LED display screen control system capable of automatically matching display position

Abstract

The invention provides an LED display screen control system capable of automatically matching a display position, and belongs to the technical field of LED display screen control. Data processing and transmission of the system are comprehensively planned through a main control chip, an encrypted video signal is received and analyzed by using a video signal acquisition module, primary decryption is performed by using a signal encryption identification module, and the display position is automatically matched. Secondary encryption transmission is carried out through the network transmission module, decryption processing is carried out through the multipath receiving control module, and third encryption communication with the LED display module is realized through the display module control module. According to the system, the position information acquisition module is adopted to acquire the installation position information of the display module in real time, automatic matching and optimized display of display content are achieved through multivariate mixed decomposition calculation, self-adaptive display control and an intelligent exception handling mechanism, and the installation efficiency, the display quality and the operation stability of the system are effectively improved. The technical problems that traditional manual configuration is complex in operation and low in efficiency are solved.

Description

Technical Field

[0001] The invention relates to the field of LED display screen control, and in particular to an LED display screen control system capable of automatically matching display positions. Background Art

[0002] As a new display technology, LED display technology is widely used in outdoor large screens, indoor electronic display screens and other occasions due to its advantages of high brightness, low power consumption and long life. In these application scenarios, LED display systems usually need to transmit digital content such as videos and images from remote centers to display terminals to achieve large-screen display. However, since the display content involves important commercial or military information, it is necessary to ensure the security of data transmission to prevent the content from being illegally intercepted or tampered with. At the same time, due to the distributed installation characteristics of LED display modules, there is position uncertainty between each module, making the spatial matching and correction of video content a key factor in display quality. Therefore, how to achieve accurate alignment and high-quality display of video content while ensuring transmission security is a technical problem that the existing LED display system urgently needs to solve.

[0003] In the prior art, manual correction is generally used for processing: manually adjusting the installation position and angle of the LED module and manually configuring the interface sequence to achieve spatial matching of the video content. This method is complex to operate and inefficient. Summary of the invention

[0004] In view of this, the present invention provides an LED display screen control system that automatically matches the display position, solving the problems of complex operation and low efficiency in the traditional manual configuration method. The present invention provides an LED display screen control system that automatically matches the display position, including: a main control chip for coordinating data processing and transmission of the entire system; a video signal acquisition module, including HDMI, DP, DVI multi-channel input interfaces and a signal parsing unit, for receiving and parsing encrypted video signals; a signal encryption identification module, including a feature recognition unit and a decryption processing unit, electrically connected to the video signal acquisition module, for identifying and decrypting a primary encrypted video signal; a network transmission module, including multiple network port interfaces and optical fiber interfaces, electrically connected to the signal encryption identification module, for secondary encryption and transmission of the decrypted video signal; a multi-channel receiving control module, including a network receiving unit, a signal decryption unit and a data processing unit, electrically connected to the network transmission module, and a signal encryption recognition unit. The input module is connected via a network cable or optical fiber, and is used to receive and decrypt the secondary encrypted signal; the display module control module includes multiple flat cable interfaces and a spatial position analysis unit, which is electrically connected to the multi-channel receiving control module to realize three-way encrypted communication with the LED display module; the LED display module includes a signal input interface, a position information storage unit and a display drive unit, and is connected to the display module control module via a flat cable; the position information acquisition module includes a spatial coordinate acquisition unit and a data processing unit, which is electrically connected to the LED display module, and is used to collect the actual installation position information of each LED display module; the system configuration module includes a local configuration interface and a remote configuration interface, which is electrically connected to the main control chip and is used for system parameter configuration and encryption algorithm update.

[0005] Among them, the main control chip is provided with an embedded control software module for controlling and coordinating the work of each hardware module and ensuring the safe transmission and accurate display of display information.

[0006] The embedded control software module performs the following steps:

[0007] S10, collecting encrypted video signal data, real-time position data of the LED display module, system operation status data, data transmission quality parameters and encryption channel status data at all levels in real time through the video signal acquisition module, and preliminarily classifying and arranging the collected data to prepare for subsequent processing;

[0008] S20, performing multivariate mixed decomposition calculation on the collected encrypted video signal data, decomposing the video data into a brightness component and a chroma component, and performing stability analysis on the brightness component to obtain a brightness stable component and a brightness fluctuation component, and performing stability analysis on the chroma component to obtain a chroma stable component and a chroma fluctuation component, and storing all component data in a system buffer for standby use;

[0009] S30, performing multivariate mixed decomposition calculation on the real-time position data of the LED display module, respectively decomposing the spatial coordinate stability component, the coordinate drift component, the display module rotation angle stability component and the angle offset component, and establishing a position compensation coefficient matrix based on these components for subsequent position compensation calculation;

[0010] S40, based on the correlation between the data transmission quality parameters and the display effect, analyzing the stable component and the fluctuating component of the transmission bandwidth, calculating the stable component and the fluctuating component of the transmission delay, and establishing a transmission quality compensation coefficient matrix to provide a basis for achieving high-quality data transmission;

[0011] S50, using the obtained component data and compensation coefficient matrix, constructing a system state matrix including a display position deviation correction matrix, a transmission quality compensation matrix and a display effect optimization matrix, to provide a quantitative reference for the overall operation state of the system;

[0012] S60, calculating display position compensation, transmission delay compensation and display effect compensation respectively through matrix operation according to the constructed system state matrix, and integrating these compensation amounts into a unified compensation parameter set for subsequent data processing;

[0013] S70, applying the calculated compensation parameters to the video data processing process, including using the position compensation amount to perform spatial mapping correction, using the delay compensation amount to optimize the data transmission timing, and using the display effect compensation amount to improve the display quality, thereby achieving all-round optimization of the display effect;

[0014] S80, performing a multi-level encryption transmission process based on the processed data, firstly encrypting the corrected data and transmitting it, then decrypting it at the receiving end and applying the position compensation parameter for secondary encryption, and finally performing a third-level encryption communication at the display module end to ensure the security of data transmission;

[0015] S90, the system continuously performs adaptive display control during operation, including adjusting control parameters in real time according to the display effect after compensation, continuously optimizing the position compensation coefficient matrix, and dynamically updating the transmission quality compensation matrix, so as to achieve dynamic optimization of system performance;

[0016] S100. When the system detects an abnormal situation, it automatically starts the exception handling mechanism, including recalculating the compensation parameter matrix when a display abnormality is detected, automatically adjusting the transmission compensation coefficient when the transmission quality is found to be degraded, immediately updating the position compensation matrix when the position changes, and regenerating the encryption parameter matrix when encryption problems occur, to ensure the stable operation of the system.

[0017] Among them, the data collected by the position information collection module includes: three-dimensional space coordinate information of the LED display module; physical size information of the LED display module; resolution information of the LED display module; rotation angle information of the LED display module; and connection status information of the LED display module.

[0018] Among them, the position compensation coefficient matrix is ​​constructed by a least squares optimization algorithm, and the least squares optimization algorithm establishes an objective function based on the spatial coordinate stability component, the coordinate drift component, the display module rotation angle stability component and the angle offset component, and determines the optimal compensation coefficient through iterative calculation.

[0019] The transmission quality compensation coefficient matrix is ​​generated by an adaptive weighting algorithm, and the weight coefficients are dynamically adjusted according to the real-time status of the transmission bandwidth stable component, the transmission bandwidth fluctuation component, the transmission delay stable component and the transmission delay fluctuation component.

[0020] Among them, the system status matrix adopts a hierarchical structure design, including a display layer status submatrix, a transmission layer status submatrix and a control layer status submatrix. The display layer status submatrix records the display position and display effect parameters, the transmission layer status submatrix records the data transmission and encryption status parameters, and the control layer status submatrix records the system operation and exception handling parameters.

[0021] Among them, a dynamic key generation mechanism is adopted in the multi-level encrypted transmission process, and encryption parameters are calculated based on the operating parameters in the system state matrix. The encryption parameters are updated in real time with the system state and are used for primary encrypted transmission, secondary encrypted transmission and tertiary encrypted transmission.

[0022] Among them, the adaptive display control is implemented by adopting a deep neural network model. By establishing a compensation effect evaluation index system, the compensation effect evaluation index system includes a display position accuracy index, a transmission quality index and a display effect index. The control parameters are continuously optimized based on the evaluation results of the compensation effect evaluation index system.

[0023] Among them, the multivariate mixed decomposition calculation includes discrete wavelet transform decomposition operation and singular value decomposition operation. The discrete wavelet transform decomposition operation is used to perform multi-scale decomposition on the brightness component and the chrominance component. The singular value decomposition operation is used to realize the extraction of the brightness stable component, the brightness fluctuation component, the chrominance stable component and the chrominance fluctuation component.

[0024] Specifically, the present invention proposes an LED display screen control system that automatically matches the display position, which can effectively solve the problems existing in the prior art. The system ensures the security of video data during transmission by adopting a multi-level encrypted transmission mechanism. At the same time, by using the real-time collected LED module position data and combining the time-varying characteristics analysis of the video signal, the display position compensation parameters are automatically calculated to achieve accurate alignment of the video content on the LED display screen. In addition, the system can also dynamically optimize the data transmission quality and display effect to ensure that the final presented picture quality meets the requirements.

[0025] Compared with the prior art, the main technical advances of the present invention are embodied in the following aspects:

[0026] 1. It realizes multi-level encrypted transmission of video data, which not only ensures transmission security, but also further improves the anti-attack capability. The traditional single encryption method is easy to be cracked, while the present invention adopts a hybrid encryption mechanism combining symmetric encryption and asymmetric encryption, which greatly improves data security.

[0027] 2. By analyzing the installation position information of the LED module in real time and automatically calculating the display position compensation parameters, the video content can be accurately aligned on the LED screen without manual intervention. This greatly simplifies the complexity of system debugging and maintenance and improves the efficiency of use.

[0028] 3. Use multivariate hybrid decomposition to analyze the time-varying characteristics of video signals and position data, and use adaptive compensation algorithms to dynamically optimize transmission quality and display effects to ensure high quality of the final display. Compared with previous methods that require manual intervention, this invention achieves fully automatic display optimization and greatly improves the adaptive performance of the system.

[0029] In summary, the present invention innovatively integrates multiple advanced algorithms and technical means to ensure transmission security while solving the technical problems of complex operation and low efficiency of traditional manual operation methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 A flowchart of the steps executed by the embedded control software module in the present invention;

[0031] Figure 2 It is the entire link design diagram of the LED display screen in Example 2, which displays the information of the entire link securely and automatically matches the position;

[0032] Figure 3 is a description of the workflow of the video processing and sending device capable of identifying designated display information in Embodiment 2;

[0033] Figure 4It is a description of the workflow of the receiving control card capable of receiving paired specified video processing and sending equipment in Embodiment 2;

[0034] Figure 5 It is a schematic diagram of the spatial display position communication design of the LED display module circuit in Example 2;

[0035] Figure 6 It is a schematic diagram of the position relationship of multiple modules arranged into a receiving card in Example 2;

[0036] Figure 7 This is a circuit working diagram of an LED display module that can receive a paired designated receiving control card in Example 2. DETAILED DESCRIPTION

[0037] In order to make the purpose, technical solution and advantages of the embodiments of the present invention more clear, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0038] The LED display screen control system for automatically matching the display position of the present invention adopts a modular design, and is mainly composed of a main control chip, a video signal acquisition module, a signal encryption identification module, a network transmission module, a multi-channel receiving control module, a display module control module, an LED display module, a position information acquisition module and a system configuration module. Data transmission and control are carried out between the modules through a bus or a network.

[0039] The main control chip uses a high-performance ARM chip with a main frequency of no less than 1.2 GHz, a built-in cache of no less than 2 megabytes, and supports multi-task parallel processing. The main control chip is connected to each functional module through a 64-bit data bus and uses interrupts to communicate to ensure the real-time and reliability of the system. The main control chip has a built-in watchdog timer to monitor the system operation status and automatically reset or protect the system when an abnormality occurs.

[0040] The video signal acquisition module supports multiple interface standards such as HDMI2.1, DP1.4, DVI-D, etc. Each interface is equipped with an independent signal analysis unit. The signal analysis unit uses a dedicated video processing chip to support real-time processing of 4K resolution video signals, and the color depth supports up to 12 bits. The module has a built-in high-speed cache with a capacity of no less than 512 megabytes for temporary storage of video data. Signal acquisition uses a 16-bit high-speed analog-to-digital converter with a sampling rate of up to 200 MHz to ensure the accuracy of signal acquisition.

[0041] The signal encryption recognition module is implemented with FPGA, with a clock frequency of no less than 300 MHz and a built-in hardware encryption engine. The feature recognition unit adopts a parallel processing architecture to support real-time recognition of multiple encryption protocols. The decryption processing unit adopts a pipeline structure and supports encryption algorithms such as AES256 and SM4. A high-speed serial interface is used for data transmission between the module and the video signal acquisition module, with a transmission rate of up to 10 Gbps.

[0042] The network transmission module is equipped with 8 Gigabit Ethernet ports and 2 10 Gigabit Ethernet ports, and supports the network port aggregation function. The optical fiber interface supports the SFP+ standard, and the transmission distance can reach 10 kilometers. The module has a built-in network processor, supports the TCP / IP protocol stack, and has functions such as packet processing, flow control, and QoS. The secondary encryption unit uses a dedicated encryption chip and supports asymmetric encryption algorithms such as ECC384.

[0043] The multi-channel receiving control module adopts a multi-DSP parallel processing architecture, and the computing power of each DSP is not less than 1200MIPS. The network receiving unit supports giant data frames, and the maximum transmission unit can reach 9216 bytes. The signal decryption unit adopts a combination of hardware and software to support the parallel processing of multiple decryption algorithms. The data processing unit adopts a pipeline structure to support real-time data processing and forwarding.

[0044] The display module control module is equipped with 32 flat cable interfaces, and the transmission rate of each interface is not less than 3.2 Gbps. The spatial position resolution unit adopts a high-precision position calculation chip, which supports sub-millimeter position resolution accuracy. The module has a built-in display parameter configuration unit, which supports real-time adjustment of parameters such as brightness, contrast, and color temperature. The three-way encrypted communication adopts a hybrid encryption scheme, combining the advantages of symmetric encryption and asymmetric encryption.

[0045] The LED display module adopts COB packaging technology, and the pixel pitch can reach 0.9 mm. The signal input interface supports differential signal transmission and has strong anti-interference ability. The position information storage unit adopts non-volatile memory with a capacity of 32 megabytes. The display drive unit adopts constant current drive mode and supports 16-bit grayscale control. The module supports automatic address allocation function, which is convenient for unified management of the system.

[0046] The position information acquisition module uses a high-precision laser distance sensor with a measurement accuracy better than 0.1 mm. The spatial coordinate acquisition unit supports real-time measurement of three-dimensional coordinates with a sampling rate of up to 100 Hz. The data processing unit uses a 32-bit microcontroller to support real-time processing and transmission of coordinate data. The module and the LED display module use RS485 bus for communication with a bus rate of 12 megabits per second.

[0047] The system configuration module provides three local configuration interfaces: RS232, USB and Ethernet. The remote configuration interface supports Web access and uses the HTTPS protocol to ensure communication security. The module has a built-in parameter management unit that supports backup and recovery of system parameters. The encryption algorithm update uses a secure upgrade mechanism to ensure the reliability of the upgrade process.

[0048] The above modules are connected through the system bus and adopt a layered communication protocol. The bottom layer uses CAN bus for real-time control, and the bus rate is 1 megabit per second. The middle layer uses Ethernet for data transmission, supporting two rates of 1000 and 10000. The application layer adopts a custom control protocol to ensure the coordination between the modules of the system. Each module adopts a modular power supply design, the working voltage is 12 volts, and it has overvoltage and overcurrent protection functions. The overall power consumption of the system does not exceed 1000 watts, and it supports hot-swap function. All modules use industrial-grade devices, the operating temperature range is minus 20 degrees Celsius to 70 degrees Celsius, and the relative humidity range is 20% to 90%. The system reliability has a mean time between failures of more than 50,000 hours and an average repair time of less than 30 minutes.

[0049] For the embedded control software module of the present invention, the specific implementation of the steps executed by the module is described in detail as follows.

[0050] The specific implementation method of step S10 is to collect various types of data required for the operation of the system in real time. This step first obtains the encrypted video signal data through the video signal acquisition module. The system uses a high-speed analog-to-digital converter to sample the input encrypted video signal. The sampling rate can be dynamically adjusted according to the bandwidth of the video signal. It is generally set to 2.5 to 3 times the highest frequency of the video signal. The sampling resolution is 12 to 16 bits to ensure the accuracy of signal acquisition; secondly, the real-time position data of the LED display module is obtained through the position information acquisition module, and the three-dimensional spatial coordinates, physical size, resolution, rotation angle and other parameters of each LED display module are collected using a high-precision position sensor. The position measurement accuracy is better than 0. 1 mm, and the angle measurement accuracy is better than 1 degree at 0 o'clock; then the system operation status data is collected, including the working status, temperature, voltage and other parameters of each module, and the sampling period is 100 milliseconds to 1000 milliseconds; then the data transmission quality parameters are collected, mainly including network bandwidth, transmission delay, packet loss rate and other indicators, and the sampling period is 10 milliseconds to 100 milliseconds; finally, the encryption channel status data at all levels is collected, including encryption key status, encryption strength, encryption efficiency and other parameters, and the sampling period is 100 milliseconds to 1000 milliseconds; all the collected data are classified and sorted according to data type, collection time, data source and other information, and stored in the corresponding data cache area to provide a basis for subsequent data processing and analysis.

[0051] The specific implementation method of step S20 is to perform multivariate mixed decomposition calculation on the collected encrypted video signal data. This step first uses discrete wavelet transform to perform multi-scale decomposition on the video signal, selects a suitable wavelet basis function (such as Daubechies wavelet or Symlets wavelet), determines the number of decomposition layers (generally 3 to 5 layers), and obtains wavelet coefficients at different scales; then uses the singular value decomposition method to further process the wavelet coefficients to extract the main feature components and the secondary feature components; then based on the extracted feature components, the video signal is decomposed into brightness component and chrominance component, wherein the brightness component reflects the light and dark change characteristics of the image, and the chrominance component reflects the light and dark change characteristics of the image. The brightness component reflects the color characteristics of the image; then the brightness component is subjected to stability analysis. By calculating the statistical characteristics of the brightness value (such as mean, variance, skewness, kurtosis, etc.), combined with the time domain and frequency domain characteristics, the brightness component is decomposed into a stable brightness component and a fluctuating brightness component. The stable component reflects the basic brightness characteristics of the image, and the fluctuating component reflects the dynamic change characteristics of the brightness; similarly, the chromaticity component is subjected to stability analysis. By calculating the statistical characteristics and time-frequency characteristics of the chromaticity value, the chromaticity component is decomposed into a stable chromaticity component and a fluctuating chromaticity component; finally, all the decomposed component data are stored in the system cache to provide a basis for subsequent display effect optimization.

[0052] The specific implementation method of step S30 is to perform a multivariate mixed decomposition calculation on the real-time position data of the LED display module. This step first processes the spatial coordinate data, filters the original coordinate data through the Kalman filter algorithm to eliminate the influence of measurement noise, and then decomposes the spatial coordinates into a coordinate stability component and a coordinate drift component based on the filtered data using the principal component analysis method, wherein the stable component reflects the basic position characteristics of the display module, and the drift component reflects the dynamic change characteristics of the position; secondly, the rotation angle data of the display module is processed, the angle data is filtered using a complementary filtering algorithm, and then the angle data is decomposed into an angle stability component and an angle offset component through the Fourier analysis method; then, based on the decomposed components, the position compensation coefficient matrix is ​​constructed using the least squares method, and the matrix is ​​a 3 by 3 square matrix, wherein the diagonal elements reflect the main compensation coefficients of each dimension, and the non-diagonal elements reflect the cross-influence between dimensions; finally, the values ​​of the matrix elements are continuously adjusted through an iterative optimization algorithm until the preset accuracy requirements are met. Generally, the position compensation accuracy requirement is better than 0.1 mm, and the angle compensation accuracy requirement is better than 0.1 degree.

[0053] The specific implementation method of step S40 is to perform analysis and calculation based on the correlation between the data transmission quality parameters and the display effect. This step first processes the transmission bandwidth data, and uses the sliding window method to calculate the statistical characteristics of the bandwidth, including the average value, standard deviation, maximum value, minimum value, etc., and then uses the adaptive threshold segmentation method to decompose the bandwidth data into a bandwidth stable component and a bandwidth fluctuation component, wherein the fluctuation range of the stable component usually does not exceed 10% of the average bandwidth; secondly, the transmission delay data is processed, and the delay data is smoothed by the exponential smoothing method, and then the delay data is decomposed into a delay stable component and a delay fluctuation component by the wavelet decomposition method, wherein the fluctuation range of the stable component usually does not exceed 20% of the average delay; then, based on the decomposed components, an adaptive weighting algorithm is used to construct a transmission quality compensation coefficient matrix, which is a 2 by 2 square matrix, and the values ​​of the matrix elements are dynamically adjusted according to the real-time status of the transmission quality parameters; finally, the values ​​of the matrix elements are continuously optimized by the feedback control algorithm, so that the system can respond quickly to changes in transmission quality, and the response time is generally required to be less than 10 milliseconds.

[0054] The specific implementation method of step S50 is to use the obtained component data and compensation coefficient matrix to construct a system status matrix. This step first constructs a display position deviation correction matrix, which is a 3 by 3 square matrix used to describe the position deviation of the display module in three-dimensional space. The values ​​of the matrix elements are calculated based on the position compensation coefficient matrix and the real-time position data; secondly, a transmission quality compensation matrix is ​​constructed, which is a 2 by 2 square matrix used to describe the bandwidth and delay compensation during data transmission. The values ​​of the matrix elements are calculated based on the transmission quality compensation coefficient matrix and the real-time transmission data; then a display effect optimization matrix is ​​constructed, which is a 3 by 3 square matrix used to describe the optimization parameters of the display effect, including adjustment coefficients in terms of brightness, contrast, color, etc.; finally, these three matrices are combined into a complete system status matrix, and a hierarchical structure design is adopted to facilitate subsequent status monitoring and parameter optimization.

[0055] The specific implementation method of step S60 is to calculate various compensation amounts respectively through matrix operations based on the constructed system state matrix. This step first calculates the display position compensation amount, and obtains the position compensation amounts in three dimensions by multiplying the display position deviation correction matrix with the real-time position vector. The compensation accuracy is required to be better than 0.1 mm; secondly, the transmission delay compensation amount is calculated, and the delay compensation amount in the transmission process is obtained by multiplying the transmission quality compensation matrix with the real-time delay vector. The compensation accuracy is required to be better than 1 millisecond; then the display effect compensation amount is calculated, and the display effect optimization amount is obtained by multiplying the display effect optimization matrix with the real-time display parameter vector, including brightness compensation, contrast compensation, color compensation, etc.; finally, these compensation amounts are integrated into a unified compensation parameter set to provide a basis for subsequent data processing.

[0056] The specific implementation method of step S70 is to apply the calculated compensation parameters to the video data processing process. This step first uses the position compensation amount to perform spatial mapping correction on the display content, and adopts a bilinear interpolation algorithm or a cubic spline interpolation algorithm to resample the image to ensure the correct positioning of the display content on the LED display screen; secondly, the delay compensation amount is used to optimize the data transmission timing, and the impact of transmission delay on the display effect is reduced by adjusting the data packet sending time and caching strategy; then the display effect compensation amount is used to improve the display quality, including real-time adjustment of parameters such as brightness, contrast, and color to ensure the consistency and stability of the display effect; finally, the processed data is evaluated for quality, including position accuracy evaluation, timing evaluation, and display effect evaluation to ensure that the processing results meet the system requirements.

[0057] The specific implementation method of step S80 is to perform a multi-level encryption transmission process based on the processed data. This step first performs a first-level encryption on the corrected data, using the Advanced Encryption Standard algorithm with a key length of 256 bits, and the encryption strength meets the requirements of the State Cryptography Administration; secondly, the first-level encrypted data is decrypted at the receiving end, and then a second encryption is performed in combination with the position compensation parameters, using the elliptic curve encryption algorithm with a key length of 384 bits; finally, a third-level encrypted communication is performed at the display module end, using a hybrid encryption scheme, combining the advantages of symmetric encryption and asymmetric encryption to ensure the security of data transmission; during the entire encryption process, the key update cycle does not exceed 1 hour, and the calculation delay of the encryption algorithm does not exceed 1 millisecond.

[0058] The specific implementation method of step S90 is that the system continuously performs adaptive display control during operation. This step first adjusts the control parameters in real time according to the compensated display effect, and uses a deep neural network model to optimize the parameters. The network structure contains no less than 3 hidden layers, and the number of neurons in each layer is determined according to the dimension of the control parameters; secondly, the position compensation coefficient matrix is ​​continuously optimized, and the gradient descent method is used to update the matrix elements. The learning rate is dynamically adjusted according to the system state, generally in the range of 0.001 to 0.1; then the transmission quality compensation matrix is ​​dynamically updated, and the matrix elements are adjusted using an adaptive weighting algorithm. The weight coefficient is calculated according to the real-time state of the transmission quality; finally, the system performance is continuously evaluated and optimized, including display effect evaluation, transmission quality evaluation and system stability evaluation, to ensure continuous improvement of system performance.

[0059] The specific implementation method of step S100 is to automatically start the exception handling mechanism when the system detects an abnormal situation. This step first recalculates the compensation parameter matrix when a display abnormality is detected, and uses a fast convergence algorithm to accelerate the reconstruction process of the matrix to ensure that the system can complete parameter adjustment within 100 milliseconds; secondly, automatically adjust the transmission compensation coefficient when it is found that the transmission quality has decreased, and use an adaptive control algorithm to optimize the transmission parameters so that the system can adapt to changes in transmission quality within 50 milliseconds; then immediately update the position compensation matrix when the position changes, and use a real-time optimization algorithm to adjust the matrix elements to ensure that the system can complete position compensation within 200 milliseconds; finally, regenerate the encryption parameter matrix when encryption problems occur, and use a secure key negotiation mechanism to update the encryption parameters to ensure that the system recovers to a secure communication state within 1 second; during the entire exception handling process, the system will record the time, type, processing process and processing results of the exception, providing a basis for subsequent system optimization.

[0060] The calculation process involved in this module is described in detail below.

[0061] The multivariate mixed decomposition calculation process in step S20 is specifically expressed as follows:

[0062] Y video =Y brightness +Y chroma ;

[0063] Where Y video is the original video signal; Y brightness is the brightness component; Y chroma is the chrominance component.

[0064] The stability analysis calculation of the brightness component is specifically expressed as follows:

[0065] Y brightness =Y b_stable +Y b_fluctuate +ε b ;

[0066] Where Y b_stable Y is the stable component of brightness; b_fluctuate is the brightness fluctuation component; ε b is the brightness analysis error term, ranging from 0.001 to 0.01.

[0067] The stability analysis calculation of the chromaticity component is specifically expressed as follows:

[0068] Y chroma =Y c_stable +Y c_fluctuate +ε c ;

[0069] Where Y c_stableis the stable component of chrominance; Y c_fluctuate is the chromaticity fluctuation component; ε c is the colorimetric analysis error term, ranging from 0.001 to 0.01.

[0070] The multi-scale decomposition operation based on discrete wavelet transform is specifically expressed as follows:

[0071]

[0072] Where Y dwt is the result of wavelet transform; J is the number of decomposition layers, ranging from 3 to 5; d j，k is the wavelet coefficient; ψ j，k (t) is the wavelet function; a J，k is the approximate coefficient; φ J，k (t) is the scale function; k is the displacement parameter.

[0073] The singular value decomposition operation is specifically expressed as follows:

[0074] Y svd =UΣV T ;

[0075] Where Y svd is the matrix to be decomposed; U is the left singular vector matrix; ∑ is the singular value diagonal matrix; V T is the transpose of the right singular vector matrix.

[0076] The multivariate mixed decomposition calculation of the position data in step S30 is specifically expressed as follows:

[0077] Space coordinate decomposition calculation:

[0078] P=P stable +P drift +ε p ;

[0079] Where P is the space coordinate vector; P stable is the coordinate stabilizing component; P drift is the coordinate drift component; ε p is the position measurement error, ranging from 0.1 to 1 mm.

[0080] Rotation angle decomposition calculation:

[0081] θ=θ stable +θ offset +ε θ ;

[0082] Where θ is the rotation angle; θ stable is the angular stability component; θ offset is the angle deviation component; ε θis the angle measurement error, ranging from 0.1 to 0.5 degrees.

[0083] The construction of the position compensation coefficient matrix is ​​specifically expressed as follows:

[0084]

[0085] In the formula, k ij (i, j = 1, 2, 3) is the position compensation coefficient, where k 11 , k 22 , k 33 They correspond to the main compensation coefficients in the x, y, and z directions respectively, and the other coefficients are cross compensation coefficients.

[0086] The transmission quality analysis calculation in step S40 is specifically expressed as follows:

[0087] Bandwidth analysis calculation:

[0088] B=B stable +B fluctuate +ε B ;

[0089] Where B is the transmission bandwidth; stable is the bandwidth stable component; B fluctuate is the bandwidth fluctuation component; ε B is the bandwidth measurement error, ranging from 0.1 to 1 Mbps.

[0090] Delay analysis calculation:

[0091] D=D stable +D fluctuate +ε D ;

[0092] Where D is the transmission delay; D stable is the delayed stable component; D fluctuate is the delayed fluctuation component; ε D It is the delay measurement error, ranging from 0.1 to 1 ms.

[0093] The construction of the transmission quality compensation coefficient matrix is ​​specifically expressed as follows:

[0094]

[0095] Where, t ij (i, j = 1, 2) is the transmission quality compensation coefficient, where t 11 is the bandwidth compensation coefficient, t 22 is the delay compensation coefficient, t 12 , t 21 is the cross compensation coefficient.

[0096] The system state matrix construction in step S50 is specifically expressed as follows:

[0097] Display the position deviation correction matrix:

[0098]

[0099] In the formula, p ij (i, j = 1, 2, 3) is the position deviation correction coefficient.

[0100] Transmission quality compensation matrix:

[0101]

[0102] In the formula, q ij (i, j=1, 2) is the transmission quality compensation coefficient.

[0103] Display effect optimization matrix:

[0104]

[0105] In the formula, e ij (i, j=1, 2, 3) is the display effect optimization coefficient.

[0106] The compensation amount calculation in step S60 is specifically expressed as follows:

[0107] Display position compensation calculation:

[0108] C position =M position_correction P+ε cp ;

[0109] In the formula, C position is the position compensation; P is the original position vector; ε cp It is the position compensation calculation error, ranging from 0.1 to 1 mm.

[0110] Transmission delay compensation calculation:

[0111] C delay =M quality D+ε cd ;

[0112] In the formula, C delay is the delay compensation amount; D is the original delay vector; ε cd It is the delay compensation calculation error, ranging from 0.1 to 1ms.

[0113] Calculation of display effect compensation:

[0114] C effect =M effect E+ε ce ;

[0115] In the formula, C effect is the effect compensation amount; E is the original effect vector; ε ce To compensate for the calculation error, the range is 0.001 to 0.01.

[0116] The specific calculation of the compensation parameter application in step S70 is as follows:

[0117] Spatial mapping correction calculation:

[0118] P corrected =P+C Dosition f(t)+ε m ;

[0119] Where P corrected is the corrected position; f(t) is the time-dependent correction function; ε m To correct the mapping error, the range is 0.1~1m m .

[0120] Data transmission timing optimization calculation:

[0121] T optimized =T+C delayg (B)+ε t ;

[0122] Where, T optimized is the optimized transmission timing; T is the original transmission timing; g(B) is the bandwidth-related optimization function; ε t It is the timing optimization error, ranging from 0.1 to 1ms.

[0123] Display quality improvement calculation:

[0124] Q enhanced =Q+C effect h(E)+ε q ;

[0125] In the formula, Q enhanced is the improved display quality; Q is the original display quality; h(E) is the effect-related improvement function; ε q It is the quality improvement error, ranging from 0.001 to 0.01.

[0126] The multi-level encryption calculation in step S80 is specifically expressed as follows:

[0127] First level encryption calculation:

[0128] E 1 =K 1 (D original )+ε e1 ;

[0129] In the formula, E 1 is the first-level encryption result; K 1 is the primary encryption key; D original is the original data; e1 It is the first-level encryption error, ranging from 0.001 to 0.01.

[0130] Secondary encryption calculation:

[0131] E 2 =K 2 (E 1 , C position )+ε e2 ;

[0132] In the formula, E 2 is the secondary encryption result; K 2 is the secondary encryption key; e2 It is the second-level encryption error, ranging from 0.001 to 0.01.

[0133] Three-level encryption calculation:

[0134] E 3 =K 3 (E 2 , P correctea )+ε e3 ;

[0135] In the formula, E 3 is the result of the third-level encryption; K 3 is the third-level encryption key; e3 It is the third level encryption error, ranging from 0.001 to 0.01.

[0136] The adaptive control calculation in step S90 is specifically expressed as follows:

[0137] Control parameter adjustment calculation:

[0138]

[0139] Where P control is the adjusted control parameter; P base is the basic control parameter; α, β, γ are weight coefficients;

[0140] are the gradients of quality, timing, and effect respectively; ε control To control the adjustment error, the range is 0.001 to 0.01.

[0141] Position compensation optimization calculation:

[0142]

[0143] Where M position_new is the optimized position compensation matrix; λ, μ are the learning rates; are the gradients of position and angle respectively; ε position is the position optimization error, ranging from 0.001 to 0.01.

[0144] Transmission quality optimization calculation:

[0145]

[0146] Where M quality_new is the optimized quality compensation matrix; v, ω is the learning rate; are the gradients of bandwidth and delay respectively; ε quality The error for quality optimization is in the range of 0.001 to 0.01.

[0147] The specific expression of the abnormality handling calculation in step S100 is as follows:

[0148] Display abnormal compensation calculation:

[0149] C display =f anomaly (Q error )+ε display ;

[0150] In the formula, C display To display the abnormal compensation amount; f anomaly is the exception handling function; Q error To show the mass error; ε display To display the compensation error, the range is 0.001~0.01.

[0151] Transmission anomaly compensation calculation:

[0152] C transmission =g anomaly (T error )+ε transmission ;

[0153] In the formula, C transmission is the transmission abnormality compensation; g anomaly is the exception handling function; T error is the transmission quality error; ε transmission It is the transmission compensation error, ranging from 0.001 to 0.01.

[0154] Encryption abnormality compensation calculation:

[0155] C encryption =h anomaly (E error )+ε encryption ;

[0156] In the formula, C encryption is the encryption abnormal compensation amount; h anomaly is the exception handling function; E error is the encryption quality error; ε encryption To encrypt the compensation error, the range is 0.001~0.01.

[0157] The specific principle of the present invention is to achieve safe transmission and precise alignment of display content by performing multivariate analysis on video signals and LED module position data and combining dynamic optimization control. The specific principle is as follows:

[0158] First, the system uses a hybrid encryption mechanism to perform multi-level encryption transmission on video data. This includes the symmetric encryption algorithm AES for primary encryption, the asymmetric encryption algorithm ECDSA for secondary encryption, and the third level encryption on the LED display module side. At the same time, the generation of encryption parameters is dynamically associated with the current operating status of the system, which improves the ability to resist attacks. This ensures the security of both the transmission process and the final display content.

[0159] Secondly, the system collects the installation position information of the LED module in real time, including three-dimensional spatial coordinates, physical size, resolution, rotation angle and other parameters. By performing multivariate decomposition analysis on these position data, the stable component and drift component of the spatial coordinates, as well as the stable component and offset component of the rotation angle, can be extracted. Based on these component information, the system can automatically calculate the compensation parameter matrix of the display position to achieve precise alignment of the video content on the LED screen.

[0160] In addition, the system also performs multivariate decomposition on the collected video signal data to extract the stable and fluctuating components of brightness, as well as the stable and fluctuating components of chromaticity. At the same time, the relationship between data transmission quality parameters and display effects is analyzed to establish a compensation model. By comprehensively calculating and dynamically adjusting the parameters of position compensation, transmission quality compensation, and display effect optimization, high-quality display of video content on the LED screen can be ensured.

[0161] During the operation of the entire system, various operating status data are continuously collected to build a matrix model that reflects the overall status of the system. Based on this model, the system can adaptively adjust various compensation parameters, optimize the display effect, and quickly diagnose and handle abnormal situations. This adaptive control mechanism enables the solution of the present invention to continuously maintain a high level of transmission security and display quality, meeting the use requirements in complex application environments.

[0162] The following provides a specific embodiment 1 of the embedded control software module of the present invention. The specific implementation of each step in this embodiment 1 is described in detail as follows: The specific implementation of step S10 is to collect various types of data required for the operation of the system in real time. This step obtains the encrypted video signal data Y through the video signal acquisition module. video The system uses a high-speed analog-to-digital converter to sample the input encrypted video signal. The sampling rate can be determined according to the bandwidth f of the video signal. sample Dynamic adjustment to satisfy formula f sample = k·f max , where k is the sampling coefficient, ranging from 2.5 to 3, and f max It is the highest frequency of the video signal; the sampling resolution is 12 to 16 bits to ensure the accuracy of signal acquisition; secondly, the real-time position data P of the LED display module is obtained through the position information acquisition module, and the three-dimensional spatial coordinates, physical size, resolution, rotation angle and other parameters of each LED display module are collected by a high-precision position sensor. The position measurement accuracy is better than 0.1 mm, and the angle measurement accuracy is better than 0.1 degrees.

[0163] The specific implementation method of step S20 is to perform multivariate mixed decomposition calculation on the collected encrypted video signal data, first according to formula Y video =Y brightness +Y chroma Decompose the video signal into luminance component and chrominance component; then use the formula Y brightness =Y b_stable +Y b_fluctuate +ε b Perform stability analysis on the brightness component, where Y b_stable is the brightness stable component, Y b_ffuctuate is the brightness fluctuation component, ε b is the error term for brightness analysis, ranging from 0.001 to 0.01; similarly, stability analysis is performed on the chromaticity component, using the formula Y chroma =Y c_stable +Y c_fluctuate +ε c , where Y c_stable is the chromaticity stable component, Y c_fluctuate is the chromaticity fluctuation component, ε c is the color analysis error term, ranging from 0.001 to 0.01; multi-scale decomposition operation through discrete wavelet transform Perform multi-level analysis on the signal, where is the number of decomposition levels, ranging from 3 to 5.

[0164] The specific implementation method of step S30 is to perform multivariate mixed decomposition calculation on the real-time position data of the LED display module. This step first uses the formula P=P stable +P drift+ε p Decompose the spatial coordinate data, where P stable is the coordinate stabilizing component, P drift is the coordinate drift component, ε p is the position measurement error, ranging from 0.1 to 1 mm; secondly, the formula θ = θ stable +θ offset +ε θ Decompose the rotation angle data, where θ stable is the angular stability component, θ offset is the angle offset component, ε θ is the angle measurement error, ranging from 0.1 to 0.5 degrees; finally, the position compensation coefficient matrix M is constructed position , the matrix is ​​expressed in 3×3 form and is used to achieve position compensation in three-dimensional space.

[0165] The specific implementation of step S40 is to analyze and calculate based on the correlation between the data transmission quality parameter and the display effect, using the formula B=B stable +B fluctuate +ε B Analyze the bandwidth characteristics, where B stable is the bandwidth stable component, B fluctuate is the bandwidth fluctuation component, ε B is the bandwidth measurement error, ranging from 0.1 to 1 Mbps; using the formula D = D stable +D fluctuate +ε D Analyze the delay characteristics, where D stable is the delayed stable component, D fluctuate is the delayed fluctuation component, ε D is the delay measurement error, ranging from 0.1 to 1 millisecond; construct the transmission quality compensation coefficient matrix M transmission , expressed in 2×2 form, is used to achieve bandwidth and delay compensation.

[0166] The specific implementation of step S50 is to use the obtained component data and compensation coefficient matrix to construct a system state matrix, including a display position deviation correction matrix M position_correction , transmission quality compensation matrix M quality And display effect optimization matrix M effect ,These matrices together constitute a complete description of the system status, where the display position deviation correction matrix and the display effect optimization matrix are in 3×3 form, and the transmission quality compensation matrix is ​​in 2×2 form.

[0167] The specific implementation of step S60 is to calculate various compensation amounts through matrix operations according to the constructed system state matrix, including the position compensation amount calculation C position =M position_correctionP+ε cp , delay compensation calculation C delay =M quality D+ε cd , and display effect compensation calculation C effect =M effect E+ε ce , where the error terms range from 0.1 to 1 mm, 0.1 to 1 ms, and 0.001 to 0.01, respectively.

[0168] The specific implementation of step S70 is to apply the calculated compensation parameters to the video data processing process, using the formula P corrected =P+C position f(t)+ε m Perform spatial mapping correction, where f(t) is the time-dependent correction function; use the formula T optimized =T+C delay g(B)+ε t Optimize data transmission timing, where g(B) is the bandwidth-related optimization function; use the formula Q enhanced =Q+C effect h(E)+ε q Improve display quality, where h(E) is the effect-related improvement function.

[0169] The specific implementation method of step S80 is to perform a multi-level encryption transmission process based on the processed data, using formula E 1 =K 1 (D original )+ε e1 Perform first level encryption, E 2 =K 2 (E 1 , C position )+ε e2 Perform secondary encryption, E 3 =K 3 (E 2 , P corrected )+ε e3 Perform three-level encryption, where K 1 , K 2 , K 3 are the encryption keys at each level, ε e1 , ε e2 , ε e3 Encryption errors at all levels.

[0170] The specific implementation method of step S90 is that the system continuously performs adaptive display control during operation, using the formula To achieve control parameter adjustment, use the formula Optimize position compensation using the formula Optimize transmission quality, where α, β, γ, λ, μ, v, and ω are various learning rates or weight coefficients, ranging from 0.001 to 0.1.

[0171] The specific implementation of step S100 is to automatically start the abnormality handling mechanism when the system detects an abnormality, using formula C display =f anomaly (Q error )+ε display To handle display anomalies, use formula C transmission =g anomaly (T error )+ε transmission To handle transmission anomalies, use formula C encryption =h anomaly (E error )+ε encryption Handle encryption exceptions, where f anomaly , g anomaly 、h anomaly is the corresponding exception handling function, and the range of each error term is 0.001 to 0.01.

[0172] In order to better understand and implement the present invention, the following provides a specific application scenario of the present invention, Example 2: The display information in Example 2 refers to materials such as video images that need to be played on the LED display screen. Figure 3 As shown in FIG. 1 , for conventional video processing and sending equipment, a hardware interface such as an HDMI interface is used to receive the HDMI output from a computer graphics card, and the content displayed on the computer monitor is completely consistent. Figure 2 As shown, in Embodiment 2, the video image material to be played is encrypted, so that after the video processing and sending device receives the image data transmitted from the HDMI interface, it recognizes that the encryption password is embedded in the data stream, and the video processing device has a key for decrypting the password, and then processes the display information such as the video image and transmits it to the next stage. In this Embodiment 2, the first-level encryption of these display information is implemented in the following manner.

[0173] Use a dedicated playback software for playing display materials. The software has the function of inserting specified encryption information. Only when the playback software is turned on and the display information is played, the playback software will insert the encryption password in the playback data stream. For example, the total number of pixels of the LED display screen is 1920 points * 1080 points. The playback software will add 8-64 bytes of data outside the point range, such as the starting point (column coordinates, row coordinates) (1920, 1080), representing the 8-64 bytes of encryption password, and the interval time of inserting the password is dynamically adjusted. The configuration software transmits the decryption keys corresponding to these encryption passwords to the video processing and sending device. When the video processing and sending device receives the image data stream containing the encryption information, it will process these display information and transmit it to the next level. In this way, the illegal insertion of the HDMI line into the video processing and sending device and the illegal playback can be excluded at the first level.

[0174] If a general playback software is used, an area with encryption information needs to be inserted into the video image data that is to be played. Generally, the refresh rate of video data is 25-60Hz, which means that there are 25-60 frames of display data in one second. The total number of pixels of a standard 2K display is 1920*1080 points, and the total number of pixels of a 4K display is 3840*2160. Among so many pixels and within 1 second, only limited feature data points need to be inserted in a certain frame of data. These limited points are located at the edge of the display pixels. For example, the four corner points (0,0), (1919,0), (0,1079), and (1919,1079) are replaced with encrypted feature codes, a total of 4 points, each with 3 colors, and a 12-byte password transmission can be completed. In this way, because there is only 16ms of time for replacement within 1 second, and there are only 4 corner points, and a lower brightness value can be selected, it will not affect the normal display content. The advantage of this type of encryption is that it can be played with any playback software and computer without relying on dedicated playback software, but it can also achieve the function of transmitting the correct display information backward only after the video processing device obtains the correct decryption key.

[0175] After confirming the first-level encryption and decryption pairing information, use the configuration software to configure the decryption algorithm used to decode the encrypted information in the video material to the video processing and sending device that can identify the specified display content, such as Figure 4As shown, when the device is connected to a video playback source such as a computer using an HDMI cable or the like, if the video playback source plays content that does not contain a specific password area, the video processing and sending device cannot find legal playback content, and the playback content is not output to the receiving control card. On the contrary, when the video processing device identifies the correct playback content via a decryption algorithm, the content to be played is sent to the receiving control card after secondary encryption through a network port or an optical fiber port. If the video processing and sending device is illegally replaced at this time, even if a video processing and sending device of the same brand and model is used, because the first-level decryption information and the second-level re-encryption information dedicated to the operator are not configured through the configuration software, the replaced video processing device cannot correctly transmit the content to be displayed to the receiving control card.

[0176] Similarly, the configuration software is used to send the paired decryption algorithm of the secondary encrypted information to the receiving control card through the video processing sending device via the network cable or optical fiber, so that the receiving control card on the link can only receive the video processing sending device corresponding to the secondary encryption algorithm. If the receiving control card is connected to an unpaired video processing sending device, the receiving control card cannot receive illegal information and stops outputting to the LED display module, causing the LED display module to be in a black screen state.

[0177] Similarly, the configuration software is used to send the decryption algorithm of the three-level encrypted information to all LED display modules through the video processing and receiving control card, so that all LED display modules can only receive the content from the paired receiving card. If an illegal receiving control card is replaced at this time, the LED module will not receive the dedicated three-level encrypted command, and the display content will no longer be displayed.

[0178] For an LED display screen, the entire LED display screen is composed of multiple LED display modules, which are closely connected to form a large display plane. Here, for example, there are 30 LED display modules in the horizontal direction and 30 in the vertical direction. The common LED display screen is composed of a box made of iron or aluminum as the structure of the installation module. Each box is usually 2 modules wide and 3 modules high, or 3 modules wide and 6 modules high, etc. When the box is not used, all the modules carried by a receiving card can be regarded as a box. Each LED box is generally connected to the LED display module by a flat cable by an LED receiving control card. This combination method brings a problem. When assembling this LED display screen, the engineering and technical personnel need to connect the flat cable according to the interface sequence specified by the receiving control card, and then connect the network cable of the receiving control card in a fixed routing method. After the connection is completed, use the control software to manually set the width and height points of a receiving control card, set the starting point coordinates of each receiving control card, and set the starting point coordinates and width and height points of each output interface of the video processing and sending device. If the flat cable of the module is inserted incorrectly, or the access method of the network cable is uncertain, and the distance between the video processing and sending equipment and the LED display is relatively far, then this manual setting method will be very troublesome.

[0179] like Figure 5 As shown, the LED display module in this embodiment 2 has a communication sensor arranged at the edge of the LED display module that can transmit to the adjacent LED display module in a non-contact and wired manner. Specifically, in this example, infrared receiving transistors for receiving are arranged at the upper edge and left edge of the module, and infrared emitting diodes for sending are arranged at the lower edge and right edge of the module.

[0180] The video processing and sending device is defined as T, and T has more than one network cable interface, which is defined as T1, T2, T3 to Tm.

[0181] Define the receiving control card as R, and multiple Rs are connected to a certain network cable interface to form the network cable link. Then the receiving control cards are TxR1, TxR2, TxR3, to TxRn, where 1<=x<=m.

[0182] Each receiving control card has multiple flat cable output interfaces, and these output interfaces are defined as TxRyJ1, TxRyJ2, TxRyJ3, TxRyJk, where 1<=x<=m, 1<=y<=n.

[0183] When the LED display module is connected to any output interface of a receiving control card, the unique address TxRyJz of the LED display module is automatically generated according to the interface position of the receiving control card. Among them, 1<=x<=m, 1<=y<=n, 1<=z<=k.

[0184] The module transmits its unique address to the adjacent module on its right and lower side via infrared transmission, and at the same time, the module can receive the address information transmitted to it by the modules on its upper and left sides. Each module transmits its upper, left, and module address information to the receiving control card via flat cables.

[0185] like Figure 6 As shown, here it is assumed that a total of 4 modules #1-#4 are connected, and the module addresses are T1R2J3, T1R2J6, T1R2J7, and T1R2J1. #1 cannot receive the module addresses on its upper and left sides, and the data transmitted back to the receiving control card is (0, 0, T1R2J3). #2 cannot receive the module address on its upper side, but can receive the module address on the left side, and the data transmitted back to the receiving control card is (0, T1R2J3, T1R2J6). #3 can receive the module address on its upper side, but cannot receive the module address on the left side, and the data transmitted back to the receiving control card is (T1R2J3, 0, T1R2J7). #4 can receive the module address on its upper side, can receive the module address on the left side, and the data transmitted back to the receiving control card is (T1R2J6, T1R2J7, T1R2J1).

[0186] The receiving control card can determine the number of modules it carries based on the module address received on the interface. In this example, it is determined that 4 modules are carried. The position information received by interface J1 is (T1R2J6, T1R2J7, T1R2J1), indicating that the upper module of the module carried by this interface is interface J6, and the module on its left is interface J7. The position information received by interface 3 is (0, 0, T1R2J3), indicating that there is no module carried by this receiving card on the upper and left sides of the module carried by this interface. The position information received by interface 6 is (0, T1R2J3, T1R2J6), indicating that there is no module on the upper side of the module carried by this interface, and the module on its left is interface J3. The position information received by interface 7 is (T1R2J3, 0, T1R2J7), indicating that the upper side of the module carried by this interface is interface J3, and there is no module on its left side. In this way, the receiving control card can obtain the spatial arrangement position information of the four modules, and calculate that the width of the receiving control card is twice the number of points of the width of one module, and the height is twice the number of points of the height of one module. Then, the data relative to the starting point (0, 0) of the receiving card can be automatically distributed to each interface, and the corresponding module display is carried. Here, the display information of the starting point (0, 0), width and height (w, h) is sent from J3 to the #1 module, the display information of the starting point (w, 0), width and height (w, h) is sent from J6 to the #2 module, the display information of the starting point (0, h), width and height (w, h) is sent from J7 to the #3 module, and the display information of the starting point (w, h), width and height (w, h) is sent from J1 to the #4 module, so that the corresponding interface outputs the display content of the correct position and size to the LED display module.

[0187] The above automatic processing means that engineers do not need to worry about the location of the cable interface of the LED display module, and can connect it to the output interface of the receiving control card at will.

[0188] Similarly, the TxRy ​​receiving control card transmits the information of the LED display module it carries, including the starting point coordinates and size information such as width and height, to the video processing and sending device T step by step.

[0189] like Figure 7 As shown, the video processing and sending device T can automatically calculate the number of pixels of the entire display screen, automatically calculate the starting coordinates and the load size of each output interface such as a network cable or optical fiber, etc., based on the collected information such as the starting point coordinate position and the number of loaded points of the carried receiving control card, and send the corresponding display information to the output interface, so that the engineering personnel no longer need to manually calculate and physically identify the network cable number, and can arbitrarily connect the communication network cable to the output port of the video processing and sending device to complete the automatic matching of the spatial display information.

[0190] In order to better understand and implement the present invention, the following is an example 3 of a specific application scenario of the present invention: In the process of developing a large-scale shopping mall LED display system, the R&D team of a large technology company applied the LED display control system of the present invention that automatically matches the display position to achieve intelligent control of a 300-square-meter arc-shaped LED display. The display screen is composed of 1,000 LED display modules, each of which has a resolution of 128×128 pixels, a physical size of 320 mm×320 mm, and a module spacing of 2 mm. The entire display screen is designed in an arc shape, with an arc radius of 15 meters and a span angle of 120 degrees. The entire project was implemented by a technical team led by Engineer Zhang from the company's R&D center.

[0191] During the implementation of the system, the video signal is first collected and processed. The highest frequency of the input video signal is 60 Hz. According to the sampling theorem, the sampling coefficient k is set to 2.8, then the sampling frequency f sample The frequency is 168 Hz. A 16-bit high-speed analog-to-digital converter is used for signal acquisition to ensure that the sampling accuracy reaches 0.0015%. After the video signal is decomposed by multiple mixing, the brightness stability component Y b_stable The average value is 0.85, the fluctuation range does not exceed 0.05, and the brightness analysis error term ε b Controlled within 0.003; Chroma stability component Y c_stable The average value is 0.75, the fluctuation range does not exceed 0.08, and the color analysis error term ε c Controlled within 0.005.

[0192] Position information is collected using a high-precision laser sensor to measure the three-dimensional coordinates of each LED display module in real time. stable The measurement accuracy is better than 0.05 mm, and the coordinate drift component P drift The maximum value of is controlled within 0.3 mm, and the position measurement error ε p No more than 0.2 mm. Rotation angle stability component θ stable The measurement accuracy is better than 0.05 degrees, and the angle offset component θ offset The maximum value of is controlled within 0.2 degrees, and the angle measurement error ε θ Not more than 0.1 degree.

[0193] Data transmission uses a 10G network, and the measured bandwidth is stable component B stable 9.5 Gbps, bandwidth fluctuation component B fluctuate No more than 0.3 Gbps, bandwidth measurement error ε B Controlled within 0.2 Gbps. Transmission delay stability component D stable The delay fluctuation component D is 0.8 milliseconds. fluctuateThe delay measurement error is no more than 0.2 milliseconds. D Controlled within 0.15 milliseconds.

[0194] The system operation data statistics are shown in Table 1 below:

[0195] Table 1 System operation data table

[0196] Parameter Type Parameter Value Error margin Position compensation accuracy 0.08 mm ±0.02 mm Angle compensation accuracy 0.06 degrees ±0.02 degrees Bandwidth compensation effect 98.5％ ±0.5％ Delay compensation effect 97.8％ ±0.8％ Show performance rating 95.6 points ±1.2 points System response time 5 ms ±1 ms

[0197] The system realizes adaptive control during operation. The control parameters are adjusted using a deep neural network model. The network contains four hidden layers, with 256, 128, 64, and 32 neurons in each layer. The quality weight coefficient α is 0.4, the timing weight coefficient β is 0.3, and the effect weight coefficient γ is 0.3. The position learning rate λ is set to 0.01, the angle learning rate μ is set to 0.015, the bandwidth learning rate v is set to 0.02, and the delay learning rate ω is set to 0.025.

[0198] Encrypted transmission uses a multi-level encryption scheme. The first-level encryption uses the AES256 algorithm with a key length of 256 bits. The encryption strength meets the requirements of the National Cryptography Administration. The second-level encryption uses the ECC384 algorithm with a key length of 384 bits. The third-level encryption uses a hybrid encryption scheme that combines the advantages of the AES and RSA algorithms. During the encryption process, the first-level encryption error ε e1 Controlled within 0.002, the secondary encryption error ε e2 Controlled within 0.003, the three-level encryption error ε e3 Controlled within 0.004.

[0199] The response time statistics of the exception handling mechanism are shown in Table 2 below:

[0200] Table 2 Exception handling corresponding timetable

[0201] Exception Type Response time Processing time Recovery rate Display abnormality 20 ms 80 ms 99.5％ Transmission anomaly 15 ms 35 ms 99.8％ Position offset 25 ms 175 ms 99.6％ Encryption exception 30 ms 970 ms 99.9％

[0202] After 3 months of continuous operation test, the system showed excellent performance and stability. Display effect compensation amount C effect The average value is 0.92, which effectively compensates for the calculation error ε ce Controlled within 0.008. Position compensation amount C position The average value is 0.95, and the position compensation calculation error ε cp Controlled within 0.15 mm. Delay compensation amount C delay The average value is 0.88, and the delay compensation calculation error ε cd Controlled within 0.12 milliseconds.

[0203] Compared with the traditional LED display screen control system, the present invention has achieved significant progress in the following aspects: 1. The traditional system uses manual setting of display module position parameters, which requires technical personnel to debug one by one, which is time-consuming and has low precision. The present invention uses an automatic matching algorithm to achieve automatic acquisition and real-time optimization of position parameters, shortening the installation and debugging time from the original 5 days to 1 day, and improving the position accuracy by 5 times. 2. The traditional system uses fixed data transmission parameters and cannot adapt to changes in network status. The present invention uses an adaptive control algorithm to achieve dynamic optimization of transmission parameters, which improves system stability by 3 times and reduces the incidence of problems such as screen tearing and delay by 90%. 3. The traditional system uses a single encryption scheme, which has security risks, while the present invention uses a multi-level encryption scheme, which significantly improves the security of data transmission and improves the system security level by 2 levels. 4. The traditional system lacks an effective exception handling mechanism, and manual intervention is required when the system fails. The present invention uses an intelligent exception handling mechanism to achieve automatic detection and processing of faults, which improves system availability by 50% and reduces maintenance costs by 60%. 5. The traditional system uses fixed display parameters and cannot automatically adjust according to environmental changes. The present invention uses a deep learning algorithm to achieve automatic optimization of the display effect, which improves the display quality by 30% and user satisfaction by 45%.

[0204] It should be noted that the variables involved in the present invention are explained in detail as shown in Table 3 and Table 4 below.

[0205] Table 3 Variable explanation table (Part I)

[0206]

[0207]

[0208] Table 4 Variable explanation table (Part II)

[0209]

[0210] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A LED display screen control system that automatically matches the display position, characterized in that: include: The main control chip is used to coordinate the data processing and transmission of the entire system; The video signal acquisition module includes HDMI, DP, DVI multi-channel input interfaces and a signal analysis unit, which is used to receive and analyze encrypted video signals; The signal encryption recognition module includes a feature recognition unit and a decryption processing unit, which is electrically connected to the video signal acquisition module and is used to recognize and decrypt the primary encrypted video signal; The network transmission module includes a plurality of network ports and optical fiber ports, and is electrically connected to the signal encryption identification module, and is used to re-encrypt and transmit the decrypted video signal; The multi-channel receiving control module includes a network receiving unit, a signal decryption unit and a data processing unit, and is connected to the network transmission module through a network cable or an optical fiber to receive and decrypt the secondary encrypted signal; The display module control module includes a plurality of flat cable interfaces and a spatial position analysis unit, and is electrically connected to the multi-channel receiving control module to realize three-way encrypted communication with the LED display module; The LED display module includes a signal input interface, a position information storage unit and a display drive unit, and is connected to the display module control module via a flat cable; The position information acquisition module includes a spatial coordinate acquisition unit and a data processing unit, which is electrically connected to the LED display module and is used to acquire the actual installation position information of each LED display module; The system configuration module includes a local configuration interface and a remote configuration interface, which are electrically connected to the main control chip and are used for system parameter configuration and encryption algorithm update.

2. The LED display screen control system for automatically matching display positions according to claim 1 is characterized in that: The main control chip is provided with an embedded control software module for controlling and coordinating the work of each hardware module and ensuring the safe transmission and accurate display of display information.

3. The LED display screen control system for automatically matching display positions according to claim 1 is characterized in that: The embedded control software module performs the following steps: S10, collecting encrypted video signal data, real-time position data of the LED display module, system operation status data, data transmission quality parameters and encryption channel status data at all levels in real time through the video signal acquisition module, and preliminarily classifying and arranging the collected data to prepare for subsequent processing; S20, performing multivariate mixed decomposition calculation on the collected encrypted video signal data, decomposing the video data into a brightness component and a chroma component, and performing stability analysis on the brightness component to obtain a brightness stable component and a brightness fluctuation component, and performing stability analysis on the chroma component to obtain a chroma stable component and a chroma fluctuation component, and storing all component data in a system buffer for standby use; S30, performing multivariate mixed decomposition calculation on the real-time position data of the LED display module, respectively decomposing the spatial coordinate stability component, the coordinate drift component, the display module rotation angle stability component and the angle offset component, and establishing a position compensation coefficient matrix based on these components for subsequent position compensation calculation; S40, based on the correlation between the data transmission quality parameters and the display effect, analyzing the stable component and the fluctuating component of the transmission bandwidth, calculating the stable component and the fluctuating component of the transmission delay, and establishing a transmission quality compensation coefficient matrix to provide a basis for achieving high-quality data transmission; S50, using the obtained component data and compensation coefficient matrix, constructing a system state matrix including a display position deviation correction matrix, a transmission quality compensation matrix and a display effect optimization matrix, to provide a quantitative reference for the overall operation state of the system; S60, calculating display position compensation, transmission delay compensation and display effect compensation respectively through matrix operation according to the constructed system state matrix, and integrating these compensation amounts into a unified compensation parameter set for subsequent data processing; S70, applying the calculated compensation parameters to the video data processing process, including using the position compensation amount to perform spatial mapping correction, using the delay compensation amount to optimize the data transmission timing, and using the display effect compensation amount to improve the display quality, thereby achieving all-round optimization of the display effect; S80, performing a multi-level encryption transmission process based on the processed data, firstly encrypting the corrected data and transmitting it, then decrypting it at the receiving end and applying the position compensation parameter for secondary encryption, and finally performing a third-level encryption communication at the display module end to ensure the security of data transmission; S90, the system continuously performs adaptive display control during operation, including adjusting control parameters in real time according to the display effect after compensation, continuously optimizing the position compensation coefficient matrix, and dynamically updating the transmission quality compensation matrix, so as to achieve dynamic optimization of system performance; S100. When the system detects an abnormal situation, it automatically starts the exception handling mechanism, including recalculating the compensation parameter matrix when a display abnormality is detected, automatically adjusting the transmission compensation coefficient when the transmission quality is found to be degraded, immediately updating the position compensation matrix when the position changes, and regenerating the encryption parameter matrix when encryption problems occur, to ensure the stable operation of the system.

4. The LED display screen control system for automatically matching display positions according to claim 1 is characterized in that: The data collected by the position information collection module includes: three-dimensional space coordinate information of the LED display module; physical size information of the LED display module; resolution information of the LED display module; rotation angle information of the LED display module; and connection status information of the LED display module.

5. The LED display screen control system for automatically matching display positions according to claim 3 is characterized in that: The position compensation coefficient matrix is ​​constructed by a least squares optimization algorithm, which establishes an objective function based on a spatial coordinate stability component, a coordinate drift component, a display module rotation angle stability component, and an angle offset component, and determines the optimal compensation coefficient through iterative calculations.

6. The LED display screen control system for automatically matching display positions according to claim 3, characterized in that: The transmission quality compensation coefficient matrix is ​​generated by an adaptive weighting algorithm, and the weight coefficients are dynamically adjusted according to the real-time status of the transmission bandwidth stable component, the transmission bandwidth fluctuation component, the transmission delay stable component and the transmission delay fluctuation component.

7. The LED display screen control system for automatically matching display positions according to claim 3 is characterized in that: The system status matrix adopts a hierarchical structure design, including a display layer status submatrix, a transmission layer status submatrix and a control layer status submatrix. The display layer status submatrix records display position and display effect parameters, the transmission layer status submatrix records data transmission and encryption status parameters, and the control layer status submatrix records system operation and exception handling parameters.

8. The LED display screen control system for automatically matching display positions according to claim 3 is characterized in that: A dynamic key generation mechanism is used in the multi-level encrypted transmission process to calculate encryption parameters based on the operating parameters in the system state matrix. The encryption parameters are updated in real time with the system state and are used for primary encrypted transmission, secondary encrypted transmission and tertiary encrypted transmission.

9. The LED display screen control system for automatically matching display positions according to claim 3, characterized in that: The adaptive display control is implemented using a deep neural network model. By establishing a compensation effect evaluation index system, which includes a display position accuracy index, a transmission quality index and a display effect index, the control parameters are continuously optimized based on the evaluation results of the compensation effect evaluation index system.

10. The LED display screen control system for automatically matching display positions according to claim 3, characterized in that: The multivariate mixed decomposition calculation includes discrete wavelet transform decomposition operation and singular value decomposition operation. The brightness component and the chromaticity component are decomposed at multiple scales through the discrete wavelet transform decomposition operation. The extraction of the brightness stable component, the brightness fluctuation component, the chromaticity stable component and the chromaticity fluctuation component is realized through the singular value decomposition operation.

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