Search Results (22)

With the rapid development of offshore wind energy toward deep water, the structural safety of truss-type legs for jack-up wind turbine installation vessels (WTIVs) under complex operational and environmental loads has become a key concern. This study focuses on the directional coupling effect between crane slewing angles and wave directions, which has rarely been systematically investigated in previous research. A finite element model of a 1500 t-class WTIV truss leg is established using SESAM, and its reliability is verified by mesh convergence analysis and literature comparison. The influences of crane slewing angle, wave direction, and their coupling on structural displacement and stress are analyzed quantitatively, and strength evaluation is carried out under typical working conditions in accordance with classification society rules. The results show that the structural response presents significant directional dependence and stiffness anisotropy. The peak displacement and stress occur at a crane slewing angle of 270°, with the maximum displacement approximately 33% higher than the minimum value. Obvious response amplification is observed when the crane slewing angle and wave direction are aligned within 225–270°, which constitutes the most unfavorable loading combination. The strength assessment demonstrates that all conditions meet the specification requirements, and the survival condition is the most critical, with a maximum stress of 289.66 MPa and a maximum displacement of 338.6 mm. This study reveals the coupling mechanism between operational loads and environmental loads and identifies the critical dangerous angle sector. The research findings can provide reasonable references for offshore lifting operation management and operational planning of marine truss leg structures. Full article

This paper develops accurate three-dimensional trajectory tracking and anti-sway control strategies for offshore container cranes operating in an open-sea environment. A 5-DOF nonlinear dynamic model is developed that simultaneously accounts for the crane’s structural motion, trolley movement, spreader hoisting with variable rope length, and both lateral and longitudinal payload sway. The model further incorporates external disturbances induced by wave-excited ship motions. To ensure smooth, efficient, and accurate load transportation from the initial to the target position, an effective trajectory-planning scheme is proposed using a quintic polynomial trajectory refined by a ZVD shaper to suppress residual oscillations. A sliding mode control method is then designed to achieve accurate trajectory tracking and load-sway suppression under external disturbances. Numerical simulations demonstrate that the proposed trajectory planning method effectively reduces the residual oscillations and verifies the effectiveness and robustness of the proposed sliding mode control strategy. Full article

This study focuses on the susceptibility and surface degradation of low-alloy carbon steel 42CrMo4 to corrosion and cavitation erosion, as this steel is widely used in marine environments with aggressive chemical species and harsh conditions. Due to its high strength and fatigue resistance, 42CrMo4 steel is often employed in offshore mechanical components such as shafts and fasteners as well as crane parts in ports and harbors. Various experimental methods, including corrosion and cavitation tests, were used to assess the steel’s surface integrity under extreme conditions. Surface changes were monitored using modern analytical tools for precise assessments, including image and morphological analyses, to quantify degradation levels and specific parameters of defects induced by corrosion and cavitation. Non-destructive techniques such as optical microscopy (OM), scanning electron microscopy (SEM), energy-dispersive spectroscopy (EDS), and image analysis software were employed for the quantitative assessment of morphological parameters and elemental analysis. EDS analysis revealed changes in elemental composition, indicating corrosion products that caused significant mass loss and defect formation, with degradation increasing over time. The average corrosion rate of 42CrMo4 steel in a 3.5% NaCl solution reached a peak value of 0.846 mm/year after 120 days of exposure. Cavitation erosion behavior was measured based on mass loss, indicating the occurrence of different cavitation periods, with the steady-state period achieved after 60 min. The number of formed pits increased until 120 min, after which it decreased slightly. This indicates that a time frame of 120 min was identified as significant for changes in the mechanism of pit formation. Specifically, up to 120 min, pit formation was the dominant mechanism of cavitation erosion, while after that, as the number of pits slightly declined, the growth and merging of formed pits became the dominant mechanism. The cavitation erosion tests showed mass loss and mechanical damage, characterized by the formation of pits and cavities. The findings indicate that the levels of surface degradation were higher for corrosion than for cavitation. The presented approach also provides an assessment of the degradation mechanisms of 42CrMo4 steel exposed to corrosive and cavitation conditions. Full article

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

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

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 use of wireless technology in common marine engineering applications as a medium for data transaction in measurement and control systems, is not as popular as it should be. This article aims to demonstrate the advantages of using wireless technology in maritime engineering applications through a proposed Wi-Fi based wireless system dedicated to performance and safety monitoring in marine cargo cranes. The system is based on some concepts that were suggested in the earlier literature to perform authenticated data transmission from multiple sensors through using both the ESP-NOW protocol and the WebSerial remote serial monitor. The introduced system will be integrated with an already installed system in order to render the means for implementing effective principles in automation and control engineering, such as functional safety and predictive maintenance. Additionally, this article will highlight the economic efficiency of adopting wireless technology instead of cabling as a medium for data transaction in measurement and control systems in marine engineering applications such as cargo cranes. Full article

Vessel-mounted cranes operate in complex marine environments, where precise measurement of cargo positions and attitudes is a key technological challenge to ensure operational stability and safety. This study introduces an integrated measurement system that combines vision and inertial sensing technologies, utilizing a stereo camera and two inertial measurement units (IMUs) to capture cargo motion in five degrees of freedom (DOF). By merging data from the stereo camera and IMUs, the system accurately determines the cargo’s position and attitude relative to the camera. The specific methodology is introduced as follows: First, the YOLO model is adopted to identify targets in the image and generate bounding boxes. Then, using the principle of binocular disparity, the depth within the bounding box is calculated to determine the target’s three-dimensional position in the camera coordinate system. Simultaneously, the IMU measures the attitude of the cargo, and a Kalman filter is applied to fuse the data from the two sensors. Experimental results indicate that the system’s measurement errors in the x, y, and z directions are less than 2.58%, 3.35%, and 3.37%, respectively, while errors in the roll and pitch directions are 3.87% and 5.02%. These results demonstrate that the designed measurement system effectively provides the necessary motion information in 5-DOF for vessel-mounted crane control, offering new approaches for pose detection of marine cranes and cargoes. Full article

Deep learning is crucial in marine logistics and container crane error detection, diagnosis, and prediction. A novel deep learning technique using Long Short-Term Memory (LSTM) detected and anticipated errors in a system with imbalanced data. The LSTM model was trained on real operational error data from container cranes. The custom algorithm employs the Synthetic Minority Oversampling TEchnique (SMOTE) to balance the imbalanced data for operational data errors (i.e., too few minority class samples). Python was used to program. Pearson, Spearman, and Kendall correlation matrices and covariance matrices are presented. The model’s training and validation loss is shown, and the remaining data are predicted. The test set (30% of actual data) and forecasted data had RMSEs of 0.065. A heatmap of a confusion matrix was created using Matplotlib and Seaborn. Additionally, the error outputs for the time series for the next n seconds were projected, with the n seconds input by the user. Accuracy was 0.996, precision was 1.00, recall was 0.500, and f1 score was 0.667, according to the evaluation criteria that were produced. Experiments demonstrated that the technique is capable of identifying critical elements. Thus, future attempts will improve the model’s structure to forecast industrial big data errors. However, the advantage is that it can handle imbalanced data, which is usually what most industries have. With additional data, the model can be further improved. Full article

The levels of informatization, automation, and intelligence are continuously improving; however, the risks associated with the increased design and operational complexity of ship systems are increasing. Large-scale ship accidents can occur for several reasons. Existing accident analysis methods that examine marine accidents from the perspective of causal one-to-one correspondence have limitations in systematically analyzing complex marine risks during cause identification for the prevention of similar accidents. This study focuses on a systematic causality analysis of the factors related to human error in marine accidents that may occur during the arrival and departure of mega container ships. In particular, a representative case of the Motor Vessel (MV) Milano Bridge crane contact accident at Busan New Port is considered. To explore the complex organizational–technical, human–technical, and organizational–human relationships relevant to this case, human factors (seafarer, pilot, etc.) that are closely related to the linked causes were analyzed using the functional resonance analysis method. This study aims to reduce human error and prevent marine accidents, including pilotage. Full article

During various marine container handling operations, performed mainly in larger-scale container terminals, containers get damaged regularly. Our previous studies showed that each physical impact results in some form of physical deformation of the backbone structure. Even at low accelerations, the spreaders of the quay cranes impact the containers with enough force to substantially bend the metal parts of the corners of the containers, when additional hooking procedures are required. This means that the first time resulted in the metal rods hitting the metal frame with an average 15-ton mass at the average speed of 1.7 m/s. The metal rods of the hooking mechanisms’ impact areas of the containers are structurally important, and each impact surely damages the containers, diminishing their total operational time. We have already proposed the Impacts Detection Methodology (IDM) and its application system, tested in Klaipeda City port, and it proved to be efficient in real-time operations, detecting concurrent impacts with each new handling cycle. In this paper, we provide a summarisation of a larger number of detections using the IDM, and as a result of this analysis, we have detected that more impact events happen when containers are taken from the upper parts of the ship, in comparison to the ones taken from the shafts. Results suggest that more critical events occur due to operator actions and experiences working with the machinery, yet the same operators tend to make fewer impact mistakes taking the containers from the shafts as the vertical cell guides tend to direct the movements and lower the levels of the natural sway of the spreader inside closed environments. This surely damages the metal infrastructure of the shafts, as seen in our previous study, but minimizes the chances of secondary impacts occurring during hooking. Full article

During the rough marine environment, heave compensation is used to offset the heave motion of the vessel when a marine crane lifts and lands the load. Thus, load motion and vessel motion are realized decoupled. In previous studies, the interference items such as hydraulic cylinder friction, underwater drag force and nonlinear friction in the active heave compensation system of a marine hydraulic crane are compensated as a concentrated interference force to be estimated. In this paper, we disassembled the interference items; the disturbance observer and adaptive rate are designed to estimate unmodeled disturbance force and system uncertain parameters, respectively; and we designed an active heave compensator with the adaptive nonlinear cascade controller which has the disturbance observer (DOB-ANCC). For the heave compensation of load displacement, this paper derived the control law of the nonlinear system model based on the backstepping method. The outer loop control is displacement control and the inner loop control is pressure control. The simulation verifies the effectiveness of the control strategy proposed in this paper and the availability of heave displacement compensation for a marine crane hoisting load. The compensation efficiency of the designed controller (DOB-ANCC) for the heave motion of the load can reach more than 95%, and the maximum displacement tracking error of the controller can reach ± 0.035 m. Full article

In seaports, low-carbon energy systems and energy efficiency have become increasingly important as a result of the evolution of environmental and climate change challenges. In order to ensure the continued success of seaports, technological advancements must be introduced to a number of systems, such as seaport vehicles, harbor cranes, and the power sources of berthed ships. Harbor areas might need a microgrid to handle these aspects. Typically, microgrids that substitute conventional generator units with renewable energy sources (RES) suffer from system inertia problems, which adversely affect microgrid frequency stability. A load frequency controller (LFC) based on a novel modified proportional integral derivative with filter (MPIDF) is presented in this paper for enhancing the performance of marine microgrid system (MMS). The serval optimization algorithm (SOA), a recent bio-inspired optimization algorithm, is used to optimize the MPIDF controller coefficients. This controller is tested on a marine microgrid containing a number of RES such as wind turbine generators, sea wave energy, and solar generation. The efficacy of the proposed MPIDF controller is verified with respect to other controllers such as PIDF and PI. Similarly, the proposed meta-heuristic algorithm is validated as compared to other algorithms including particle swarm optimization (PSO), ant colony optimization (ACO), and jellyfish swarm optimization (JSO). This study also evaluates the robustness of the proposed controller to different perturbations in step load, changes in system parameters, and other parameter variations. Full article