Intelligent LED screen practical training simulation and fault diagnosis system and method

Abstract

The invention discloses an intelligent LED screen practical training simulation and fault diagnosis system and method. The system comprises a practical training scene configuration module, an LED control simulation module, a fault generation and diagnosis module, a data acquisition and analysis module, an interaction and feedback module, a plurality of cooperative control modules and a safety monitoring module. Multiple splicing modes such as single lamp panel, regular splicing and special-shaped combination are achieved through the practical training scene configuration module, free combination configuration of the control module is achieved, the limitation of traditional practical training scene solidification is broken through, and practical training requirements of different levels and different types are met; based on a diagnosis mechanism of fault feature similarity calculation, various fault types and superposed faults can be accurately simulated, rapid identification and root positioning of the faults are realized, scientific fault checking training is provided for practical trainees, and the fault diagnosis capability is improved.

Description

Technical Field

[0001] This invention relates to the field of LED practical training and fault diagnosis technology, specifically to an intelligent LED screen practical training simulation and fault diagnosis system and method. Background Technology

[0002] With the widespread application of LED display technology in various scenarios, the market demand for professionals with skills in LED screen installation, debugging, operation control, and fault diagnosis is increasing. Currently, LED training equipment generally suffers from the following technical bottlenecks: training scenarios are fixed, relying heavily on physical hardware splicing, making it difficult to simulate diverse screen shapes and control combinations; fault training lacks systematicity, only simulating a few fixed fault types and failing to achieve accurate fault feature extraction and intelligent diagnosis; the training process lacks data-driven evaluation, making it difficult to quantify student operational accuracy and fault-finding efficiency; the ability to conduct collaborative training with multiple devices is insufficient, unable to simulate large-scale LED screen splicing application scenarios; and safety protection mechanisms are simplistic, lacking comprehensive monitoring of electrical safety and equipment operating status during training. Summary of the Invention

[0003] The purpose of this invention is to provide an intelligent LED screen training simulation and fault diagnosis system and method to solve the problems existing in the prior art.

[0004] To achieve the above objectives, the present invention provides the following technical solution: an intelligent LED screen training simulation and fault diagnosis system, comprising a training scenario configuration module, an LED control simulation module, a fault generation and diagnosis module, a data acquisition and analysis module, an interaction and feedback module, a multi-unit collaborative control module, and a safety monitoring module; The training scenario configuration module is used to configure the LED screen splicing mode, control module combination method and training task type; The LED control simulation module is used to simulate the collaborative workflow of the LED display receiver card, transmitter card, video controller and video splicer, and to restore the signal transmission and processing logic of the real LED control system. The fault generation and diagnosis module is used to generate preset fault scenarios and perform fault diagnosis based on feature analysis. The data acquisition and analysis module is used to collect electrical parameters, operating data and status information during the training process and to analyze and process them. The interaction and feedback module is used to provide a human-computer interaction interface and output training feedback information; The multi-unit collaborative control module is used to realize the splicing, collaboration and synchronous control of multiple training devices to simulate the application scenario of a large LED screen. The safety monitoring module is used to monitor electrical safety and equipment operating status during the training process.

[0005] Furthermore, the training scenario configuration module includes a splicing mode configuration unit, a control combination configuration unit, and a task type configuration unit; Splicing mode configuration unit: Supports configuration of single light board training, multi-light board regular splicing training and irregular light board combination splicing training, and can set the number of light boards, splicing angle, arrangement method and target screen size parameters; Control combination configuration unit: Supports free combination and configuration of receiving card, transmitting card, video controller and video splicer, and can select different signal transmission paths and connection topologies; Task type configuration unit: Supports the selection and parameter configuration of basic operation training, fault diagnosis training and multi-unit collaborative training tasks, and can set the training duration, assessment standards and feedback methods; basic operation training includes light board installation, control module combination and signal debugging, and fault diagnosis training includes preset fault troubleshooting and custom fault analysis.

[0006] Furthermore, the LED control simulation module includes a control module simulation unit, a signal transmission simulation unit, and a display effect simulation unit; The control module simulation unit simulates the signal receiving, parsing and forwarding functions of the receiving card, the signal encoding, format conversion and output functions of the sending card, the image cropping, scaling and color correction functions of the video controller, and the multi-image fusion and splicing edge processing functions of the video splicer. Signal transmission simulation unit: Simulates the attenuation characteristics, transmission delay, and anti-interference performance of two signal transmission paths: wired transmission and control port transmission, and reproduces the signal transmission effect under different transmission methods; Display effect simulation unit: Based on the configured splicing mode, control parameters and signal type, it simulates the display of the LED screen in real time, including the display effects of text, images and videos, and supports parameter adjustment and effect preview of brightness, contrast and saturation.

[0007] Furthermore, the fault generation and diagnosis module includes a fault type storage unit, a fault triggering unit, a feature extraction unit, and a diagnostic analysis unit; Fault type storage unit: Stores preset fault types such as black screen, flickering screen, distorted screen, color distortion, signal interruption, and splicing misalignment. Each fault type corresponds to a set of standard fault characteristic parameters, which include electrical parameter thresholds, signal transmission characteristics, and display status characteristics. Fault Trigger Unit: Based on the training task configuration, it can activate the corresponding fault scenario through time triggering, operation triggering or manual triggering, and supports single fault triggering and multiple fault superposition triggering; Feature extraction unit: Real-time acquisition of electrical parameters, signal transmission data and display status data when a fault occurs, and filtering and feature parameter extraction of the data; electrical parameters include operating voltage, operating current and power, signal transmission data includes transmission rate, bit error rate and signal strength, and display status data includes pixel brightness rate, color deviation value and screen stability; Diagnostic Analysis Unit: By calculating fault feature similarity, the extracted fault feature parameters are compared with stored standard fault feature parameters to determine the fault type and root cause, and a fault diagnosis report and troubleshooting suggestions are generated. The fault feature similarity calculation formula used by the diagnostic analysis unit is as follows: in, For fault feature similarity, For the extracted first One fault characteristic parameter, For storage of the first A standard fault characteristic parameter, For the first The weights of each feature parameter, with values ​​ranging from 0 to 1. ≤1, and , This represents the total number of fault characteristic parameters. The range of values ​​for is 0≤ ≤1, The closer to 0, the higher the fault matching degree. The closer to 1, the lower the fault matching degree.

[0008] Furthermore, the data acquisition and analysis module includes a parameter acquisition unit, a data preprocessing unit, and a data evaluation unit; Parameter acquisition unit: Real-time acquisition of training-related parameters such as operating voltage, operating current, signal transmission rate, bit error rate, lamp board splicing position deviation, and operation response time of the LED control simulation module; Data preprocessing unit: The mean filtering algorithm is used to denoise the collected raw data, remove random interference signals, and normalize the parameters of different dimensions to the same data range to ensure the comparability of the data. Data Evaluation Unit: Calculates the accuracy of the light board splicing training using a splicing accuracy evaluation formula, evaluates the standardization of the control module combination and signal debugging operations through operational compliance analysis, and generates a quantitative evaluation report of the training operation; the splicing accuracy evaluation formula used by the data evaluation unit is: in, For splicing accuracy, For the first Block light panel The actual splicing point coordinate, For the first Block light panel The actual splicing point coordinate, For the first Block light panel The theory of splicing points coordinate, For the first Block light panel The theory of splicing points coordinate, The number of light panels involved in the splicing. This refers to the number of splicing points for each light panel. This refers to the standard spacing between splicing points; The range of values ​​for is 0≤ ≤1, The closer the value is to 1, the higher the splicing accuracy. The closer to 0, the lower the splicing accuracy.

[0009] Furthermore, the multiple collaborative control modules include a device communication unit, a synchronization control unit, and a splicing expansion unit; Equipment communication unit: Based on the Ethernet communication protocol, it realizes signal interaction and data transmission between multiple training devices, and supports device identification, encrypted data transmission and communication status monitoring; Synchronization control unit: Real-time monitoring of the command response time difference of multiple devices through synchronization error calculation formula, dynamically adjusting the timing of control command output of each device to ensure the synchronization of collaborative work of multiple devices; Splicing expansion unit: Supports physical and logical splicing configuration of multiple training devices, and can combine the display areas of multiple training devices into a large integrated display interface, supporting custom combination shape and display partition settings.

[0010] Furthermore, the safety monitoring module includes an electricity parameter monitoring unit, an abnormal alarm unit, and an emergency handling unit; Power consumption parameter monitoring unit: Real-time monitoring of power supply voltage, power supply current, power and leakage current of training equipment, and setting safety threshold range; Abnormal alarm unit: When the power consumption parameters exceed the safety threshold, the equipment operating status is abnormal, or a violation occurs, it will immediately issue an audible and visual alarm signal and display abnormal prompt information on the interactive interface; Emergency response unit: In the event of a serious safety anomaly, it automatically cuts off the power supply to the training equipment and records the equipment status data at the time of the anomaly.

[0011] Furthermore, the formula for calculating the multi-unit collaborative synchronization error used in the synchronization control unit is as follows: in, For synchronization error, For the first Command response time of the training equipment. The preset baseline response time, The number of training devices participating in the collaboration; ≥0, A smaller value indicates better synchronization among multiple devices. The larger the value, the worse the synchronization.

[0012] A diagnostic method for an intelligent LED screen training simulation and fault diagnosis system includes the following steps: Step 1: System Initialization and Scene Configuration Start the intelligent LED screen training simulation and fault diagnosis system. Each module completes self-testing and initialization, and establishes data communication links between modules. Users input training requirements through the interaction and feedback module. The training scenario configuration module completes the configuration of splicing mode, control combination method and training task type according to the input instructions, generates training scenario parameter file and synchronizes it to each relevant module. Step 2: LED control simulation operation The LED control simulation module receives the training scenario parameter file. The control module simulation unit starts the simulation workflow of the receiving card, sending card, video controller and video splicer. The signal transmission simulation unit simulates the signal transmission process according to the configured transmission path. The display effect simulation unit outputs the corresponding LED screen display effect in real time, forming a basic training operation environment. Step 3: Fault Generation and Triggering If the training task is fault diagnosis training, the fault generation and diagnosis module activates the fault scenario at the preset node according to the configured fault type, triggering method and triggering time; after the fault is triggered, the LED control simulation module synchronously simulates the signal transmission, control module operation and display effect under the fault state to realize the realistic reproduction of the fault scenario; Step 4: Data Acquisition and Feature Extraction The parameter acquisition unit of the data acquisition and analysis module collects electrical parameters, signal transmission data, operation data and equipment status data in real time during the training process, and transmits them to the data preprocessing unit for noise reduction and normalization. If it is in a fault scenario, the feature extraction unit of the fault generation and diagnosis module extracts fault feature parameters in real time to form a fault feature dataset. Step 5: Fault Diagnosis and Practical Training Evaluation The diagnostic analysis unit of the fault generation and diagnosis module calls the fault feature similarity calculation formula, compares the fault feature dataset with the standard fault feature parameters, determines the fault type, fault root cause and troubleshooting priority, and generates a fault diagnosis report; the data evaluation unit of the data acquisition and analysis module calls the splicing accuracy evaluation formula, combines the operation compliance analysis results, and generates a quantitative evaluation report of the training operation. Both types of reports are transmitted to the interaction and feedback module. Step 6: Multi-device collaborative training If the training task involves multi-device collaborative training, the device communication unit of the multi-device collaborative control module establishes a communication connection between the multiple training devices. The synchronization control unit calls the multi-device collaborative synchronization error calculation formula to dynamically adjust the command response time of each device to ensure synchronization. The splicing expansion unit combines the display areas of multiple devices into a preset large display interface to simulate the control and display effects of a large LED screen. Step 7: Training Feedback and System Reset The interaction and feedback module displays fault diagnosis reports, training evaluation reports, and equipment operating status information in text and chart formats, providing troubleshooting guidance and operation optimization suggestions. After the user completes the training operation, the system outputs a training completion signal, each module resets to its initial state, and stores the training data for subsequent statistical analysis.

[0013] Compared with the prior art, the beneficial effects of the present invention are: This invention enables various splicing modes, such as single LED panels, regular splicing, and irregular combinations, through a training scenario configuration module, and allows for free combination and configuration of control modules. This breaks the limitations of traditional, rigid training scenarios and adapts to different levels and types of training needs. Based on a fault feature similarity calculation diagnostic mechanism, it can accurately simulate various fault types and superimposed faults, enabling rapid fault identification and root cause location, providing trainees with scientific fault diagnosis training and improving their fault diagnosis capabilities. Through quantitative indicators such as splicing accuracy evaluation and operational compliance analysis, it achieves full data collection and objective evaluation of the training process, avoiding the subjectivity of traditional training evaluations and helping trainees accurately identify operational shortcomings. It supports physical and logical splicing of multiple devices, and combined with a synchronization error control algorithm, it can simulate application scenarios of large LED screens, expanding the application scope of training and improving trainees' collaborative operation capabilities. It constructs a three-level safety protection mechanism for power parameter monitoring, abnormal alarms, and emergency handling, monitoring safety risks in the training process in real time, automatically responding to abnormal situations, and ensuring the personal safety of trainees and the stable operation of equipment. Attached Figure Description

[0014] Figure 1 This is a system module diagram of the present invention; Figure 2 This is a schematic diagram of the training scenario configuration module of the present invention; Figure 3 This is a schematic diagram of the LED control simulation module of the present invention; Figure 4 This is a schematic diagram of the fault generation and diagnosis module of the present invention; Figure 5 This is a flowchart of the method of the present invention. Detailed Implementation

[0015] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0016] Please see Figure 1-5 The present invention provides an intelligent LED screen training simulation and fault diagnosis system, including a training scenario configuration module, an LED control simulation module, a fault generation and diagnosis module, a data acquisition and analysis module, an interaction and feedback module, a multi-unit collaborative control module, and a safety monitoring module. The training scenario configuration module is used to configure the LED screen splicing mode, control module combination method and training task type; The LED control simulation module is used to simulate the collaborative workflow of LED display receiver card, transmitter card, video controller and video splicer, and to restore the signal transmission and processing logic of real LED control system. The fault generation and diagnosis module is used to generate preset fault scenarios and perform fault diagnosis based on feature analysis; The data acquisition and analysis module is used to collect electrical parameters, operating data and status information during the training process and to analyze and process them. The interaction and feedback module is used to provide a human-computer interaction interface and output training feedback information; Multiple collaborative control modules are used to realize the splicing, collaboration and synchronous control of multiple training devices to simulate the application scenario of a large LED screen. The safety monitoring module is used to monitor electrical safety and equipment operating status during the training process.

[0017] The training scenario configuration module includes a splicing mode configuration unit, a control combination configuration unit, and a task type configuration unit; Splicing mode configuration unit: Supports configuration of single light board training, multi-light board regular splicing training and irregular light board combination splicing training, and can set the number of light boards, splicing angle, arrangement method and target screen size parameters; Control combination configuration unit: Supports free combination and configuration of receiving card, transmitting card, video controller and video splicer, and can select different signal transmission paths and connection topologies; Task type configuration unit: Supports the selection and parameter configuration of basic operation training, fault diagnosis training and multi-unit collaborative training tasks, and can set the training duration, assessment standards and feedback methods; basic operation training includes light board installation, control module combination and signal debugging, and fault diagnosis training includes preset fault troubleshooting and custom fault analysis.

[0018] The LED control simulation module includes a control module simulation unit, a signal transmission simulation unit, and a display effect simulation unit. The control module simulation unit simulates the signal receiving, parsing and forwarding functions of the receiving card, the signal encoding, format conversion and output functions of the sending card, the image cropping, scaling and color correction functions of the video controller, and the multi-image fusion and splicing edge processing functions of the video splicer. Signal transmission simulation unit: Simulates the attenuation characteristics, transmission delay, and anti-interference performance of two signal transmission paths: wired transmission and control port transmission, and reproduces the signal transmission effect under different transmission methods; Display effect simulation unit: Based on the configured splicing mode, control parameters and signal type, it simulates the display of the LED screen in real time, including the display effects of text, images and videos, and supports parameter adjustment and effect preview of brightness, contrast and saturation.

[0019] The fault generation and diagnosis module includes a fault type storage unit, a fault triggering unit, a feature extraction unit, and a diagnostic analysis unit; Fault type storage unit: Stores preset fault types such as black screen, flickering screen, distorted screen, color distortion, signal interruption, and splicing misalignment. Each fault type corresponds to a set of standard fault characteristic parameters, which include electrical parameter thresholds, signal transmission characteristics, and display status characteristics. Fault Trigger Unit: Based on the training task configuration, it can activate the corresponding fault scenario through time triggering, operation triggering or manual triggering, and supports single fault triggering and multiple fault superposition triggering; Feature extraction unit: Real-time acquisition of electrical parameters, signal transmission data and display status data when a fault occurs, and filtering and feature parameter extraction of the data; electrical parameters include operating voltage, operating current and power, signal transmission data includes transmission rate, bit error rate and signal strength, and display status data includes pixel brightness rate, color deviation value and screen stability; Diagnostic Analysis Unit: By calculating fault feature similarity, the extracted fault feature parameters are compared with stored standard fault feature parameters to determine the fault type and root cause, and a fault diagnosis report and troubleshooting suggestions are generated. The fault feature similarity calculation formula used by the diagnostic analysis unit is as follows: in, For fault feature similarity, For the extracted first One fault characteristic parameter, For storage of the first A standard fault characteristic parameter, For the first The weights of each feature parameter, with values ​​ranging from 0 to 1. ≤1, and , This represents the total number of fault characteristic parameters. The range of values ​​for is 0≤ ≤1, The closer to 0, the higher the fault matching degree. The closer to 1, the lower the fault matching degree.

[0020] The data acquisition and analysis module includes a parameter acquisition unit, a data preprocessing unit, and a data evaluation unit; Parameter acquisition unit: Real-time acquisition of training-related parameters such as operating voltage, operating current, signal transmission rate, bit error rate, lamp board splicing position deviation, and operation response time of the LED control simulation module; Data preprocessing unit: The mean filtering algorithm is used to denoise the collected raw data, remove random interference signals, and normalize the parameters of different dimensions to the same data range to ensure the comparability of the data. Data Evaluation Unit: Calculates the accuracy of the light board splicing training using a splicing accuracy evaluation formula, evaluates the standardization of the control module combination and signal debugging operations through operational compliance analysis, and generates a quantitative evaluation report of the training operation; the splicing accuracy evaluation formula used by the data evaluation unit is: in, For splicing accuracy, For the first Block light panel The actual splicing point coordinate, For the first Block light panel The actual splicing point coordinate, For the first Block light panel The theory of splicing points coordinate, For the first Block light panel The theory of splicing points coordinate, The number of light panels involved in the splicing. This refers to the number of splicing points for each light panel. This refers to the standard spacing between splicing points; The range of values ​​for is 0≤ ≤1, The closer the value is to 1, the higher the splicing accuracy. The closer to 0, the lower the splicing accuracy.

[0021] The multi-unit collaborative control module includes a device communication unit, a synchronization control unit, and a splicing expansion unit; Equipment communication unit: Based on the Ethernet communication protocol, it realizes signal interaction and data transmission between multiple training devices, and supports device identification, encrypted data transmission and communication status monitoring; Synchronization control unit: Real-time monitoring of the command response time difference of multiple devices through synchronization error calculation formula, dynamically adjusting the timing of control command output of each device to ensure the synchronization of collaborative work of multiple devices; Splicing expansion unit: Supports physical and logical splicing configuration of multiple training devices, and can combine the display areas of multiple training devices into a large integrated display interface, supporting custom combination shape and display partition settings.

[0022] The safety monitoring module includes an electricity parameter monitoring unit, an abnormal alarm unit, and an emergency response unit; Power consumption parameter monitoring unit: Real-time monitoring of power supply voltage, power supply current, power and leakage current of training equipment, and setting safety threshold range; Abnormal alarm unit: When the power consumption parameters exceed the safety threshold, the equipment operating status is abnormal, or a violation occurs, it will immediately issue an audible and visual alarm signal and display abnormal prompt information on the interactive interface; Emergency response unit: In the event of a serious safety anomaly, it automatically cuts off the power supply to the training equipment and records the equipment status data at the time of the anomaly.

[0023] The formula for calculating the synchronization error of multiple units used in the synchronization control unit is as follows: in, For synchronization error, For the first Command response time of the training equipment. The preset baseline response time, The number of training devices participating in the collaboration; ≥0, A smaller value indicates better synchronization among multiple devices. The larger the value, the worse the synchronization.

[0024] A diagnostic method for an intelligent LED screen training simulation and fault diagnosis system includes the following steps: Step 1: System Initialization and Scene Configuration Start the intelligent LED screen training simulation and fault diagnosis system. Each module completes self-testing and initialization, and establishes data communication links between modules. Users input training requirements through the interaction and feedback module. The training scenario configuration module completes the configuration of splicing mode, control combination method and training task type according to the input instructions, generates training scenario parameter file and synchronizes it to each relevant module. Step 2: LED control simulation operation The LED control simulation module receives the training scenario parameter file. The control module simulation unit starts the simulation workflow of the receiving card, sending card, video controller and video splicer. The signal transmission simulation unit simulates the signal transmission process according to the configured transmission path. The display effect simulation unit outputs the corresponding LED screen display effect in real time, forming a basic training operation environment. Step 3: Fault Generation and Triggering If the training task is fault diagnosis training, the fault generation and diagnosis module activates the fault scenario at the preset node according to the configured fault type, triggering method and triggering time; after the fault is triggered, the LED control simulation module synchronously simulates the signal transmission, control module operation and display effect under the fault state to realize the realistic reproduction of the fault scenario; Step 4: Data Acquisition and Feature Extraction The parameter acquisition unit of the data acquisition and analysis module collects electrical parameters, signal transmission data, operation data and equipment status data in real time during the training process, and transmits them to the data preprocessing unit for noise reduction and normalization. If it is in a fault scenario, the feature extraction unit of the fault generation and diagnosis module extracts fault feature parameters in real time to form a fault feature dataset. Step 5: Fault Diagnosis and Practical Training Evaluation The diagnostic analysis unit of the fault generation and diagnosis module calls the fault feature similarity calculation formula, compares the fault feature dataset with the standard fault feature parameters, determines the fault type, fault root cause and troubleshooting priority, and generates a fault diagnosis report; the data evaluation unit of the data acquisition and analysis module calls the splicing accuracy evaluation formula, combines the operation compliance analysis results, and generates a quantitative evaluation report of the training operation. Both types of reports are transmitted to the interaction and feedback module. Step 6: Multi-device collaborative training If the training task involves multi-device collaborative training, the device communication unit of the multi-device collaborative control module establishes a communication connection between the multiple training devices. The synchronization control unit calls the multi-device collaborative synchronization error calculation formula to dynamically adjust the command response time of each device to ensure synchronization. The splicing expansion unit combines the display areas of multiple devices into a preset large display interface to simulate the control and display effects of a large LED screen. Step 7: Training Feedback and System Reset The interaction and feedback module displays fault diagnosis reports, training evaluation reports, and equipment operating status information in text and chart formats, providing troubleshooting guidance and operation optimization suggestions. After the user completes the training operation, the system outputs a training completion signal, each module resets to its initial state, and stores the training data for subsequent statistical analysis.

[0025] Example 1: Basic Operation and Assembly Training Scenario In vocational school LED training classes, students are required to complete practical training on LED screen regular splicing and basic control module combination: Hardware configuration: Training platform: It features a detachable desktop and a magnetic LED light panel mounting structure, and has a built-in 5V safety power supply, signal transmission interface and safety monitoring module hardware; Communication module: It adopts a gigabit Ethernet module to support high-speed data transmission between industrial panel PCs and training platforms, as well as multiple training devices.

[0026] Implementation process: Step 1: After system startup, the industrial tablet PC runs the intelligent LED screen training simulation and fault diagnosis system. Each module completes self-checks, and the training scenario configuration module enters standby mode. Students select "Basic Operation Training" via the touchscreen, configure the splicing mode as "4 LED boards 2×2 regular splicing", the control combination as "1 sending card, 2 receiving cards and 1 video controller", select "control network port transmission" for the transmission path, and set the training duration to 45 minutes.

[0027] Step 2: The training scenario parameter file is synchronized to the LED control simulation module. The control module simulation unit starts the signal encoding function of the sending card, the signal parsing function of the receiving card, and the image processing function of the video controller. The signal transmission simulation unit simulates the signal transmission process of the control network port. The display effect simulation unit outputs the basic display image after splicing 4 light boards on the industrial tablet computer screen.

[0028] Step 3: Following the training instructions, students install four LED light boards using the magnetic suction device on the training platform, connect the receiving card and the transmitting card via network cable to complete the physical combination of the control module; operate the interactive interface of the industrial tablet PC, adjust the brightness parameters of the video controller to 80%, and the LED control simulation module updates the display effect synchronously.

[0029] Step 4: The parameter acquisition unit of the data acquisition and analysis module collects parameters such as the splicing position deviation of the light board, signal transmission rate, and working voltage in real time. The data preprocessing unit performs noise reduction processing on the position deviation data to remove random jitter interference during the operation.

[0030] Step 5: The data evaluation unit calls the splicing accuracy evaluation formula, substituting the actual coordinates and theoretical coordinates (standard spacing) of the four splicing points of each of the four light panels. =10cm), the splicing accuracy was calculated. =0.92, and at the same time analyze the compliance of the control module connection, such as the network cable connection sequence and interface matching degree, generate a training evaluation report, showing "the splicing accuracy is good, the control module connection is compliant, and it is recommended to optimize the horizontal deviation of the third light board".

[0031] Step 6: After the training, students review the evaluation report and adjust the installation position of the light panel according to the suggestions. The system stores the splicing parameters, operation records and evaluation results of this training, and resets each module to its initial state, waiting for the next training session to start.

[0032] Example 2: Fault Diagnosis Training Scenario In technical training institutions, trainees are required to complete practical training in diagnosing and troubleshooting common LED screen faults: Hardware configuration: Training platform: It has a front and rear maintenance structure, built-in power control box, ventilation structure and fault simulation hardware module, and supports magnetic receiving card installation and multiple types of fault triggering; Testing tools: Equipped with training and testing tools such as digital multimeters and network cable testers, which can interact with the system and upload test data in real time.

[0033] Implementation process: Step 1: After the system initialization is complete, the trainee selects "Fault Diagnosis Training" on the desktop computer, configures the fault type as "screen flickering and signal interruption superposition fault", the trigger method as "operation trigger", and incorrectly connects the receiving card network cable. The assessment standard is "complete fault location and troubleshooting within 30 minutes".

[0034] Step 2: The LED control simulation module starts the basic control process, and the display effect simulation unit outputs a normal display screen; after the student connects the receiving card network cable according to the incorrect operation procedure, the fault triggering unit activates and superimposes the fault scene, and the LED control simulation module synchronously simulates the fault phenomena of screen flickering and signal interruption.

[0035] Step 3: The parameter acquisition unit of the data acquisition and analysis module collects parameters such as operating current, signal transmission bit error rate, and pixel brightness rate in real time under fault conditions; the feature extraction unit of the fault generation and diagnosis module extracts fault feature parameters from the collected data to form a fault feature dataset containing 12 feature items.

[0036] Step 4: The diagnostic analysis unit calls the fault feature similarity calculation formula to compare the extracted fault feature dataset with the stored standard fault feature parameters for "screen flickering" and "signal interruption," and assigns weights to the feature parameters. Based on the degree of fault impact, a weighting of 0.3 is applied to the signal transmission bit error rate and 0.25 to the operating current fluctuation, thus calculating the similarity of the flickering fault. =0.12, signal interruption fault similarity =0.08, the fault type is determined to be a combination of screen flickering and signal interruption, and the root cause is "incorrect connection of the receiving card network cable, resulting in abnormal signal transmission and unstable power supply".

[0037] Step 5: The system displays a fault diagnosis report through the interactive interface, prompting "An abnormally high signal transmission bit error rate was detected, and the operating current fluctuation exceeded the normal range, suspected to be a network cable connection fault. Please check the network cable interface and connection sequence of the receiver card." The student used a network cable tester to check the network cable connection status and found that the network cable was connected in reverse. After reconnecting it correctly, the fault disappeared.

[0038] Step 6: The data acquisition and analysis module re-acquires the equipment operating parameters, confirms that all parameters have returned to normal, and the data evaluation unit generates a training evaluation report, displaying "accurate fault diagnosis, troubleshooting time 18 minutes, standardized operation, training qualified"; the system stores the fault diagnosis process data and student operation records for subsequent teaching review.

[0039] Example 3: Multi-device collaborative training scenario During internal company training, employees are required to complete a practical training task involving the coordinated assembly of six training devices to create a large LED screen. Hardware configuration: Training equipment: 6 identical intelligent LED screen training devices, each equipped with an independent control unit and display area; Collaborative Controller: Equipped with an industrial-grade collaborative control host, supporting Ethernet switch cascading to achieve centralized control and data synchronization of 6 devices; Display terminal: Equipped with 4K high-definition video source equipment, it can output video signals to the collaborative system to simulate the video display needs of a large LED screen.

[0040] Implementation process: Step 1: Establish communication connection between the 6 training devices and the collaborative control host. After system initialization, trainees are configured with "multi-device collaborative training", splicing mode is "3×2 large rectangular splicing", display requirement is "4K video split-screen display", and synchronization accuracy requirement is "synchronization error ≤5ms".

[0041] Step 2: The device communication unit of the multi-cooperative control module completes the identification and data encryption link establishment of the 6 devices; the splicing expansion unit logically combines the display areas of the 6 devices into a 3×2 large display interface, divides it into 6 display partitions, and assigns corresponding video display content.

[0042] Step 3: The LED control simulation module receives the coordinated control command, and each device synchronously starts the control process. The video source device outputs a 4K video signal; the synchronous control unit collects the command response time of the six devices in real time and compares it with... =12ms, =13ms =11ms, =14ms =12ms, =13ms, call the multi-station collaborative synchronization error calculation formula and substitute the reference response time. =12.5ms, the synchronization error is calculated. =1.02ms, which meets the synchronization accuracy requirements.

[0043] Step 4: Train employees to adjust the overall display parameters through the collaborative control host, with brightness at 75% and contrast at 60%. All training devices respond synchronously to the adjustment commands, and the display effect simulates the unit outputting a uniform 4K video display image without splicing misalignment or image delay. The safety monitoring module monitors the power consumption parameters of the 6 devices in real time to ensure stable power supply.

[0044] Step 5: During the training, the system simulates a signal transmission delay fault in one of the devices, increasing the response time to 25ms. The synchronization control unit detects a synchronization error. =5.8ms, exceeding the safety threshold, immediately issued a slight audible and visual alarm, and dynamically adjusted the response time of other devices to bring the synchronization error back under control at 4.2ms; trained employees to troubleshoot the signal transmission interface of the device, and after cleaning the interface dust, the device returned to normal synchronization.

[0045] Step 6: After the training is completed, the system generates a collaborative training report, which shows "Multiple devices are successfully spliced, synchronization accuracy meets the standard, emergency fault handling is timely, and the training task is completed"; each device is reset to standby state, and the collaborative control host stores the configuration parameters and operation data of this collaborative training.

[0046] Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A smart LED screen training simulation and fault diagnosis system, characterized in that: It includes a training scenario configuration module, an LED control simulation module, a fault generation and diagnosis module, a data acquisition and analysis module, an interaction and feedback module, a multi-unit collaborative control module, and a safety monitoring module; The training scenario configuration module is used to configure the LED screen splicing mode, control module combination method and training task type; The LED control simulation module is used to simulate the collaborative workflow of the LED display receiver card, transmitter card, video controller and video splicer, and to restore the signal transmission and processing logic of the real LED control system. The fault generation and diagnosis module is used to generate preset fault scenarios and perform fault diagnosis based on feature analysis. The data acquisition and analysis module is used to collect electrical parameters, operating data and status information during the training process and to analyze and process them. The interaction and feedback module is used to provide a human-computer interaction interface and output training feedback information; The multi-unit collaborative control module is used to realize the splicing, collaboration and synchronous control of multiple training devices to simulate the application scenario of a large LED screen. The safety monitoring module is used to monitor electrical safety and equipment operating status during the training process.

2. The intelligent LED screen training simulation and fault diagnosis system according to claim 1, characterized in that: The training scenario configuration module includes a splicing mode configuration unit, a control combination configuration unit, and a task type configuration unit. Splicing mode configuration unit: Supports configuration of single light board training, multi-light board regular splicing training and irregular light board combination splicing training, and can set the number of light boards, splicing angle, arrangement method and target screen size parameters; Control combination configuration unit: Supports free combination and configuration of receiving card, transmitting card, video controller and video splicer, and can select different signal transmission paths and connection topologies; Task type configuration unit: Supports the selection and parameter configuration of basic operation training, fault diagnosis training and multi-unit collaborative training tasks, and can set the training duration, assessment standards and feedback methods; basic operation training includes light board installation, control module combination and signal debugging, and fault diagnosis training includes preset fault troubleshooting and custom fault analysis.

3. The intelligent LED screen training simulation and fault diagnosis system according to claim 1, characterized in that: The LED control simulation module includes a control module simulation unit, a signal transmission simulation unit, and a display effect simulation unit. The control module simulation unit simulates the signal receiving, parsing and forwarding functions of the receiving card, the signal encoding, format conversion and output functions of the sending card, the image cropping, scaling and color correction functions of the video controller, and the multi-image fusion and splicing edge processing functions of the video splicer. Signal transmission simulation unit: Simulates the attenuation characteristics, transmission delay, and anti-interference performance of two signal transmission paths: wired transmission and control port transmission, and reproduces the signal transmission effect under different transmission methods; Display effect simulation unit: Based on the configured splicing mode, control parameters and signal type, it simulates the display of the LED screen in real time, including the display effects of text, images and videos, and supports parameter adjustment and effect preview of brightness, contrast and saturation.

4. The intelligent LED screen training simulation and fault diagnosis system according to claim 1, characterized in that: The fault generation and diagnosis module includes a fault type storage unit, a fault triggering unit, a feature extraction unit, and a diagnostic analysis unit. Fault type storage unit: Stores preset fault types such as black screen, flickering screen, distorted screen, color distortion, signal interruption, and splicing misalignment. Each fault type corresponds to a set of standard fault characteristic parameters, which include electrical parameter thresholds, signal transmission characteristics, and display status characteristics. Fault Trigger Unit: Based on the training task configuration, it can activate the corresponding fault scenario through time triggering, operation triggering or manual triggering, and supports single fault triggering and multiple fault superposition triggering; Feature extraction unit: Real-time acquisition of electrical parameters, signal transmission data and display status data when a fault occurs, and filtering and feature parameter extraction of the data; Electrical parameters include operating voltage, operating current and power; signal transmission data includes transmission rate, bit error rate and signal strength; display status data includes pixel brightness, color deviation value and image stability. Diagnostic Analysis Unit: By calculating fault feature similarity, the extracted fault feature parameters are compared with stored standard fault feature parameters to determine the fault type and root cause, and a fault diagnosis report and troubleshooting suggestions are generated. The fault feature similarity calculation formula used by the diagnostic analysis unit is as follows: in, For fault feature similarity, For the extracted first One fault characteristic parameter, For storage of the first A standard fault characteristic parameter, For the first The weights of each feature parameter, with values ​​ranging from 0 to 1. ≤1, and , This represents the total number of fault characteristic parameters. The range of values ​​for is 0≤ ≤1, The closer to 0, the higher the fault matching degree. The closer to 1, the lower the fault matching degree.

5. The intelligent LED screen training simulation and fault diagnosis system according to claim 1, characterized in that: The data acquisition and analysis module includes a parameter acquisition unit, a data preprocessing unit, and a data evaluation unit; Parameter acquisition unit: Real-time acquisition of training-related parameters such as operating voltage, operating current, signal transmission rate, bit error rate, lamp board splicing position deviation, and operation response time of the LED control simulation module; Data preprocessing unit: The mean filtering algorithm is used to denoise the collected raw data, remove random interference signals, and normalize the parameters of different dimensions to the same data range to ensure the comparability of the data. Data Evaluation Unit: Calculates the accuracy of the light board splicing training using a splicing accuracy evaluation formula, evaluates the standardization of the control module combination and signal debugging operations through operational compliance analysis, and generates a quantitative evaluation report of the training operation; the splicing accuracy evaluation formula used by the data evaluation unit is: in, For splicing accuracy, For the first Block light panel The actual splicing point coordinate, For the first Block light panel The actual splicing point coordinate, For the first Block light panel The theory of splicing points coordinate, For the first Block light panel The theory of splicing points coordinate, The number of light panels involved in the splicing. This refers to the number of splicing points for each light panel. This refers to the standard spacing between splicing points; The range of values ​​for is 0≤ ≤1, The closer the value is to 1, the higher the splicing accuracy. The closer to 0, the lower the splicing accuracy.

6. The intelligent LED screen training simulation and fault diagnosis system according to claim 1, characterized in that: The multiple collaborative control modules include a device communication unit, a synchronization control unit, and a splicing expansion unit; Equipment communication unit: Based on the Ethernet communication protocol, it realizes signal interaction and data transmission between multiple training devices, and supports device identification, encrypted data transmission and communication status monitoring; Synchronization control unit: Real-time monitoring of the command response time difference of multiple devices through synchronization error calculation formula, dynamically adjusting the timing of control command output of each device to ensure the synchronization of collaborative work of multiple devices; Splicing expansion unit: Supports physical and logical splicing configuration of multiple training devices, and can combine the display areas of multiple training devices into a large integrated display interface, supporting custom combination shape and display partition settings.

7. The intelligent LED screen training simulation and fault diagnosis system according to claim 1, characterized in that: The safety monitoring module includes an electricity parameter monitoring unit, an abnormal alarm unit, and an emergency handling unit. Power consumption parameter monitoring unit: Real-time monitoring of power supply voltage, power supply current, power and leakage current of training equipment, and setting safety threshold range; Abnormal alarm unit: When the power consumption parameters exceed the safety threshold, the equipment operating status is abnormal, or a violation occurs, it will immediately issue an audible and visual alarm signal and display abnormal prompt information on the interactive interface; Emergency response unit: In the event of a serious safety anomaly, it automatically cuts off the power supply to the training equipment and records the equipment status data at the time of the anomaly.

8. The intelligent LED screen training simulation and fault diagnosis system according to claim 6, characterized in that: The formula for calculating the multi-unit collaborative synchronization error used in the synchronization control unit is as follows: in, For synchronization error, For the first Command response time of the training equipment. The preset baseline response time, The number of training devices participating in the collaboration; ≥0, A smaller value indicates better synchronization among multiple devices. The larger the value, the worse the synchronization.

9. The diagnostic method of the intelligent LED screen training simulation and fault diagnosis system according to any one of claims 1-8, characterized in that: Includes the following steps: Step 1: System Initialization and Scene Configuration Start the intelligent LED screen training simulation and fault diagnosis system. Each module completes self-testing and initialization, and establishes data communication links between modules. Users input training requirements through the interaction and feedback module. The training scenario configuration module completes the configuration of splicing mode, control combination method and training task type according to the input instructions, generates training scenario parameter file and synchronizes it to each relevant module. Step 2: LED control simulation operation The LED control simulation module receives the training scenario parameter file. The control module simulation unit starts the simulation workflow of the receiving card, sending card, video controller and video splicer. The signal transmission simulation unit simulates the signal transmission process according to the configured transmission path. The display effect simulation unit outputs the corresponding LED screen display effect in real time, forming a basic training operation environment. Step 3: Fault Generation and Triggering If the training task is fault diagnosis training, the fault generation and diagnosis module activates the fault scenario at the preset node according to the configured fault type, triggering method and triggering time; after the fault is triggered, the LED control simulation module synchronously simulates the signal transmission, control module operation and display effect under the fault state to realize the realistic reproduction of the fault scenario; Step 4: Data Acquisition and Feature Extraction The parameter acquisition unit of the data acquisition and analysis module collects electrical parameters, signal transmission data, operation data and equipment status data in real time during the training process, and transmits them to the data preprocessing unit for noise reduction and normalization. If a fault scenario occurs, the feature extraction unit of the fault generation and diagnosis module simultaneously extracts fault feature parameters to form a fault feature dataset. Step 5: Fault Diagnosis and Practical Training Evaluation The diagnostic analysis unit of the fault generation and diagnosis module calls the fault feature similarity calculation formula, compares the fault feature dataset with the standard fault feature parameters, determines the fault type, fault root cause and troubleshooting priority, and generates a fault diagnosis report; the data evaluation unit of the data acquisition and analysis module calls the splicing accuracy evaluation formula, combines the operation compliance analysis results, and generates a quantitative evaluation report of the training operation. Both types of reports are transmitted to the interaction and feedback module. Step 6: Multi-device collaborative training If the training task involves multi-device collaborative training, the device communication unit of the multi-device collaborative control module establishes a communication connection between the multiple training devices. The synchronization control unit calls the multi-device collaborative synchronization error calculation formula to dynamically adjust the command response time of each device to ensure synchronization. The splicing expansion unit combines the display areas of multiple devices into a preset large display interface to simulate the control and display effects of a large LED screen. Step 7: Training Feedback and System Reset The interaction and feedback module displays fault diagnosis reports, training evaluation reports and equipment operating status information in the form of text and charts, and provides fault troubleshooting guidance and operation optimization suggestions. After the user completes the training operation, the system outputs a training completion signal, each module resets to its initial state, and the training data is stored for subsequent statistical analysis.

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