A Ship Damage Control Synchronized Visualization Method and Platform

Abstract

The present invention discloses a method and platform for synchronous visualization of ship damage control, which relates to the technical field of ship monitoring, and includes: configuring edge monitoring nodes to obtain multiple ship damage monitoring nodes; analyzing real-time multi-modal data of multiple ship monitoring zones to generate multiple damage situation codes; analyzing multiple damage situation codes to configure update frequencies to obtain multiple situation update frequencies; decoding multiple damage situation codes to synthesize virtual images to obtain multiple partition damage images for visual display; using multiple situation update frequencies as visual iteration constraints for multiple partition damage images, and receiving the feedback codes of multiple ship damage monitoring nodes to perform visual damage image iteration on the ship damage control display screen. The present invention solves the technical problem that the prior art cannot comprehensively display the damage situation of the whole ship in real time, which affects the efficiency and accuracy of emergency response, and achieves the technical effect of improving the damage situation perception and emergency response efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of ship monitoring, and particularly to a ship damage control synchronization visualization method and platform. Background Art

[0002] Traditional ship damage control monitoring systems often rely on scattered sensors and independent monitoring nodes. It is difficult to integrate the damage data of each partition into unified situation information, resulting in the monitoring system being unable to display the damage situation of the entire ship in real time and comprehensively. The traditional monitoring system lacks the integration of multi-modal data and dynamic visualization means, and crew members cannot view the damage status of each partition in a timely and clear manner on the display screen, affecting the efficiency and accuracy of emergency response. Summary of the Invention

[0003] This application provides a ship damage control synchronization visualization method and platform, which are used to solve the technical problems that the existing technology cannot display the damage situation of the entire ship in real time and comprehensively, and affects the efficiency and accuracy of emergency response.

[0004] In view of the above problems, this application provides a ship damage control synchronization visualization method and platform.

[0005] In the first aspect of this application, a ship damage control synchronization visualization method is provided. The method includes:

[0006] Configure edge monitoring nodes according to ship partitions to obtain multiple ship damage monitoring nodes for multiple ship monitoring partitions; receive and analyze real-time multi-modal data of the multiple ship monitoring partitions through the multiple ship damage monitoring nodes to generate multiple damage situation codes; the damage control situation display center receives and configures the update frequency by analyzing the multiple damage situation codes to obtain multiple situation update frequencies; after the damage control situation display center synthesizes virtual images by decoding the multiple damage situation codes to obtain multiple partition damage images, synchronize the multiple partition damage images to the ship damage control display screen for visual display; the damage control situation display center uses the multiple situation update frequencies as the visual iteration constraints of the multiple partition damage images, and receives the feedback codes of the multiple ship damage monitoring nodes for visual damage image iteration of the ship damage control display screen.

[0007] In the second aspect of this application, a ship damage control synchronization visualization platform is provided. The platform includes:

[0008] Node configuration unit, which configures edge monitoring nodes according to ship partitions to obtain multiple ship damage monitoring nodes for multiple ship monitoring partitions; multimodal data analysis unit, which receives and analyzes real-time multimodal data of the multiple ship monitoring partitions through the multiple ship damage monitoring nodes to generate multiple damage situation codes; update frequency configuration unit, which receives through the damage control situation display center and configures the update frequency by analyzing the multiple damage situation codes to obtain multiple situation update frequencies; virtual image synthesis unit, which synthesizes virtual images by decoding the multiple damage situation codes through the damage control situation display center. After obtaining multiple partition damage images, the multiple partition damage images are synchronized to the ship damage control display screen for visual display; visualization iteration unit, which uses the multiple situation update frequencies as the visualization iteration constraints for the multiple partition damage images through the damage control situation display center, and receives the feedback codes of the multiple ship damage monitoring nodes to perform visualization damage image iteration on the ship damage control display screen.

[0009] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0010] This application configures edge monitoring nodes according to ship partitions to obtain multiple ship damage monitoring nodes for multiple ship monitoring partitions; receives and analyzes real-time multimodal data of multiple ship monitoring partitions through multiple ship damage monitoring nodes to generate multiple damage situation codes; the damage control situation display center receives and configures the update frequency by analyzing multiple damage situation codes to obtain multiple situation update frequencies; the damage control situation display center synthesizes virtual images by decoding multiple damage situation codes. After obtaining multiple partition damage images, the multiple partition damage images are synchronized to the ship damage control display screen for visual display; the damage control situation display center uses the multiple situation update frequencies as the visualization iteration constraints for the multiple partition damage images, and receives the feedback codes of the multiple ship damage monitoring nodes to perform visualization damage image iteration on the ship damage control display screen. This invention solves the technical problem that the prior art cannot display the damage situation of the whole ship in real time and comprehensively, which affects the efficiency and accuracy of emergency disposal. By configuring edge monitoring nodes in each ship partition, receiving and analyzing multimodal data to generate damage situation codes, the damage control situation display center parses and synthesizes damage images of each partition, and realizes dynamic iteration of images with the update frequency as the constraint, so as to achieve real-time monitoring and synchronous visual display of ship damage information, and achieve the technical effect of improving the perception of damage situation and the efficiency of emergency response. Description of the Drawings

[0011] To more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the accompanying drawings required for the description of the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can be obtained based on these drawings.

[0012] Figure 1 Schematic flow diagram of a ship damage control synchronization visualization method provided by an embodiment of the present application;

[0013] Figure 2 Schematic structural diagram of a ship damage control synchronization visualization platform provided by an embodiment of the present application.

[0014] Explanation of reference numerals: Node configuration unit 11, multimodal data analysis unit 12, update frequency configuration unit 13, virtual image synthesis unit 14, visualization iteration unit 15. Detailed implementation manners

[0015] The present application provides a ship damage control synchronization visualization method and platform, aiming to solve the technical problem that the prior art cannot comprehensively display the damage situation of the entire ship in real time, which affects the efficiency and accuracy of emergency response. By configuring edge monitoring nodes in each ship area, receiving and analyzing multimodal data to generate damage situation codes, and the damage control situation display center analyzes and synthesizes the damage images of each area, and realizes dynamic iteration of the images with the update frequency as the constraint, the real-time monitoring and synchronous visualization display of ship damage information are realized, achieving the technical effect of improving the perception of damage situation and the efficiency of emergency response.

[0016] The following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, rather than all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present application.

[0017] It should be noted that any variations of the terms "including" and "having" are intended to cover non-exclusive inclusion. For example, a process, method, platform, product, or server that includes a series of steps or units does not necessarily have to be limited to those clearly listed steps or units, but may include other steps or modules that are not clearly listed or are inherent to these processes, methods, products, or devices.

[0018] Embodiment 1, as Figure 1 shown, the present application provides a ship damage control synchronization visualization method, and the method includes:

[0019] Step S100: Configure edge monitoring nodes according to ship partitions to obtain multiple ship damage monitoring nodes for multiple ship monitoring partitions.

[0020] In the embodiment of the present application, first, the hull is divided into multiple monitoring partitions according to the functional areas and physical boundaries of the ship. For example, the engine room, deck, living area, cargo hold area, etc. On this basis, at the boundary of each monitoring partition, edge monitoring nodes are configured according to the standards of ship structure design. These nodes include temperature, vibration, pressure sensors, etc. Next, sensors such as temperature sensors and pressure sensors are installed on each edge node. Each edge node is configured according to a unified specification to enable standardized data collection between monitoring nodes in different areas.

[0021] Through the above steps, the configuration of edge monitoring nodes for each ship partition is completed, enabling each monitoring partition to have the ability to monitor damage, and finally obtaining multiple edge damage monitoring nodes for multiple ship partitions.

[0022] Furthermore, in the method provided by the embodiment of the application, configuring edge monitoring nodes according to ship partitions to obtain multiple ship damage monitoring nodes for multiple ship monitoring partitions further includes:

[0023] Invoke damage data networking according to the first damage feature of the first ship monitoring partition to obtain multiple sample damage data sets of multiple damage types; after quantifying the damage levels of the multiple sample damage data sets, use the multiple sample damage data sets to construct a damage evaluation model to obtain multiple first damage recognition models; parallel the multiple first damage recognition models to obtain the first damage recognition layer; by cascading the first damage recognition layer with the damage situation coding module, complete the configuration of the first ship damage monitoring node; and so on, configure edge monitoring nodes according to ship partitions to obtain the multiple ship damage monitoring nodes.

[0024] In the embodiment of the present application, the first ship monitoring partition refers to an independent area in the hull structure, which has clear physical boundaries and functional divisions in the overall ship structure and can be used as a separate monitoring unit for collecting and analyzing damage data. The first damage feature refers to the damage attributes initially defined or recognized within this partition, including features such as temperature, pressure, and deformation. Based on the first damage feature, first, invoke damage data networking to extract relevant historical data and damage records from the database. This process uses database query technology or API interfaces to invoke damage sample data sets from multiple data sources. These data sets cover different types of damage events, such as cracks and temperature anomalies. Through this process, multiple sample damage data sets of multiple damage types are obtained.

[0025] Next, the damage levels of multiple sample damage datasets are quantified. Specifically, a clustering algorithm, such as K-means clustering, is used to divide the dataset into multiple levels. First, damage data features, such as temperature, pressure, vibration intensity, etc., are extracted and standardized, and then the clustering algorithm is used for data grouping to ensure that each level represents data with similar damage characteristics. Further, through threshold analysis, the critical numerical ranges of each type of damage, such as a temperature exceeding 70°C being marked as severe, are used as the judgment criteria for the damage level, thereby generating a sample dataset marked with damage levels.

[0026] After that, using the quantified dataset, a machine learning algorithm is employed to construct a damage evaluation model. The decision tree model is used in the model training process. When performing model training, first, data preprocessing is carried out. By feature selection, the features crucial for damage recognition, such as changes in specific temperature and pressure, are determined, and the data is standardized. Then these data are input into the decision tree algorithm, and the optimal features are selected through recursive splitting and information gain, ultimately constructing a decision tree model that can effectively identify different damage levels. This process is repeated on multiple groups of sample datasets to separately construct independent evaluation models for different damage types, thereby obtaining multiple first damage recognition models.

[0027] Then, multiple damage evaluation models are configured in parallel to form the first damage recognition layer. In this layer, each model works independently but is commonly connected to the input end. That is, a simple connection is made between the models, enabling multiple models to operate together and output results synchronously.

[0028] After the results are independently output by each model in the first damage recognition layer, these results are transmitted to the damage situation coding module through cascading technology. The coding module structurally encodes the recognition results, usually using predefined coding rules. Logical mapping processing converts the output results of the damage recognition layer into a standardized coding format, facilitating the identification and processing by the damage control system. During the coding process, unified situation coding information is generated based on the damage levels and positions output by each model.

[0029] By cascading and configuring the first damage recognition layer and the damage situation coding module, the establishment of the first ship damage monitoring node is completed. Through the above configuration process, taking the first partition as an example, this configuration step is repeated for other partitions in turn, ultimately obtaining ship damage monitoring nodes for multiple partitions.

[0030] Furthermore, in the method provided by the application embodiment, the pre-constructed damage situation coding module further includes:

[0031] Define entity nodes according to the first damage feature to obtain multiple damage type nodes; define rule nodes according to the damage levels of the first damage feature to obtain multiple groups of damage level nodes; configure coding rules for the multiple groups of damage level nodes to obtain multiple groups of damage rule nodes; construct the entity relationships among the multiple damage type nodes, multiple groups of damage level nodes, and multiple groups of damage rule nodes to obtain the damage situation coding module.

[0032] In the embodiment of the present application, first, a classification model is used to define entity nodes for the first damage feature, that is, the damage features are divided into independent nodes according to damage types such as cracks, temperature anomalies, and deformations. The classification model is constructed through training on a large amount of historical data, which comes from the historical records of ship damage monitoring and covers various damage types and their characteristics. A classification model, such as a support vector machine, after being trained with these data, can identify the damage types corresponding to different feature values. In actual operation, damage feature data such as temperature, vibration, and pressure are input into the classification model, and the model divides the data into different damage type nodes based on the feature parameters. For example, the model marks the crack type as "C", the temperature anomaly as "T", and the deformation as "D", and these nodes are stored in the database to form a preliminary structured node framework of the system.

[0033] After the damage type nodes are created, rule nodes are further defined according to the severity of each damage feature. This process divides each damage type into different levels, such as mild, moderate, and severe, by presetting thresholds. For example, for the rule nodes of temperature anomalies, it is set that when the temperature is lower than 60°C, it is mild, when it is between 60°C and 80°C, it is moderate, and when it exceeds 80°C, it is severe; for crack damage, when the length is less than 5mm, it is mild, when it is between 5 - 15mm, it is moderate, and when it exceeds 15mm, it is severe. Each damage level corresponds to a rule node, ensuring that the system can accurately identify and classify the severity of damage based on these rule nodes.

[0034] After the rule node definition is completed, it enters the coding rule configuration stage for subsequent implementation of standardized coding. In this step, a manual coding template is used to assign a unique code to each rule node. For example, the mild, moderate, and severe levels of temperature anomalies are coded as "T1", "T2", "T3" respectively; the mild, moderate, and severe levels of cracks are "C1", "C2", "C3" respectively. The coding template uses a manually defined format to unify the coding structure, such as "[type code]-[level code]", to ensure that the damage features and levels have consistent identifiers in subsequent processing and transmission.

[0035] Finally, establish the entity relationships among the damage type nodes, damage level nodes, and damage rule nodes to form a complete damage situation coding module. This process is achieved through relational database design. Each node is regarded as an independent table, and a foreign key relationship is established through the main table and sub-table structure. The damage type nodes are stored in the main table, while the level nodes and rule nodes are stored in the sub-tables and associated with the main table through foreign keys to automatically generate codes during query. The specific operation is to define the foreign key relationship through SQL statements, enabling each damage type node to find the relevant level and coding rule nodes along the entity relationship, so that the coding results can be generated in real time during actual monitoring.

[0036] Through the above steps, the definition and coding configuration of the damage type nodes, rule nodes, and damage rule nodes are completed, a complete entity relationship is constructed, and finally a standardized damage situation coding module is formed.

[0037] Step S200: Receive and analyze the real-time multimodal data of the multiple ship monitoring zones through the multiple ship damage monitoring nodes to generate multiple damage situation codes.

[0038] In the embodiment of the present application, first in the first ship damage monitoring node, the input interface module receives and transfers the real-time multimodal data of the first ship monitoring zone to the first damage recognition layer. In the damage recognition layer, the data undergoes multi-dimensional damage situation analysis and recognition to obtain multiple real-time damage situation information. These real-time damage situation information is output from the recognition layer and transferred to the cascaded damage situation coding module for generating the coding combination of damage information, and finally the first damage situation code is output. According to this process, through each ship damage monitoring node, the multimodal data of its respective zone is received and analyzed in turn, the multi-dimensional damage situation recognition and coding combination generation are completed, and thus multiple damage situation codes are output.

[0039] Furthermore, in the method provided by the embodiment of the application, receiving and analyzing the real-time multimodal data of the multiple ship monitoring zones through the multiple ship damage monitoring nodes to generate multiple damage situation codes further includes:

[0040] In the first ship damage monitoring node, the input interface module receives and transfers the real-time multimodal data of the first ship monitoring zone to the first damage recognition layer; through the first damage recognition layer, multi-dimensional damage situation recognition is performed to obtain multiple real-time damage situation information; the multiple real-time damage situation information is output from the first damage recognition layer to the cascaded damage situation coding module for generating the coding combination of damage codes, and the first damage situation code is output; and so on, through the multiple ship damage monitoring nodes, the real-time multimodal data of the multiple ship monitoring zones is received and analyzed to generate the multiple damage situation codes.

[0041] In the embodiment of the present application, the input interface module receives real-time multi-modal data from the sensor network of the first ship monitoring zone. These data are from different types of sensors, including temperature sensors, vibration sensors, and pressure sensors, and transfer these data to the first damage identification layer.

[0042] In the first damage identification layer, different damage features are respectively identified through multiple damage identification models. The multiple models in the identification layer operate in parallel. Each model independently receives and analyzes the sensor data to ensure that each damage feature can be effectively identified. In this way, the damage identification layer generates multi-dimensional damage situation information, including the type of damage (such as temperature anomaly, crack), severity (such as mild, moderate, severe), and location (such as engine room, cargo hold, etc.).

[0043] Once the identification is completed, the output information of the multiple damage identification models is standardized into real-time damage situation information and output from the first damage identification layer to the damage situation coding module. In the coding module, these identification information generate structured codes through predefined coding templates. The coding template combines the information of the identification layer in the format of "[damage type]-[severity]-[location]". For example, when a severe damage of fire (temperature anomaly) occurs in the engine room area, the code generated by the coding module is "T3-MC", where "T" represents temperature anomaly, 3 represents severe, and MC represents the engine room location. Through the fixed format of the coding template, it is ensured that the generated codes are consistent, enabling the quick interpretation and transmission of the codes for different damage features. The coding module automatically combines the damage type, severity, and location information to output the first damage situation code, representing the real-time damage state of the monitoring zone.

[0044] According to the same process, each ship damage monitoring node operates independently in multiple zones and generates multiple damage situation codes respectively through the steps of receiving, identifying, and coding.

[0045] Step S300: The damage control situation display center receives and configures the update frequency by analyzing the multiple damage situation codes to obtain multiple situation update frequencies.

[0046] In the embodiment of the present application, in the damage control situation display center, first, it receives the damage situation codes from multiple zones. These codes provide the type of damage (such as temperature anomaly, crack), severity (such as mild, moderate, severe), and specific location (such as engine room, cargo hold, etc.) of each zone. After receiving these codes, the display center analyzes the damage information of each zone to determine the risk level of each zone.

[0047] According to the analysis results, configure the update frequency for each partition. Specifically, adopt a priority allocation mechanism. For severely damaged partitions, such as high temperatures exceeding 100°C or cracks over 20 mm, configure them for high-frequency updates, for example, refreshing every 10 seconds; for moderately damaged partitions, such as temperatures between 60 - 100°C or cracks between 10 - 20 mm, configure them for medium-frequency updates, for example, refreshing every 30 seconds; and for slightly damaged partitions, such as temperatures below 60°C or cracks less than 10 mm, configure them for low-frequency updates, refreshing every 60 seconds.

[0048] Through this configuration, different update frequencies are assigned to each partition, enabling high-risk partitions to be monitored more frequently. Finally, after analysis and configuration, the damage control situation display center obtains multiple situation update frequencies.

[0049] Furthermore, in the method provided by the application embodiment, the damage control situation display center receives and configures the update frequency through analyzing the multiple damage situation codes, and obtains multiple situation update frequencies, further including:

[0050] Pre-construct an update frequency constraint table; after performing the decoding process of the multiple damage situation codes through mapping by the multiple real-time decoding engines in the damage situation decoding module to obtain multiple partition damage situations, traverse the update frequency constraint table with the multiple partition damage situations to obtain the multiple situation update frequencies.

[0051] In the embodiment of the present application, first pre-construct an update frequency constraint table in the damage control situation display center. This constraint table is configured through preset priority rules, classifying the update frequency of the damage situation according to the damage type and severity. For example, set severe damage of temperature anomaly in the table for high-frequency update (once every 10 seconds), moderate damage for medium-frequency update (once every 30 seconds), and slight damage for low-frequency update (once every 60 seconds). Through the construction of this constraint table, it is possible to quickly search and assign the update frequencies of different damage situations.

[0052] Next, the damage situation decoding module is started, and multiple real-time decoding engines work in parallel to parse the damage situation codes from each partition one by one. Each decoding engine uses parallel decoding technology to convert different damage coding information into the damage situation of the partition. The decoded content includes damage type (such as temperature anomaly, crack), severity (slight, moderate, severe), and location information (such as engine room, cargo hold, etc.). For example, when the decoding engine parses the temperature anomaly code "T3-MC", the obtained information after decoding is temperature anomaly, severe, and the location is the engine room area. Through parallel decoding processing, the damage situations of each partition can be quickly and accurately identified and generated by the decoding module.

[0053] After obtaining the damage situation of multiple partitions, start traversing the update frequency constraint table to allocate appropriate update frequencies for the damage situations of each partition. Using hash mapping technology, the decoded damage types and severities will automatically match the corresponding entries in the constraint table, thus quickly finding the corresponding update frequencies. For example, severe damage caused by abnormal temperature will match the high-frequency update entry (10 seconds), while mild damage caused by cracks will match the low-frequency update entry (60 seconds). Through this traversal process, it is ensured that the situation information of each partition can be updated at an appropriate frequency, which not only guarantees real-time monitoring of high-risk areas but also reasonably allocates system resources.

[0054] Finally, through decoding and traversing the constraint table, multiple situation update frequencies are obtained, and the update frequency of each partition is dynamically configured according to its damage characteristics and severity.

[0055] Step S400: After the damage control situation display center synthesizes virtual images by decoding the multiple damage situation codes and obtains multiple partition damage images, it synchronizes the multiple partition damage images to the ship damage control display screen for visual display.

[0056] In the embodiment of the present application, first, encoding rules are extracted from multiple ship damage monitoring nodes, and multiple encoding mapping tables are created based on the extraction results. Then, the decoding process of these mapping tables is configured to construct multiple real-time decoding engines. After these decoding engines are connected in parallel, a damage situation decoding module is formed and configured into the display center. In the decoding module, multiple real-time decoding engines map and execute the decoding process of the damage situation codes, thereby obtaining the damage situations of multiple partitions. Subsequently, the damage picture libraries of the partitions are traversed using the partition damage situation data, and virtual image calls and syntheses are performed to generate the damage images of each partition. Finally, with the partition as the display constraint, the multiple generated partition damage images are synchronized to the ship damage control display screen to achieve an intuitive visual display of the damage situation.

[0057] Furthermore, in the method provided by the application embodiment, after the damage control situation display center synthesizes virtual images by decoding the multiple damage situation codes and obtains multiple partition damage images, and synchronizes the multiple partition damage images to the ship damage control display screen for visual display, it further includes:

[0058] Extract encoding rules at the multiple ship damage monitoring nodes, and create multiple encoding mapping tables based on the extraction results; configure the decoding processes for the multiple encoding mapping tables, and construct multiple real-time decoding engines based on the configuration results; after identifying the multiple real-time decoding engines with the multiple ship monitoring zones, connect the multiple real-time decoding engines in parallel to generate a damage situation decoding module; after configuring the damage situation decoding module in the damage control situation display center, perform decoding processing on the multiple damage situation encodings through mapping by the multiple real-time decoding engines in the damage situation decoding module to obtain multiple zonal damage situations; traverse the zonal damage picture library with the multiple zonal damage situations to perform virtual image call synthesis to obtain the multiple zonal damage images; use the multiple ship monitoring zones as display constraints, and synchronize the multiple zonal damage images to the ship damage control display screen for visual display.

[0059] In the embodiment of the present application, among the multiple ship damage monitoring nodes, first extract the encoding rules and analyze the damage situation encoding structures of each node. Using the pattern matching algorithm, analyze each type of encoding field one by one, such as damage type, severity, location, etc., and extract the rule information of each damage encoding. Based on the extracted encoding rules, use a hash table to generate multiple encoding mapping tables, recording the mapping relationships between each encoding structure and damage information for subsequent decoding lookup and processing.

[0060] After completing the creation of the encoding mapping tables, configure the decoding processes. At this stage, define the decoding processes for each encoding through state machines, and each state machine specifically parses a certain type of encoding information. The state machine gradually reads each field of the encoding and matches the rules in the mapping table. For example, when the decoding process reads an encoding in the "Tx-Px" format, the state machine recognizes that "T" represents a temperature anomaly and stores the corresponding information. After configuring the decoding processes, generate a real-time decoding engine for each configuration process, and these engines can run in parallel to independently decode the damage encodings of their respective zones.

[0061] After the decoding engines are constructed, configure them in parallel to form an integrated damage situation decoding module. The parallel connection is achieved through multi-threading technology, and each engine independently processes the damage encoding data of its respective zone to ensure fast and concurrent decoding. For example, the decoding engines for the cargo hold and the engine room can run simultaneously to decode the encoding data of their respective zones. Through the parallel configuration, the decoding module meets the real-time decoding requirements of multiple zones.

[0062] After the damage situation decoding module is configured in the damage control situation display center, it officially enters the decoding stage, and multiple parallel decoding engines start to decode the received damage situation encoding in real time. Each engine parses the encoding information through the look-up table matching technology, matches the encoding fields with the rules in the mapping table, and converts them into standardized partition damage situation information. This information includes key damage types (such as abnormal temperature, cracks), severity levels (such as mild, moderate, severe), and locations (such as engine room, cargo hold). For example, when the decoding engine reads the encoding "T3-MC", through the look-up table, it is confirmed that this encoding represents an abnormal temperature in the engine room area and the severity level is severe.

[0063] After obtaining the damage situations of multiple partitions, it enters the virtual image synthesis stage. At this time, it traverses the damage situations of each partition and calls the corresponding virtual image templates in the partition damage picture library. Using image rendering and texture mapping technologies, the decoded damage information is converted into intuitive images. For example, if the decoded information is abnormal temperature severe in the engine room, this information is mapped to the heat map template, showing a gradual color change from green to red to display the degree of temperature increase; if it is a crack damage, select the crack image template to mark the crack position and length with high-contrast lines. Through this image calling and rendering, partition damage images that conform to the actual damage situation are generated.

[0064] After completing the synthesis of the damage images of each partition, the generated images are transmitted to the ship damage control display screen through real-time synchronization technology. Each partition image occupies a fixed area on the display screen to ensure that they do not overlap with each other, enabling the operator to intuitively view the damage status of each partition. The display screen performs display constraints according to the partitions and updates the damage images at a high frequency, so that the damage information of all partitions can be presented synchronously.

[0065] Through the above steps, the damage control situation display center has completed the whole process from encoding rule extraction, decoding process configuration, virtual image synthesis to real-time synchronous display, and finally multiple partition damage images are presented on the display screen.

[0066] Step S500: The damage control situation display center uses the multiple situation update frequencies as the visualization iteration constraints for the multiple partition damage images, and receives the feedback encodings of the multiple ship damage monitoring nodes to perform the visualization damage image iteration of the ship damage control display screen.

[0067] In the embodiment of the present application, in the damage control situation display center, first, the situation update frequency of each partition is set as a visual iteration constraint, which is used to dynamically control the refresh frequency of the damage images in different partitions. This update frequency is determined by the severity, change rate, and risk level of the damage. For example, partitions with severe high-temperature anomalies (such as temperatures exceeding 100 °C) or large cracks (exceeding 20 mm) are configured for high-frequency updates, that is, refreshed every 10 seconds, to ensure that the damage information in these high-risk areas is reflected in real time on the display screen. For partitions with minor damage (such as temperatures below 60 °C or cracks less than 5 mm), they are configured for low-frequency updates, refreshed every 60 seconds, to reduce system resource consumption while maintaining appropriate monitoring.

[0068] After configuring the visual iteration constraint, the damage control situation display center receives the backhaul codes from each ship damage monitoring node through a wireless or wired transmission protocol. These backhaul codes contain the real-time damage information of each partition, including the damage type (such as temperature anomaly, crack), severity (minor, moderate, severe), and location (such as engine room, cargo hold). When the backhaul code of each partition arrives, it enters the decoding module, parses the code fields one by one, and extracts the damage type, severity, and location to provide the latest situation information for display update.

[0069] After decoding, it is determined whether to immediately refresh the partition image according to the preset visual iteration constraint. For example, if the update frequency of a certain partition is 10 seconds, then every time 10 seconds is reached, the virtual image rendering engine is enabled to refresh and update the image of that partition. This rendering engine redraws the partition damage situation based on the decoding result. For example, when the temperature continues to rise, the color of the heat map will deepen or the coverage area will expand; when the crack grows, the crack image will display longer or deeper marks according to the decoding data.

[0070] The images of high-frequency update partitions (once every 10 seconds) are continuously refreshed, enabling the subtle changes in damage conditions such as temperature and cracks to be presented immediately; medium-frequency update partitions (once every 30 seconds) are displayed at a stable frequency, suitable for medium-risk areas; low-frequency update partitions (once every 60 seconds) are updated at longer time intervals for regular monitoring of low-risk areas. Through this partition update mechanism, it is ensured that high-risk areas receive high-frequency attention, while low-risk areas are monitored at low frequency, effectively optimizing the system resource allocation. Finally, the visual damage image iteration of the ship damage control display screen is completed through the above steps.

[0071] Furthermore, in the method provided by the application embodiment, before configuring the edge monitoring nodes according to the ship partitions to obtain multiple ship damage monitoring nodes for multiple ship monitoring partitions, it further includes:

[0072] Configure the monitoring sensors for the multiple ship monitoring zones according to the differences in damage characteristics to obtain multiple sensor requirement information; obtain M groups of device parameter information of M sample sensors by calling device model data after aggregating the multiple sensor requirement information; use the spatial scale of the multiple ship monitoring zones as the monitoring range constraint, and use the M groups of device parameter information as the device layout constraint to optimize the layout of the monitoring sensors for the multiple ship monitoring zones to obtain multiple multimodal monitoring arrays; map and construct one-way communication links between the multiple multimodal monitoring arrays and multiple ship damage monitoring nodes.

[0073] In the embodiment of the present application, when configuring the monitoring sensors for multiple ship monitoring zones, first clarify the monitoring requirements for each zone according to the differences in damage characteristics. The damage characteristics of each zone have been pre-fixed, and based on this characteristic, the sensor requirement information for each zone is directly generated. For example, assume that the first ship monitoring zone is the engine room area, and the monitoring requirements for this area include damage characteristics such as fire, overheating, oil leakage, and abnormal vibration. Therefore, the required first sensor requirement information is temperature sensors, smoke sensors, oil and gas leakage sensors, and vibration sensors.

[0074] After generating the multiple sensor requirement information, aggregate these requirements and enter the device model data call stage. By querying the device database, call and filter out suitable sensor devices according to the requirement conditions to obtain M groups of device parameter information of M sample sensors. Specifically, since the effective monitoring ranges of sensors are different and the device prices vary, preferentially select devices that meet the required monitoring range and have the optimal cost. For example, for temperature monitoring in the engine room area, if this area needs to cover a range of 30 meters, then search for a suitable temperature sensor model in the database to ensure that the sensor can meet both the monitoring requirements and the budget.

[0075] After completing the call of the device parameter information, enter the optimization configuration stage of sensor layout. In this stage, use the spatial scale of the ship monitoring zone as the monitoring range constraint, and use the M groups of device parameter information as the device layout constraint, and use the particle swarm optimization algorithm to optimize the sensor positions. The particle swarm algorithm gradually finds the optimal layout positions of the sensors by simulating the iterative movement of particles in space. For example, arrange the sensors in the engine room near the heat sources to monitor the temperature rise in a timely manner, and arrange the vibration sensors at key points such as structural columns to improve the sensitivity to abnormal vibration. After iterative optimization, multiple multimodal monitoring arrays are finally generated, and each array has been optimized according to the zone characteristics, achieving a balance between coverage integrity and monitoring efficiency.

[0076] After the multi-modal monitoring array is configured, a one-way communication link is established between each array and the ship damage monitoring node. A wireless transmission protocol, such as LoRa or ZigBee, is used to set up an independent communication link for each array to ensure that sensor data can be transmitted unidirectionally and efficiently to the monitoring node. Specifically, for long-distance partitions, such as from the engine room to the central control area, the low-power, long-distance LoRa protocol is selected, while for local areas such as inside the engine room, the ZigBee protocol that supports high bandwidth is adopted. Each sensor is assigned an independent channel and frequency band to avoid interference and improve data transmission stability.

[0077] Through the above process, the full-process configuration from sensor requirement generation, device parameter invocation, optimized layout to communication link mapping is completed. The finally formed multi-modal monitoring array and one-way communication link ensure the real-time monitoring ability of each partition, enabling the ship damage monitoring system to accurately monitor features such as fire, overheating, leakage, and abnormal vibration, providing reliable support for the safety management of the entire ship.

[0078] Furthermore, in the method provided by the application embodiment, with the spatial scale of the multiple ship monitoring partitions as the monitoring range constraint and the M groups of device parameter information as the device layout constraint, the monitoring sensor layout of the multiple ship monitoring partitions is optimized to obtain multiple multi-modal monitoring arrays, and it further includes:

[0079] Use the first required sensors in the first sensor requirement information to traverse the M groups of device parameter information to obtain the first group of required parameter information, where the first group of required parameter information includes the sensing coverage areas of N available sensors and the N device purchase unit prices; with the spatial scale of the first ship monitoring partition as the monitoring range constraint and the N sensing coverage areas as the device layout constraint, optimize the layout coverage of the first ship monitoring partition to obtain multiple device layout configurations; use the N device purchase unit prices to evaluate the multiple device layout configurations, and perform a minimum value call based on the evaluation results to obtain the first monitoring modality unit; and so on, optimize the layout coverage of the first ship monitoring partition according to the first sensor requirement information to obtain multiple monitoring modality units to form the first multi-modal monitoring array; and so on, optimize the monitoring sensor layout of the multiple ship monitoring partitions to obtain the multiple multi-modal monitoring arrays.

[0080] In the embodiments of the present application, during the process of configuring the monitoring sensors for multiple ship monitoring zones, first, the first sensor requirement information is used to identify the specific parameter requirements of each type of required sensor in the zone. Taking the engine room zone as an example, the first required sensor is a temperature sensor. The model and parameter information of M groups of sensor devices are called from the database to traverse these device data and screen out the sensors that meet the requirements, thereby obtaining the first group of required parameter information. This information includes the sensing coverage areas (monitoring ranges of each sensor) and unit procurement prices of N available temperature sensors. For example, the sensing coverage area of a certain sensor is 20 meters and the unit price is 100 yuan, and another is 30 meters and the unit price is 150 yuan.

[0081] After obtaining the first group of required parameter information, the monitoring range of the first ship monitoring zone is constrained by the spatial scale to ensure full coverage of the entire monitoring area. Using the sensing coverage areas of N sensors as the device layout constraints, layout coverage optimization is carried out, and appropriate sensor types and quantities are selected to achieve full coverage within the monitoring area. At this time, a layout optimization algorithm, such as particle swarm optimization, is used to try different sensor combinations according to the partition spatial layout, and multiple device layout configurations are generated. Each configuration contains different sensor distribution combinations, sensor types and quantities, and all configurations meet the full coverage requirements of the monitoring range. For example, a layout configuration may contain two sensors with a 20-meter coverage and one sensor with a 30-meter coverage, while another configuration may contain three sensors with a 15-meter coverage.

[0082] Among the multiple generated device layout configurations, the N device procurement unit prices are used to evaluate the cost of the configurations. By calculating the total procurement cost of each configuration one by one, the most cost-effective configuration is found. The minimum value calling method is adopted to select the configuration with the lowest total cost as the optimized final solution, and the first monitoring mode unit is obtained. This unit not only ensures the monitoring coverage within the zone but also minimizes the device procurement cost.

[0083] According to the same process, the layout coverage of other required sensors in the first zone is optimized, and all optimized mode units are combined to form the first multi-mode monitoring array to meet the multiple monitoring requirements of the first zone. Subsequently, the configuration optimization of other ship monitoring zones is carried out in turn to generate the multi-mode monitoring arrays of all zones.

[0084] Through these configured multi-mode monitoring arrays, each ship damage monitoring node receives and analyzes the real-time multi-mode data of each ship monitoring zone. These monitoring nodes synchronously process the sensor data from each zone, comprehensively analyze various damage information such as temperature anomalies, oil and gas leaks, and vibrations, and realize the real-time monitoring of the overall condition of the ship.

[0085] In the embodiments of the present application, in summary, the embodiments of the present application at least have the following technical effects:

[0086] In the present application, edge monitoring nodes are configured according to the ship's partitions to obtain multiple ship damage monitoring nodes for multiple ship monitoring partitions; multiple real-time multimodal data of multiple ship monitoring partitions are received and analyzed by the multiple ship damage monitoring nodes to generate multiple damage situation codes; the damage control situation display center receives and configures the update frequency by analyzing the multiple damage situation codes to obtain multiple situation update frequencies; after the damage control situation display center synthesizes virtual images by decoding the multiple damage situation codes to obtain multiple partition damage images, the multiple partition damage images are synchronized to the ship damage control display screen for visual display; the damage control situation display center uses the multiple situation update frequencies as the visual iteration constraints for the multiple partition damage images, and receives the feedback codes of the multiple ship damage monitoring nodes for visual damage image iteration of the ship damage control display screen. The present invention solves the technical problem that the prior art cannot comprehensively display the damage situation of the whole ship in real time, which affects the efficiency and accuracy of emergency response. By configuring edge monitoring nodes in each ship partition, receiving and analyzing multimodal data to generate damage situation codes, the damage control situation display center analyzes and synthesizes the damage images of each partition, and realizes dynamic image iteration with the update frequency as the constraint, so as to realize real-time monitoring and synchronous visual display of ship damage information, and achieve the technical effect of improving the damage situation perception and emergency response efficiency.

[0087] Embodiment 2, based on the same inventive concept as a ship damage control synchronous visualization method in the foregoing embodiment, as Figure 2 shown, the present application provides a ship damage control synchronous visualization platform, and the platform and method embodiments in the embodiments of the present application are based on the same inventive concept. Among them, the platform includes:

[0088] Node configuration unit 11, which configures edge monitoring nodes according to ship partitions to obtain multiple ship damage monitoring nodes for multiple ship monitoring partitions; multimodal data analysis unit 12, which receives and analyzes real-time multimodal data of the multiple ship monitoring partitions through the multiple ship damage monitoring nodes to generate multiple damage situation codes; update frequency configuration unit 13, which receives through the damage control situation display center and configures the update frequency by analyzing the multiple damage situation codes to obtain multiple situation update frequencies; virtual image synthesis unit 14, which synthesizes virtual images by decoding the multiple damage situation codes through the damage control situation display center. After obtaining multiple partition damage images, the multiple partition damage images are synchronized to the ship damage control display screen for visual display; visualization iteration unit 15, which uses the multiple situation update frequencies as the visualization iteration constraints for the multiple partition damage images through the damage control situation display center, and receives the feedback codes of the multiple ship damage monitoring nodes to perform visualization damage image iteration on the ship damage control display screen.

[0089] Further, the platform is also used to implement the following functions:

[0090] In the first ship damage monitoring node, the input interface module receives and transfers the real-time multimodal data of the first ship monitoring partition to the first damage recognition layer; through the first damage recognition layer, multi-dimensional damage situation recognition is performed to obtain multiple real-time damage situation information; the multiple real-time damage situation information is output by the first damage recognition layer to the cascaded damage situation coding module for the combination generation of damage codes, and the first damage situation code is output; and so on, the real-time multimodal data of the multiple ship monitoring partitions is received and analyzed through the multiple ship damage monitoring nodes to generate the multiple damage situation codes.

[0091] Further, the platform is also used to implement the following functions:

[0092] According to the first damage characteristics of the first ship monitoring partition, damage data is called through the network to obtain multiple sample damage data sets of multiple damage types; after quantifying the damage levels of the multiple sample damage data sets, the multiple sample damage data sets are used to construct a damage evaluation model to obtain multiple first damage recognition models; the multiple first damage recognition models are connected in parallel to obtain the first damage recognition layer; by cascading the first damage recognition layer with the damage situation coding module, the configuration of the first ship damage monitoring node is completed; and so on, edge monitoring nodes are configured according to ship partitions to obtain the multiple ship damage monitoring nodes.

[0093] Further, the platform is also used to implement the following functions:

[0094] Define entity nodes according to the first damage feature to obtain multiple damage type nodes; define rule nodes according to the damage level of the first damage feature to obtain multiple groups of damage level nodes; configure coding rules for the multiple groups of damage level nodes to obtain multiple groups of damage rule nodes; construct the entity relationship between the multiple damage type nodes, multiple groups of damage level nodes and multiple groups of damage rule nodes to obtain the damage situation coding module.

[0095] Further, the platform is also used to implement the following functions:

[0096] Extract coding rules from the multiple ship damage monitoring nodes, and create multiple coding mapping tables based on the extraction results; configure the decoding process for the multiple coding mapping tables, and construct multiple real-time decoding engines based on the configuration results; after identifying the multiple real-time decoding engines with the multiple ship monitoring partitions, connect the multiple real-time decoding engines in parallel to generate a damage situation decoding module; after configuring the damage situation decoding module in the damage control situation display center, perform decoding processing of the multiple damage situation encodings through mapping by the multiple real-time decoding engines in the damage situation decoding module to obtain multiple partition damage situations; traverse the partition damage picture library with the multiple partition damage situations to perform virtual image call synthesis to obtain the multiple partition damage images; use the multiple ship monitoring partitions as display constraints, and synchronize the multiple partition damage images to the ship damage control display screen for visual display.

[0097] Further, the platform is also used to implement the following functions:

[0098] Pre-construct an update frequency constraint table; after performing decoding processing of the multiple damage situation encodings through mapping by the multiple real-time decoding engines in the damage situation decoding module to obtain multiple partition damage situations, traverse the update frequency constraint table with the multiple partition damage situations to obtain the multiple situation update frequencies.

[0099] Further, the platform is also used to implement the following functions:

[0100] Configure the monitoring sensors for the multiple ship monitoring zones according to the damage characteristic differences to obtain multiple sensor requirement information; obtain M groups of device parameter information of M sample sensors by invoking device model data after aggregating the multiple sensor requirement information; optimize the layout of the monitoring sensors for the multiple ship monitoring zones with the spatial scale of the multiple ship monitoring zones as the monitoring range constraint and the M groups of device parameter information as the device layout constraint to obtain multiple multimodal monitoring arrays; map and construct one-way communication links between the multiple multimodal monitoring arrays and multiple ship damage monitoring nodes.

[0101] Further, the platform is also used to implement the following functions:

[0102] Traverse the M groups of device parameter information with the first required sensor in the first sensor requirement information to obtain the first group of required parameter information, where the first group of required parameter information includes the sensing coverage areas of N available sensors and the device purchase unit prices of N; optimize the layout coverage of the first ship monitoring zone with the spatial scale of the first ship monitoring zone as the monitoring range constraint and the N sensing coverage areas as the device layout constraint to obtain multiple device layout configurations; evaluate the multiple device layout configurations with the N device purchase unit prices and perform a minimum value call based on the evaluation results to obtain the first monitoring modality unit; and so on, optimize the layout coverage of the first ship monitoring zone according to the first sensor requirement information to obtain multiple monitoring modality units that constitute the first multimodal monitoring array; and so on, optimize the layout of the monitoring sensors for the multiple ship monitoring zones to obtain the multiple multimodal monitoring arrays.

[0103] It should be noted that the above sequence of embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. And the above describes specific embodiments of this specification. The processes depicted in the drawings do not necessarily require the specific order and continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0104] The above are only the preferred embodiments of the present application and are not used to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

[0105] This specification and the drawings are only exemplary descriptions of the present application and are considered to have covered any and all modifications, variations, combinations, or equivalents within the scope of the present application. Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalent technologies, the present application is intended to include these changes and modifications.

Claims

1. A synchronous visualization method for ship damage control, characterized in that: The method comprises: Configure edge monitoring nodes according to ship partitions to obtain multiple ship damage monitoring nodes in multiple ship monitoring partitions; Receiving and analyzing the real-time multimodal data of the multiple ship monitoring partitions through the multiple ship damage monitoring nodes to generate multiple damage situation codes; The damage control situation display center receives and configures the update frequency by analyzing the multiple damage situation codes to obtain multiple situation update frequencies; The damage control situation display center synthesizes virtual images by decoding the multiple damage situation codes to obtain multiple partition damage images, and then synchronizes the multiple partition damage images to the ship damage control display screen for visual display; The damage control situation display center uses the multiple situation update frequencies as visualization iteration constraints of the multiple partition damage images, receives the return codes from the multiple ship damage monitoring nodes, and performs visualization damage image iteration of the ship damage control display screen; Pre-constructing a damage situation encoding module, the method comprises: Define entity nodes according to the first damage feature to obtain multiple damage type nodes; Define rule nodes according to the damage level of the first damage feature to obtain multiple groups of damage level nodes; Performing coding rule configuration on the multiple groups of damage level nodes to obtain multiple groups of damage rule nodes; The entity relationships among the multiple damage type nodes, the multiple groups of damage level nodes and the multiple groups of damage rule nodes are constructed to obtain the damage situation encoding module.

2. A method for synchronous visualization of ship damage control according to claim 1, characterized in that: Receiving and analyzing the real-time multimodal data of the multiple ship monitoring partitions through the multiple ship damage monitoring nodes to generate multiple damage situation codes, the method comprising: In the first ship damage monitoring node, the input interface module receives and transmits the real-time multimodal data of the first ship monitoring partition to the first damage identification layer; Performing multi-dimensional damage situation identification via the first damage identification layer to obtain multiple real-time damage situation information; The plurality of real-time damage situation information are outputted by the first damage identification layer to the cascaded damage situation coding module for combined generation of damage codes, and a first damage situation code is outputted; By analogy, the real-time multimodal data of the multiple ship monitoring partitions are received and analyzed by the multiple ship damage monitoring nodes to generate the multiple damage situation codes.

3. A method for synchronous visualization of ship damage control according to claim 2, characterized in that: Edge monitoring nodes are configured according to ship partitions to obtain multiple ship damage monitoring nodes in multiple ship monitoring partitions. The method includes: Calling damage data online according to the first damage feature of the first ship monitoring zone to obtain multiple sample damage data sets of multiple damage types; After quantifying the damage levels of the plurality of sample damage data sets, constructing a damage assessment model using the plurality of sample damage data sets to obtain a plurality of first damage identification models; Connecting the plurality of first damage identification models in parallel to obtain the first damage identification layer; The configuration of the first ship damage monitoring node is completed by cascading the first damage identification layer with the damage situation encoding module; By analogy, the edge monitoring nodes are configured according to the ship partitions to obtain the multiple ship damage monitoring nodes.

4. A method for synchronous visualization of ship damage control according to claim 1, characterized in that: After the damage control situation display center obtains multiple partition damage images by decoding the multiple damage situation codes to perform virtual image synthesis, the multiple partition damage images are synchronized to the ship damage control display screen for visual display, and the method includes: Extracting coding rules at the plurality of ship damage monitoring nodes, and creating a plurality of coding mapping tables based on the extraction results; Performing decoding process configuration on the multiple encoding mapping tables, and constructing multiple real-time decoding engines based on the configuration results; After identifying the multiple real-time decoding engines using the multiple ship monitoring zones, connecting the multiple real-time decoding engines in parallel to generate a damage situation decoding module; After the damage situation decoding module is configured in the damage control situation display center, the multiple real-time decoding engines in the damage situation decoding module map and perform decoding processing of the multiple damage situation codes to obtain multiple partition damage situations; Using the multiple partition damage situations to traverse the partition damage library, perform virtual image call synthesis, and obtain the multiple partition damage images; The multiple ship monitoring partitions are used as display constraints, and the damage images of the multiple partitions are synchronized to the ship damage control display screen for visual display.

5. A method for synchronous visualization of ship damage control according to claim 4, characterized in that: The damage control situation display center receives and configures the update frequency by analyzing the multiple damage situation codes to obtain multiple situation update frequencies. The method includes: Pre-build update frequency constraint table; After the decoding processing of the multiple damage situation codes is executed through the multiple real-time decoding engine mappings in the damage situation decoding module to obtain multiple partition damage situations, the update frequency constraint table is traversed using the multiple partition damage situations to obtain the multiple situation update frequencies.

6. A method for synchronous visualization of ship damage control according to claim 1, characterized in that: Before configuring edge monitoring nodes according to ship partitions to obtain multiple ship damage monitoring nodes in multiple ship monitoring partitions, the method includes: Performing monitoring sensor configuration of the plurality of ship monitoring zones according to differences in damage characteristics, and obtaining a plurality of sensor requirement information; By calling device model data after aggregating the plurality of sensor requirement information, M groups of device parameter information of M types of sample sensors are obtained; Taking the spatial scales of the multiple ship monitoring partitions as monitoring range constraints and taking the M groups of equipment parameter information as equipment layout constraints, optimizing the layout of monitoring sensors for the multiple ship monitoring partitions to obtain multiple multi-modal monitoring arrays; Mapping constructs unidirectional communication links between the multiple multimodal monitoring arrays and multiple ship damage monitoring nodes.

7. A method for synchronous visualization of ship damage control according to claim 6, characterized in that: Taking the spatial scales of the multiple ship monitoring partitions as monitoring range constraints and taking the M groups of equipment parameter information as equipment layout constraints, optimizing the layout of monitoring sensors for the multiple ship monitoring partitions to obtain multiple multimodal monitoring arrays, the method includes: Using the first demand sensor in the first sensor demand information to traverse the M sets of device parameter information to obtain a first set of demand parameter information, wherein the first set of demand parameter information includes N sensing coverage areas of N available sensors and N device purchase unit prices; Taking the spatial scale of the first ship monitoring zone as the monitoring range constraint and the N sensing coverage areas as the equipment deployment constraint, optimizing the deployment coverage of the first ship monitoring zone to obtain multiple equipment deployment configurations; Using the purchase unit prices of the N devices to evaluate the layout configurations of the multiple devices, and performing a minimum value call based on the evaluation results to obtain a first monitoring modal unit; By analogy, the first ship monitoring partition is optimized for layout and coverage according to the first sensor requirement information, and a plurality of monitoring modal units are obtained to form a first multi-modal monitoring array; By analogy, the monitoring sensors are optimally deployed for the multiple ship monitoring zones to obtain the multiple multimodal monitoring arrays.

8. A ship damage control synchronous visualization platform, characterized in that: The platform includes: A node configuration unit, wherein the node configuration unit performs edge monitoring node configuration according to the ship partitions to obtain multiple ship damage monitoring nodes of multiple ship monitoring partitions; a multimodal data analysis unit, which receives and analyzes the real-time multimodal data of the multiple ship monitoring partitions through the multiple ship damage monitoring nodes to generate multiple damage situation codes; An update frequency configuration unit, wherein the update frequency configuration unit receives the damage control situation display center and configures the update frequency by analyzing the multiple damage situation codes to obtain multiple situation update frequencies; A virtual image synthesis unit, wherein the virtual image synthesis unit synthesizes virtual images by decoding the multiple damage situation codes through the damage control situation display center, obtains multiple partition damage images, and then synchronizes the multiple partition damage images to the ship damage control display screen for visual display; A visualization iteration unit, wherein the visualization iteration unit uses the multiple situation update frequencies as visualization iteration constraints of the multiple partition damage images through the damage control situation display center, receives the return codes of the multiple ship damage monitoring nodes, and performs visualization damage image iteration of the ship damage control display screen; Furthermore, the platform is also used to implement the following functions: Define entity nodes according to the first damage feature to obtain multiple damage type nodes; define rule nodes according to the damage level of the first damage feature to obtain multiple groups of damage level nodes; configure encoding rules for the multiple groups of damage level nodes to obtain multiple groups of damage rule nodes; construct entity relationships among the multiple damage type nodes, the multiple groups of damage level nodes and the multiple groups of damage rule nodes to obtain the damage situation encoding module.

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