Multi-layer fusion island power transmission submarine cable channel dynamic risk management and control method
By employing a multi-layer fusion-based 3D modeling and risk assessment method, the problems of data isolation and response lag in isolated submarine power transmission cable channels were solved, enabling real-time risk assessment and early warning for submarine cable channels and improving the efficiency and economic benefits of risk management.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-09
- Publication Date
- 2026-04-10
AI Technical Summary
Existing risk management methods for isolated submarine power transmission cable channels suffer from problems such as isolated data, insufficient visualization, and delayed response, resulting in low efficiency in risk assessment and difficulty in dealing with cascading failures during high-risk periods.
By employing a multi-layer fusion method, a 3D model is constructed using WebGL and the Cesium engine. Combined with the fuzzy AHP algorithm and the random forest algorithm, a multi-dimensional risk assessment index system is built to achieve real-time risk assessment and early warning response for submarine cable channels.
It has achieved three-dimensional information fusion and visual modeling of submarine cable channels, supports dynamic risk analysis, improves the timeliness of risk warning and operation and maintenance efficiency, and reduces operation and maintenance costs.
Smart Images
Figure CN121836359A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the technical field of submarine cable management and control, and in particular to a multi-layer fusion island power transmission submarine cable channel dynamic risk management and control method. BACKGROUND
[0002] At present, as the main energy artery connecting the mainland and offshore islands, the island power transmission submarine cable channel has unique complexity and vulnerability due to the influence of high pressure, high salt and high corrosion marine environment. The existing risk management and control system faces serious challenges in data integration dimension. Marine monitoring data is scattered in closed systems of different management departments: ship AIS (Automatic Identification System) trajectory data of the maritime department is updated every 15 minutes, the surveying and mapping precision of seabed topography of the natural resources department is limited to 50 meters, and the time resolution of marine environment monitoring data of the meteorological department is up to 6 hours. These heterogeneous data not only have deviations in coordinate systems, but also are incompatible in storage format and interface protocol. A provincial power company's operation and maintenance report in 2022 shows that its cross-sea cable project needs to interface with 7 independent databases, and only data cleaning and coordinate conversion consumes 63% of the operation and maintenance analysis time, which seriously restricts the risk judgment efficiency. This risk judgment hysteresis is prone to cause chain failures and threaten regional power supply safety during high-risk periods such as typhoon season.
[0003] In the existing island power transmission submarine cable channel risk management and control method, part of the method is based on two-dimensional GIS (Geographic Information System) platform to realize the visualization integration of submarine cable position data, and to realize early warning by setting risk threshold. This kind of scheme mainly focuses on the superposition display and static alarm mechanism of power transmission line and meteorological data, and has defects such as insufficient visualization, poor predictability caused by single-layer data, and inability of static analysis to reflect multi-factor risk. Part of the method introduces point cloud data and three-dimensional modeling algorithm, aiming to improve the expression accuracy of the seabed environment through fine modeling. This kind of scheme mainly realizes risk identification through laser radar point cloud collection, model reconstruction and collision analysis, and has defects such as lack of real-time, lack of multi-source data fusion mechanism, and lack of management and control and alarm processing measures.
[0004] For the related technologies in the above, the inventors believe that the risk management and control method of the island power transmission submarine cable channel has the defects of data isolation, insufficient visualization and response lag. SUMMARY
[0005] To address the issues of data isolation, insufficient visualization, and delayed response in existing risk management methods for isolated submarine power transmission cable channels, this application provides a multi-layer fusion-based dynamic risk management method for such channels. This method integrates three-dimensional information of the submarine power transmission cable channel and performs visual modeling. It also establishes a multi-factor dynamic evaluation mechanism for risk assessment and promptly invokes corresponding early warning response strategies for risk warning. This improves the timeliness of risk warning response and helps to enhance the operational efficiency and economic benefits of risk management for submarine power transmission cable channels.
[0006] Firstly, the aforementioned inventive objective of this application is achieved through the following technical solution: A method for dynamic risk management of isolated submarine power transmission cable channels with multi-layer fusion, the method comprising: Multi-source heterogeneous data of isolated island power transmission submarine cable channels are acquired, and the multi-source heterogeneous data is preprocessed to obtain a spatiotemporally consistent multi-layer dataset. The multi-layer dataset is divided into layers, and 3D modeling is performed using WebGL and Cesium engine according to the layer division results to construct a multi-layer 3D model of the isolated island power transmission submarine cable channel. Risk factors of submarine cables are extracted from the multi-layer dataset. A multi-dimensional risk assessment index system for power transmission submarine cable channels is constructed using the fuzzy AHP algorithm and the random forest algorithm. The risk assessment mechanism of the multi-layer three-dimensional model is then optimized. The current status of the power transmission submarine cable channel is assessed based on the multi-dimensional risk assessment index system, and an early warning mechanism corresponding to the risk level is matched to the risk assessment results for early warning response.
[0007] In a preferred embodiment, this application can be further configured as follows: the step of dividing the multi-layer dataset into layers and performing 3D modeling according to the layer division results using WebGL and the Cesium engine to construct a multi-layer 3D model of the isolated island power transmission submarine cable channel specifically includes: The multi-layer dataset is divided into layers based on the data source, including a basic geographic layer, a submarine cable layer, an environmental dynamic layer, and a risk density layer; The model is constructed using WebGL and the Cesium engine based on the layer division results, creating a multi-layer 3D model. The layer information and layer relationships of the multi-layer dataset are then visualized.
[0008] In a preferred embodiment, this application can be further configured as follows: the step of dividing the multi-layer dataset into layers and constructing a multi-layer 3D model of the isolated submarine power transmission cable channel using WebGL and the Cesium engine according to the layer division results further includes: The real-time data interface of the multi-layer three-dimensional model is established, real-time data of the power transmission sea cable channel is acquired in real time through the real-time data interface, and the power transmission sea cable channel is monitored in a state. When the state or data of the power transmission sea cable channel changes, the multi-layer three-dimensional model is automatically updated in corresponding layer information.
[0009] In a preferred example, the application can be further configured to: extract the submarine cable risk factors of the multi-layer data set, construct a multi-dimensional risk evaluation index system of the power transmission sea cable channel by a fuzzy AHP algorithm and a random forest algorithm, and optimize the risk evaluation mechanism of the multi-layer three-dimensional model, specifically including: According to the risk evaluation requirement of the power transmission sea cable channel, the submarine cable risk factors of the multi-layer data set are extracted, and the submarine cable risk factors include ship collision risk factors, geological disaster risk factors and environmental corrosion risk factors; The submarine cable risk factors are weighted and distributed by a fuzzy AHP algorithm, and a multi-dimensional risk evaluation index system of the power transmission sea cable channel is constructed; The submarine cable risk factors in the multi-dimensional risk evaluation index system are trained by a random forest algorithm with historical accident data as training samples, and the risk evaluation mechanism of the multi-layer three-dimensional model is optimized.
[0010] In a preferred example, the application can be further configured to: the calculation process of the ship collision risk factor in the submarine cable risk factors of the multi-layer data set according to the risk evaluation requirement of the power transmission sea cable channel, specifically including: The ship collision risk factor is represented by the Euclidean distance between the ship and the submarine cable, and the ship collision risk factor calculation expression is as follows: (1) Wherein, The Euclidean distance between the ship and the submarine cable is represented by (d , The ship coordinates are represented by (x , The submarine cable coordinates are represented by (x
[0011] In a preferred example, the application can be further configured to: the calculation process of the geological disaster risk factor in the submarine cable risk factors of the multi-layer data set according to the risk evaluation requirement of the power transmission sea cable channel, specifically including: The landslide probability is calculated based on a logistic regression model, and the geological disaster risk factor is represented by the landslide probability, and the geological disaster risk factor calculation expression is as follows: (2) Wherein, represents a landslide probability, represents an earthquake magnitude, a represents a submarine slope, and h represents a sediment thickness.
[0012] In a preferred example, the application can be further configured to: the calculation process of the environmental corrosion risk factor in the submarine cable risk factor of the multi-layer data set extracted according to the risk assessment requirement of the submarine cable channel, specifically includes: The environmental corrosion risk factor is expressed by the seawater corrosion rate, and the calculation expression of the environmental corrosion risk factor is as follows: (3) wherein, represents the seawater corrosion rate, represents the seawater PH value, represents the seawater temperature, represents the seawater flow rate.
[0013] In a preferred example, the application can be further configured to: the risk assessment of the current state of the submarine cable channel according to the multi-dimensional risk evaluation index system, and the pre-warning response of the pre-warning mechanism matched according to the risk assessment result, specifically includes: According to the multi-dimensional risk evaluation index system, the current state of the submarine cable channel is real-time risk assessed, and the risk level evaluation result of the submarine cable is output; According to the pre-set pre-warning response strategy, the pre-warning mechanism matching of the corresponding risk level is carried out combined with the risk level evaluation result, and the pre-warning strategy response is carried out according to the matching result.
[0014] In a preferred example, the application can be further configured to: obtain the multi-source heterogeneous data of the island submarine cable channel, and carry out data preprocessing on the multi-source heterogeneous data to obtain the multi-layer data set consistent in time and space, specifically including: Obtain the geographical data, marine environment data, ship traffic data and geological disaster data of the island submarine cable channel to obtain the multi-source heterogeneous data of the island submarine cable channel; Carry out data preprocessing on the multi-source heterogeneous data, eliminate the abnormal values and noise data in the multi-source heterogeneous data, and obtain the preprocessed multi-source heterogeneous data; Convert the preprocessed multi-source heterogeneous data into a unified data format, and carry out time and space alignment and data assimilation processing to obtain the multi-layer data set consistent in time and space and suitable for three-dimensional modeling.
[0015] In the second aspect, the above application purpose is achieved by the following technical scheme: The application relates to a multi-layer fusion island power transmission submarine cable channel dynamic risk management and control system. A data acquisition and preprocessing layer is used for acquiring multi-source heterogeneous data of an island power transmission submarine cable channel, performing data preprocessing on the multi-source heterogeneous data, and obtaining a spatiotemporally consistent multi-layer data set; A three-dimensional visualization model layer is used for layer division of the multi-layer data set, and three-dimensional modeling is performed according to the layer division results through WebGL and a Cesium engine, so that a multi-layer three-dimensional model of the island power transmission submarine cable channel is constructed; A dynamic risk assessment layer is used for extracting submarine cable risk factors of the multi-layer data set, constructing a multi-dimensional risk evaluation index system of the power transmission submarine cable channel through a fuzzy AHP algorithm and a random forest algorithm, and optimizing a risk evaluation mechanism of the multi-layer three-dimensional model; A warning response and execution layer is used for risk assessment of a current state of the power transmission submarine cable channel according to the multi-dimensional risk evaluation index system, and a warning response is performed according to a warning mechanism corresponding to a risk grade matched according to a risk assessment result The application has at least one of the following beneficial technical effects: 1. The application uses submarine topography detection, GIS, cable operation state monitoring and other heterogeneous data sources, and through a three-dimensional layer fusion model, the information such as the topography, structure, environment and operation of the submarine cable channel is superimposed and modeled, the problem that a two-dimensional GIS or single point cloud modeling in the prior art cannot express multi-source environmental characteristics and channel details is broken through, the structure data, operation state data and environmental data (such as sea conditions, weather, topography and the like) are unified in space / time and fused in layers, a dynamic risk analysis model is constructed, through stereoscopic information fusion and visualization modeling of the power transmission submarine cable channel, stereoscopic expression and three-dimensional visual interaction in a complex scene are realized; 2. The application adopts a three-dimensional engine (such as Cesium) to perform spatial layer fusion display on the submarine cable path, environmental factors and risk indexes, supports dynamic change, layered control and heat map superposition, constructs a multi-dimensional risk evaluation index system of environmental factors (such as water flow, submarine sedimentation), structure factors (such as burial depth, sheath aging) and operation factors (such as temperature, current anomaly), realizes quantitative evaluation and dynamic updating of risk grades in combination with a fuzzy AHP and a random forest algorithm, and solves the problem of risk perception lag and low accuracy caused by traditional static rules or single factor judgment; 3. Support real-time access and automatic fusion of submarine cable operation data and environment perception data, can dynamically update three-dimensional risk layer and trigger different levels of response strategy, has adaptive processing capability, reduces operation and maintenance cost, improves operation and maintenance efficiency and economic benefit, and supports three-dimensional interaction, risk query and hierarchical control on PC, Web and mobile terminal devices. BRIEF DESCRIPTION OF DRAWINGS
[0016] In order to more clearly illustrate the specific embodiments of the present application or the technical solutions in the prior art, the drawings needed in the specific embodiments or the prior art description will be briefly introduced below. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, each element or part is not necessarily drawn according to the actual scale.
[0017] Figure 1 is the implementation flowchart of step S10 of the island power transmission submarine cable channel dynamic risk management and control method of the multi-layer fusion of the present embodiment.
[0018] Figure 2 is the implementation flowchart of step S10 of the island power transmission submarine cable channel dynamic risk management and control method of the present embodiment.
[0019] Figure 3 is the implementation flowchart of step S20 of the island power transmission submarine cable channel dynamic risk management and control method of the present embodiment.
[0020] Figure 4 is the implementation flowchart of step S30 of the island power transmission submarine cable channel dynamic risk management and control method of the present embodiment.
[0021] Figure 5 is the implementation flowchart of step S40 of the island power transmission submarine cable channel dynamic risk management and control method of the present embodiment.
[0022] Figure 6 is the structure block diagram of the island power transmission submarine cable channel dynamic risk management and control system of the multi-layer fusion of the present embodiment. DETAILED DESCRIPTION
[0023] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.
[0024] It should be understood that the terms "comprises" and "comprising," when used in this specification and accompanying claims, indicate the presence of the described features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.
[0025] It should also be understood that the terms used in the specification of the application are merely for the purpose of describing particular embodiments and do not intend to limit the application. As used in the specification and the appended claims of the application, the singular forms "a," "an," and "the" are intended to include the plural forms unless the context clearly indicates otherwise.
[0026] It should be further understood that the term "and / or" used in the specification of the application and the appended claims means any combination of one or more of the associated listed items and all possible combinations thereof.
[0027] In an embodiment, as shown in Figure 1 The application discloses a multi-layer fusion island power transmission submarine cable channel dynamic risk management and control method, which specifically comprises the following steps: S10: Obtain multi-source heterogeneous data of the island power transmission submarine cable channel, and perform data preprocessing on the multi-source heterogeneous data to obtain a spatiotemporally consistent multi-layer data set.
[0028] Specifically, as shown in Figure 2 The step S10 comprises: S101: Obtain geographic data, marine environment data, ship traffic data, and geological disaster data of the island power transmission submarine cable channel to obtain multi-source heterogeneous data of the island power transmission submarine cable channel.
[0029] Specifically, the accurate geographic position, topography, surrounding island distribution, and other information of the submarine cable channel are obtained by satellite remote sensing, geographic information system (GIS), and the like to obtain the geographic data; the marine environment parameters such as water depth, flow rate, flow direction, sea wave, and tide are monitored in real time by using marine monitoring equipment (such as a buoy, a sonar, a tide gauge, and the like) to obtain the marine environment data; the position, speed, heading, and ship type of the ship are obtained by accessing an automatic identification system (AIS) and radar data to obtain the ship traffic data; the vibration frequency is monitored by using an ocean bottom seismometer (OBS), and the risk is predicted in combination with a historical landslide database (such as a NOAA geological database) to obtain the geological disaster data.
[0030] S102: Perform data preprocessing on the multi-source heterogeneous data, eliminate the abnormal values and noise data in the multi-source heterogeneous data, and obtain the preprocessed multi-source heterogeneous data.
[0031] Specifically, the collected multi-source heterogeneous data is preprocessed, such as cleaning, filtering, and calibration, to remove noise data and outliers, and obtain preprocessed multi-source heterogeneous data.
[0032] S103: The preprocessed multi-source heterogeneous data is converted into a unified data format, and spatio-temporal alignment and data assimilation processing are performed to obtain multi-layer data sets that are spatio-temporal consistent and suitable for three-dimensional modeling.
[0033] Specifically, different types of data are converted into a unified geographic coordinate system and data format, and multi-source heterogeneous data is aligned according to time and space dimensions to ensure spatio-temporal consistency of each layer of data. Through data assimilation technology, the spatio-temporal resolution difference problem of different data sources is solved, and interpolation and fusion processing are performed on the data to generate multi-layer data sets suitable for three-dimensional modeling.
[0034] It should be noted that the embedding and fusion of multi-source heterogeneous data can also be achieved by using a multi-modal Transformer network.
[0035] S20: The multi-layer data set is divided into layers, and three-dimensional modeling is performed according to the layer division results through WebGL and the Cesium engine to construct a multi-layer three-dimensional model of the island power transmission submarine cable channel.
[0036] Specifically, as shown in FIG. 20, step S20 includes: Figure 3 S201: The multi-layer data set is divided into layers according to the data source, including a basic geographic layer, a submarine cable layer, an environmental dynamic layer, and a risk density layer.
[0037] Specifically, according to the different data sources, the multi-layer data set of geographic information, marine environment, ship traffic, and geological disasters is divided into layers, including a basic geographic layer, a submarine cable layer, an environmental dynamic layer, and a risk density layer.
[0038] The basic geographic layer represents the seafloor topography, which is represented by converting DEM data into a triangular mesh (TIN model). The color gradient represents the depth, with blue representing deep and light green representing shallow. The contour lines are represented by drawing contour lines every 10 meters, with the depth value marked.
[0039] The submarine cable layer is represented by modeling the pipeline of the submarine cable pipeline. Specifically, a cylindrical three-dimensional model is used to simulate the submarine cable, with a diameter scaled to the actual size, such as 0.5 meters. The color coding represents the state, such as green for normal and red for failure. The burial depth is marked: the burial depth value is marked every 100 meters along the pipeline, with units in meters.
[0040] Among them, the environmental dynamic layer is represented by ship trajectory, the ship position is rendered in real time, the arrow direction represents the heading, and the speed is represented by color gradient, such as green <10 knots, red >20 knots; ocean current simulation is based on vector field data, and the flow direction and speed are dynamically displayed using particle system.
[0041] Among them, the risk density layer is represented by a heat map, and the color is rendered according to the geological disaster probability, such as green: 0%~30%, yellow: 30%~60%, red: 60%~100%; historical accident markers include marking the location and reason of submarine cable fracture in the past 5 years in the form of icons.
[0042] It should be noted that the color gradient rendering method used in this embodiment can also be replaced by three-dimensional space light projection rendering or voxel transparency superposition rendering, or a time sliding axis dynamic evolution curve visual layer can be introduced to replace the static heat map.
[0043] S202: Three-dimensional modeling is performed according to the layer division result through WebGL and Cesium engine, a multi-layer three-dimensional model is constructed, and the layer information and layer association relationship of the multi-layer data set are visualized.
[0044] Specifically, a browser-side three-dimensional scene is constructed based on WebGL and Cesium engine, GPU accelerated rendering is supported, and the data of each layer is fused into the three-dimensional scene for modeling according to the layer division result, thereby constructing a multi-layer three-dimensional model. Through setting different transparency, color, texture and other properties, the clear display of layer information and layer association relationship is realized.
[0045] Specifically, step S20 further includes: S203: Establishing a real-time data interface of the multi-layer three-dimensional model, and acquiring real-time data of the submarine cable channel in real time through the real-time data interface to monitor the state of the submarine cable channel.
[0046] Specifically, the real-time data interface of the multi-layer three-dimensional model is dynamically connected with the data acquisition system to acquire real-time data of the submarine cable channel in real time, and the state of the submarine cable channel is monitored to ensure that the three-dimensional model can reflect the latest state of the submarine cable channel in real time.
[0047] S204: When the state or data of the submarine cable channel changes, the corresponding layer information of the multi-layer three-dimensional model is automatically updated.
[0048] Specifically, when the monitoring data or the state of the submarine cable channel changes, the multi-layer three-dimensional model can automatically update the corresponding layer information to dynamically display the real-time evolution of the environmental changes and risk factors of the submarine cable channel.
[0049] S30: Extract submarine cable risk factors from multi-layer datasets, construct a multi-dimensional risk assessment index system for power transmission submarine cable channels using fuzzy AHP algorithm and random forest algorithm, and optimize the risk assessment mechanism of multi-layer three-dimensional model.
[0050] Specifically, such as Figure 4 As shown, step S30 includes: S301: Extract submarine cable risk factors from a multi-layer dataset based on the risk assessment requirements of the power transmission submarine cable channel. The submarine cable risk factors include ship collision risk factors, geological disaster risk factors, and environmental corrosion risk factors.
[0051] Specifically, based on the risk assessment requirements of the power transmission submarine cable channel, a multi-layer dataset of submarine cable risk factors is set up, including environmental factors, structural factors, and operational factors. In this embodiment, ship collision risk factors, geological disaster risk factors, and environmental corrosion risk factors are used as examples for illustration.
[0052] The calculation process of the ship collision risk factor in this embodiment specifically includes: The ship collision risk factor is represented by the Euclidean distance between the ship and the submarine cable. The formula for calculating the ship collision risk factor is as follows: (1) in, This represents the Euclidean distance between the ship and the submarine cable. , ) represents the ship's coordinates, ( , () indicates the coordinates of the submarine cable.
[0053] The calculation process of the geological disaster risk factor in this embodiment specifically includes: The landslide probability is calculated based on a logistic regression model, and the geological hazard risk factor is expressed as the landslide probability. The calculation expression for the geological hazard risk factor is as follows: (2) in, Indicates the probability of a landslide. Indicates the earthquake magnitude. α Indicates the slope of the seabed. h Indicates the thickness of the sediment.
[0054] The calculation process for the environmental corrosion risk factor in this embodiment specifically includes: The environmental corrosion risk factor is expressed as the seawater corrosion rate. The calculation formula for the environmental corrosion risk factor is as follows: (3) in, Indicates the seawater corrosion rate, Indicates the pH value of seawater. Indicates seawater temperature, Indicates the speed of seawater flow.
[0055] S302: By using the fuzzy AHP algorithm to assign weights to submarine cable risk factors, a multi-dimensional risk assessment index system for power transmission submarine cable channels is constructed.
[0056] Specifically, the judgment matrix is constructed using the fuzzy AHP algorithm to determine the weights of submarine cable risk factors, and then the weights of the submarine cable risk factors are allocated to construct a multi-dimensional risk assessment index system for power transmission submarine cable channels. In this embodiment, the input factors of the judgment matrix are ship collision risk factors, geological disaster risk factors, and environmental corrosion risk factors.
[0057] S303: Using the random forest algorithm with historical accident data as training samples, the risk factors of submarine cables in the multi-dimensional risk assessment index system are trained, and the risk assessment mechanism of the multi-layer three-dimensional model is optimized.
[0058] Specifically, the random forest algorithm uses ship collision risk factors, geological disaster risk factors, environmental corrosion risk factors, relative heading angle, seawater current velocity, water current intensity, anchor towing risk level, and geological disturbance probability as input features, and historical accident data as training samples. By setting parameters such as the number of decision trees and maximum depth, it trains the submarine cable risk factors in the multi-dimensional risk assessment index system with data, outputs the risk level corresponding to the multi-dimensional risk assessment index system, and forms a risk assessment mechanism to optimize the multi-layer three-dimensional model.
[0059] It should be noted that this embodiment also uses 5-fold cross-validation to verify the training results of the random forest algorithm, ensuring that the accuracy of the multi-dimensional risk assessment index system in determining the corresponding risk level is higher than 95%, and ensuring the generalization performance of the model.
[0060] In this embodiment, incremental learning is also used to incrementally train the daily number of new nodes and update the node splitting rules.
[0061] It should be noted that, in addition to the combination of AHP and random forest for risk assessment, other machine learning algorithms such as decision trees, support vector machines (SVM), or convolutional neural networks can be used as alternatives.
[0062] S40: Conduct a risk assessment of the current status of the power transmission submarine cable channel based on the multi-dimensional risk assessment index system, and respond to the early warning by matching the corresponding risk level early warning mechanism according to the risk assessment results.
[0063] Specifically, such as Figure 5 As shown, step S40 includes: S401: Based on the multi-dimensional risk assessment index system, conduct real-time risk assessment of the current status of the power transmission submarine cable channel and output the risk level assessment results of the power transmission submarine cable.
[0064] Specifically, according to the multi-dimensional risk assessment index system, the current status of the power transmission submarine cable channel is assessed in real time. For example, when the current status of the power transmission submarine cable channel is comprehensively assessed through the multi-dimensional risk assessment index system, and the output risk level reaches the preset risk threshold, it will be classified into the corresponding risk level, and the risk level assessment result of the power transmission submarine cable will be output.
[0065] S402: Based on the pre-set early warning response strategy and the risk level assessment results, match the early warning mechanism for the corresponding risk level, and respond to the early warning strategy according to the matching results.
[0066] Specifically, based on the established early warning response strategy and the risk level assessment results, the corresponding early warning mechanism is invoked for matching, and the corresponding early warning mechanism is responded to according to the matching results. For example, the early warning signal is sent to relevant management personnel, maintenance personnel and maritime departments through multiple means such as SMS, email, audible and visual alarms, and APP push, while generating specific response strategy suggestions.
[0067] Furthermore, it provides a touch-screen interface, allowing user interaction and control on desktop or mobile devices (such as tablets and smartphones). It supports multi-view viewing, risk timeline playback, historical event review, and voice command queries.
[0068] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.
[0069] In one embodiment, a multi-layer fusion dynamic risk management system for isolated submarine power transmission cable channels is provided. This multi-layer fusion dynamic risk management system for isolated submarine power transmission cable channels corresponds one-to-one with the multi-layer fusion dynamic risk management method for isolated submarine power transmission cable channels in the above embodiments. For example... Figure 6 As shown, this multi-layered dynamic risk management system for isolated submarine power transmission cable channels includes a data acquisition and preprocessing layer, a 3D visualization model layer, a dynamic risk assessment layer, and an early warning response and execution layer. Detailed descriptions of each functional module are as follows: The data acquisition and preprocessing layer is used to acquire multi-source heterogeneous data of the isolated island power transmission submarine cable channel, and to preprocess the multi-source heterogeneous data to obtain a spatiotemporally consistent multi-layer dataset.
[0070] The 3D visualization model layer is used to divide the multi-layer dataset into layers and then use WebGL and the Cesium engine to perform 3D modeling based on the layer division results, thus constructing a multi-layer 3D model of the isolated island power transmission submarine cable channel.
[0071] The dynamic risk assessment layer is used to extract submarine cable risk factors from multi-layer datasets. A multi-dimensional risk assessment index system for power transmission submarine cable channels is constructed using fuzzy AHP algorithm and random forest algorithm, and the risk assessment mechanism is optimized for multi-layer three-dimensional models.
[0072] The early warning response and execution layer is used to conduct risk assessments on the current status of the power transmission submarine cable channel based on a multi-dimensional risk assessment index system, and to match the corresponding risk level early warning mechanism to conduct early warning responses based on the risk assessment results.
[0073] Specific limitations regarding the multi-layer fusion dynamic risk management system for isolated submarine power transmission channels can be found in the limitations of the multi-layer fusion dynamic risk management method for isolated submarine power transmission channels mentioned above, and will not be repeated here. Each module in the aforementioned multi-layer fusion dynamic risk management system for isolated submarine power transmission channels can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.
[0074] Those skilled in the art will recognize that the units of the various examples described in connection with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application of the technical solution and the constraints involved. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of the invention.
[0075] In the embodiments provided by the present invention, it should be understood that the division of units is only a logical functional division. In actual implementation, there may be other division methods, such as multiple units can be combined into one unit, one unit can be split into multiple units, or some features can be ignored.
[0076] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.
[0077] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.
[0078] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered within the scope of the claims and specification of the present invention.
Claims
1. A method for dynamic risk management of isolated submarine power transmission cable channels using multi-layer fusion, characterized in that, The method includes: Multi-source heterogeneous data of isolated island power transmission submarine cable channels are acquired, and the multi-source heterogeneous data is preprocessed to obtain a spatiotemporally consistent multi-layer dataset. The multi-layer dataset is divided into layers, and 3D modeling is performed using WebGL and Cesium engine according to the layer division results to construct a multi-layer 3D model of the isolated island power transmission submarine cable channel. Risk factors of submarine cables are extracted from the multi-layer dataset. A multi-dimensional risk assessment index system for power transmission submarine cable channels is constructed using the fuzzy AHP algorithm and the random forest algorithm. The risk assessment mechanism of the multi-layer three-dimensional model is then optimized. The current status of the power transmission submarine cable channel is assessed based on the multi-dimensional risk assessment index system, and an early warning mechanism corresponding to the risk level is matched to the risk assessment results for early warning response.
2. The method for dynamic risk management of isolated submarine power transmission cable channels with multi-layer fusion as described in claim 1, characterized in that, The process of dividing the multi-layer dataset into layers and constructing a multi-layer 3D model of the isolated submarine power transmission cable channel using WebGL and the Cesium engine based on the layer division results specifically includes: The multi-layer dataset is divided into layers based on the data source, including a basic geographic layer, a submarine cable layer, an environmental dynamic layer, and a risk density layer; The model is constructed using WebGL and the Cesium engine based on the layer division results, creating a multi-layer 3D model. The layer information and layer relationships of the multi-layer dataset are then visualized.
3. The method for dynamic risk management of isolated submarine power transmission cable channels with multi-layer fusion as described in claim 2, characterized in that, The process of dividing the multi-layer dataset into layers and constructing a multi-layer 3D model of the isolated submarine power transmission cable channel using WebGL and the Cesium engine based on the layer division results also includes: Establish a real-time data interface for the multi-layer 3D model, and obtain real-time data of the power transmission submarine cable channel through the real-time data interface to monitor the status of the power transmission submarine cable channel. When a change in the status or data of the power transmission submarine cable channel is detected, the corresponding layer information of the multi-layer 3D model is automatically updated.
4. The method for dynamic risk management of isolated submarine power transmission cable channels with multi-layer fusion as described in claim 1, characterized in that, The process of extracting submarine cable risk factors from the multi-layer dataset, constructing a multi-dimensional risk assessment index system for power transmission submarine cable channels using the fuzzy AHP algorithm and the random forest algorithm, and optimizing the risk assessment mechanism of the multi-layer 3D model specifically includes: Based on the risk assessment requirements of the power transmission submarine cable channel, submarine cable risk factors are extracted from the multi-layer dataset. These submarine cable risk factors include ship collision risk factors, geological disaster risk factors, and environmental corrosion risk factors. The risk factors of the submarine cable are weighted by the fuzzy AHP algorithm to construct a multi-dimensional risk evaluation index system for the power transmission submarine cable channel. Using historical accident data as training samples, the random forest algorithm is used to train the submarine cable risk factors in the multi-dimensional risk assessment index system, and the risk assessment mechanism of the multi-layer three-dimensional model is optimized.
5. The method for dynamic risk management of isolated submarine power transmission cable channels with multi-layer fusion as described in claim 4, characterized in that, The calculation process for extracting the ship collision risk factor from the multi-layer dataset of submarine cable risk factors based on the risk assessment requirements of the submarine cable transmission channel specifically includes: The ship collision risk factor is represented by the Euclidean distance between the ship and the submarine cable, and the calculation expression for the ship collision risk factor is as follows: （1） in, This represents the Euclidean distance between the ship and the submarine cable. , ) represents the ship's coordinates, ( , () indicates the coordinates of the submarine cable.
6. The method for dynamic risk management of isolated submarine power transmission cable channels with multi-layer fusion according to claim 4, characterized in that, The calculation process for extracting the geological hazard risk factor from the submarine cable risk factors in the multi-layer dataset based on the risk assessment requirements of the submarine cable transmission channel specifically includes: The landslide probability is calculated based on a logistic regression model, and the landslide probability is used to represent the geological hazard risk factor. The calculation expression for the geological hazard risk factor is as follows: （2） in, Indicates the probability of a landslide. Indicates the earthquake magnitude. α Indicates the slope of the seabed. h Indicates the thickness of the sediment.
7. The method for dynamic risk management of isolated submarine power transmission cable channels with multi-layer fusion as described in claim 4, characterized in that, The calculation process for extracting the environmental corrosion risk factor from the multi-layer dataset of submarine cable risk factors based on the risk assessment requirements of the submarine cable transmission channel specifically includes: The environmental corrosion risk factor is expressed as the seawater corrosion rate, and the calculation expression for the environmental corrosion risk factor is as follows: （3） in, Indicates the seawater corrosion rate, Indicates the pH value of seawater. Indicates seawater temperature, Indicates the speed of seawater flow.
8. The method for dynamic risk management of isolated submarine power transmission cable channels with multi-layer fusion as described in claim 1, characterized in that, The process of conducting a risk assessment of the current status of the submarine power transmission cable channel based on the multi-dimensional risk assessment index system, and matching the corresponding risk level early warning mechanism to issue an early warning response based on the risk assessment results, specifically includes: According to the multidimensional risk assessment index system, the current status of the power transmission submarine cable channel is assessed in real time, and the risk level assessment result of the power transmission submarine cable is output. Based on the pre-set early warning response strategy and the risk level assessment results, an early warning mechanism is matched for the corresponding risk level, and an early warning strategy response is implemented based on the matching results.
9. The method for dynamic risk management of isolated submarine power transmission cable channels with multi-layer fusion according to claim 1, characterized in that, The process of acquiring multi-source heterogeneous data of isolated submarine power transmission cable channels, and preprocessing the multi-source heterogeneous data to obtain a spatiotemporally consistent multi-layer dataset, specifically includes: Geographic data, marine environment data, ship traffic data, and geological disaster data of the isolated island power transmission submarine cable channel are acquired to obtain multi-source heterogeneous data of the isolated island power transmission submarine cable channel; The multi-source heterogeneous data is preprocessed to remove outliers and noise data, resulting in preprocessed multi-source heterogeneous data. The preprocessed multi-source heterogeneous data is converted into a unified data format and subjected to spatiotemporal alignment and data assimilation to obtain a spatiotemporally consistent multi-layer dataset suitable for 3D modeling.
10. A multi-layer fusion dynamic risk management system for isolated submarine power transmission cable channels, characterized in that, The system is applied to the multi-layer fusion dynamic risk management method for isolated submarine power transmission channels as described in any one of claims 1-9, and the system includes: The data acquisition and preprocessing layer is used to acquire multi-source heterogeneous data of the isolated island power transmission submarine cable channel, and to perform data preprocessing on the multi-source heterogeneous data to obtain a spatiotemporally consistent multi-layer dataset. The 3D visualization model layer is used to divide the multi-layer dataset into layers and to perform 3D modeling according to the layer division results using WebGL and the Cesium engine, thereby constructing a multi-layer 3D model of the isolated island power transmission submarine cable channel. The dynamic risk assessment layer is used to extract submarine cable risk factors from the multi-layer dataset. A multi-dimensional risk assessment index system for the power transmission submarine cable channel is constructed using the fuzzy AHP algorithm and the random forest algorithm. The risk assessment mechanism of the multi-layer three-dimensional model is optimized. The early warning response and execution layer is used to conduct risk assessment on the current status of the power transmission submarine cable channel based on the multi-dimensional risk assessment index system, and to match the early warning mechanism with the corresponding risk level based on the risk assessment results to conduct early warning response.