A virtual reality training system for ship equipment

Abstract

This invention belongs to the field of ship equipment training technology, and particularly relates to a virtual reality training system for ship equipment. It includes a scene virtual module, a training simulation module, a real-time rendering control module, a 3D scene module, and a virtual interaction module. The scene virtual module creates training models; the training simulation module provides training interaction algorithms and generates interactive content; the 3D scene module tracks the 3D posture of a motion camera and positions the virtual scene viewpoint; the virtual interaction module generates tracking data based on human-computer interaction information and generates virtual feedback information based on the interaction content; the auxiliary module generates training data according to training needs and provides the generation and output of training effects, notification information, evaluation information, etc. This virtual reality training system for ship equipment is mainly used to further improve the effectiveness of virtual reality training for ship equipment, providing a technical route for expanding training content and optimizing training programs.

Description

Technical Field

[0001] This invention belongs to the field of ship equipment training technology, and in particular relates to a virtual reality training system for ship equipment. Background Technology

[0002] The normal operation of ship equipment is the fundamental guarantee for the healthy navigation of a ship. The maintenance and operation of ship equipment involves a large number of control devices and hardware facilities. Most of these devices are large in size and have many interconnected structures, making it difficult to observe and understand them directly and effectively on actual ships. Theoretical teaching is usually only conducted through device models or video tutorials. However, in order to meet application needs, extensive and comprehensive training on device operation is also an essential part. Currently, some training institutions have launched virtual reality training for large-scale equipment based on virtual reality technologies such as VR and AR. However, the current focus is mainly on 3D model display and 3D animation simulation in virtual reality scenarios, which cannot further meet the needs for operation training of more refined devices. Summary of the Invention

[0003] The purpose of this invention is to provide a virtual reality training system for realizing virtual reality training of ship equipment, enriching training content, optimizing the training process according to specific training matters, and identifying training focus.

[0004] To achieve the above objectives, the present invention adopts the following technical solution.

[0005] A virtual reality training system for ship equipment includes a scene virtual module, a training simulation module, a real-time rendering control module, a three-dimensional scene module, and a virtual interaction module.

[0006] The scenario virtual module is used to acquire and create training scenario models and ship equipment models; the training simulation module provides training interaction algorithms, collects human-computer interaction information, and generates model interaction content.

[0007] The 3D scene module is used to track the 3D pose of the motion camera and locate the virtual scene viewpoint; the virtual interaction module is used to generate tracking data based on human-computer interaction information and generate virtual feedback information based on the interaction content; the auxiliary module is used to generate training data based on training needs and provide the generation and output of training effects, notification information, evaluation information and other content.

[0008] The virtual scenario module is used to acquire and create training scenario models and ship equipment models; the training scenario model is used to provide virtual scenarios of training spaces, external environments of ship equipment, etc.; the ship equipment model is used to provide virtual scenarios of ship equipment systems, supporting control panels, and other ship equipment.

[0009] The training simulation module provides training interaction algorithms, collects human-computer interaction information, and generates model interaction content; the training simulation module is used to generate model interaction content including:

[0010] Establish a set of elements for ship equipment training tasks, which includes training task objectives, training task actions, training tool set, and training environment set.

[0011] Training task objectives refer to the equipment, components, and other objects to be operated in the ship equipment training task; training task actions refer to a series of necessary operational contents configured to complete the ship equipment training task; training toolset refers to the necessary equipment and tools required to complete the ship equipment training task; training environment set refers to the relevant element information used to construct the specific environment or context of the ship equipment training task.

[0012] The training simulation module is used to collect human-computer interaction information, including: acquiring human-computer interaction information through a virtual reality interaction system; obtaining the type of ship equipment training task to be carried out later through methods such as actively acquiring interaction intentions and making autonomous judgments; and retrieving the corresponding task code according to the type of ship equipment training task to be performed, and generating the corresponding task data information.

[0013] To further improve or specifically implement the aforementioned virtual reality training system for ship equipment, at least the following steps are required to create a virtual scene:

[0014] a1. Search for the corresponding and necessary target and environmental information in the virtual scene, and analyze the interaction information between the targets and between the targets and the environment;

[0015] a2. Based on the specific content of the target information, environmental information, and interactive information, acquire and collect basic data such as images and videos used to reproduce the aforementioned virtual information content;

[0016] a3. Perform necessary image processing on basic data such as images and videos to extract texture mapping information;

[0017] a4. Use 3D modeling software to create three-dimensional model units in a virtual scene;

[0018] a5. Use a 3D engine platform to construct environmental information in a virtual scene and introduce the three-dimensional model units established in the previous steps into the virtual environment; use the training simulation module and the virtual interaction module to construct a user interface in the three-dimensional scene.

[0019] In a further improvement or specific implementation of the aforementioned virtual reality training system for ship equipment, the training simulation module is used to create interactive algorithms based on at least the following steps:

[0020] b1. Generate interactive operation data based on the training content of ship equipment. The interactive operation data includes the interaction data between the individual and each unit of the ship equipment during the virtual reality training process, as well as the corresponding action and attribute change data of the ship equipment body and related structures under the influence of each interactive operation. The interactive data and action or attribute change data are reflected through dynamic changes in the model, dynamic data of the visualization interface, etc.

[0021] b2. Generate and extract dynamic characteristic data of ship equipment based on the operating characteristics and attributes of the ship equipment. The dynamic characteristic data includes motion attribute data, static and dynamic structural data, and power-related data. Establish a dynamic characteristic database of ship equipment and update the dynamic characteristic database of ship equipment according to the training content of ship equipment.

[0022] b3. Establish a corresponding data interaction and retrieval process based on the training content of ship equipment, obtain the specific content of ship equipment training from human-computer interaction information, extract the necessary feature data from the ship equipment dynamic feature database according to the training content, and send it to the scene virtual module to output the corresponding virtual device dynamic or static information.

[0023] To further improve or specifically implement the aforementioned virtual reality training system for ship equipment, at least the following steps are required to obtain the set of training task elements for ship equipment:

[0024] C1. The disassembly of the ship equipment training task operation steps yields corresponding sub-steps. Each sub-step consists of a single training task action performed in response to the training task objective, as well as the required training tool elements and training environment elements. The ship equipment training task consists of several sub-steps.

[0025] C2. Establish a sub-step identification table, which consists of a task target ID, a single training task action ID, a training tool element ID, and a training environment element ID.

[0026] C3. Establish a directed network that expresses the ship equipment training task through the orderly combination of sub-steps. The directed network consists of network vertices and directed line segments between the vertices. Each network vertex is composed of a sub-step. Several sub-steps connected by several directed line segments constitute a complete ship equipment training task. The graphic representation of the directed line segments indicates the logical relationship between the sub-steps. The direction of the directed line segments indicates the execution order of the sub-steps. Several line segments connecting any two sub-steps represent several different processing steps that can be selected in the ship equipment training task. The intersecting line segments passing through any sub-step indicate that the ship equipment training task needs to select the content of the next sub-step after passing through that sub-step.

[0027] C4. Establish a symbolic representation of the aforementioned directed line segment logical relationships, and combine it with the directed network representing the training tasks of each ship device to establish a directed table containing the logical relationships of sub-steps, and complete the coding of the ship device training tasks expressed by the sub-steps and the logical relationships of the sub-steps.

[0028] A further improvement or specific implementation of the aforementioned virtual reality training system for ship equipment, for the aforementioned directed network, whose vertices are a dataset of N sub-steps l = {1, 2, ..., N}, for any sub-step i, j ∈ l, if sub-step i is a prerequisite step for sub-step j, then the directed edge affinity e ij =1 otherwise e ij =0;

[0029] To analyze the rationality of sub-step allocation within a directed network, the network density of vertices in the directed network is used to express the degree of connection between vertices in the directed network. Assume the directed edge affinity is e. ij If the number of directed edges with a value of 1 is M, then the network density can be expressed as: After determining the network density r, a preliminary judgment can be made on the training intensity between the sub-steps represented by the vertices in the directed network. If the network density is too small, it means that the sub-steps are divided too finely, and the number of sub-steps into which the ship equipment training task is divided is too large, which will lead to an excessive amount of data used to express the ship equipment training task. Some sub-steps need to be merged. Conversely, if the network density is too large, it means that the number of sub-steps is too small, and it is not possible to decompose the details of the ship equipment training task sufficiently, which is not conducive to ensuring the training effect. Further step decomposition is required.

[0030] To improve training quality, we should identify the more important key sub-steps from the numerous sub-steps derived from the decomposition of ship equipment training tasks. As a common approach, this can be achieved by analyzing the association values ​​between the vertices corresponding to each sub-step and other related vertices. To represent; through the associated value f i A preliminary analysis of the importance of sub-step i is conducted to identify the several sub-steps with the highest importance, so that the training weight of the corresponding sub-steps can be increased based on the correlation value during the training process.

[0031] Further improvements or specific implementations of the aforementioned virtual reality training system for ship equipment, in order to optimize the process steps of ship equipment training tasks, in addition to the pre-set fixed training content, to facilitate enhanced training for a specific target sub-step during the training process, it is necessary to establish a training sequence with a relatively fewer number of sub-steps and a relatively shorter preparation time. That is, for a specific sub-step k that we want to train, we need to determine a sub-step sequence {k1, k2, ... k}. n ...k x}, where sub-step k n-1 Sub-step k n Prerequisite steps, sub-step k x It is a prerequisite step for sub-step k, such that the objective function goal = min[ω1x + ω2(t1 + t2.... + t] x [The minimum value is obtained.]

[0032] In a further improvement or specific implementation of the aforementioned virtual reality training system for ship equipment, the environmental information in the virtual scene includes surface structure information of the space where the equipment is located, information of other non-interactive devices in the space where the ship equipment is located, and path navigation information;

[0033] The surface structure information is generated based on terrain editing tools and spatial structure editing tools. The surface structure information is then improved by filling and optimizing the relevant data of the surface structure through the acquisition and collection of basic data.

[0034] The non-interactive device information is generated based on structure or building editing tools or texture mapping tools to create 3D scene information of the non-interactive device.

[0035] The route navigation information is generated based on road modeling tools and path finding assistance tools to generate different path nodes and routes between path nodes. The operational range of routes and nodes is edited by acquiring and collecting information such as actual path width and length.

[0036] In a further improvement or specific implementation of the aforementioned virtual reality training system for ship equipment, the three-dimensional model unit creates a corresponding local unit model using three-dimensional modeling software based on the interactive area and functional modules involved. After converting it into a three-dimensional model recognizable by the 3D engine platform using a format conversion tool, it is input into the 3D engine platform for loading and texture configuration. The 3D engine platform attribute configuration tool assigns relevant dynamic and static attributes to the corresponding local unit model, and establishes corresponding feedback models under different interactive content based on the feedback information provided by the virtual interaction module. Attached Figure Description

[0037] This application has no accompanying drawings. Detailed Implementation

[0038] The present invention will be described in detail below with reference to specific embodiments.

[0039] This application discloses a virtual reality training system for ship equipment, which is mainly used to further improve the effectiveness of virtual reality training for ship systems and to provide a technical approach for expanding training content and optimizing training programs.

[0040] The virtual reality training system for ship equipment in this application mainly consists of a scene virtual module, a training simulation module, a real-time rendering control module, a three-dimensional scene module, and a virtual interaction module;

[0041] The virtual scene module is used to acquire and create training scene models and ship equipment models; the training simulation module provides training interaction algorithms, collects human-computer interaction information, and generates model interaction content; the 3D scene module is used to track the 3D posture of the motion camera and locate the virtual scene viewpoint; the virtual interaction module is used to generate tracking data based on human-computer interaction information and generate virtual feedback information based on the interaction content; the auxiliary module is used to generate training data according to training needs and provide the generation and output of training effects, notification information, evaluation information, etc.

[0042] The virtual scenario module is used to acquire and create training scenario models and ship equipment models. The training scenario model provides a virtual environment for training spaces, the external environment of ship equipment, etc.; the ship equipment model provides a virtual environment for ship equipment systems, supporting control panels, etc. To create a virtual scenario, at least the following steps must be completed:

[0043] a1. Search for the corresponding and necessary target and environmental information in the virtual scene, and analyze the interaction information between the targets and between the targets and the environment;

[0044] a2. Based on the specific content of the target information, environmental information, and interactive information, acquire and collect basic data such as images and videos used to reproduce the aforementioned virtual information content;

[0045] a3. Perform necessary image processing on basic data such as images and videos to extract texture mapping information;

[0046] a4. Use 3D modeling software to create three-dimensional model units in a virtual scene;

[0047] a5. Use a 3D engine platform to construct environmental information in a virtual scene and introduce the three-dimensional model units established in the previous steps into the virtual environment; use the training simulation module and the virtual interaction module to construct a user interface in the three-dimensional scene;

[0048] Specifically, the environmental information in the virtual scene includes surface structure information of the space where the ship's equipment is located, information of other non-interactive devices in the space where the ship's equipment is located, and path navigation information;

[0049] The surface structure information is generated based on terrain editing tools and spatial structure editing tools. The surface structure information is then improved by filling and optimizing the relevant data of the surface structure through the acquisition and collection of basic data.

[0050] The non-interactive device information is generated based on structural or building editing tools or texture mapping tools to create 3D scene information for non-interactive devices.

[0051] The route navigation information is generated based on road modeling tools and path finding assistance tools to generate different path nodes and the routes between path nodes. The actual path width and length information is acquired and collected to complete the editing of the operable range of the route and nodes.

[0052] Specifically, the 3D model unit is created by 3D modeling software according to the interactive area and functional module involved. After being converted into a 3D model that can be recognized by the 3D engine platform by a format conversion tool, it is input into the 3D engine platform for loading and texture configuration. The 3D engine platform attribute configuration tool assigns relevant dynamic and static attributes to the corresponding local unit model, and establishes corresponding feedback models under different interactive content based on the feedback information provided by the virtual interactive module.

[0053] The training simulation module provides training interaction algorithms, collects human-computer interaction information, and generates model interaction content; the training simulation module is used to create interaction algorithms based on at least the following steps:

[0054] b1. Generate interactive operation data based on the training content of ship equipment. The interactive operation data includes the interaction data between individuals and various units of ship equipment during virtual reality training, as well as the corresponding action and attribute change data of the ship equipment body and related structures under the influence of each interactive operation. The interaction data and action or attribute change data are reflected through dynamic changes in the model, dynamic data of the visualization interface, etc.

[0055] b2. Generate and extract dynamic characteristic data of ship equipment based on the operating characteristics and attributes of the ship equipment, including motion characteristic data such as motion attribute data, static and dynamic structural data, and power-related data; establish a dynamic characteristic database of ship equipment and update the dynamic characteristic database of ship equipment according to the training content of ship equipment.

[0056] b3. Establish a corresponding data interaction and retrieval process based on the training content of ship equipment, obtain the specific content of ship equipment training from human-computer interaction information, extract the necessary feature data from the ship equipment dynamic feature database according to the training content, and send it to the scene virtual module to output the corresponding virtual device dynamic or static information.

[0057] The training simulation module generates interactive model content by establishing a set of elements for ship equipment training tasks. This set includes training task objectives, training task actions, a training toolset, and a training environment set. The training task objectives refer to the equipment, components, and other objects to be operated in the ship equipment training task. The training task actions refer to a series of necessary operational activities configured to complete the ship equipment training task. The training toolset refers to the necessary equipment and tools required to complete the ship equipment training task. The training environment set refers to the relevant element information used to construct the specific environment or context of the ship equipment training task.

[0058] To obtain the set of elements for shipboard equipment training tasks, at least the following steps must be completed:

[0059] C1. The disassembly of the ship equipment training task operation steps yields corresponding sub-steps, where each sub-step consists of a single training task action performed in response to the training task objective, as well as the required training tool elements and training environment elements; the ship equipment training task consists of several sub-steps.

[0060] C2. Establish a sub-step identification table, which consists of a task target ID, a single training task action ID, a training tool element ID, and a training environment element ID.

[0061] C3. Establish a directed network to represent the ship equipment training task through the ordered combination of sub-steps. The directed network consists of network vertices and directed line segments between the vertices. Each network vertex is composed of a sub-step. Several sub-steps connected by several directed line segments constitute a complete ship equipment training task. The graphic representation of the directed line segments indicates the logical relationship between the sub-steps. The direction of the directed line segments indicates the execution order of the sub-steps. Several line segments connecting any two sub-steps represent several different processing steps that can be selected in the ship equipment training task. The intersecting line segments passing through any sub-step indicate that the ship equipment training task needs to select the content of the next sub-step after passing through that sub-step.

[0062] C4. Establish a symbolic representation of the aforementioned directed line segment logical relationship, and combine it with the directed network representing the training tasks of each ship device to establish a directed table containing the logical relationship of sub-steps, and complete the coding of the ship device training tasks expressed by the sub-steps and the logical relationship of the sub-steps.

[0063] The training simulation module is used to collect human-computer interaction information, including: acquiring human-computer interaction information through a virtual reality interaction system; obtaining the type of ship equipment training task to be performed later through active acquisition of interaction intent and autonomous judgment; retrieving the corresponding task code according to the type of ship equipment training task to be performed; and generating the corresponding task data information.

[0064] For the aforementioned directed network, its vertices are a dataset of N sub-steps, l = {1, 2, ..., N}. For any sub-step i, j ∈ l, if sub-step i is a prerequisite step for sub-step j, then the directed edge affinity e ij =1 otherwise e ij =0;

[0065] To analyze the rationality of sub-step allocation within a directed network, the network density of vertices in the directed network is used to express the degree of connection between vertices in the directed network. Assume the directed edge affinity is e. ij If the number of directed edges with a value of 1 is M, then the network density can be expressed as: After determining the network density r, a preliminary judgment can be made on the training intensity between the sub-steps represented by the vertices in the directed network. If the network density is too small, it means that the sub-steps are divided too finely, and the number of sub-steps into which the ship equipment training task is divided is too large, which will lead to an excessive amount of data used to express the ship equipment training task. Some sub-steps need to be merged. Conversely, if the network density is too large, it means that the number of sub-steps is too small, and it is not possible to decompose the details of the ship equipment training task sufficiently, which is not conducive to ensuring the training effect. Further step decomposition is required.

[0066] To improve training quality, we should identify the more important key sub-steps from the numerous sub-steps derived from the decomposition of ship equipment training tasks. As a common approach, this can be achieved by analyzing the association values ​​between the vertices corresponding to each sub-step and other related vertices. To represent; through the associated value f i A preliminary analysis of the importance of sub-step i is conducted to identify the several sub-steps with the highest importance, so that the training weight of the corresponding sub-steps can be increased based on the correlation value during the training process.

[0067] Furthermore, to optimize the training process for ship equipment, in addition to the pre-defined fixed training content, to facilitate enhanced training on specific target sub-steps during the training process, a training sequence with fewer sub-steps and shorter preparation time needs to be established. That is, for a specific sub-step k to be trained, a sub-step sequence {k1, k2, ... k} needs to be determined. n ...k x}, where sub-step k n-1 Sub-step k n Prerequisite steps, sub-step k x It is a prerequisite step for sub-step k, such that the objective function goal = min[ω1x + ω2(t1 + t2.... + t] x [Achieve minimum value]

[0068] Based on the aforementioned objective function and indicators, the rationality of the allocation of the device training system consisting of sub-steps can be judged and analyzed, thereby optimizing the allocation method of sub-steps. At the same time, based on the correlation, key sub-step items that are not easily discovered can be identified, providing a reference for optimizing the planning of device training content.

[0069] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit the scope of protection of the present invention. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the essence and scope of the technical solutions of the present invention.

Claims

1. A virtual reality training system for ship equipment, characterized in that, It includes a scene virtualization module, a training simulation module, a real-time rendering control module, a 3D scene module, and a virtual interaction module; The virtual scenario module is used to acquire and create training scenario models and ship equipment models; the training simulation module provides training interaction algorithms, collects human-computer interaction information, and generates model interaction content. The 3D scene module is used to track the 3D pose of the motion camera and locate the virtual scene viewpoint; the virtual interaction module is used to generate tracking data based on human-computer interaction information and generate virtual feedback information based on the interaction content. The auxiliary module is used to generate training data based on training needs, and to generate and output training effectiveness, notification information, and evaluation information. The training scenario model is used to provide a virtual scene of the training space and the external environment of the ship's equipment; the ship equipment model is used to provide a virtual scene of the ship's equipment system and its supporting control panel. Establish a set of elements for ship equipment training tasks, which includes training task objectives, training task actions, training tool set, and training environment set. The training task objective refers to the equipment and components to be operated in the ship equipment training task; the training task actions refer to a series of necessary operational contents configured to complete the ship equipment training task; the training toolset refers to the necessary equipment and tools required to complete the ship equipment training task; and the training environment set refers to the relevant element information used to construct the specific environment or context of the ship equipment training task. The training simulation module is used to collect human-computer interaction information, including: acquiring human-computer interaction information through a virtual reality interaction system; obtaining the type of ship equipment training task to be performed subsequently through actively acquiring interaction intentions and autonomous judgment; and retrieving the corresponding task code according to the type of ship equipment training task to be performed, and generating the corresponding task data information. To obtain the set of elements for shipboard equipment training tasks, at least the following steps must be completed: C1. The disassembly of the ship equipment training task operation steps yields corresponding sub-steps. Each sub-step consists of a single training task action performed in response to the training task objective, as well as the required training tool elements and training environment elements. The ship equipment training task consists of several sub-steps. C2. Establish a sub-step identification table, which consists of a task target ID, a single training task action ID, a training tool element ID, and a training environment element ID. C3. Establish a directed network that expresses the ship equipment training task through the orderly combination of sub-steps. The directed network consists of network vertices and directed line segments between the vertices. Each network vertex is composed of a sub-step. Several sub-steps connected by several directed line segments constitute a complete ship equipment training task. The graphic representation of the directed line segments indicates the logical relationship between the sub-steps. The direction of the directed line segments indicates the execution order of the sub-steps. Several line segments connecting any two sub-steps represent several different processing steps that can be selected in the ship equipment training task. The intersecting line segments passing through any sub-step indicate that the ship equipment training task needs to select the content of the next sub-step after passing through that sub-step. C4. Establish a symbolic representation of the aforementioned directed line segment logical relationship, and combine it with the directed network representing the training tasks of each ship device to establish a directed table containing the logical relationship of sub-steps, and complete the coding of the ship device training tasks expressed by the sub-steps and the logical relationship of the sub-steps. For the aforementioned directed network, its vertices are the sub-step dataset consisting of N sub-steps. For any sub-step If sub-step Sub-step The prerequisite steps for execution are directed edge association. otherwise ; To analyze the rationality of sub-step allocation within a directed network, the network density of vertices in the directed network is used to express the degree of connection between vertices in the directed network. This assumes the associativity of directed edges. The number of directed edges is Then the network density can be expressed as Determine network density Then, a preliminary judgment can be made on the training intensity between the sub-steps represented by the vertices in the directed network. If the network density is too small, it means that the sub-steps are divided too finely, and the number of sub-steps into which the ship equipment training task is divided is too large, which will lead to an excessive amount of data used to express the ship equipment training task. Some sub-steps need to be merged. Conversely, if the sub-steps are too small, it means that the details of the ship equipment training task cannot be decomposed sufficiently, which is not conducive to ensuring the training effect. Further step decomposition processing is required. To improve training quality, we should identify the more important key sub-steps from the numerous sub-steps derived from the decomposition of ship equipment training tasks. As a common approach, this can be achieved by analyzing the association values ​​between the vertices corresponding to each sub-step and other related vertices. To represent; through associated values Pair steps A preliminary analysis of the importance of each sub-step was conducted to identify the most important sub-steps, so that the training weight of the corresponding sub-steps could be increased based on the correlation value during the training process.

2. The virtual reality training system for ship equipment according to claim 1, characterized in that, To create a virtual scene, at least the following steps must be completed: a1. Search for the corresponding and necessary target and environmental information in the virtual scene, and analyze the interaction information between the targets and between the targets and the environment; a2. Based on the specific content of target information, environmental information, and interactive information, acquire and collect basic image and video data for the reproduction of virtual information content; a3. Perform necessary image processing on the basic image and video data to extract texture mapping information; a4. Use 3D modeling software to create three-dimensional model units in a virtual scene; a5. Use a 3D engine platform to construct environmental information in a virtual scene and introduce the three-dimensional model units established in the previous steps into the virtual environment; use the training simulation module and the virtual interaction module to construct a user interface in the three-dimensional scene.

3. The virtual reality training system for ship equipment according to claim 1, characterized in that, The training simulation module is used to create interactive algorithms based on at least the following steps: b1. Generate interactive operation data based on the training content of ship equipment. The interactive operation data includes the interaction data between the individual and each unit of the ship equipment during the virtual reality training process, as well as the corresponding action and attribute change data of the ship equipment body and related structures under the influence of each interactive operation. The interactive data and action or attribute change data are reflected through dynamic changes in the model and dynamic data in the visualization interface. b2. Generate and extract dynamic characteristic data of ship equipment based on the operating characteristics and attributes of the ship equipment. The dynamic characteristic data includes motion attribute data, static and dynamic structural data, and power-related data. Establish a dynamic characteristic database of ship equipment and update the dynamic characteristic database of ship equipment according to the training content of ship equipment. b3. Establish a corresponding data interaction and retrieval process based on the training content of ship equipment, obtain the specific content of ship equipment training from human-computer interaction information, extract the necessary feature data from the ship equipment dynamic feature database according to the training content, and send it to the scene virtual module to output the corresponding virtual device dynamic or static information.

4. The virtual reality training system for ship equipment according to claim 1, characterized in that, To optimize the training process for shipboard equipment, in addition to the pre-defined fixed training content, a training sequence with fewer sub-steps and shorter preparation time needs to be established to facilitate enhanced training for specific target sub-steps during the training process. This sequence is designed for specific sub-steps that require targeted training. It is necessary to determine a sequence of sub-steps. Sub-steps Sub-step Prerequisite steps, sub-steps Sub-step The prerequisite steps make the objective function Obtain the minimum value.

5. The virtual reality training system for ship equipment according to claim 2, characterized in that, The environmental information in the virtual scene includes surface structure information of the space where the device is located, information of other non-interactive devices in the space where the ship device is located, and path navigation information; Surface structure information is generated based on terrain editing tools and spatial structure editing tools. The surface structure information is then improved by filling and optimizing the relevant data of the surface structure through the acquired and collected basic data. The non-interactive device information is generated based on structure or building editing tools or texture mapping tools to create 3D scene information of the non-interactive device. The route navigation information is generated based on road modeling tools and path finding assistance tools to generate different path nodes and routes between path nodes. The actual path width and length information is acquired and collected to complete the editing of the operable range of the route and nodes.

6. The virtual reality training system for ship equipment according to claim 5, characterized in that, The three-dimensional model unit is created by the three-dimensional modeling software according to the interactive area and functional module involved. The model is then converted into a three-dimensional model that can be recognized by the 3D engine platform by the format conversion tool and then input into the 3D engine platform for loading and texture configuration. The 3D engine platform attribute configuration tool is used to assign relevant dynamic and static attributes to the corresponding local unit model, and the corresponding feedback model is established according to the feedback information provided by the virtual interaction module for different interactive content.

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