Ship damage management synchronous visualization method and platform

Abstract

The invention discloses a ship damage management synchronous visualization method and platform, and relates to the technical field of ship monitoring, and the method comprises the steps: carrying out the configuration of edge monitoring nodes, and obtaining a plurality of ship damage monitoring nodes; analyzing the real-time multi-modal data of the plurality of ship monitoring partitions, and generating a plurality of damage situation codes; analyzing the plurality of damage situation codes to perform update frequency configuration to obtain a plurality of situation update frequencies; decoding the plurality of damage situation codes to perform virtual image synthesis to obtain a plurality of partition damage images, and performing visual display; and taking the plurality of situation updating frequencies as visual iteration constraints of the plurality of partition damage images, and receiving return codes of the plurality of ship damage monitoring nodes to perform visual damage image iteration of the ship damage management display screen. The technical problems that the whole ship damage condition cannot be comprehensively displayed in real time in the prior art, and the emergency disposal efficiency and accuracy are affected are solved, and the technical effect of improving the damage situation awareness and emergency response efficiency is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of ship monitoring, and in particular to a ship damage control synchronous 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 of the entire ship in real time and comprehensively. Traditional monitoring systems lack the integration and dynamic visualization of multimodal data. The crew cannot view the damage status of each partition on the display screen in a timely and clear manner, affecting the efficiency and accuracy of emergency response. Summary of the invention

[0003] The present application provides a method and platform for synchronous visualization of ship damage control, which is used to solve the technical problem that the existing technology cannot fully and real-time display the damage of the entire ship, and there is a problem that affects the efficiency and accuracy of emergency response.

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

[0005] In a first aspect of the present application, a method for synchronous visualization of ship damage control is provided, the method comprising:

[0006] Edge monitoring nodes are configured according to ship partitions to obtain multiple ship damage monitoring nodes of multiple ship monitoring partitions; real-time multimodal data of the multiple ship monitoring partitions are received and analyzed by the multiple ship damage monitoring nodes to generate multiple damage situation codes; a damage control situation display center receives and configures update frequencies 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 visual iteration constraints of the multiple partition damage images, receives the return codes of the multiple ship damage monitoring nodes to iterate the visual damage images of the ship damage control display screen.

[0007] The second aspect of the present application provides a ship damage control synchronous visualization platform, the platform comprising:

[0008] A node configuration unit, wherein the node configuration unit configures edge monitoring nodes according to ship partitions to obtain multiple ship damage monitoring nodes of multiple ship monitoring partitions; a multimodal data analysis unit, wherein the multimodal data analysis unit 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 and configures the update frequency through the damage control situation display center 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 through the damage control situation display center 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; 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 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] The present 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; a damage control situation display center receives and configures update frequencies 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 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 multiple situation update frequencies as visual iteration constraints for multiple partition damage images, receives the return codes of multiple ship damage monitoring nodes to iterate the visual damage images of the ship damage control display screen. The present invention solves the technical problem that the prior art cannot fully and real-time display the damage of the entire ship, 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 coding, the damage control situation display center parses and synthesizes the damage image of each partition, and realizes dynamic iteration of the image with the update frequency as a constraint, real-time monitoring and synchronous visual display of ship damage information are realized, so as to achieve the technical effect of improving damage situation awareness and emergency response efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0012] Figure 1 A schematic diagram of a synchronous visualization method for ship damage control provided in an embodiment of the present application;

[0013] Figure 2 A schematic diagram of the structure of a ship damage control synchronous visualization platform provided in an embodiment of the present application.

[0014] Explanation of the accompanying drawings: node configuration unit 11, multimodal data analysis unit 12, update frequency configuration unit 13, virtual image synthesis unit 14, visualization iteration unit 15. DETAILED DESCRIPTION

[0015] The present application provides a method and platform for synchronous visualization of ship damage control, aiming to solve the technical problem that the existing technology cannot fully and real-time display the damage of the entire ship, 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 coding, the damage control situation display center parses and synthesizes the damage image of each partition, and realizes dynamic iteration of the image with the update frequency as a constraint, realizing real-time monitoring and synchronous visualization of ship damage information, and achieving the technical effect of improving damage situation awareness and emergency response efficiency.

[0016] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

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

[0018] Embodiment 1, as Figure 1 As shown, the present application provides a method for synchronous visualization of ship damage control, the method comprising:

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

[0020] In an embodiment of the present application, the hull is first divided into multiple monitoring zones according to the functional areas and physical boundaries of the ship. For example, the engine room, deck, living area and cargo hold area, etc. On this basis, at the boundary of each monitoring zone, 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, pressure sensors, etc. are installed on each edge node. Each edge node is configured according to uniform specifications to achieve standardized data collection between monitoring nodes in different areas.

[0021] Through the above steps, the configuration of the edge monitoring nodes of each ship partition is completed, so that each monitoring partition has damage monitoring capabilities, and finally multiple edge damage monitoring nodes of multiple ship partitions are obtained.

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

[0023] According to the first damage feature of the first ship monitoring zone, damage data is called online 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 damage assessment models to obtain multiple first damage identification models; the multiple first damage identification models are connected 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; and by analogy, edge monitoring nodes are configured according to the ship zones to obtain the multiple ship damage monitoring nodes.

[0024] In an embodiment of the present application, the first ship monitoring zone refers to an independent area in the hull structure, which has clear physical boundaries and functional divisions in the overall structure of the ship, and can be used as a separate monitoring unit to collect and analyze damage data. The first damage feature refers to the damage attribute that is initially defined or identified in the zone, including temperature, pressure, deformation and other characteristics. Based on the first damage feature, the damage data is first called online to extract relevant historical data and damage records from the database. This process calls damage sample data sets from multiple data sources through database query technology or API interfaces. These data sets cover different types of damage events, such as cracks, temperature anomalies, etc. Through this process, multiple sample damage data sets of multiple damage types are obtained.

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

[0026] The quantized data set is then used to construct a damage assessment model using a machine learning algorithm. The model training process uses a decision tree model. When training the model, data preprocessing is first performed, and features that are critical to damage identification, such as changes in specific temperature and pressure, are determined through feature selection, and the data is standardized. This data is then input into the decision tree algorithm, and the optimal features are selected through recursive segmentation and information gain, and finally a decision tree model that can effectively identify different damage levels is constructed. This process is repeated on multiple groups of sample data sets, and independent evaluation models for different damage types are constructed, thereby obtaining multiple first damage identification models.

[0027] Then, multiple damage assessment models are configured in parallel to form the first damage identification layer. In this layer, each model works independently but is connected to the input terminal. That is, a simple connection is made between the models so that multiple models can run together and output results synchronously.

[0028] After each model of the first damage identification layer independently outputs results, these results are passed to the damage situation coding module through cascading technology. The coding module performs structured coding on the identification results, usually using predefined coding rules. Logical mapping processing converts the output results of the damage identification layer into a standardized coding format to facilitate identification and processing by the damage control system. During the coding process, unified situation coding information is generated based on the damage level and location output by each model.

[0029] By cascading the first damage identification layer and the damage situation coding module, the first ship damage monitoring node is established. Through the above configuration process, taking the first partition as an example, the configuration steps are repeated for other partitions in turn, and finally the ship damage monitoring nodes of multiple partitions are obtained.

[0030] Furthermore, in the method provided in the embodiment of the application, the damage situation coding module is pre-built, and 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 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.

[0032] In an embodiment of the present application, firstly, the entity node definition of the first damage feature is performed through a classification model, that is, the damage feature is divided into independent nodes according to the damage type, such as cracks, temperature anomalies, deformation, etc. The classification model is constructed by training a large amount of historical data. These data come from the damage monitoring history records of the ship, covering a variety of damage types and their characteristics. Classification models, such as support vector machines, are trained with these data to identify the types of damage corresponding to different characteristic values. In actual operation, damage feature data, such as temperature, vibration, pressure, etc., are input into the classification model, and the model divides the data into different damage type nodes based on the characteristic parameters. For example, the model marks the crack type as "C", the temperature anomaly as "T", and the deformation as "D". These nodes are stored in the database to form a preliminary structured node framework of the system.

[0033] After the damage type node is created, the rule node is 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 node of temperature anomaly, the temperature below 60°C is set as mild, 60°C to 80°C is set as moderate, and over 80°C is set as severe; for crack damage, the length is set as mild when it is less than 5mm, moderate when it is 5-15mm, and severe when it is over 15mm. Each damage level corresponds to a rule node, ensuring that the system can accurately identify and classify the severity of the damage based on these rule nodes.

[0034] After completing the definition of the rule nodes, enter the coding rule configuration stage to implement standardized coding later. 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 temperature anomalies are coded as "T1", "T2", and "T3" respectively; the mild, moderate, and severe cracks are coded as "C1", "C2", and "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 characteristics and levels have consistent identification in subsequent processing and transmission.

[0035] Finally, the entity relationships among damage type nodes, damage level nodes, and damage rule nodes are constructed to form a complete damage situation coding module. This process is implemented through relational database design, where each node is treated 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-table and are associated with the main table through foreign keys so that the coding can be automatically generated when querying. The specific operation is to define the foreign key relationship through SQL statements so that each damage type node can find the relevant level and coding rule nodes along the entity relationship, so that the coding results can be generated in real time in actual monitoring.

[0036] Through the above steps, the definition and coding configuration of 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: 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.

[0038] In an embodiment of the present application, first, 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. In the damage identification layer, the data undergoes multi-dimensional damage situation analysis and identification to obtain multiple real-time damage situation information. These real-time damage situation information are output from the identification layer and transmitted to the cascaded damage situation coding module to generate a coding combination of the damage information, and finally output the first damage situation code. According to this process, each ship damage monitoring node receives and analyzes the multimodal data of each partition in turn, completes multi-dimensional damage situation identification and coding combination generation, and outputs multiple damage situation codes.

[0039] Furthermore, in the method provided in the embodiment of the application, the real-time multimodal data of the multiple ship monitoring partitions are received and analyzed by the multiple ship damage monitoring nodes to generate multiple damage situation codes, and further includes:

[0040] 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; multi-dimensional damage situation identification is performed through the first damage identification layer to obtain multiple real-time damage situation information; the multiple real-time damage situation information is output by the first damage identification layer to the cascaded damage situation coding module for combined 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 are received and analyzed by the multiple ship damage monitoring nodes to generate the multiple damage situation codes.

[0041] In an embodiment of the present application, the input interface module receives real-time multimodal data from a sensor network of the first ship monitoring zone, which is derived from different types of sensors, including temperature sensors, vibration sensors, and pressure sensors, and transmits the data to the first damage identification layer.

[0042] In the first damage identification layer, different damage features are identified separately through multiple damage identification models. Multiple models in the identification layer run in parallel, and each model independently receives and analyzes 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, cracks), severity (such as mild, moderate, severe) and location (such as cabin, cargo hold, etc.).

[0043] Once the identification is completed, the output information of multiple damage identification models is standardized into real-time damage situation information and output from the first damage identification layer to the damage situation encoding module. In the encoding module, these identification information are converted into 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 severe damage caused by fire (temperature anomaly) occurs in the cabin area, the code generated by the coding module is "T3-MC", where "T" represents temperature anomaly, 3 represents severe, and MC represents the cabin location. The fixed format of the coding template ensures that the generated codes are consistent, so that the codes of different damage characteristics can be quickly interpreted and transmitted. The coding module automatically combines the damage type, severity and location information to output the first damage situation code, which represents the real-time damage status of the monitored partition.

[0044] Following the same process, each ship damage monitoring node operates independently in multiple partitions and generates multiple damage situation codes through receiving, identifying and encoding steps.

[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, the damage control situation display center first receives damage situation codes from multiple partitions, which provide the damage type (such as temperature anomaly, crack), severity (such as mild, moderate, severe) and specific location (such as cabin, cargo hold, etc.) of each partition. After receiving these codes, the display center analyzes the damage information of each partition and determines the risk level of each partition.

[0047] According to the analysis results, the update frequency of each partition is configured. Specifically, a priority allocation mechanism is adopted. For severely damaged partitions, such as high temperatures exceeding 100°C or cracks larger than 20mm, high-frequency updates are configured, such as refreshes every 10 seconds; for moderately damaged partitions, such as temperatures between 60-100°C or cracks between 10-20mm, medium-frequency updates are configured, such as refreshes every 30 seconds; and for slightly damaged partitions, such as temperatures below 60°C or cracks smaller than 10mm, low-frequency updates are configured, refreshes every 60 seconds.

[0048] Through this configuration, different update frequencies are assigned to each partition, so that high-risk partitions can 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 in the embodiment of the application, 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, and further includes:

[0050] Pre-construct an update frequency constraint table; after performing decoding processing of the multiple damage situation codes via the multiple real-time decoding engine mappings in the damage situation decoding module to obtain multiple partition damage situations, use the multiple partition damage situations to traverse the update frequency constraint table to obtain the multiple situation update frequencies.

[0051] In an embodiment of the present application, an update frequency constraint table is first pre-constructed in the damage control situation display center. This constraint table is configured by preset priority rules to classify the update frequency of the damage situation according to the damage type and severity. For example, the table sets severe damage of temperature anomaly as high-frequency update (once every 10 seconds), moderate damage as medium-frequency update (once every 30 seconds), and mild damage as low-frequency update (once every 60 seconds). Through the construction of this constraint table, the update frequency of different damage situations can be quickly found and allocated.

[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 code information into the damage situation of the partition. The decoding content includes damage type (such as temperature anomaly, cracks), severity (mild, moderate, severe) and location information (such as cabin, cargo hold, etc.). For example, when the decoding engine parses the temperature anomaly code "T3-MC", the information obtained after decoding is temperature anomaly, severe, and the location is the cabin area. Through parallel decoding processing, the damage situation of each partition can be quickly and accurately identified and generated by the decoding module.

[0053] After obtaining the damage status of multiple partitions, the update frequency constraint table is traversed to assign the appropriate update frequency to the damage status of each partition. Using hash mapping technology, the decoded damage type and severity are automatically matched to the corresponding entries in the constraint table, so that the corresponding update frequency can be quickly found. For example, severe damage caused by temperature anomalies will match high-frequency update entries (10 seconds), while mild damage caused by cracks will match low-frequency update entries (60 seconds). This traversal process ensures that the status information of each partition can be updated at an appropriate frequency, which not only ensures real-time monitoring of high-risk areas, but also reasonably allocates system resources.

[0054] Finally, through decoding and constraint table traversal, 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 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.

[0056] In an embodiment of the present application, first, coding rules are extracted in multiple ship damage monitoring nodes, and multiple coding mapping tables are created based on the extraction results. Then, the decoding process is configured for these mapping tables, and multiple real-time decoding engines are constructed. After these decoding engines are connected in parallel, a damage situation decoding module is formed, and it is configured to the display center. In the decoding module, multiple real-time decoding engines map and execute the decoding processing of the damage situation coding to obtain the damage situation of multiple partitions. Subsequently, these partition damage situation data are used to traverse the damage gallery of the partitions, and virtual image calls and synthesis are performed to generate damage images for each partition. Finally, with the partitions as display constraints, the generated multiple partition damage images are synchronized to the ship damage control display screen to achieve an intuitive and visual display of the damage situation.

[0057] Furthermore, in the method provided in the embodiment of the application, 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, and further includes:

[0058] Coding rules are extracted at the multiple ship damage monitoring nodes, and multiple coding mapping tables are created based on the extraction results; decoding processes are configured for the multiple coding mapping tables, and multiple real-time decoding engines are constructed based on the configuration results; after the multiple real-time decoding engines are identified by the multiple ship monitoring partitions, the multiple real-time decoding engines are connected 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 decoding processing of the multiple damage situation codes is performed through the mapping of the multiple real-time decoding engines in the damage situation decoding module to obtain multiple partition damage situations; the multiple partition damage situations are used to traverse the partition damage gallery, perform virtual image call synthesis, and obtain the multiple partition damage images; the multiple ship monitoring partitions are used as display constraints, and the multiple partition damage images are synchronized to the ship damage control display screen for visual display.

[0059] In the embodiment of the present application, in multiple ship damage monitoring nodes, the coding rules are first extracted to parse the damage situation coding structure of each node. Using the pattern matching algorithm, various coding fields, such as damage type, severity, location, etc., are analyzed one by one to extract the rule information of each damage coding. Based on the extracted coding rules, a hash table is used to generate multiple coding mapping tables to record the mapping relationship between each coding structure and damage information for subsequent decoding, searching and processing.

[0060] After the encoding mapping table is created, the decoding process is configured. At this stage, the decoding process is defined for each encoding through the state machine, and each state machine is dedicated to parsing a certain type of encoding information. The state machine reads each field of the encoding step by step and matches the rules in the mapping table. For example, when the decoding process reads the encoding in the "Tx-Px" format, the state machine recognizes that the "T" represents temperature anomaly and stores the corresponding information. After the decoding process is configured, a real-time decoding engine is generated for each configuration process. These engines can run in parallel and independently decode the damage code of their respective partitions.

[0061] After the decoding engines are built, they are configured in parallel to form an integrated damage situation decoding module. Parallelization is achieved through multi-threading technology, and each engine independently processes the damage code data of each partition to ensure fast and concurrent decoding. For example, the decoding engines in the cargo hold and the cabin can run at the same time, respectively decoding the code data of their respective partitions. By configuring in parallel, the decoding module meets the real-time decoding requirements of multiple partitions.

[0062] When the damage situation decoding module is configured to the damage control situation display center, it officially enters the decoding stage, and multiple parallel decoding engines begin to decode the received damage situation codes in real time. Each engine parses the coded information through the lookup table matching technology, matches the coded field with the rules in the mapping table, and converts it into standardized partition damage situation information. This information includes key damage types (such as temperature anomalies, cracks), severity (such as mild, moderate, severe) and location (such as cabin, cargo hold). For example, when the decoding engine reads the code "T3-MC", it confirms through the lookup table that the code indicates a temperature anomaly in the cabin area and the severity is severe.

[0063] After obtaining the damage status of multiple partitions, the virtual image synthesis stage is entered. At this time, the damage status of each partition is traversed, and the corresponding virtual image template in the partition damage library is called. The decoded damage information is converted into an intuitive image using image rendering and texture mapping technology. For example, if the cabin temperature is abnormally severe, the information is mapped to a thermal map template, showing a gradient color from green to red, showing the degree of temperature increase; if it is crack damage, the crack image template is selected to mark the crack position and length with high-contrast lines. Through this image call and rendering, a partition damage image that conforms to the actual damage situation is generated.

[0064] After completing the synthesis of damage images for 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, so that operators can intuitively view the damage status of each partition. The display screen is displayed according to the partition, and the damage image is updated 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 completed the entire process from coding rule extraction, decoding process configuration, virtual image synthesis to real-time synchronous display, and finally presented multiple partition damage images on the display screen.

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

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

[0068] After configuring the visualization iteration constraints, the damage control situation display center receives the feedback codes from each ship damage monitoring node through wireless or wired transmission protocols. These feedback codes contain real-time damage information for each partition, including damage type (such as temperature anomaly, cracks), severity (mild, moderate, severe) and location (such as engine room, cargo hold). When the feedback code of each partition arrives, it enters the decoding module, parses the code fields one by one, extracts the damage type, severity and location, and provides the latest situation information for display updates.

[0069] After decoding is completed, the preset visualization iteration constraints determine whether to refresh the partition image immediately. For example, if the update frequency of a partition is 10 seconds, the virtual image rendering engine is enabled to refresh the image of the partition every time 10 seconds are reached. This rendering engine redraws the image of the partition damage situation based on the decoding results. For example, when the temperature continues to rise, the color of the heat map will deepen or the coverage will expand; when the crack grows, the crack image will show longer or deeper marks based on the decoded data.

[0070] The images of high-frequency update partitions (once every 10 seconds) are continuously refreshed, so that subtle changes in damage conditions such as temperature and cracks can be presented immediately; medium-frequency update partitions (once every 30 seconds) are displayed at a stable frequency and are suitable for medium-risk areas; low-frequency update partitions (once every 60 seconds) are updated at longer time intervals and are used 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 a low frequency, effectively optimizing system resource allocation. Finally, the above steps complete the iteration of the visual damage image of the ship damage control display.

[0071] Furthermore, in the method provided in the embodiment of the application, the edge monitoring node is configured according to the ship partition to obtain multiple ship damage monitoring nodes of multiple ship monitoring partitions, and before that, it also includes:

[0072] The monitoring sensors of the multiple ship monitoring partitions are configured according to the differences in damage characteristics to obtain multiple sensor requirement information; M groups of equipment parameter information of M types of sample sensors are obtained by calling the equipment model data after aggregating the multiple sensor requirement information; the spatial scales of the multiple ship monitoring partitions are used as monitoring range constraints, and the M groups of equipment parameter information are used as equipment layout constraints to optimize the layout of monitoring sensors for the multiple ship monitoring partitions to obtain multiple multimodal monitoring arrays; and the multiple multimodal monitoring arrays are mapped to construct unidirectional communication links with multiple ship damage monitoring nodes.

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

[0074] After generating multiple sensor demand information, these demands are aggregated and enter the equipment model data call stage. By querying the equipment database, appropriate sensor equipment is called and screened according to the demand conditions, and M sets of equipment parameter information for M sample sensors are obtained. Specifically, due to the different effective monitoring ranges of sensors and different equipment prices, priority is given to equipment that meets the required monitoring range and has the best cost. For example, for temperature monitoring in the cabin area, if the area needs to cover a range of 30 meters, the appropriate temperature sensor model is searched in the database to ensure that the sensor can meet both the monitoring needs and the budget.

[0075] After completing the call of equipment parameter information, the optimal configuration stage of sensor deployment is entered. In this stage, the spatial scale of the ship monitoring partition is used as the monitoring range constraint, and M groups of equipment parameter information are used as the equipment deployment constraint, and the particle swarm optimization algorithm is used to optimize the sensor position. The particle swarm algorithm gradually finds the optimal deployment position of the sensor by simulating the iterative movement of particles in space. For example, the sensors in the cabin are deployed near the heat source to monitor the temperature rise in time, and the vibration sensors are deployed at key points such as structural columns to improve the sensitivity to vibration anomalies. After iterative optimization, multiple multimodal monitoring arrays are finally generated. Each array completes the optimal configuration according to the partition characteristics, achieving a balance between coverage integrity and monitoring efficiency.

[0076] After the multimodal monitoring array is configured, a one-way communication link is established between each array and the ship damage monitoring node. Using wireless transmission protocols, such as LoRa or ZigBee, an independent communication link is set up for each array to ensure that sensor data can be transmitted to the monitoring node in a one-way and efficient manner. Specifically, for long-distance partitions, such as from the cabin to the central control area, the low-power, long-distance LoRa protocol is selected, while for local areas such as the interior of the cabin, the high-bandwidth ZigBee protocol is used. Each sensor is assigned an independent channel and frequency band to avoid interference and improve data transmission stability.

[0077] Through the above process, the whole process configuration from sensor demand generation, equipment parameter call, optimized layout to communication link mapping is completed. The multi-modal monitoring array and unidirectional communication link finally formed ensure the real-time monitoring capability of each partition, so that the ship damage monitoring system can accurately monitor the characteristics of fire, overheating, leakage and vibration abnormality, and provide reliable support for the safety management of the whole ship.

[0078] Furthermore, in the method provided in the embodiment of the application, the spatial scales of the multiple ship monitoring partitions are used as the monitoring range constraint, and the M groups of equipment parameter information are used as the equipment layout constraint to optimize the layout of monitoring sensors for the multiple ship monitoring partitions to obtain multiple multimodal monitoring arrays, and further includes:

[0079] The first demand sensor in the first sensor demand information is used to traverse the M groups of equipment parameter information to obtain a first group of demand parameter information, wherein the first group of demand parameter information includes N sensing coverage areas of N available sensors and N equipment purchase unit prices; the spatial scale of the first ship monitoring partition is used as the monitoring range constraint, and the N sensing coverage areas are used as the equipment layout constraint, the layout coverage of the first ship monitoring partition is optimized to obtain multiple equipment layout configurations; the N equipment purchase unit prices are used to evaluate the multiple equipment layout configurations, and a minimum value call is performed based on the evaluation result to obtain a first monitoring modal unit; by analogy, the layout coverage of the first ship monitoring partition is optimized according to the first sensor demand information to obtain multiple monitoring modal units to form a first multimodal monitoring array; by analogy, the monitoring sensor layout of the multiple ship monitoring partitions is optimized to obtain the multiple multimodal monitoring arrays.

[0080] In an embodiment of the present application, in the process of configuring monitoring sensors for multiple ship monitoring zones, the first sensor requirement information is first used to identify the specific parameter requirements of each required sensor in the zone. Taking the engine room area 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 filter out sensors that meet the requirements, thereby obtaining the first set of required parameter information. This information includes the sensing coverage area of ​​N available temperature sensors (the monitoring range of each sensor) and the unit price of the equipment purchase. For example, the sensing coverage area of ​​a certain sensor is 20 meters, the unit price is 100 yuan, and the other is 30 meters, the unit price is 150 yuan.

[0081] After obtaining the first set of demand parameter information, the spatial scale of the first ship monitoring partition is constrained to ensure coverage of the entire monitoring area. The sensing coverage area of ​​N sensors is used as the equipment layout constraint to optimize the layout coverage and select the appropriate sensor type and quantity to achieve full coverage in 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 to generate multiple equipment layout configurations. Each configuration contains a different combination of sensor distribution, sensor type and quantity, and all configurations meet the full coverage requirements of the monitoring range. For example, one layout configuration may contain two sensors with 20-meter coverage and one sensor with 30-meter coverage, while another configuration may contain three sensors with 15-meter coverage.

[0082] Among the multiple equipment deployment configurations generated, N equipment purchase unit prices are used to evaluate the configuration costs, and the total purchase cost of each configuration is calculated one by one to find the most cost-effective configuration. The minimum call method is used to select the configuration with the lowest total cost as the final solution after optimization, and the first monitoring modal unit is obtained, which not only ensures the monitoring coverage within the partition, but also minimizes the equipment purchase cost.

[0083] Following the same process, the layout and coverage of other required sensors in the first partition are optimized, and all optimized modal units are combined to form the first multimodal monitoring array to meet the multiple monitoring requirements of the first partition. Subsequently, the configuration of other ship monitoring partitions is optimized in turn to generate multimodal monitoring arrays for all partitions.

[0084] Through these configured multimodal monitoring arrays, each ship damage monitoring node receives and analyzes real-time multimodal data from each ship monitoring partition. These monitoring nodes synchronously process sensor data from each partition, comprehensively analyze various damage information such as temperature anomalies, oil and gas leakage, vibration, etc., and realize 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 have at least the following technical effects:

[0086] The present 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; a damage control situation display center receives and configures update frequencies 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 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 multiple situation update frequencies as visual iteration constraints for multiple partition damage images, receives the return codes of multiple ship damage monitoring nodes to iterate the visual damage images of the ship damage control display screen. The present invention solves the technical problem that the prior art cannot fully and real-time display the damage of the entire ship, 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 coding, the damage control situation display center parses and synthesizes the damage image of each partition, and realizes dynamic iteration of the image with the update frequency as a constraint, real-time monitoring and synchronous visual display of ship damage information are realized, so as to achieve the technical effect of improving damage situation awareness and emergency response efficiency.

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

[0088] A node configuration unit 11, wherein the node configuration unit 11 configures edge monitoring nodes according to ship partitions to obtain multiple ship damage monitoring nodes of multiple ship monitoring partitions; a multimodal data analysis unit 12, wherein the multimodal data analysis unit 12 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 13, wherein the update frequency configuration unit 13 receives and configures the update frequency through the damage control situation display center by analyzing the multiple damage situation codes to obtain multiple situation update frequencies; a virtual image synthesis unit 14, wherein the virtual image synthesis unit 14 synthesizes virtual images by decoding the multiple damage situation codes through the damage control situation display center to obtain 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 15, wherein the visualization iteration unit 15 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.

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

[0090] 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; multi-dimensional damage situation identification is performed through the first damage identification layer to obtain multiple real-time damage situation information; the multiple real-time damage situation information is output by the first damage identification layer to the cascaded damage situation coding module for combined 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 are received and analyzed by the multiple ship damage monitoring nodes to generate the multiple damage situation codes.

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

[0092] According to the first damage feature of the first ship monitoring zone, damage data is called online 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 damage assessment models to obtain multiple first damage identification models; the multiple first damage identification models are connected 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; and by analogy, edge monitoring nodes are configured according to the ship zones to obtain the multiple ship damage monitoring nodes.

[0093] Furthermore, 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 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.

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

[0096] Coding rules are extracted at the multiple ship damage monitoring nodes, and multiple coding mapping tables are created based on the extraction results; decoding processes are configured for the multiple coding mapping tables, and multiple real-time decoding engines are constructed based on the configuration results; after the multiple real-time decoding engines are identified by the multiple ship monitoring partitions, the multiple real-time decoding engines are connected 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 decoding processing of the multiple damage situation codes is performed through the mapping of the multiple real-time decoding engines in the damage situation decoding module to obtain multiple partition damage situations; the multiple partition damage situations are used to traverse the partition damage gallery, perform virtual image call synthesis, and obtain the multiple partition damage images; the multiple ship monitoring partitions are used as display constraints, and the multiple partition damage images are synchronized to the ship damage control display screen for visual display.

[0097] Furthermore, 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 codes via the multiple real-time decoding engine mappings in the damage situation decoding module to obtain multiple partition damage situations, use the multiple partition damage situations to traverse the update frequency constraint table to obtain the multiple situation update frequencies.

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

[0100] The monitoring sensors of the multiple ship monitoring partitions are configured according to the differences in damage characteristics to obtain multiple sensor requirement information; M groups of equipment parameter information of M types of sample sensors are obtained by calling the equipment model data after aggregating the multiple sensor requirement information; the spatial scales of the multiple ship monitoring partitions are used as monitoring range constraints, and the M groups of equipment parameter information are used as equipment layout constraints to optimize the layout of monitoring sensors for the multiple ship monitoring partitions to obtain multiple multimodal monitoring arrays; and the multiple multimodal monitoring arrays are mapped to construct unidirectional communication links with multiple ship damage monitoring nodes.

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

[0102] The first demand sensor in the first sensor demand information is used to traverse the M groups of equipment parameter information to obtain a first group of demand parameter information, wherein the first group of demand parameter information includes N sensing coverage areas of N available sensors and N equipment purchase unit prices; the spatial scale of the first ship monitoring partition is used as the monitoring range constraint, and the N sensing coverage areas are used as the equipment layout constraint, the layout coverage of the first ship monitoring partition is optimized to obtain multiple equipment layout configurations; the N equipment purchase unit prices are used to evaluate the multiple equipment layout configurations, and a minimum value call is performed based on the evaluation result to obtain a first monitoring modal unit; by analogy, the layout coverage of the first ship monitoring partition is optimized according to the first sensor demand information to obtain multiple monitoring modal units to form a first multimodal monitoring array; by analogy, the monitoring sensor layout of the multiple ship monitoring partitions is optimized to obtain the multiple multimodal monitoring arrays.

[0103] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. And the above-mentioned specific embodiments of this specification are described. The processes depicted in the accompanying 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 description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

[0105] This specification and drawings are merely exemplary illustrations of the present application and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, a person skilled in the art may make various modifications and variations 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 equivalents, the present application intends to include these modifications and variations.

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 for the multiple partition damage images, receives the feedback codes from the multiple ship damage monitoring nodes, and performs visualization damage image iteration on the ship damage control display screen.

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 3, characterized in that: 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.

5. A method for synchronous visualization of ship damage control according to claim 4, 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.

6. A method for synchronous visualization of ship damage control according to claim 5, 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.

7. 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.

8. A method for synchronous visualization of ship damage control according to claim 7, 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.

9. 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 feedback codes of the multiple ship damage monitoring nodes, and performs visualization damage image iteration of the ship damage control display screen.

Images