WebGL rendering-based device state display system and method

Abstract

The invention discloses an equipment state display system and method based on WebGL rendering, the system comprises an equipment end, a cloud server and an interaction end, the cloud server is configured with a WebGL rendering module, an intelligent prediction module, an intelligent classification module and an overhaul database, the WebGL rendering module is used for generating a 3D model in real time according to various parameter data, and the 3D model is used for displaying the 3D model. The intelligent prediction module comprises a pre-trained prediction model, the prediction model is used for predicting the state and fault description of the equipment end in future time, the intelligent classification module comprises a pre-trained classification model, and the classification model is used for matching maintenance knowledge in the maintenance database according to the fault description of the equipment end. According to the method, the classification model is configured, so that the maintenance scheme with the highest correlation and the historical cases are given to the interaction end based on the fault description and the matching result for reference of the user using the interaction end, and the real-time 3D model can be accessed and the corresponding maintenance scheme and the historical cases can be displayed by utilizing the VR equipment or the AR equipment; and immersive maintenance is provided for maintenance personnel.

Description

Technical Field

[0001] The present application relates to the field of device rendering technology, and more specifically to a device status display system and method based on WebGL rendering. Background Art

[0002] The rapid development of the wind power industry has put forward higher requirements on the reliability, safety and economy of wind turbines. Real-time monitoring and fault diagnosis of wind turbine operating status has become one of the key technologies in wind farm operation and maintenance management.

[0003] As the core equipment of a wind farm, the operating status of the wind turbine directly affects the power generation efficiency and equipment life of the wind farm. The key parameters of the wind turbine operating status include speed, vibration, temperature, current, etc. Abnormal fluctuations in these parameters often indicate potential failures or performance degradation of wind turbine components. Timely and accurate monitoring and diagnosis of the operating status of the wind turbine can effectively improve the power generation efficiency of the wind turbine, extend the equipment life, reduce operation and maintenance costs, and ensure the safety of equipment and personnel.

[0004] Traditional wind turbine condition monitoring systems usually use SCADA systems and condition monitoring instruments for data collection and storage, and use 2D charts, numerical alarms, etc. to display data and provide fault alarms. However, this traditional monitoring method has the following limitations: 1. Poor intuitiveness of data display. 2D charts are difficult to intuitively and comprehensively display the three-dimensional structure and component layout of the fan, which is not conducive to operators quickly locating and identifying faulty parts.

[0005] 2. Insufficient depth of data interpretation. Traditional methods lack in-depth mining and intelligent analysis of monitoring data, making it difficult to discover the inherent laws and evolution trends of wind turbine failures, and prone to problems such as missed reports and false reports.

[0006] 3. Poor human-computer interaction experience. The 2D interface has a single interactive mode, lacks immersion and real-time performance, is not conducive to the operator's active analysis and exploration, and reduces the practicality and ease of use of the monitoring system.

[0007] 4. The maintenance is difficult. The traditional maintenance method is generally based on manual experience or carrying a computer to check relevant information, which greatly affects the efficiency of maintenance. Summary of the invention

[0008] In this embodiment, a device status display system, method, electronic device and storage medium based on WebGL rendering are provided to solve the problems of traditional device status display and inspection and maintenance in related technologies.

[0009] In a first aspect, an embodiment of the present invention provides a device status display system based on WebGL rendering, wherein the device status display system based on WebGL rendering includes a device end, a cloud server, and an interactive end, wherein the device end is configured with a data acquisition module and a data transmission module, the data acquisition module is used to obtain various parameter data of the device end, and the data transmission module is used to transmit various parameter data to the cloud server; The cloud server is configured with a WebGL rendering module, an intelligent prediction module, an intelligent classification module and a maintenance database. The WebGL rendering module is used to generate a 3D model in real time according to various parameter data, and map the various parameter data to the 3D model; the intelligent prediction module includes a pre-trained prediction model, and the prediction model is used to predict the state and fault description of the device end in the future. The intelligent classification module includes a pre-trained classification model, and the classification model is used to match the maintenance knowledge in the maintenance database according to the device end fault description; the interactive end is connected to the cloud server through a network, and is used to display the 3D model generated by the cloud server, the part of the 3D model that needs to be repaired, and the corresponding maintenance knowledge. The interactive end includes a VR device or an AR device.

[0010] In an optional embodiment, the device side is also configured with a data processing module and a local database, the data processing module is used to process various parameter data of the device side, including data filtering, data calibration and format conversion, and the local database is used to store the processed parameter data.

[0011] In an optional embodiment, the WebGL rendering module includes a 3D rendering engine and a data mapping unit, wherein the 3D rendering engine is used to render according to the preprocessed data to generate a 3D model, and the data mapping unit is used to map the preprocessed data to the 3D model to generate a device-side 3D model for real-time display.

[0012] In an optional embodiment, the intelligent prediction module includes a pre-trained prediction model, and the construction of the prediction model includes: Acquire historical operation data of the equipment end, wherein the historical operation data includes working data, fault data and maintenance data; Preprocessing the historical operation data; Use correlation analysis, principal component analysis, and recursive feature elimination to obtain the features that most affect the occurrence of faults; Based on the acquired features, the fault prediction neural network model is provided for learning and training, and the parameters of the fault prediction neural network model are adjusted to adjust the performance of the fault prediction neural network model, so as to obtain the trained fault prediction neural network model, and the trained fault prediction neural network model is used as the prediction model; The prediction model is deployed and integrated into the system of the cloud server to predict the status of the wind turbine in the future and generate a fault description.

[0013] In an optional embodiment, the maintenance database construction includes: Construct the maintenance database structure, which includes fault description, fault type, maintenance plan and historical cases; The data of the maintenance database is preprocessed by using a pre-trained BERT model to segment the text into words or phrases and convert the text into vectors.

[0014] In an optional embodiment, the classification model matches the maintenance knowledge in the maintenance database according to the maintenance category required by the equipment end, including: Obtain the fault description generated by the prediction model, and calculate the similarity between the fault description generated by the prediction model and the fault description in the maintenance database based on the classification model; The top K similarity fault descriptions are taken as matching results, and the maintenance plans and historical cases corresponding to the fault descriptions are returned to the interaction end.

[0015] In an optional embodiment, the interactive end establishes communication with the cloud server, and the interactive end can display the 3D model constructed by the cloud server, the parts of the 3D model that need to be repaired, and the maintenance plans and historical cases obtained by the classification model, and can interact with the 3D model.

[0016] Compared with the prior art, the device status display system based on WebGL rendering of the present invention has the following beneficial effects: The present invention uses WebGL technology to display the operating status of the device side in real time, and provides intuitive, dynamic and interactive status display images. The data acquisition module collects the operating data of the device side in real time, the data processing module performs preprocessing, the data transmission module ensures the real-time and reliability of the data, and the WebGL rendering module implements efficient 3D rendering. Predictive maintenance is performed by using AI technology, that is, historical data is used to predict when the device side may fail or appear abnormal, so as to perform timely maintenance. In addition, by configuring the classification model, the fault description and the corresponding maintenance plan and historical cases in the maintenance database can be returned to the interactive end according to the matching results, so as to provide the most relevant maintenance plan and historical cases to the interactive end based on the fault description and matching results for reference by users using the interactive end. VR devices or AR devices can be used to access real-time 3D models and display corresponding maintenance plans and historical cases for immersive maintenance by maintenance personnel.

[0017] In a second aspect, an embodiment of the present invention provides a device status display method based on WebGL rendering, comprising the following steps: Get various parameter data of the device; Send the parameter data to the cloud server, and generate a 3D model in real time based on the parameter data; Predict the future state of the equipment end through the pre-trained prediction model and generate a fault description. Match the fault description with the fault description in the maintenance database through the pre-trained classification model to obtain the corresponding maintenance plan and historical cases. Use the interactive terminal to display the 3D model, maintenance status, corresponding maintenance plan and historical cases of the equipment.

[0018] In a third aspect, an embodiment of the present invention provides an electronic device, comprising a processor, a communication interface, a memory and a bus, wherein the processor, the communication interface and the memory communicate with each other through the bus, and the processor can call logical instructions in the memory to execute the steps of the method provided in the second aspect.

[0019] In a fourth aspect, an embodiment of the present invention provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the device status display method based on WebGL rendering as described in the second aspect.

[0020] Compared with the prior art, the beneficial effects of the device status display method, electronic device and storage medium based on WebGL rendering of the present invention are the same as those of the device status display system based on WebGL rendering described in the first aspect, so they are not repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0022] Figure 1 It is a structural block diagram of a device status display system based on WebGL rendering in an embodiment of the present invention; Figure 2 This is a structural block diagram of a WebGL rendering module in an embodiment of the present invention; Figure 3 This is a flow chart of a method for displaying device status based on WebGL rendering in an embodiment of the present invention; Figure 4 1 is a structural block diagram of an electronic device in an embodiment of the present invention. DETAILED DESCRIPTION

[0023] In order to more clearly understand the purpose, technical solutions and advantages of the present application, the present application is described and illustrated below in conjunction with the accompanying drawings and embodiments.

[0024] Unless otherwise defined, the technical terms or scientific terms involved in this application shall have the general meaning understood by people with general skills in the technical field to which this application belongs. The words "one", "a", "the", "these" and the like in this application do not indicate a quantitative limitation, and they may be singular or plural. The terms "include", "comprise", "have" and any variants thereof involved in this application are intended to cover non-exclusive inclusions; for example, a process, method and system, product or device comprising a series of steps or modules (units) is not limited to the listed steps or modules (units), but may include unlisted steps or modules (units), or may include other steps or modules (units) inherent to these processes, methods, products or devices. The words "connect", "connected", "coupled" and the like involved in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The "multiple" involved in this application refers to two or more. "And / or" describes the association relationship of associated objects, indicating that there may be three relationships, for example, "A and / or B" may mean: A exists alone, A and B exist at the same time, and B exists alone. Generally, the character " / " indicates that the objects associated with each other are in an "or" relationship. The terms "first", "second", "third", etc. in this application are only used to distinguish similar objects and do not represent a specific ordering of the objects.

[0025] The embodiment of the present invention also provides a device status display system based on WebGL rendering. The terms "module", "unit", "subunit", etc. used below can implement a combination of software and / or hardware for a predetermined function. Although the system described in the following embodiments is preferably implemented in software, the implementation of hardware or a combination of software and hardware is also possible and conceivable.

[0026] Figure 1 is a structural block diagram of the device status display system based on WebGL rendering of the present invention, such as Figure 1 As shown, the device status display system based on WebGL rendering includes a device end, a cloud server and an interactive end, wherein the device end is configured with a data acquisition module and a data transmission module, the data acquisition module is used to obtain various parameter data of the device end, and the data transmission module is used to transmit various parameter data to the cloud server; It should be noted that a communication connection is established between the device side, the cloud server and the interactive side. For ease of understanding, in this embodiment, the device side is used as a wind turbine for illustration. Specifically, a data acquisition module is set on the wind turbine. The data acquisition module includes various types of sensors and is installed at different positions of the wind turbine. For example, a speed sensor is installed on the wind turbine rotor to measure the speed of the wind turbine blades. Vibration sensors are installed on the wind turbine tower and blades to detect vibration. Temperature sensors are installed on motors, bearings and other key components to monitor temperature changes. Current sensors are installed on the power output port to measure current intensity. These sensors collect data at predetermined time intervals to ensure real-time and accuracy. By setting a data acquisition module on the wind turbine, various parameter data of the wind turbine (device side) can be obtained.

[0027] It should be further explained that the device side is also configured with a data processing module and a local database. The data processing module is used to process various parameter data on the device side, including data filtering, data calibration and format conversion, and the local database is used to store the processed parameter data.

[0028] Specifically, the raw data collected by the data acquisition module is transmitted to the data processing module through the data acquisition module. Exemplarily, the data processing module performs the following processing: data filtering, removing noise and outliers to ensure the accuracy of the data. Data calibration, calibrating the data according to the characteristics of the sensor and environmental conditions to improve the reliability of the data. Format conversion, converting the data into a standard format for subsequent processing and storage. The processed data is stored in a database. The database can be a local database or a cloud database, depending on the specific application scenario and system architecture.

[0029] The data transmission module is used to transmit various parameter data to the cloud server. In this embodiment, the WebSocket protocol is used for data transmission, which supports two-way communication and real-time data update. The SSL / TLS protocol is used to encrypt the data to ensure the security of data transmission. The transmitted data is compressed to reduce bandwidth usage and improve transmission efficiency. Furthermore, the data transmitted to the Web server is stored in the server's database in real time for subsequent use.

[0030] Combination Figure 2As shown, the cloud server is configured with a WebGL rendering module, an intelligent prediction module, an intelligent classification module, and a maintenance database. The WebGL rendering module is used to generate a 3D model in real time according to various parameter data, and map various parameter data to the 3D model; specifically, the WebGL rendering module includes a 3D rendering engine and a data mapping unit. The 3D rendering engine is used to render according to the preprocessed data to generate a 3D model. The data mapping unit is used to map the preprocessed data to the 3D model, and is used to generate a device-side 3D model for real-time display. The WebGL rendering module consists of a 3D rendering engine and a data mapping unit, which are responsible for 3D rendering the received real-time data to generate an efficient and real-time 3D model display. Among them, the 3D rendering engine is based on WebGL technology to achieve efficient 3D graphics rendering, and can generate a three-dimensional model and status display image of the wind turbine in real time.

[0031] The data mapping unit maps the received real-time data to the 3D model, and updates the model's operating status and parameter display in real time. The data mapping unit can flexibly adjust the data mapping method and display effect according to different data types and display requirements. The WebGL rendering module supports real-time dynamic rendering, and can update the 3D model and display effect in real time according to the real-time changes of data, ensuring the real-time and accuracy of the display.

[0032] The intelligent prediction module includes a pre-trained prediction model, which is used to predict the status of the device in the future and the fault description. It should be noted that the construction of the prediction model includes: Obtain historical operation data of the equipment, including working data, fault data and maintenance data; among them, working data includes parameters such as speed, vibration, temperature, current, etc., fault data includes fault type, fault phenomenon, fault time, etc., and maintenance data includes maintenance time, maintenance process, maintenance personnel, maintenance results, etc.

[0033] Preprocessing of historical operation data; preprocessing includes data cleaning to remove noise and outliers to ensure data purity; data calibration, calibrating the data according to the characteristics of the sensor and environmental conditions to ensure data accuracy; data standardization, standardizing or normalizing data of different dimensions to ensure data consistency.

[0034] Use correlation analysis, principal component analysis, and recursive feature elimination to obtain the features that most affect the occurrence of faults; extract features that are helpful to the model from the original data to improve the model's predictive ability. Common extracted features include: Time domain characteristics: such as mean, variance, skewness, kurtosis, etc., are used to describe the distribution characteristics of data.

[0035] Frequency domain features: such as spectrum features extracted by Fourier transform, are particularly suitable for the analysis of vibration data.

[0036] Time series characteristics: such as autocorrelation and time delay, are used to describe the time dependence of data.

[0037] Based on the acquired features, the fault prediction neural network model is provided for learning and training, and the parameters of the fault prediction neural network model are adjusted to adjust the performance of the fault prediction neural network model, so as to obtain the trained fault prediction neural network model, and the trained fault prediction neural network model is used as the prediction model; The prediction model is deployed and integrated into the cloud server system to predict the status of the wind turbine in the future and generate fault descriptions.

[0038] It should be noted that the fault prediction neural network model can also be replaced by a recurrent neural network (RNN) according to the actual application scenario. It is suitable for time series data, can capture long-term dependencies, and predict the future state of the wind turbine.

[0039] The intelligent classification module includes a pre-trained classification model, which is used to match the maintenance knowledge in the maintenance database according to the equipment-side fault description; the interactive end is connected to the cloud server through the network, and is used to display the 3D model generated by the cloud server, the parts of the 3D model that need to be repaired, and the corresponding maintenance knowledge. The interactive end includes a VR device or an AR device.

[0040] It should be noted that the construction of the maintenance database includes: Construct a maintenance database structure, which includes fault description, fault type, maintenance plan and historical cases; among them, the fault description is a detailed description of the fault, the fault type indicates the category of the fault, such as electrical fault, mechanical fault, the maintenance plan is the detailed maintenance steps and suggestions for the fault, and the historical case is the processing record and experience summary of similar faults in the past.

[0041] Data preprocessing of the maintenance database uses the pre-trained BERT model to segment the text into words or phrases and convert the text into vectors.

[0042] Preprocess the data of the maintenance database, such as removing irrelevant characters, punctuation marks, stop words, etc., by segmenting the text into words or phrases and then converting the text into a numerical vector. In this embodiment, the pre-trained BERT model is used to process the text. Optionally, the text can also be processed by TF-IDF or Word2Vec, which is used as a basis for subsequent calculations or correlation matching.

[0043] The classification model matches the maintenance knowledge in the maintenance database according to the maintenance category required by the equipment end, including: Obtain the fault description generated by the prediction model, and calculate the similarity between the fault description generated by the prediction model and the fault description in the maintenance database based on the classification model; Specifically, the fault description generated by the prediction model is converted into a vector through the pre-trained BERT model and matched with the fault description in the maintenance database. Optionally, the similarity between the input fault description and the fault description in the knowledge base is calculated using methods such as cosine similarity and Euclidean distance to obtain a similarity ranking; in this embodiment, cosine similarity is used for similarity calculation.

[0044] It should be noted that cosine similarity is widely used in information retrieval, text mining, recommendation systems and other fields to measure the similarity between documents or projects. For example, in text analysis, documents can be converted into word frequency vectors, and then cosine similarity can be used to compare the similarity between different documents. In recommendation systems, similar projects can be recommended to users by calculating the cosine similarity between the user's rating vectors for the projects.

[0045] Furthermore, the top K similarity fault descriptions are taken as matching results, and the maintenance solutions and historical cases corresponding to the fault descriptions are returned to the interaction end.

[0046] According to the matching results, the fault description in the maintenance database and the corresponding maintenance plan and historical cases are returned to the interactive end, so that the most relevant maintenance plan and historical cases are given to the interactive end based on the fault description and the matching results for reference by users using the interactive end.

[0047] The interactive end establishes communication with the cloud server, and the interactive end can display the 3D model constructed by the cloud server, the parts of the 3D model that need to be repaired, and the maintenance plan and historical cases obtained by the classification model, and can interact with the 3D model.

[0048] It should be noted that, in this embodiment, the interactive end includes a VR device or an AR device, and the VR device and the AR device and their related devices, such as the handle, can interact with the cloud server. Specifically, taking the VR device as an example, a VR device with a network connection function is selected, and the VR device is connected to the cloud server through the VR device, so that the VR device can display a real-time rendered 3D model. At the same time, according to the maintenance status of the device end, the most similar maintenance suggestions can be given and displayed on the VR device or AR device, so that the user can immerse in maintenance and avoid the disadvantages of traditional computer review of materials.

[0049] It should be noted that the rendered wind turbine status image is displayed through the Web interface. The user interface adopts a responsive design and is also compatible with a variety of terminal devices (such as PC, tablet, mobile phone, etc.), providing a good user experience. Users can view the operating status of the wind turbine in real time through the browser of the interactive end and perform interactive operations such as rotation, zooming and moving. The interactive function is implemented using JavaScript and WebGL technology, and users can observe the operating status of the wind turbine in detail from different angles and views. The user interface also integrates a variety of auxiliary functions, such as historical data query, data analysis and alarm prompts. The historical data query function allows users to view the wind turbine operating data for a specific time period; the data analysis function provides a variety of charts and statistical data to help users conduct in-depth analysis; the alarm prompt function monitors the operating status of the wind turbine in real time and issues an alarm in time when abnormal conditions are found.

[0050] The embodiment of the present invention also provides a method for displaying device status based on WebGL rendering, such as Figure 3 As shown, Figure 3 : is a flowchart of a method for displaying device status based on WebGL rendering in the present invention, the method comprising: S11, obtaining various parameter data of the device end; S12, sending the parameter data to the cloud server, and generating a 3D model by real-time rendering according to the parameter data; S13, predicting the state of the device at a future time through a pre-trained prediction model and generating a fault description, matching the fault description with the fault description in the maintenance database through a pre-trained classification model, and obtaining a corresponding maintenance plan and historical cases; S14. Use the interactive terminal to display the 3D model, maintenance status, corresponding maintenance plan and historical cases of the equipment.

[0051] The present invention uses WebGL technology to display the operating status of the device side in real time, and provides intuitive, dynamic and interactive status display images. By collecting the operating data of the device side in real time and preprocessing the blocks, the data transmission module ensures the real-time and reliability of the data, and realizes efficient 3D rendering through WebGL technology. Predictive maintenance is performed by using AI technology, that is, predicting when the device side may fail or abnormal state through historical data, so as to perform timely maintenance. In addition, by configuring the classification model, the fault description and the corresponding maintenance plan and historical cases in the maintenance database can be returned to the interactive end according to the matching results, so as to provide the most relevant maintenance plan and historical cases to the interactive end for reference by users using the interactive end based on the fault description and matching results. VR devices or AR devices can be used to access real-time 3D models and display corresponding maintenance plans and historical cases for immersive maintenance by maintenance personnel.

[0052] Figure 4 A structural block diagram of an electronic device provided by an embodiment of the present invention, such as Figure 4 As shown, the electronic device may include: a processor 610, a communication interface 620, a memory 630 and a communication bus 640, wherein the processor 610, the communication interface 620 and the memory 630 communicate with each other through the communication bus 640. The processor 610 may call the logic instructions in the memory 630 to execute the following method: Get various parameter data of the device; Send the parameter data to the cloud server, and generate a 3D model in real time based on the parameter data; Predict the future state of the equipment end through the pre-trained prediction model and generate a fault description. Match the fault description with the fault description in the maintenance database through the pre-trained classification model to obtain the corresponding maintenance plan and historical cases. Use the interactive terminal to display the 3D model, maintenance status, corresponding maintenance plan and historical cases of the equipment.

[0053] In addition, the logic instructions in the above-mentioned memory 630 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0054] An embodiment of the present invention further provides a non-transitory computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the method provided in each of the above embodiments is implemented, for example, including: Get various parameter data of the device; Send the parameter data to the cloud server, and generate a 3D model in real time based on the parameter data; Predict the future state of the equipment end through the pre-trained prediction model and generate a fault description. Match the fault description with the fault description in the maintenance database through the pre-trained classification model to obtain the corresponding maintenance plan and historical cases. Use the interactive terminal to display the 3D model, maintenance status, corresponding maintenance plan and historical cases of the equipment.

[0055] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods of each embodiment or some parts of the embodiment.

[0056] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A device status display system based on WebGL rendering, characterized in that: The device status display system based on WebGL rendering includes a device end, a cloud server and an interactive end, wherein the device end is configured with a data acquisition module and a data transmission module, the data acquisition module is used to obtain various parameter data of the device end, and the data transmission module is used to transmit various parameter data to the cloud server; The cloud server is configured with a WebGL rendering module, an intelligent prediction module, an intelligent classification module and a maintenance database. The WebGL rendering module is used to generate a 3D model in real time according to various parameter data, and map the various parameter data to the 3D model; the intelligent prediction module includes a pre-trained prediction model, and the prediction model is used to predict the state and fault description of the device end in the future. The intelligent classification module includes a pre-trained classification model, and the classification model is used to match the maintenance knowledge in the maintenance database according to the device end fault description; the interactive end is connected to the cloud server through a network, and is used to display the 3D model generated by the cloud server, the part of the 3D model that needs to be repaired, and the corresponding maintenance knowledge. The interactive end includes a VR device or an AR device.

2. The device status display system based on WebGL rendering according to claim 1, characterized in that: The device side is also configured with a data processing module and a local database. The data processing module is used to process various parameter data of the device side, including data filtering, data calibration and format conversion. The local database is used to store the processed parameter data.

3. The device status display system based on WebGL rendering according to claim 2 is characterized in that: The WebGL rendering module includes a 3D rendering engine and a data mapping unit. The 3D rendering engine is used to render according to the preprocessed data to generate a 3D model. The data mapping unit is used to map the preprocessed data to the 3D model to generate a device-side 3D model for real-time display.

4. The device status display system based on WebGL rendering according to claim 1, characterized in that: The intelligent prediction module includes a pre-trained prediction model, and the construction of the prediction model includes: Acquire historical operation data of the equipment end, wherein the historical operation data includes working data, fault data and maintenance data; Preprocessing the historical operation data; Use correlation analysis, principal component analysis, and recursive feature elimination to obtain the features that most affect the occurrence of faults; Based on the acquired features, the fault prediction neural network model is provided for learning and training, and the parameters of the fault prediction neural network model are adjusted to adjust the performance of the fault prediction neural network model, so as to obtain the trained fault prediction neural network model, and the trained fault prediction neural network model is used as the prediction model; The prediction model is deployed and integrated into the system of the cloud server to predict the status of the wind turbine in the future and generate a fault description.

5. The device status display system based on WebGL rendering according to claim 4, characterized in that: The maintenance database construction includes: Construct the maintenance database structure, which includes fault description, fault type, maintenance plan and historical cases; The data of the maintenance database is preprocessed by using a pre-trained BERT model to segment the text into words or phrases and convert the text into vectors.

6. The device status display system based on WebGL rendering according to claim 5, characterized in that: The classification model matches the maintenance knowledge in the maintenance database according to the maintenance category required by the equipment end, including: Obtain the fault description generated by the prediction model, and calculate the similarity between the fault description generated by the prediction model and the fault description in the maintenance database based on the classification model; The top K similarity fault descriptions are taken as matching results, and the maintenance plans and historical cases corresponding to the fault descriptions are returned to the interaction end.

7. The device status display system based on WebGL rendering according to claim 6, characterized in that: The interactive end establishes communication with the cloud server, and the interactive end can display the 3D model constructed by the cloud server, the parts of the 3D model that need to be repaired, and the maintenance plans and historical cases obtained by the classification model, and can interact with the 3D model.

8. A device status display method based on WebGL rendering, characterized in that: include: Get various parameter data of the device; Send the parameter data to the cloud server, and generate a 3D model in real time based on the parameter data; Predict the future state of the equipment end through the pre-trained prediction model and generate a fault description. Match the fault description with the fault description in the maintenance database through the pre-trained classification model to obtain the corresponding maintenance plan and historical cases. Use the interactive terminal to display the 3D model, maintenance status, corresponding maintenance plan and historical cases of the equipment.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the device status display method based on WebGL rendering as described in claim 8 is implemented.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the device status display method based on WebGL rendering as claimed in claim 8 are implemented.

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