease in induced vibration displacement within the optimized inspection robot body. Modal analysis indicated substantial differences between the first six non-rigid natural frequencies of this vehicle body and those associated with its servo motor frequencies—indicating no risk of resonance occurring. This study employs finite element analysis techniques to assess stability under varying wind loads while verifying structural safety for this wall-climbing inspection robot. Full article

This study presents an integrated methodology for evaluating operations and maintenance (O&M) costs for floating offshore wind turbines (FOWTs), incorporating vessel motion dynamics. By combining UWiSE, a discrete-event simulation tool, with SafeTrans, a voyage simulation software, vessel motion effects during offshore operations are modeled. The approach is demonstrated in a case study at two wind farm sites, Marram Wind and Celtic Sea C. Three major component replacement (MCR) strategies were assessed: Tow-to-Port (T2P), Floating-to-Floating (FTF), and Self-Hoisting Crane (SHC). The T2P strategy yielded the highest O&M costs—94 kEUR/MW/year at Marram Wind and 97 kEUR/MW/year at Celtic Sea C—due to the extended MCR durations (90–180 days), leading to lower availability (90–94%). In contrast, the FTF and SHC strategies offered significantly lower costs and downtime. The SHC strategy was most cost-effective, reducing costs by up to 64% while achieving 97–98% availability. The integrated approach was found to be either more restrictive or more permissive depending on the specific sea states influencing the motion responses. This variability highlights the critical role of motion-based dynamics in promoting safe and efficient O&M practices, particularly for advancing FOWT operations. Full article

With the increased scale and deployment of floating wind turbines in deep sea environments, jack-up installation vessels are unable to conduct maintenance operations due to limitations in water depth. This has led to the recognition of the advantages of floating cranes in offshore maintenance activities. However, the dynamic coupling between the crane and the floating wind turbine under wave and wind action can result in complex responses, which also relate to complex mooring configurations. The ability to maintain stability during maintenance operations has become a primary concern. In order to address this issue, a method of connecting a floating crane with a floating wind turbine is proposed, simulating the berthing of a floating offshore wind turbine (FOWT) to a crane. Thus, a systematic comparison was conducted with frequency- and time-domain simulation using ANSYS-AQWA software. The simulation results demonstrated the feasibility and dynamic efficiency of this novel berthing approach. Connecting the crane vessel to a floating wind turbine significantly reduced the crane tip movement. Simulations showed that the crane tip movement in the X-, Y-, and Z-directions was reduced by over 30%, which implies that it may be feasible to conduct offshore on-site maintenance operations for the FOWT by using floating crane vessels if the two bodies were properly constrained. Full article

The Revolving Floating Crane (RFC) is a specialized engineering vessel crucial for offshore lifting operations, such as offshore platform construction and deep-water salvaging. It boasts impressive lifting capacity, good adaptability to various environmental conditions, and high operational efficiency. Conventionally, the safety and stability of RFC operations heavily depend on manual ballast water allocation, which is directly influenced by factors such as personnel status and sea conditions. These manual operations often result in reduced lifting efficiency, higher energy consumption, and compromised operational safety. In response, this paper introduces a ballast water-allocation approach based on the Point-to-Point (PTP) theory for the intelligent operation process of the RFC. The fundamental principles of the PTP theory are analyzed, and a method tailored to optimize ballast water allocation for RFC is proposed. Considering the unique characteristics of the ballast system and the specific requirements of lifting operations, an optimization model for PTP-based ballast water allocation is established. Numerical experiments are conducted to verify the efficacy and reliability of the proposed method. Comparing it to the conventional approaches, the results demonstrate a notable 17.75% reduction in energy consumption and an impressive 73.49% decrease in decision-making time, showcasing the superiority of the proposed approach. Finally, the engineering feasibility of the PTP-based optimization method for ballast water allocation is validated through actual lifting experiments, underscoring its potential to enhance RFC operations. Full article

Floating structures have become a major part of offshore structure communities as offshore engineering moves from shallow waters to deeper ones. Floating installation ships or platforms are widely used in these engineering operations. Unexpected wave-induced motions affect floating structures, especially in harsh sea conditions. Horizontal motions on the sea surface can be offset by a dynamic positioning system, and heave motions can be controlled by a heave compensation system. Active heave compensation (AHC) systems are applied to control vertical heave motions and improve safety and efficiency. Predictive control based on machine learning prediction algorithms further improves the performance of active heave compensation control systems. This study proposes a predictive control strategy for an active heave compensation system with a machine learning prediction algorithm to minimise the heave motion of crane payload. A predictive active compensation model is presented to verify the proposed predictive control strategy, and proportion–integration–differentiation control with predictive control is adopted. The reliability of back propagation neural network (BPNN) and long short-term memory recurrent neural network (LSTM RNN) prediction algorithms is proven. The influence of the predictive error on compensation performance is analysed by comparing predictive feedforward cases with actual-data feedforward cases. Predictive feedforward control with regular and irregular wave conditions is discussed, and the possible strategies are examined. After implementing the proposed predictive control strategy based on a machine learning algorithm in an active heave compensation system, the heave motion of the payload is reduced considerably. This investigation is expected to contribute to the motion control strategy of floating structures. Full article

Waves have an important influence on the motion performances of offshore crane vessels. The floating crane vessel in waves gives rise to the motion of the lifted object which is connected to the hoisting wire. Based on the geometric parameters of a revolving offshore crane vessel, combined with the specific process of the floating crane vessel at work, a model of the offshore crane vessel under full-circle swing hoisting has been established by OrcaFlex. With the change in wave direction, the dynamic response of the system is made and the impact force between the support vessel and the hanging object and the tension of the crane wire under different wave directions is obtained. At the same time, the minimum impact forces between the support vessel and the hanging object and the tension of the crane wire and their wave directions are obtained. According to the calculated result, the optimal design of the full-circle swing hoisting operation of large revolving offshore crane vessel has been determined. Full article

As important equipment in offshore engineering and freight transportation, shipboard cranes, working in non-inertial coordination systems, are complicated nonlinear systems with strong couplings and typical underactuation. To tackle the challenges in the controller design for shipboard boom cranes, which is a representative type of shipboard cranes, a comprehensive framework embedding moving horizon estimation (MHE) in model predictive control (MPC) is constructed in this paper while considering disturbances and noise. By utilizing MHE, velocity information can be estimated with high precision even though this is influenced by disturbances and measurement noises. This expected superiority can greatly ease the difficulties in directly measuring all states of shipboard boom cranes. Then, the estimated information can be passed to MPC to derive the optimal control law by solving a constrained optimal problem. During this process, the physical limits of shipboard boom cranes are fully considered. Therefore, the practicability of the proposed framework is highly suitable for the actual requirements of shipboard boom cranes. Finally, the framework is verified by designing three typical scenarios with different disturbances and/or noises. Comparisons with other control approaches are also performed to demonstrate the effectiveness. Full article