Vehicle body disassembly information linkage display method and system supporting cross-professional teaching

Abstract

The invention relates to the technical field of teaching demonstration, and provides a vehicle body disassembly information linkage display method and system supporting cross-professional teaching. The method comprises the steps that a vehicle body disassembling model is obtained, wherein the vehicle body disassembling model comprises a vehicle body disassembling unit set, a lamp control streamline auxiliary assembly and a linkage interaction control platform; a user interacts with the AIGC through the platform to generate an information sequence, and a target demand is determined after analysis; the calling platform identifies the linkage explanation content; calling an analyzer of the platform to determine a vehicle body deconstruction unit and a lamp control streamline demonstration scheme; and the vehicle body deconstruction unit, the lamp control streamline demonstration scheme and the explanation content are transmitted to the multi-terminal joint control unit for voice explanation and light synchronous display. The technical problem that cross-professional knowledge is difficult to realize visual display and interactive fusion in a traditional vehicle body disassembly teaching mode is solved, and the technical effects of realizing linkage display and teaching of multidisciplinary knowledge and improving the teaching depth and breadth through the vehicle body disassembly model, the lamp control streamline and the AIGC intelligent interaction are achieved.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of teaching demonstration, in particular to a vehicle body disassembly information linkage display method and system supporting cross-professional teaching. BACKGROUND

[0002] Under the background of rapid development of the new energy automobile industry, higher vocational education and industrial training have higher requirements for the cultivation of cross-professional compound technical talents. Traditional vehicle body disassembly teaching usually uses static entity models or two-dimensional schematic diagrams for display, and there are problems such as isolated subject knowledge, insufficient dynamic demonstration, and single interactive experience: mechanical majors focus on structure cognition, electrical majors focus on circuit principle, and cross-disciplinary knowledge such as material chemistry and control algorithm involved in new energy technology are difficult to be linked through a single display form. Although some colleges and universities introduce AR augmented reality technology to realize three-dimensional visualization, existing solutions mostly stop at the level of superimposing basic models, lack deep integration with intelligent interactive systems, and cause deviation between teaching content and real user needs. SUMMARY

[0003] The application provides a vehicle body disassembly information linkage display method and system supporting cross-professional teaching, aiming to solve the technical problem that cross-professional knowledge is difficult to realize intuitive display and interactive integration under the traditional vehicle body disassembly teaching mode.

[0004] The first aspect of the application provides a vehicle body disassembly information linkage display method supporting cross-professional teaching, which comprises: acquiring a vehicle body disassembly model, wherein the vehicle body disassembly model comprises a vehicle body disassembly unit set, a lamp control flow line auxiliary component, and a linkage interactive control platform; a target user interacts with an AIGC system through the linkage interactive control platform to obtain an interactive information sequence, performs memory iteration analysis on the interactive information sequence, and determines a target interactive demand; the linkage interactive control platform is called to identify the target interactive demand to determine target linkage explanation content; a linkage control analyzer of the linkage interactive control platform is called to identify the target interactive demand to determine a target vehicle body disassembly unit and a target linkage lamp control flow line demonstration scheme; and the target vehicle body disassembly unit, the target linkage lamp control flow line demonstration scheme, and the target linkage explanation content are transmitted to a multi-end linkage control unit of the linkage interactive control platform for voice explanation and lamp light gradual change flow synchronization display.

[0005] In another aspect of the present application, a vehicle body disassembly information linkage display system supporting cross-professional teaching is provided. The system comprises: a vehicle body disassembly model acquisition module that acquires a vehicle body disassembly model, wherein the vehicle body disassembly model comprises a vehicle disassembly unit set, a light control streamline auxiliary component, and a linkage interactive control platform; a memory iterative analysis module that obtains an interactive information sequence by target users interacting with an AIGC system through the linkage interactive control platform, performs memory iterative analysis on the interactive information sequence, and determines a target interactive requirement; an explanation content identification module that identifies target linkage explanation content by calling the linkage interactive control platform to perform linkage explanation content identification on the target interactive requirement; a display identification module that identifies target vehicle disassembly units and target linkage light control streamline demonstration schemes by calling a linkage control analyzer of the linkage interactive control platform to perform linkage display identification on the target interactive requirement; and an explanation display module that transmits the target vehicle disassembly units, the target linkage light control streamline demonstration schemes, and the target linkage explanation content to a multi-terminal linkage control unit of the linkage interactive control platform for voice explanation and light gradient flow synchronous display.

[0006] The one or more technical solutions provided in the present application have at least the following technical effects or advantages: The above-mentioned vehicle body disassembly information linkage display method supporting cross-professional teaching first acquires a vehicle body disassembly model comprising a vehicle disassembly unit, a light control streamline auxiliary component, and a linkage interactive control platform. Then, target users interact with an AIGC system through the linkage interactive control platform to generate an interactive information sequence, and through memory iterative analysis, identify the interactive requirement of the users. Subsequently, through the linkage interactive control platform, the explanation content and the display scheme related to the requirement of the users are determined, and further, through a linkage control analyzer, the vehicle disassembly units and the light control streamline demonstration schemes that need to be displayed are identified. Finally, these information is transmitted to a multi-terminal linkage control unit for voice explanation and light gradient flow synchronous display, thereby providing an interactive and immersive teaching experience for the users.

[0007] The above description is only a summary of the technical solutions of the present application. In order to more clearly understand the technical means of the present application, the specific embodiments of the present application can be implemented in accordance with the content of the description, and in order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the following specific embodiments of the present application are described. BRIEF DESCRIPTION OF DRAWINGS

[0008] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings needed in the embodiment description. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without any creative effort.

[0009] Figure 1 A flowchart of a vehicle body disassembly information linkage display method supporting cross-professional teaching in an embodiment.

[0010] Figure 2 A system architecture diagram of a vehicle body disassembly information linkage display system supporting cross-professional teaching in an embodiment.

[0011] Legend: vehicle body disassembly model acquisition module 11, memory iteration analysis module 12, explanation content identification module 13, display identification module 14, and explanation display module 15. DETAILED DESCRIPTION

[0012] The embodiments of the present application provide a vehicle body disassembly information linkage display method and system supporting cross-professional teaching, and solve the technical problem that cross-professional knowledge cannot be intuitively displayed and interactively integrated in a traditional vehicle body disassembly teaching mode.

[0013] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the scope of protection of the present application.

[0014] It should be noted that the terms "comprising" and "having" and any variations thereof are intended to cover not exclusively including, for example, a process, method, system, product or server including a series of steps or units does not have to be limited to those steps or units clearly listed, but can include other steps or modules that are not clearly listed or inherent to the process, method, product or device.

[0015] Embodiment one, as shown in the present application provides a vehicle body disassembly information linkage display method supporting cross-professional teaching, which comprises: Figure 1 acquiring a vehicle body disassembly model, wherein the vehicle body disassembly model comprises a vehicle body disassembly unit set, a light control streamline auxiliary component, and a linkage interaction control platform.

[0016] ​In the embodiments of the present application, a vehicle body disassembly model is first obtained, which is pre-built based on a complete vehicle and includes a vehicle body disassembly unit set, a light control flow line auxiliary component, and a linkage interaction control platform. The vehicle body disassembly unit set shows the detailed structure and layout of each component of the vehicle, including the vehicle body shell, the chassis, the three-electricity system (battery module, drive motor, and electronic control unit), internal electronic equipment, and various connecting components. Through the vehicle body disassembly model, one can clearly see how each subsystem and component of the vehicle is connected and works together, providing an intuitive view to help users understand the complex vehicle structure. The light control flow line auxiliary component is used to assist in displaying the working principle of the vehicle internal system through light control flow lines. The color, brightness, and motion trajectory of the light flow lines can be changed and adjusted according to different units of the vehicle body to highlight the working state of each unit. For example, the current flow of the battery module can be represented by a specific color of light flow line, helping users more intuitively understand the charging and discharging process of the battery. The linkage interaction control platform is the control center, through which users interact with the vehicle body disassembly model. The linkage interaction control platform integrates various control functions and feedback mechanisms, and can dynamically adjust the display content of the vehicle disassembly unit according to the user's operation and needs. Through the combination with the AIGC (Artificial Intelligence Generated Content) system, the linkage interaction control platform can respond to the user's questions in real time and provide personalized display and explanation according to different interactive content. Through this vehicle body disassembly model, users can be provided with comprehensive, interactive, and intuitive teaching experience, which is suitable for interdisciplinary and multi-professional teaching needs.

[0017] The target user interacts with the AIGC system through the linkage interaction control platform to obtain an interactive information sequence, and performs memory iterative analysis on the interactive information sequence to determine the target interaction demand.

[0018] In one embodiment, the target user interacts with the AIGC system in real time through the linkage interaction control platform. The user can initiate interaction through the platform, such as asking questions, selecting display content, or requesting specific disassembly information, etc. When the user inputs a certain instruction or question, the AIGC system will generate corresponding interactive information sequences according to the user's input. These information sequences include the user's behavior, selection, question, and platform feedback content. Usually, one user behavior and one feedback information constitute one interactive information. Subsequently, the recorded interactive information sequence is subjected to memory iterative analysis, which includes double memory recognition and explicit and implicit double analysis. Through memory iterative analysis, the target interaction demand of the user can be identified, so as to provide more accurate and personalized teaching content for the user and improve the user experience effect.

[0019] Further, the present application provides that the target user interacts with the AIGC system through the linkage interaction control platform to obtain an interactive information sequence, including: The target user logs in to the linkage interactive control platform, and the AIGC system pops up an interactive confirmation instruction; after the target user confirms the interactive confirmation instruction, the target user interacts with the AIGC system and records the interactive information sequence.

[0020] Preferably, the target user first enters the linkage interactive control platform through a device (such as a computer, a tablet, or a smart terminal) and completes the login through an identity verification or authorization process. After logging in, the platform provides an interface for the user to interact with the vehicle body disassembly model, teaching content, and other systems. Subsequently, the AIGC system automatically generates and pops up an interactive confirmation instruction, usually a prompt message or a question, asking the user to confirm whether to start the interaction. The purpose of the interactive confirmation instruction is to ensure that the user is ready for the next operation and to clarify the user's intention, such as whether to start exploring the vehicle body disassembly model or whether to start learning the working principle of a specific system. After receiving the interactive confirmation instruction, the user can choose to confirm or skip this step. If the user confirms the interaction, the confirmation will be recorded and the next stage of interactive operation will be entered. If the user chooses to skip or exit, the platform will give appropriate prompts. After the user confirms, the platform allows the user to communicate with the AIGC system by inputting questions, selecting display content, or other interactive forms. At this time, the AIGC system generates feedback information based on the user's input information and records the input information and feedback information in real time to form an interactive information. By arranging the interactive information in chronological order, an interactive information sequence is obtained, which will be used to analyze user needs and provide intelligent basis for subsequent interaction.

[0021] Further, the present application provides memory iterative analysis of the interactive information sequence to determine the target interactive demand, comprising: extracting first interactive information from the interactive information sequence; based on a preset demand keyword library, performing two-stage memory identification on the first interactive information to determine first interactive information memory; using the first interactive information memory to perform memory iterative analysis on second interactive information in the interactive information sequence to determine second interactive information memory; and iteratively analyzing the interactive information sequence based on the second interactive information memory to determine target interactive information memory; and performing explicit and implicit double analysis on the target interactive information memory to determine the target interactive demand.

[0022] Preferably, when the target user interacts with the AIGC system, the platform records the user's operation and feedback in real time, forming an interactive information sequence, and then extracts the first interactive information from the interactive information sequence according to the stored order. This first interactive information contains the user's behavior information and the system's feedback information, which can help understand the user's preliminary needs. Subsequently, the first interactive information is subjected to first-order keyword extraction, and a set of keywords in the information is identified. Based on these keyword sets, second-order key sentence extraction is performed, that is, key sentences related to these keywords are extracted. Then, the extracted key sentences and keywords are combined to generate a first interactive information memory vector, which is used to represent the preliminary information of the user's needs. After completing the extraction of the first interactive information memory, the subsequent second interactive information, that is, the further operation or feedback of the user after the first round of interaction, is analyzed. Through the same memory iteration analysis of the second interactive information, that is, first-order and second-order extraction, the second interactive information memory is obtained and used as a reference for subsequent interaction. With the user's continued interaction, more interactive information will be processed through memory iteration analysis, and each new interactive information will be further analyzed and processed based on the previous memory to ensure continuous improvement of the understanding of the user's needs, and finally form a complete target interactive information memory. This target interactive information memory integrates all the interactive behaviors, preferences and needs of the user, forming the most accurate understanding of the user's needs. Then, the obtained target interactive information memory is subjected to explicit and implicit double analysis. In this process, the explicit interactive demand analyzer is used to analyze the explicit demand of the target interactive information memory, and the target interactive information memory is analyzed according to the historical interactive record set of the target user. Finally, the explicit demand and implicit demand analysis results are fused to obtain the final target interactive demand, thereby providing customized display content and interactive experience for the user, ensuring that the teaching content and display meet the user's learning intention and needs.

[0023] Further, the application provides double-order memory identification of the first interactive information based on a preset demand keyword library to determine the first interactive information memory, comprising: According to the preset demand keyword library, the first-order keyword extraction of the first interactive information is performed to determine the first interactive information keyword set. Based on the first interactive information keyword set, the second-order key sentence extraction of the first interactive information is performed to determine the first interactive information key sentence set. The first interactive information keyword set and the first interactive information key sentence set are added to the initially empty vector to obtain the first interactive information memory vector.

[0024] Optionally, after obtaining the first interaction information, a preset demand keyword library is traversed, which contains standard terms or high-frequency demand words related to teaching content, vehicle body system, display method, etc., such as battery module, battery pack, drive motor, suspension structure, electric control system, working principle, display, disassembly, etc. For the preset keywords traversed, first-order keyword extraction is performed by comparing with the disassembled words of the first interaction information, and words satisfying the preset threshold are obtained to form a first interaction information keyword set. Subsequently, sentence-level segmentation is performed on the first interaction information, in which process, sentences containing any keyword in the first interaction information keyword set are searched from all sentences of the first interaction information, and these sentences are arranged as a first interaction information key sentence set, for example, if the user inputs “I want to understand the working process and structure of the electric control system”, the keyword extraction result is “electric control system” “working process” “structure”, and the corresponding key sentence is the whole sentence “I want to understand the working process and structure of the electric control system”. Then, an empty vector container is initialized, denoted as the first interaction information memory vector, and all keywords in the first interaction information keyword set are added to the first dimension of the vector as the first interaction information memory vector, and all sentences in the first interaction information key sentence set are added to the second dimension of the vector as the first interaction information memory vector, forming the final first interaction information memory vector, which is used as a comprehensive memory representation of the current user input, and is used for iterative analysis of more interaction information to gradually determine the user's complete interaction demand.

[0025] Further, the application provides that the first interaction information is subjected to keyword splitting, and the keywords in the splitting result are respectively subjected to inner product mapping with the preset demand keyword library, and the keywords with inner product mapping results greater than or equal to a preset threshold are added to the first interaction information keyword set.

[0026] Optionally, for the extracted first interaction information, a Chinese word segmentation tool (such as jieba) is used for segmentation to obtain an original keyword list, and the original keyword list is cleaned to remove stop words (such as meaningless words such as "of" and "is") and punctuation marks. For the cleaned original keyword list, a pre-trained word embedding model (such as Word2Vec or BERT) is used to convert it into a word vector form to form an original keyword vector for each original keyword. Subsequently, for each original keyword vector, the inner product of each preset keyword vector in the preset demand keyword library is calculated. The larger the inner product value, the higher the semantic similarity. Then, the calculated inner product mapping result is compared with a preset threshold (for example, 0.75). If the inner product mapping result of a certain original keyword vector is greater than or equal to the set threshold, it is considered that the original keyword corresponding to the vector is strongly related to the teaching goal. At this time, the original keyword will be added to the first interaction information keyword set for subsequent key sentence extraction, memory construction, and improvement of the understanding ability of natural language input, so that subsequent interaction recognition and teaching display are more accurate and intelligent.

[0027] Further, the present application provides explicit and implicit double analysis on the target interaction information memory to determine the target interaction demand, including: calling an explicit interaction demand analyzer to analyze the demand of the target interaction information memory and determine the explicit interaction demand; calling a historical interaction record set of the target user; associating and matching the target interaction information memory with the historical interaction record set to obtain an associated historical interaction record set; extracting the implicit common demand of the associated historical interaction record set to determine the implicit interaction demand; and fusing the explicit interaction demand and the implicit interaction demand to obtain the target interaction demand.

[0028] Optionally, for the obtained target interaction information memory, the target interaction information memory is input into an explicit interaction demand analyzer for demand analysis. The explicit interaction demand analyzer is a pre-trained BERT model, which can identify explicit interaction demands according to keywords and key sentences in the target interaction information memory, for example, a battery pack corresponds to a power system, and a corresponding display operation is displayed. Subsequently, a set of historical interaction records generated by the user in the platform is called from a local database or cloud storage, including the user's past interaction data with the platform each time, such as question content, selection module, click record, historical display path, dwell time, feedback evaluation, etc. Then, based on the keywords and key sentences in the target interaction information memory, the historical records with high keyword coincidence rate and strong semantic correlation are searched from the set of historical interaction records, the search method is similar to the aforementioned inner product calculation, and the searched records are associated with the target interaction information memory to form an associated set of historical interaction records. Then, the associated set of historical interaction records is subjected to implicit common demand extraction, that is, by demand reverse analysis on the associated set of historical interaction records, the top m high-frequency demands (such as the top 5 most frequently queried contents) are obtained as an implicit interaction demand set. Finally, the explicit interaction demand set and the implicit interaction demand set are fused by a weighted method to generate a fusion demand vector as the final target interaction demand, which is used for subsequent teaching content linkage, lamp control streamline matching and voice explanation triggering, etc., to improve the user's participation and learning effect.

[0029] Further, the present application provides implicit common demand extraction on the associated set of historical interaction records to determine implicit interaction demands, including: extracting a set of historical interaction results of the associated set of historical interaction records; performing demand reverse analysis on the set of historical interaction results to determine a set of historical interaction demands; extracting historical interaction demands with appearance frequencies in the top m positions in the set of historical interaction demands to obtain implicit interaction demands.

[0030] Optionally, in the implicit common demand extraction process, the interaction result field is first extracted from the associated historical interaction record set, the interaction result field refers to the actual display, explanation or feedback content triggered after responding to the user's historical request, for example, the three-dimensional structure of the battery pack is displayed, the animation of the electric control system workflow is displayed, the energy flow LED light control demonstration is activated, etc. By summarizing these interaction result fields, a historical interaction result set is formed. Then, the input data of the training explicit interaction demand analyzer is taken as the output data of the demand reverse analysis analyzer, the label data of the training explicit interaction demand analyzer is taken as the input data of the demand reverse analysis analyzer, the BERT model is pre-trained to build a demand reverse analysis analyzer, and then the historical interaction result set is input into the demand reverse analysis analyzer for reverse analysis to obtain the historical interaction demand of each historical interaction result, for example, "displaying battery module operation animation" is reverse analyzed as "user wants to know how the battery module works" and "voice explanation of electric control system structure" is reverse analyzed as "user wants to understand the composition structure of the electric control system". By summarizing the reverse analyzed historical interaction demand, a historical interaction demand set can be obtained. Then, the historical interaction demand set is traversed and counted to count the number of occurrences of each historical interaction demand, and the historical interaction demands are arranged in descending order according to the counted frequency, and then the historical interaction demands with the top m frequencies are extracted from the arranged results. These high-frequency historical interaction demands will be defined as implicit interaction demands, which represent that the user has not directly expressed in the current session, but from the historical behavior it can be seen that the content of high continuous attention or interest, so as to make the system have the ability to prospectively recommend or display teaching content, and improve the intelligence and adaptability of cross-professional teaching.

[0031] The linkage interaction control platform is called to identify the target interaction demand and determine the target linkage explanation content.

[0032] In one embodiment, after obtaining the target interactive demand, the interactive content analyzer in the linkage interactive control platform is called to identify the target interactive demand, and the target linkage explanation content is determined. The explanation content analyzer can be built based on Transformer. Specifically, an initial explanation content analyzer structure is first constructed using Transformer, including an input layer, an output layer, a full connection layer, an encoder, a decoder, etc. Then, the weights of the initial explanation content analyzer are initialized using random numbers, and the training data (including historical interactive demands and historical explanation contents) are input into the initialized initial explanation content analyzer for forward propagation. The input layer, encoder, decoder, full connection layer, and output layer are used for layer-by-layer transmission, and the prediction results including the linkage explanation content are calculated. Then, the cross-entropy loss function is used to calculate the loss value between the prediction results and the sample data, and the gradients of the loss to the weights of each layer are calculated through back propagation. The Adam optimizer is used to optimize the parameters of the analyzer to adjust the weights to minimize the value of the loss function. The above process is repeated until the maximum number of iterations is reached. After training, the data not used for training is used to test the performance of the analyzer to evaluate the accuracy of the analyzer in the explanation content generation task. If the accuracy meets the expectation, the current initial explanation content analyzer is output as the final explanation content analyzer. Otherwise, the learning rate, training batch size, and other hyperparameters are adjusted to further improve the content generation effect of the explanation content analyzer.

[0033] The linkage control analyzer of the linkage interactive control platform is called to identify the target interactive demand, and the target vehicle body disassembly unit and the target linkage lamp control flow line demonstration scheme are determined.

[0034] In one embodiment, when the target interactive demand is identified, the pre-trained linkage control analyzer in the linkage interactive control platform is called to identify the target interactive demand, and the target vehicle body disassembly unit and the target linkage lamp control flow line demonstration scheme are determined. The target vehicle body disassembly unit is composed of any number of vehicle body disassembly units from the vehicle body disassembly unit set, which is used to display the structural composition, operation logic, or associated position of the vehicle. The target linkage lamp control flow line demonstration scheme is a dynamic light path that matches the functional state of the vehicle body structure component, which is used to visually express the energy flow, signal control, or operation sequence of the system through changes in color, flow direction, rhythm, etc. By calling the linkage control analyzer, automatic identification and execution from user demand to display content can be realized, and the corresponding disassembly components and dynamic light effects can be accurately matched. This not only improves the intelligent level of the display, but also ensures that the teaching content and display form are highly consistent, thereby effectively improving the intuitiveness, interactivity, and immersion of cross-disciplinary teaching.

[0035] Further, the application provides a linkage control analyzer of the linkage interactive control platform, linkage display identification is performed on the target interactive demand, a target vehicle body deconstruction unit and a target linkage lamp control flow line demonstration scheme are determined, and the linkage display identification comprises the following steps: A plurality of sample interactive demands, a plurality of sample vehicle body deconstruction units and a plurality of sample linkage lamp control flow line demonstration schemes are obtained as positive samples; the plurality of sample vehicle body deconstruction units and the plurality of sample linkage lamp control flow line demonstration schemes are interfered and derived to obtain a plurality of interference sample vehicle body deconstruction units and a plurality of sample interference linkage lamp control flow line demonstration schemes; the plurality of interference sample vehicle body deconstruction units and the plurality of sample interference linkage lamp control flow line demonstration schemes and the plurality of sample interactive demands are used as negative samples; the initialized support vector machine is trained by using the positive sample set and the negative sample set until a requirement is met, and the linkage control analyzer trained is obtained.

[0036] Optionally, first, a standardized training sample library is established, which includes multiple sample interaction requirements and corresponding multiple sample vehicle body disassembly units, multiple sample linkage light control flow line demonstration schemes. These sample data will constitute the positive sample set for model training, that is, interaction requirement→correct structure unit+light control scheme, and then the positive sample set is converted into a trainable vector format as data with label 1. Subsequently, in order to improve the generalization ability, the multiple sample vehicle body disassembly units and multiple sample linkage light control flow line demonstration schemes in the positive samples are subjected to interference derivation processing to generate a batch of interference sample vehicle body disassembly units and sample interference linkage light control flow line demonstration schemes that may have certain similarity but do not match in semantics. Then, the multiple interference sample vehicle body disassembly units and multiple sample interference linkage light control flow line demonstration schemes, and multiple sample interaction requirements are integrated into a negative sample set, and the negative sample set is converted into a trainable vector format as data with label 0. The interference methods include but are not limited to structure level mismatch (such as incorrectly associating battery module requirements with suspension systems, instrument panels, and other unrelated disassembly units), light control scheme mismatch (such as incorrectly matching display energy flow requirements as static red constant light or pulse flicker, which does not conform to the semantics of the light effect), and similar word interference (such as interchanging high-voltage distribution units and electrically controlled relay groups, which have similar semantics but different technical meanings). Then, a support vector machine classifier (SVM) is initialized, and the kernel function (such as RBF) and training parameters (such as learning rate, fault tolerance rate C value, etc.) are set. Then, all samples are input into the SVM model for training. In the training process, the boundary features between positive and negative samples are used to construct a decision hyperplane through a maximum interval optimization algorithm. Then, through continuous iteration, the model reaches the set accuracy on the validation data. After training is completed, the SVM model can automatically identify the most likely matching vehicle body structure display unit and corresponding light control flow line scheme according to the input interaction requirement vector, realizing intelligent display driven by requirements. The trained model is integrated into the linkage interaction control platform as a linkage control analyzer, realizing intelligent mapping between interaction requirements and vehicle display content to enhance the adaptability and precision of the system.

[0037] The target vehicle body disassembly unit, target linkage light control flow line demonstration scheme, and target linkage explanation content are transmitted to the multi-terminal control unit of the linkage interaction control platform for voice explanation and light gradient flow synchronization display.

[0038] In one embodiment, after obtaining the target vehicle body disassembly unit, the target linkage lamp control flow line demonstration scheme and the target linkage explanation content, the recognized target vehicle body disassembly unit, the target linkage lamp control flow line demonstration scheme and the target linkage explanation content are packaged into a multi-terminal linkage control instruction set, and transmitted to a multi-terminal linkage control unit subordinate to the linkage interactive control platform. The multi-terminal linkage control unit is composed of multiple hardware, including a physical structure display table, an intelligent lamp control controller, a voice explanation module, etc., and is used to realize the unified display of teaching content. After receiving the linkage control instruction, all related devices will be automatically scheduled, so that the vehicle body disassembly unit performs dynamic explosion display or transparent cross-section highlight display according to the preset order. At the same time, the linkage lamp control flow line demonstration scheme controls the embedded light belt to flow along the predetermined path, and changes the color sequence, direction, brightness and rhythm according to the set sequence, to realize the visual dynamic demonstration of the circuit flow direction or energy transmission path. At the same time, the voice explanation module calls the recognized explanation text and broadcasts it in real time through the AI voice synthesis engine, strictly aligning the voice output with the structure display and the lamp control rhythm to ensure the high integration of multi-modal information. In addition, it also supports user interaction during the display process, such as pausing, jumping or content switching of the display rhythm through gestures, click instructions, etc. At the same time, the linkage control unit has a state feedback mechanism, which can real-time feedback the execution state of each control module, and automatically calibrate the linkage consistency of voice and lamp effect based on the feedback. Through this complete linkage display process, users can obtain immersive, synchronized and intelligent teaching experience, and achieve the cross-professional learning goal of visual structure, perceptible principle and audible control.

[0039] Further, the method further comprises: obtaining a voice explanation start time node and a lamp light gradual change flow display time node; performing synchronization consistency analysis based on the voice explanation start time node and the lamp light gradual change flow display time node to obtain a synchronization consistency factor; performing linkage control delay analysis based on the voice explanation start time node and the lamp light gradual change flow display time node to obtain a linkage control delay factor; performing weighted analysis on the synchronization consistency factor and the linkage control delay factor, and optimizing the multi-terminal linkage control unit according to the weighted analysis result.

[0040] Preferably, in order to ensure that the voice commentary and the light gradient flow are highly synchronized and coordinated in the linkage display process, a synchronization control mechanism is introduced to analyze and optimize the time nodes of voice output and light effect demonstration. Specifically, first, the starting time node of the voice commentary and the starting time node of the light gradient flow in each linkage display are recorded, and these two time nodes are collected in real time by sensors or logs in the multi-terminal linkage control unit for subsequent synchronization calculation. Then, the synchronization consistency of the two time nodes is analyzed, the time difference between them is calculated, and the difference is used as a synchronization consistency factor, which is used to quantify the starting synchronization degree of voice and light. The smaller the value, the more synchronized. Subsequently, the actual starting time delay of the voice commentary starting time node and the light gradient flow display time node from the instruction sending to each hardware is obtained, including the voice commentary module response delay and the intelligent light controller response delay. By calculating the difference between the two, the linkage time delay factor is obtained, which is used to measure the actual response delay deviation between the two hardware. After obtaining the synchronization consistency factor and the linkage time delay factor, the two factors are analyzed comprehensively by weighting to form the final optimization adjustment parameter. If the optimization adjustment parameter exceeds the set threshold, the execution offset of the light or voice module will be automatically adjusted, for example, the light control delay starting time, the preloaded voice output and other ways are adjusted in proportion, so that the starting rhythm of the two is more coordinated. The optimization result will be dynamically updated to the multi-terminal linkage control unit to realize the precise synchronization of voice and light on the time axis in the whole process, thereby improving the immersion and teaching accuracy of the linkage display.

[0041] In summary, the embodiments of the present application have at least the following technical effects: The embodiment of the application first acquires a vehicle body disassembly model, wherein the vehicle body disassembly model comprises a vehicle body disassembly unit set, a lamp control flow line auxiliary component and a linkage interactive control platform; then, a target user interacts with an AIGC system through the linkage interactive control platform to obtain an interactive information sequence, and memory iteration analysis is performed on the interactive information sequence to determine a target interaction demand; subsequently, the linkage interactive control platform is called to identify linkage explanation content for the target interaction demand to determine target linkage explanation content; then, a linkage control analyzer of the linkage interactive control platform is called to identify linkage display for the target interaction demand to determine a target vehicle body disassembly unit and a target linkage lamp control flow line demonstration scheme; finally, the target vehicle body disassembly unit, the target linkage lamp control flow line demonstration scheme and the target linkage explanation content are transmitted to a multi-terminal linkage control unit of the linkage interactive control platform for voice explanation and lamp light gradual change flow synchronization display. These technical effects jointly solve the technical problem that under the traditional vehicle body disassembly teaching mode, cross-professional knowledge cannot be intuitively displayed and interacted, and achieve the technical effects of realizing linkage display and teaching of multi-disciplinary knowledge through vehicle body disassembly models, lamp control flow lines and AIGC intelligent interaction, and improving teaching depth and breadth.

[0042] In the second embodiment, based on the same inventive concept as the vehicle body disassembly information linkage display method supporting cross-professional teaching in the foregoing embodiments, as shown in the following table, the application provides a vehicle body disassembly information linkage display system supporting cross-professional teaching, which comprises: Figure 2 a vehicle body disassembly model acquisition module 11: acquiring a vehicle body disassembly model, wherein the vehicle body disassembly model comprises a vehicle body disassembly unit set, a lamp control flow line auxiliary component and a linkage interactive control platform; a memory iteration analysis module 12: a target user interacts with an AIGC system through the linkage interactive control platform to obtain an interactive information sequence, and memory iteration analysis is performed on the interactive information sequence to determine a target interaction demand; an explanation content identification module 13: calling the linkage interactive control platform to identify linkage explanation content for the target interaction demand to determine target linkage explanation content; a display identification module 14: calling a linkage control analyzer of the linkage interactive control platform to identify linkage display for the target interaction demand to determine a target vehicle body disassembly unit and a target linkage lamp control flow line demonstration scheme; and an explanation display module 15: transmitting the target vehicle body disassembly unit, the target linkage lamp control flow line demonstration scheme and the target linkage explanation content to a multi-terminal linkage control unit of the linkage interactive control platform for voice explanation and lamp light gradual change flow synchronization display.

[0043] Further, the memory iteration analysis module 12 is further used to perform the following method: The target user logs in the linkage interaction control platform, and the AIGC system pops up an interaction confirmation instruction; after the target user confirms the interaction confirmation instruction, the target user interacts with the AIGC system, and interaction information sequences are recorded.

[0044] Further, the memory iterative analysis module 12 is further used to execute the following method: The first interaction information is extracted from the interaction information sequence; the first interaction information is subjected to two-stage memory identification based on a preset demand keyword library, and first interaction information memory is determined; the second interaction information in the interaction information sequence is subjected to memory iterative analysis by using the first interaction information memory, and second interaction information memory is determined; the interaction information sequence is subjected to memory iterative analysis according to the second interaction information memory, and target interaction information memory is determined; the target interaction information memory is subjected to explicit and implicit double analysis, and target interaction demand is determined.

[0045] Further, the memory iterative analysis module 12 is further used to execute the following method: According to the preset demand keyword library, the first interaction information is subjected to one-stage keyword extraction, and a first interaction information keyword set is determined; the first interaction information is subjected to two-stage key sentence extraction based on the first interaction information keyword set, and a first interaction information key sentence set is determined; the first interaction information keyword set and the first interaction information key sentence set are added to an initially empty vector, and a first interaction information memory vector is obtained.

[0046] Further, the memory iterative analysis module 12 is further used to execute the following method: The first interaction information is subjected to keyword splitting, and the keywords in the splitting result are respectively subjected to inner product mapping with the preset demand keyword library; keywords with an inner product mapping result greater than or equal to a preset threshold are added to the first interaction information keyword set.

[0047] Further, the memory iterative analysis module 12 is further used to execute the following method: An explicit interaction demand analyzer is called to analyze the demand of the target interaction information memory, and an explicit interaction demand is determined; a historical interaction record set of the target user is called; the target interaction information memory is associated and matched with the historical interaction record set, and an associated historical interaction record set is obtained; an implicit common demand of the associated historical interaction record set is extracted, and an implicit interaction demand is determined; the explicit interaction demand and the implicit interaction demand are fused, and the target interaction demand is obtained.

[0048] Further, the memory iterative analysis module 12 is further used to execute the following method: extract a historical interaction result set of the associated historical interaction record set; perform demand inverse solution on the historical interaction result set to determine a historical interaction demand set; extract a historical interaction demand with a frequency of occurrence in the top m positions in the historical interaction demand set to obtain an implicit interaction demand.

[0049] Further, the display identification module 14 is also used to execute the following method: Obtain a plurality of sample interaction demands, and a plurality of sample vehicle body disassembly units and a plurality of sample linkage light control flow line demonstration schemes as positive samples; perform interference derivation on the plurality of sample vehicle body disassembly units and the plurality of sample linkage light control flow line demonstration schemes to obtain a plurality of interference sample vehicle body disassembly units and a plurality of sample interference linkage light control flow line demonstration schemes; take the plurality of interference sample vehicle body disassembly units and the plurality of sample interference linkage light control flow line demonstration schemes, and the plurality of sample interaction demands as negative samples; train the initialized support vector machine using the positive sample set and the negative sample set until the requirement is met to obtain the linkage control analyzer after training.

[0050] Further, the explanation display module 15 is also used to execute the following method: Obtain a voice explanation start time node and a light gradient flow display time node; perform synchronization consistency analysis based on the voice explanation start time node and the light gradient flow display time node to obtain a synchronization consistency factor; perform linkage control delay analysis based on the voice explanation start time node and the light gradient flow display time node to obtain a linkage control delay factor; perform weighted analysis on the synchronization consistency factor and the linkage control delay factor, and optimize the multi-terminal linkage control unit according to the weighted analysis result.

[0051] It should be noted that the above sequence of the embodiments of the present application is only for description, and does not represent the advantages and disadvantages of the embodiments. The above describes a specific embodiment of the present application. The processes depicted in the drawings do not necessarily require the specific order and continuous order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are also possible or can be advantageous.

[0052] The above only describes the preferred embodiments of the present application, and does not limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

[0053] The specification and drawings are, of course, subject to various interpretations and should not be viewed in any limiting sense. It will be understood that various modifications and changes can be made to the application disclosed without departing from the scope of the application. It is therefore intended that the application be limited only by the scope of the appended claims.

Claims

1. A method for linking and displaying vehicle body disassembly information to support interdisciplinary teaching, characterized in that: The method includes: Obtain a vehicle body disassembly model, wherein the vehicle body disassembly model includes a set of vehicle body deconstruction units, lighting control streamline auxiliary components, and a linkage and interactive control platform; The target user interacts with the AIGC system through the linkage and interactive control platform to obtain the interaction information sequence, and performs memory iterative analysis on the interaction information sequence to determine the target interaction needs; The linkage and interactive control platform is invoked to identify the linkage explanation content of the target interaction requirement and determine the target linkage explanation content. The linkage control analyzer of the linkage interaction control platform is invoked to identify the linkage display of the target interaction requirements and determine the target vehicle body deconstruction unit and the target linkage lighting control flow demonstration scheme. The target vehicle body deconstruction unit, the target linkage lighting control flow demonstration scheme, and the target linkage explanation content are transmitted to the multi-terminal joint control unit of the linkage interactive control platform for voice explanation and synchronous display of light gradient flow.

2. The method for linked display of vehicle body disassembly information supporting interdisciplinary teaching as described in claim 1, characterized in that, Target users interact with the AIGC system through the interactive control platform to obtain a sequence of interactive information, including: When the target user logs into the linkage and interactive control platform, the AIGC system pops up an interaction confirmation command. After the target user confirms the interaction confirmation command, they interact with the AIGC system and record the sequence of interaction information.

3. The method for linked display of vehicle body disassembly information supporting interdisciplinary teaching as described in claim 1, characterized in that, The interactive information sequence is analyzed using memory iteration to determine the target interactive requirements, including: Extract the first interactive information from the interactive information sequence; Based on a pre-defined keyword library, the first interactive information is subjected to dual-level memory recognition to determine the memory of the first interactive information. The memory of the second interactive information in the interactive information sequence is iteratively analyzed using the memory of the first interactive information to determine the memory of the second interactive information. Similarly, based on the second interactive information memory, the interactive information sequence is iteratively analyzed to determine the target interactive information memory; The target interaction information memory is analyzed both explicitly and implicitly to determine the target interaction needs.

4. The method for linked display of vehicle body disassembly information supporting interdisciplinary teaching as described in claim 3, characterized in that, Based on a pre-defined keyword database, a two-stage memory recognition process is performed on the first interactive information to determine the memory of the first interactive information, including: Based on the preset keyword library, first-order keyword extraction is performed on the first interactive information to determine the keyword set of the first interactive information. Based on the keyword set of the first interactive information, second-order key sentence extraction is performed on the first interactive information to determine the key sentence set of the first interactive information. Add the first set of interactive information keywords and the first set of interactive information key sentences into an initially empty vector to obtain the first interactive information memory vector.

5. The method for linked display of vehicle body disassembly information supporting interdisciplinary teaching as described in claim 4, characterized in that, The first interactive information is split into keywords, and the keywords in the splitting results are mapped with the preset demand keyword library. Keywords whose inner product mapping results are greater than or equal to a preset threshold are added to the first interactive information keyword set.

6. The method for linked display of vehicle body disassembly information supporting interdisciplinary teaching as described in claim 3, characterized in that, The target interaction information memory is analyzed using both explicit and implicit methods to determine the target interaction needs, including: The explicit interaction requirements analyzer is invoked to perform requirement parsing on the target interaction information memory and determine the explicit interaction requirements. Retrieve the target user's historical interaction records; The target interaction information memory is associated and matched with the historical interaction record set to obtain the associated historical interaction record set; Implicit common needs are extracted from the aforementioned set of related historical interaction records to determine implicit interaction needs; The explicit interaction requirements and the implicit interaction requirements are merged to obtain the target interaction requirements.

7. The method for linked display of vehicle body disassembly information supporting interdisciplinary teaching as described in claim 6, characterized in that, The implicit common needs are extracted from the aforementioned set of related historical interaction records to determine implicit interaction needs, including: Extract the set of historical interaction results from the set of associated historical interaction records; The historical interaction result set is used to perform reverse demand analysis to determine the historical interaction demand set; Extract the historical interaction requests that appear in the top m positions from the set of historical interaction requests to obtain implicit interaction requests.

8. The method for linked display of vehicle body disassembly information supporting interdisciplinary teaching as described in claim 1, characterized in that, The linkage control analyzer of the linkage interaction control platform is invoked to identify and display the target interaction requirements, and to determine the target vehicle body deconstruction unit and the target linkage lighting control flow demonstration scheme, including: Multiple sample interaction requirements, as well as multiple sample vehicle body deconstruction units and multiple sample linkage lighting control streamline demonstration schemes are obtained as positive samples; Interference derivation is performed on the multiple sample vehicle body deconstruction units and multiple sample linked lighting control streamline demonstration schemes to obtain multiple interference sample vehicle body deconstruction units and multiple sample interference linked lighting control streamline demonstration schemes. The multiple interference sample vehicle body deconstruction units and multiple sample interference linkage lighting control streamline demonstration schemes, as well as the multiple sample interaction requirements, are used as negative samples. The initial support vector machine is trained using the positive and negative sample sets until the requirements are met, thus obtaining the trained linkage control analyzer.

9. The method for linked display of vehicle body disassembly information supporting interdisciplinary teaching as described in claim 1, characterized in that, Also includes: Obtain the start time of the voice explanation and the time of the light gradient flow display; Based on the timing of the voice explanation start-up and the timing of the light gradient flow display, a synchronization consistency analysis was performed to obtain the synchronization consistency factor. Based on the voice explanation start time node and the light gradient flow display time node, joint control delay analysis is performed to obtain the joint control delay factor; The synchronization consistency factor and the joint control delay factor are weighted and analyzed, and the multi-terminal joint control unit is optimized based on the weighted analysis results.

10. A vehicle body disassembly information linkage display system supporting interdisciplinary teaching, characterized in that: The system is used to execute the vehicle body disassembly information linkage display method supporting interdisciplinary teaching as described in any one of claims 1-9, the system comprising: Vehicle body disassembly model acquisition module: acquires a vehicle body disassembly model, wherein the vehicle body disassembly model includes a set of vehicle body deconstruction units, lighting control streamline auxiliary components, and a linkage and interactive control platform; Memory Iteration Parsing Module: The target user interacts with the AIGC system through the linkage interactive control platform to obtain the interaction information sequence, and performs memory iteration parsing on the interaction information sequence to determine the target interaction needs; Content recognition module: calls the interactive control platform to recognize the interactive content of the target interaction request and determine the target interactive content; Display recognition module: calls the linkage control analyzer of the linkage interaction control platform to perform linkage display recognition on the target interaction requirements, and determines the target vehicle body deconstruction unit and the target linkage lighting control streamline demonstration scheme; Explanation and demonstration module: The target vehicle body deconstruction unit, the target linkage lighting control flow demonstration scheme, and the target linkage explanation content are transmitted to the multi-terminal joint control unit of the linkage interactive control platform for voice explanation and synchronous display of light gradient flow.

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