Image segmentation is a fundamental but essential step in image processing because it dramatically influences posterior image analysis. Multilevel thresholding image segmentation is one of the most popular image segmentation techniques, and many researchers have used meta-heuristic optimization algorithms (MAs) to determine the threshold values. However, MAs have some defects; for example, they are prone to stagnate in local optimal and slow convergence speed. This paper proposes an enhanced slime mould algorithm for global optimization and multilevel thresholding image segmentation, namely ESMA. First, the Levy flight method is used to improve the exploration ability of SMA. Second, quasi opposition-based learning is introduced to enhance the exploitation ability and balance the exploration and exploitation. Then, the superiority of the proposed work ESMA is confirmed concerning the 23 benchmark functions. Afterward, the ESMA is applied in multilevel thresholding image segmentation using minimum cross-entropy as the fitness function. We select eight greyscale images as the benchmark images for testing and compare them with the other classical and state-of-the-art algorithms. Meanwhile, the experimental metrics include the average fitness (mean), standard deviation (Std), peak signal to noise ratio (PSNR), structure similarity index (SSIM), feature similarity index (FSIM), and Wilcoxon rank-sum test, which is utilized to evaluate the quality of segmentation. Experimental results demonstrated that ESMA is superior to other algorithms and can provide higher segmentation accuracy.

In this paper, the nonlinear stiffness of a polyester rope under dynamic loads at different temperatures was experimentally investigated. The effects and evolution of the average load, load period and load amplitude on dynamic stiffness were studied. The experimental results show that the dynamic stiffness at 30 °C was greater than that at 20 °C and 40 °C. This is because the dynamic stiffness reduced as the temperature and humidity increased, while in the closed thermostat, humidity decreased with an increase in temperature. In response to this phenomenon, a new set of empirical equations was proposed to consider temperature, humidity, and dynamic load based on the existing empirical formulas, by combining the experimental results. A set of experiments was conducted at 25 °C to verify the accuracy and applicability of the formula. The experimental results and the predicted results are in good agreement.

The gas–liquid two-phase flow patterns of subsea jumpers are identified in this work using a multi-sensor information fusion technique, simultaneously collecting vibration signals and electrical capacitance tomography of stratified flow, slug flow, annular flow, and bubbly flow. The samples are then processed to obtain the data set. Additionally, the samples are trained and learned using the convolutional neural network (CNN) and feature fusion model, which are built based on experimental data. Finally, the four kinds of flow pattern samples are identified. The overall identification accuracy of the model is 95.3% for four patterns of gas–liquid two-phase flow in the jumper. Through the research of flow profile identification, the disadvantages of single sensor testing angle and incomplete information are dramatically improved, which has a great significance on the subsea jumper’s operation safety.

Non-metallic armoured optoelectronic cable winch systems (NAOCWSs) play critical roles in facilitating signal transmission and powering subsea equipment. Due to the varying depths in these applications, deploying the entire cable length is unnecessary. However, the portion of the cable that remains coiled around the winch can generate an electromagnetic field, which may interfere with signal transmission and induce electromagnetic heating. This can lead to elevated temperatures within the system, affecting the cable’s lifespan. Consequently, this study examines the distributions of magnetic and temperature fields within the NAOCWS with different currents (10–30 A) and numbers of winding layers (1–10). Findings indicate that the magnetic flux density (MFD) changes periodically, and the period is closely related to the distance between the cables. At the centre of the cable, the flux density is minimum. Temperature distribution correlates with both current amplitude and the number of winding layers, where an increase in either parameter amplifies the temperature variance between the edge and intermediate cables within the same layer. The current does not affect the internal temperature distribution pattern. With the number of winding layers determined, the layer where the highest temperature of the system is located is well defined and does not vary with current.

In-line tensioning technology has significantly reduced the cost barriers that previously hindered the expansion of the floating offshore wind industry. However, assessing the impact of in-line tensioners on the dynamic response of floating offshore wind turbines (FOWTs) lacks effectiveness, and the relevant mooring configuration specifications are not complete. Thus, a fully coupled calculation method is introduced in this paper to solve the relevant issues in mooring systems with in-line tensioners using a classic spar platform model. Three distinct design scenarios were selected to study the variation in mooring configurations of in-line tensioners along different mooring lines and at varied positions within each line. The potential occurrence of reverse tension phenomena was deliberated and assessed. We identified the varying tension patterns at the fairlead and in-line tensioner locations in mooring systems with in-line tensioners, and the influence of such variations on platform dynamics. The findings also demonstrate that the appropriate configuration of in-line tensioners should be selected to avoid the risk of reverse tension. This research has potential to contribute to the security and economy of the deployment of this emerging in-line mooring method.

Offshore winches are crucial in marine engineering, particularly in marine scientific research and deep-sea exploration. The use of fibre ropes presents significant opportunities for the weight reduction of winches as a consequence of the low length–strength ratio and characteristics of corrosion resistance. Nonetheless, a challenge arises in underestimating the stress load levels in load assessments of multi-layer winch systems using synthetic fibre ropes. Traditional computational methods reliant on symmetrically rotational models fall short in accurately predicting and assessing practical applications. This paper introduces a finite element analysis model based on a non-rotationally symmetric approach with four surfaces subjected to various radial pressure on account of the deformation of the fibre ropes. In the design model, sixteen stress detection paths have been incorporated to identify and confirm non-linear stresses. The outcomes of the finite element simulations have been compared with experimental results with two synthetic fibre ropes, each with distinct deformation characteristics utilised. The findings demonstrate that the application of the model aligns well with experimental results, showcasing its relevance and practical value in real-world scenarios. Precise theoretical calculations and experimental validation are pivotal to ensuring that equipment reliability and safety are maintained alongside the pursuit of light-weighting.