Development Of Marine Resources Research Articles

Regional significant wave height forecast in the East China Sea based on the Self-Attention ConvLSTM with SWAN model

Accurate prediction of regional significant wave heights is crucial for marine resource development, especially in areas with limited wave observations. This paper proposes a method for predicting regional significant wave heights by integrating the numerical wave model Simulating Wave Nearshore (SWAN) with the spatio-temporal prediction network Self-Attention ConvLSTM. The SWAN model is used to simulate regional significant wave heights in the East China Sea. To improve simulation accuracy, calibration of wind input, whitecapping dissipation, quadruplet wave–wave interactions, and bottom friction parameterization schemes in the model source terms were conducted, resulting in a simulated correlation coefficient of 0.97 with measured significant wave heights. The regional significant wave height training dataset constructed using the SWAN model preserves the intrinsic relationships between waves, wind speed, and wind direction over a recent period. Subsequently, a regional prediction system is built based on the output of the SWAN model, integrating the self-attention mechanism into the spatio-temporal prediction model ConvLSTM to construct SA-ConvLSTM. This model extracts correlated features among regional waves from the training dataset to predict future significant wave heights at different time intervals. The prediction performance of four spatio-temporal forecasting networks was compared to verify the accuracy of the SA-ConvLSTM model. The average errors in predicting regional significant wave heights at 3, 6, and 12 h were 0.07 m, 0.09 m, and 0.09 m, respectively. The R-Square metrics for these three prediction intervals were 0.85, 0.78, and 0.7, respectively.

Transparent coating based on multienzyme-mimicking Janus nanozyme for synergetic biofouling control in seawater

The problem of marine biofouling persists in marine resource development, particularly for marine observation. While nanomaterials with enzyme-mimicking activity show promise in combating marine biofouling, their unique physicochemical properties that enable nanozymes with multiple enzymatic activities for a synergetic antifouling effect have yet to be explored. Here, it is shown that a transparent zwitterionic coating based on Ag/Ag2S Janus nanoparticles (Ag/Ag2S JNPs) with peroxidase-, light-activated oxidase-, and haloperoxidase-mimicking activities contributes to antifouling synergy. The mechanism of the nanozyme action is revealed in a detailed experimental and computational study, in which unique Janus structures guarantee multi-enzyme-mimicking properties and produce OH, HOBr, and O2− to combat biofouling. Through the formation of hydration layers, zwitterionic coatings further enhance this antifouling capacity, as demonstrated by both indoor and outdoor marine field antifouling tests. Consequently, a coating like this shows a clear transmittance and excellent antifouling ability after 90 days in marine immersion, reducing fouling by 74.91 % and 39.71 % compared to a control coating and a commercial coating, respectively. This study not only demonstrates synergetic antifouling actions via multi-enzyme-mimicking activities but also uncovers a new paradigm in nanozyme-based environmentally friendly, sustainable antifouling strategy.

A Method for Multi-AUV Cooperative Area Search in Unknown Environment Based on Reinforcement Learning

As an emerging direction of multi-agent collaborative control technology, multiple autonomous underwater vehicle (multi-AUV) cooperative area search technology has played an important role in civilian fields such as marine resource exploration and development, marine rescue, and marine scientific expeditions, as well as in military fields such as mine countermeasures and military underwater reconnaissance. At present, as we continue to explore the ocean, the environment in which AUVs perform search tasks is mostly unknown, with many uncertainties such as obstacles, which places high demands on the autonomous decision-making capabilities of AUVs. Moreover, considering the limited detection capability of a single AUV in underwater environments, while the area searched by the AUV is constantly expanding, a single AUV cannot obtain global state information in real time and can only make behavioral decisions based on local observation information, which adversely affects the coordination between AUVs and the search efficiency of multi-AUV systems. Therefore, in order to face increasingly challenging search tasks, we adopt multi-agent reinforcement learning (MARL) to study the problem of multi-AUV cooperative area search from the perspective of improving autonomous decision-making capabilities and collaboration between AUVs. First, we modeled the search task as a decentralized partial observation Markov decision process (Dec-POMDP) and established a search information map. Each AUV updates the information map based on sonar detection information and information fusion between AUVs, and makes real-time decisions based on this to better address the problem of insufficient observation information caused by the weak perception ability of AUVs in underwater environments. Secondly, we established a multi-AUV cooperative area search system (MACASS), which employs a search strategy based on multi-agent reinforcement learning. The system combines various AUVs into a unified entity using a distributed control approach. During the execution of search tasks, each AUV can make action decisions based on sonar detection information and information exchange among AUVs in the system, utilizing the MARL-based search strategy. As a result, AUVs possess enhanced autonomy in decision-making, enabling them to better handle challenges such as limited detection capabilities and insufficient observational information.

China's Legal Governance Approaches toward Safeguarding Its Maritime Rights and Interests

Ocean development is crucial for modern states, and the importance of safeguarding and developing ocean rights and interests is becoming increasingly apparent. Economic development relies on the ocean, as does national sovereignty, security, and interests. In addition, national political and military development also depends on the ocean. China has long been committed to safeguarding its own ocean rights and interests, while also actively promoting the development of the international legal order for the ocean. In terms of international legislation, the United Nations Convention on the Law of the Sea provides a legal basis for safeguarding ocean rights and interests and plays a regulatory role in the maintenance of maritime rights and interests for all states. In terms of domestic legislation, many ocean laws in China play an important role in safeguarding China's maritime security and ocean rights and interests. As an important part of the legal system for safeguarding ocean rights and interests, maritime law enforcement has practical significance in the application of national jurisdiction at sea. China's maritime law enforcement, centered on safeguarding ocean rights and interests, is carried out by the reorganized China Coast Guard, guided by domestic and international legal norms, and strictly combats illegal and criminal activities at sea through international cooperation to protect the sustainable development of marine resources and environment and to safeguard international maritime public security and order while guaranteeing ocean rights and interests. In terms of judicial practice, China has already used legal means to effectively safeguard ocean rights and interests in the areas of marine environmental protection, maritime rights protection, fisheries law enforcement, and maritime traffic safety.

A framework for assessing the blue equity of social-ocean systems in marine governance transformation

The equitable utilization of marine resources and the maintenance of healthy and sustainable marine ecosystems are essential to advancing the United Nations Sustainable Development Goals (SDGs) and promoting the well-being of all humanity. In this paper, we propose a Blue Equity Assessment Framework, which is based on a systematic literature review approach and takes into account the characteristics of Social-Ocean Systems (SOSs). The framework consists of Distributional Equity, Procedural Equity, Recognitional Equity, and Contextual Equity. The aim of this framework is to conduct equity analyses of policies or behaviors within SOSs in order to assess whether blue equity is explicitly implemented and practiced in these societal norms and policy mechanisms. The assessment framework reveals that blue equity has a positive synergy for the majority of the SDGs. This synergy is analyzed in terms of its influence on the assessment dimensions of distributional justice, procedural justice, recognitional justice, and contextual justice. The findings aim to enhance societal understanding of blue equity issues, thereby guiding policymakers in the prioritization of blue equity in the development and utilization of marine resources and in the transformation of global ocean governance.

Research Progress of Advanced Design Method, Numerical Simulation, and Experimental Technology of Pumps in Deep-Sea Resource Exploitation

Amid the escalating global demand for raw materials, the gradual exhaustion of terrestrial mineral resources, and the rise in extraction costs and energy consumption, the development of deep-sea mineral resources has become a focal point of international interest. The pipeline lifting mining system, distinguished by its superior mining efficiency and minimized environmental impact, now accounts for over 50% of the total energy consumption in mining operations. Serving as the “heart” of this system, the deep-sea lifting pump’s comprehensive performance (high pressure tolerance, non-clogging features, elevated lift capacity, wear resistance, corrosion resistance, and high reliability, etc.), is critical to transport efficiency, operational stability, and lifespan of the mining system. As a mixed transport pump for solid and liquid media under extreme conditions, its internal flow structure is exceedingly complex, incorporating gas–liquid–solid multiphase flow. A precise understanding of its internal flow mechanisms is essential for breaking through the design limitations of deep-sea lifting pumps and enhancing their operational stability and reliability under various working conditions and multiphase media, thereby providing technical support for advancing global marine resource development and offshore equipment upgrades. This paper comprehensively reviews the design theory, optimization methods, numerical simulations, and experimental studies of deep-sea lifting pumps. It discusses the application of various design optimization techniques in hydraulic lifting pumps, details the multiphase flow numerical algorithms commonly used in deep-sea lifting pumps along with their modified models, and summarizes some experimental methodologies in this field. Lastly, it outlines the forthcoming challenges in deep-sea lifting pump research and proposes potential directions to promote the commercial development of deep-sea mining, thereby offering theoretical and engineering support for the development of deep-sea mining slurry pumps.

Real-time underwater object detection technology for complex underwater environments based on deep learning

Underwater object detection technology is crucial in many marine-related fields, including marine environmental monitoring, marine resource development, and marine ecological protection. However, this technology faces great challenges due to the poor quality of underwater optical images and the varying sizes of underwater objects. Therefore, we proposed an underwater optical detection network (UODN) based on the you only look once version 8 (YOLOv8) framework, which addresses these issues through the cross stage multi-branch (CSMB) module and large kernel spatial pyramid (LKSP) module. The aim of the CSMB module is to extract more features from underwater optical images to address the issue of poor image quality, while the LKSP module is designed to enhance the ability of the network to detect underwater objects of various scales. Furthermore, CSMBDarknet built by CSMB and LKSP can be used as the backbone of other underwater object detection algorithms for underwater feature extraction. Extensive experimental results on the underwater robot professional contest 2020 dataset revealed that the average precision (AP) of UODN increased by 1.0%, the AP50 of UODN increased by 1.1%, and the AP75 of UODN increased by 2.1% compared with those of the original YOLOv8s. Furthermore, UODN outperforms 12 state-of-the-art models on multiple underwater optical datasets, paving the way for future real-time and high-precision underwater object detection.

Coastal ecological security assessment in Laizhou Bay, China: from the perspective of demographic-social-economic-natural complex ecosystem.

Assessment of ecological security is essential for understanding the status of bay ecosystem and developing appropriate management strategy. Based on the driving force-pressure-state-impact-response (DPSIR) model, the demographic, economic, social, and ecological data of Laizhou Bay and its three neighboring counties were selected for the period from 2015 to 2021. An ecological security evaluation index system of Laizhou Bay containing 26 indicators was established, and the weights of each indicator were determined by the methods of AHP and EWM, and a comprehensive evaluation of the ecological security of Laizhou Bay was carried out by ESI. Correlations between indicators were analyzed by the Spearman's rank coefficient of correlation. The results showed that there were significant correlations between marine conditions and indicators such as population size in the surrounding area, mariculture area, industrial and domestic wastewater discharge, and treatment rate. Overall, from 2015 to 2021, the ecological security of Laizhou Bay showed a favorable trend, from a relatively unsafe level to a generally safe level, and then to a relatively safe level. Through the comprehensive evaluation of the ecological security of Laizhou Bay, we can recognize the utilization of marine resources and ecological carrying capacity, guide the rational development and utilization of marine resources, and promote the sustainable development of the marine economy.

Research on A Ship Trajectory Classification Method Based on Deep Learning

The unrestricted development and utilization of marine resources have resulted in a series of practical problems, such as the destruction of marine ecology. The wide application of radar, satellites and other detection equipment has gradually led to a large variety of large-capacity marine spatiotemporal trajectory data from a vast number of sources. In the field of marine domain awareness, there is an urgent need to use relevant information technology means to control and monitor ships and accurately classify and identify ship behavior patterns through multisource data fusion analysis. In addition, the increase in the type and quantity of trajectory data has produced a corresponding increase in the complexity and difficulty of data processing that cannot be adequately addressed by traditional data mining algorithms. Therefore, this paper provides a deep learning-based algorithm for the recognition of four main motion types of the ship from automatic identification system (AIS) data: anchoring, mooring, sailing and fishing. A new method for classifying patterns is presented that combines the computer vision and time series domains. Experiments are carried out on a dataset constructed from the open AIS data of ships in the coastal waters of the United States, which show that the method proposed in this paper achieves more than 95\% recognition accuracy. The experimental results confirm that the method proposed in this paper is effective in classifying ship trajectories using AIS data and that it can provide efficient technical support for marine supervision departments.

Optimization of Multibeam Survey Measurement Based on Greedy Algorithm

The effectiveness of multibeam bathymetric technology is widely recognized in marine depth measurements, especially in areas with complex and variable seafloor topography. This study aims to design a multibeam bathymetric survey plan for a specific maritime region, with the objectives of minimizing the total survey line length, ensuring comprehensive coverage of the target area, controlling the overlap between adjacent survey lines, and fully considering variations in seafloor topography. An optimization model was developed to determine the optimal route for comprehensive seafloor depth measurements within the specified maritime area.The model initially considers the influence of seafloor slope, establishing a single optimization objective model with the goal of minimizing the total survey line length. The decision variables primarily include the spacing between adjacent survey lines. The objective function of the model aims to reduce the number of survey lines, thereby achieving the minimization of the total survey line length. Constraints of the model encompass limitations on coverage range, calculations of coverage width, and relationships between survey lines. The model is solved using a greedy algorithm-based optimization approach, iteratively updating the positions of survey lines while determining the spacing based on the relationship between depth and coverage width. Ultimately, a layout of survey lines with the shortest total length, totaling 64 nautical miles with a configuration of 32 survey lines, is obtained for the assumed maritime area. Multibeam bathymetric technology holds broad prospects in the field of marine measurements, particularly in areas characterized by complex and variable seafloor topography. This study, by designing a multibeam bathymetric survey plan for a specific maritime region, not only contributes to improving measurement efficiency and accuracy but also reduces measurement costs and resource consumption. The outcomes of this research have significant practical implications for marine resource development, seafloor engineering construction, environmental protection, providing professionals in related fields with an effective measurement method and optimization strategy.

Multi-source remote sensing big data mining reveals cross-regional correlation between aquaculture and Enteromorpha disaster outbreaks

ABSTRACT Marine aquaculture is one of the most important marine resource utilization types, widely distributed in seashore areas. Because mass marine aquaculture development will lead to the eutrophication disaster of macroalgae blooms (green tide), it is imperative to discover the latent relationship. Inspired by the big data analysis theory, the spatiotemporal correlation change in 2017 and 2019 of the marine aquaculture and macroalgae blooms in Jiangsu Shoal in the West of the Yellow Sea and its adjacent seas were monitored and extracted respectively based on multi-source remote sensing images. Through optical and Synthetic Aperture Radar (SAR) images, the imaging characteristics of marine aquaculture in different growth cycles and sea conditions are analyzed. The relationship between the green tide and marine aquaculture harvest was explored from the early green algae distribution and spatiotemporal distribution changes. The earliest harvest area of marine aquaculture is the exact location of the outbreak of green tide. Along with the rapid reduction of aquaculture area, the distribution range of green tide gradually increased. The two showed opposite trends through many multi-source remote sensing data statistical analyses. Therefore, they have a strong correlation, which can be utilized to offer a significant value for the balance of marine environmental protection and resource development.

Fault-Tolerant Control of Autonomous Underwater Vehicle Actuators Based on Takagi and Sugeno Fuzzy and Pseudo-Inverse Quadratic Programming under Constraints.

Autonomous Underwater Vehicles (AUVs) play a significant role in ocean-related research fields as tools for human exploration and the development of marine resources. However, the uncertainty of the underwater environment and the complexity of underwater motion pose significant challenges to the fault-tolerant control of AUV actuators. This paper presents a fault-tolerant control strategy for AUV actuators based onTakagi and Sugeno (T-S) fuzzy logic and pseudo-inverse quadratic programming under control constraints, aimed at addressing potential actuator faults. Firstly, considering the steady-state performance and dynamic performance of the control system, a T-S fuzzy controller is designed. Next, based on the redundant configuration of the actuators, the propulsion system is normalized, and the fault-tolerant control of AUV actuators is achieved using the pseudo-inverse method under thrust allocation. When control is constrained, a quadratic programming approach is used to compensate for the input control quantity. Finally, the effectiveness of the fuzzy control and fault-tolerant control allocation methods studied in this paper is validated through mathematical simulation. The experimental results indicate that in various fault scenarios, the pseudo-inverse combined with a nonlinear quadratic programming algorithm can compensate for the missing control inputs due to control constraints, ensuring the normal thrust of AUV actuators and achieving the expected fault-tolerant effect.

ATSEA: A Regional Collaboration to Address Transboundary Threats to Ecosystems for Human Well-Being in the Arafura and Timor Seas

The Arafura and Timor Seas (ATS) are home to a wealth of both living and non-living marine resources, including major fisheries, significant oil and gas reserves, extensive coastal and marine habitats, and globally-significant populations of migratory, rare, threatened, and endangered marine species. These resources provide goods and services valued at more than US$7.3B to neighboring nations, annually. The waters of the ATS are bounded by Indonesia, Timor-Leste, Papua New Guinea and Australia; and significantly, are defined as a ‘semi-enclosed seas’ under the 1982 United Nations Convention on the Law of the Sea (UNCLOS). UNCLOS places a responsibility and an obligation on countries bordering enclosed and semi-enclosed seas to cooperate in resource management, the protection of the marine environment and marine scientific research. Recent assessments indicate that the marine environment in the ATS region is in serious decline, primarily as a result of over-harvesting and other direct and indirect impacts of anthropogenic stresses and global climate change. Transboundary issues such as unsustainable and illegal fishing activities, marine and land-based pollution, marine habitat and biodiversity decline, and climate change negatively impact fishery resources, ecosystem quality, and human well-being. Over the past 2 decades ATS littoral countries have progressed toward transboundary management of the region. This paper elaborates on the current status and threats to coastal and marine resources in the ATS region and in particular, the major efforts of the four littoral ATS countries to address transboundary environmental issues at the regional, national, and project site levels through the US$9.7M, 5-year, UN GEF-funded ATSEA-2 program. A key result of the ATSEA Program is regional collaboration that supports stakeholder engagement for meaningful resource management and protection is essential for the sustainable use and development of marine resources in the ATS.

Real-time safety risk assessment of floating offshore platforms based on on-site monitoring

Real-time safety risk assessment of in-service marine engineering structures is one of the key components for the intelligent development of marine resources. Floating platforms typically have weak modes and time-varying characteristics, and hence, traditional structural damage identification and safety assessment methods cannot be directly applied to floating platforms. The objective of this study was to achieve the real-time safety risk assessment of in-service floating platforms. First, a structural damage identification method for floating platforms was proposed based on virtual loads, and the physical parameters of the platforms were obtained through inversion of measurable data. The identification result was verified based on the lengths and stiffnesses of polyester cables, which affected the dynamic response of the floating platform. The results showed that the proposed method effectively detected the parameter changes of the platform during long-term service. Then, the neural network was used to construct a load–stress surrogate model at key positions of the floating offshore platform. This model could calculate the stresses at key positions in real time, thereby evaluating the safety risks of the platform. Lastly, a real-time safety risk assessment method for floating offshore platforms was proposed, which provides a technical solution for ensuring the safety of offshore platforms.

Analysis of Chinese Patents on Cathodic Protection by Applied Current Method in Marine Sector

The resource problem is the top priority of China's current development, while the ocean is an inexhaustible treasure. The development and utilization of marine resources has always been the key direction of development. The characteristics of offshore engineering operation equipment are: first, the scale of the platform is particularly large, and second, it is long-term in the harsh environment such as moisture and salinity [1]. Therefore, the anti-corrosion of offshore platforms is the research hotspot of relevant technicians, this paper systematically summarizes the patent application of external current in cathodic protection of anti-corrosion technology. It analyzes the patent type, affiliated institution, important applicant, application field and other related contents. The results show that enterprises prefer to actually invent devices, while scientific research institutions, universities and colleges are more about the creation of technical methods.

Effect of marine ecological compensation policy on coastal water pollution: Evidence from China based on a multiple period difference-in-differences approach

With the development and utilization of marine resources, coastal water pollution has become increasingly prominent. The marine ecological compensation (MEC) is a key measure to balance the utilization of marine resources and the protection of marine environment. This paper attempts to explore the governance effect of MEC policy on coastal water pollution. Based on panel data of coastal cities in China from 2006 to 2020, a multiple period difference-in-differences (DID) model is used to estimate the impact of MEC policy on coastal water pollution. The research results show that the coastal water pollution has decreased significantly in the polit cities after implementing the MEC policy. The governance effect of MEC policy on coastal water pollution will last for three year and cover areas within a geographical distance of 200 km. The transmission mechanisms of MEC policy on coastal water pollution are the reduction of land-based sewage, marine technological progress and optimization of industrial structure. Further, this paper provides operational suggestions for strengthening the governance effect of MEC policy on coastal water pollution.

Comparative analytical study of suction drum foundation penetration characteristics of guide frame platforms with real measurements.

A suction bucket foundation is a new type offering high construction efficiency, precise positioning, cost-effectiveness, and environmental friendliness. It has been extensively employed in marine resource development, particularly in offshore wind power and oil and gas extraction. It usually involves multiple suction bucket conduit rack platforms during offshore construction projects. Accurately predicting the sinking penetration resistance and determining the suction value is crucial during the construction of the suction bucket foundation, as it ensures the safe sinking of the platform foundation to the designated depth. This paper examines the feasibility of the suction bucket foundation's sinking, sinking penetration resistance, suction value, and self-weight penetration depth, using the offshore wind farm guiding frame platform foundation project in Yangjiang, Guangdong Province, as a basis of analysis. The measured data is analyzed using the API specification static equilibrium analysis method, ABAQUS finite element analysis, and data mining techniques. The suction drum base platform's sinking process was monitored for negative pressure and penetration resistance. These observed values were compared to theoretical and finite element calculations. Results demonstrated that the API specification's theoretical calculations and finite element analyses effectively predict sinking penetration resistance, the suction force value, and the penetration depth for self-gravitational penetration. On-site engineering data fit these theoretical calculations, and finite element analyses well. The findings from this study have enriched the engineering application database of the suction drum foundation, providing a valuable reference for the design and construction of similar projects and establishing the groundwork for further promotion and application.

CSEF-Net: Cross-Scale SAR Ship Detection Network Based on Efficient Receptive Field and Enhanced Hierarchical Fusion

Ship detection using synthetic aperture radar (SAR) images is widely applied to marine monitoring, ship identification, and other intelligent maritime applications. It also improves shipping efficiency, reduces marine traffic accidents, and promotes marine resource development. Land reflection and sea clutter introduce noise into SAR imaging, making the ship features in the image less prominent, which makes the detection of multi-scale ship targets more difficult. Therefore, a cross-scale ship detection network for SAR images based on efficient receptive field and enhanced hierarchical fusion is proposed. In order to retain more information and lighten the weight of the network, an efficient receptive field feature extraction backbone network (ERFBNet) is designed, and the multi-channel coordinate attention mechanism (MCCA) is embedded to highlight the ship features. Then, an enhanced hierarchical feature fusion network (EHFNet) is proposed to better characterize the features by fusing information from lower and higher layers. Finally, the feature map is input into the detection head with improved bounding box loss function. Using SSDD and HRSID as experimental datasets, average accuracies of 97.3% and 90.6% were obtained, respectively, and the network performed well in most scenarios.

A regional digital bathymetric model fusion method based on topographic slope: A case study of the south China sea and surrounding waters

High-resolution seafloor topography is important in scientific research and marine engineering in regard to marine resource development and environmental protection monitoring. In this study, multi-dimensional comparisons were made between GEBCO_2022, SRTM15_V2.5.5, SRTM30_PLUS, SYNBATH_V1.0, ETOPO_2022, and topo_25.1 in the South China Sea and surrounding waters (SCS). This study has found that ETOPO_2022 had the best overall accuracy and reliability. Based on the results of the model accuracy analysis and by considering the topographic slope, ETOPO_2022, GEBCO_2022, and SRTM15_V2.5.5 were weighted and fused to form a fusion model. The error of the fusion model was 94.80% concentrated in (−100–100 m). When compared with GEBCO_2022, SRTM15_V2.5.5, SRTM30_PLUS, SYNBATH_V1.0, ETOPO_2022, and topo_25.1, the RMSE was reduced by 2%, 9%, 62%, 15%, 1%, and 73%, respectively. The slope-based weighted fusion method has been shown that it can overcome the limitations of a single data source and provide a reference for timely reconstruction and updating of large-scale seafloor topography.

Research on Multibeam Line Measurement Problem Based on Iterative Algorithms

With the continuous advancement of marine resource development, an efficient and reasonable multi beam acoustic survey line design scheme is crucial for accurate sea area measurement. Firstly, in order to make the model closer to the actual complex scene, a three-dimensional coverage model was derived that comprehensively considers the relative angle between the measurement line and the normal direction of the seabed terrain slope projected on the horizontal plane, referring to the three-dimensional sound beam propagation characteristics of multi beam sound waves. Then, based on the working principle and geometric relationship of multi beam recording, a formula for calculating the recording coverage width under multi-directional slope conditions considering measurement equipment parameters was derived, and an expression for the overlap rate of adjacent measurement lines was given. In addition, different measurement lines and slope normal direction angles . Finally, based on the actual sea area situation of the rectangular area within the specific given range, iteratively traverse and set different combinations of survey lines, calculate the total length of the combination and the corresponding coverage area, and calculate the coverage rate. Select the survey line combination with the shortest total length and the highest coverage rate as the optimal solution. This article focuses on the design of multi beam acoustic survey lines and establishes a universal mathematical model to achieve optimization solutions in different practical scenarios.