Partition correction method and system based on touch display module pin signal

Abstract

The invention relates to the technical field of touch display, and discloses a partition correction method and system based on a pin signal of a touch display module, and the method comprises the following steps: the pin signal of the touch display module is divided into a plurality of functional areas, and the functional areas comprise a display driving signal area, a touch signal area and a system control signal area; the invention further provides a partition correction system based on the touch display module pin signals, the partition correction system comprises a plurality of signal areas, each signal area is responsible for a specific signal transmission task, and each signal area comprises a display driving signal area, a touch signal area, a system control signal area and a physical isolation module. And physical isolation measures are arranged between the signal areas. The display driving signal area, the touch signal area and the system control signal area are reasonably divided, and the pin spacing adjustment and the shielding layer arrangement are adopted, so that the technical effects of reducing signal interference and optimizing signal transmission quality are achieved.

Description

Technical Field

[0001] The present invention relates to the field of touch display technology, and in particular to a partition correction method and system based on touch display module pin signals. Background Art

[0002] Touch display modules are an important component of modern electronic devices and are widely used in smart phones, tablet computers, smart homes, car navigation and other fields. They not only provide image display functions, but also respond to user touch inputs. With the continuous development of technology, the functions of touch display modules are becoming increasingly diversified, and performance requirements are becoming increasingly higher. In order to meet various requirements such as fast response, low power consumption, and high stability, the pin signal processing of touch display modules has become a crucial link. Especially in the case of multi-signal processing, how to ensure the independence and efficient transmission of different signals has become the key to design optimization.

[0003] Existing touch display modules adopt a pin signal zoning correction method, which divides the pin signals into multiple areas according to their functions, such as display drive signal area, touch signal area and system control signal area. Each area processes different types of signals to reduce mutual interference between signals. Some technical solutions also combine physical isolation measures, such as adjusting pin spacing, setting shielding layers and other measures to enhance the isolation effect between signal areas. At the same time, by monitoring signal quality and performing simple filtering processing, some systems can correct the signal in real time, thereby maintaining the stability of signal transmission.

[0004] However, the existing partition correction method of the pin signal of the touch display module often has a rough division of the signal area, and fails to fully consider the mutual influence between different signals, resulting in the difficulty of effectively controlling the interference of signals in complex environments. Most of the existing signal monitoring and correction methods only rely on static models and simple filters. These methods cannot accurately estimate and adjust the signal in real time and dynamically, especially in the case of complex electromagnetic environment or unstable signal quality. It is impossible to achieve the ideal effect. Most of the existing signal path optimization technologies only consider a single goal, such as signal strength or delay, and lack comprehensive optimization of multiple goals, which makes other factors in the signal transmission process, such as power consumption and signal loss, unable to be effectively balanced. Therefore, the present invention provides a partition correction method and system based on the pin signal of the touch display module to solve the shortcomings of the prior art. Summary of the invention

[0005] In view of the shortcomings of the prior art, the present invention provides a partition correction method and system based on the pin signal of the touch display module, which solves the problem that the drainage tube in the drainage device in the prior art is prone to bending and the drainage tube sealing operation is not convenient and stable when replacing the drainage bag.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: A partition correction method based on a touch display module pin signal comprises the following steps: Divide the pin signals of the touch display module into multiple functional areas, including a display drive signal area, a touch signal area, and a system control signal area; Physical isolation measures are provided between multiple functional areas, wherein the physical isolation measures reduce signal coupling effects by increasing pin spacing and providing a shielding layer; Deploy dummy pads in the functional area, wherein the dummy pads do not participate in signal transmission and are used to absorb excess signal energy; Calculate the coupling coefficient between functional areas based on physical field simulation and adjust the layout of the pin signal area; Dynamically monitor the quality of pin signals, and adjust the transmission path, strength and frequency according to the quality results of the monitored pin signals to optimize the stability and response speed of the pin signals.

[0007] Preferably, the physical isolation measures include the following steps: Increase the spacing between signal areas by properly designing the pin layout; By setting a shielding layer between different signal areas, interference between signals can be isolated; According to the electromagnetic field simulation results and the calculation of the signal coupling coefficient, the design parameters of the pin spacing and the shielding layer are dynamically adjusted.

[0008] Preferably, the design of the pin spacing and the shielding layer is optimized by physical field simulation and signal coupling effect calculation. The electromagnetic field simulation calculation is based on an electromagnetic field simulation model to calculate the coupling coefficient between the pin signal areas, and the design parameters of the pin spacing and the shielding layer are determined according to the simulation results. The calculation formula of the coupling coefficient is: ; in, For pin and pins The coupling coefficient between and They represent the electric field distribution of pins i and j respectively, S is the surface of the calculation area, is the dielectric constant of vacuum, Represents the small area element of the integral, i and is the index of the signal source.

[0009] Preferably, the signal coupling effect is further adjusted according to the electromagnetic field simulation results, the pin layout and the shielding layer design are optimized, the signal transmission path and the signal interference are optimized, and the pin layout is optimized by minimizing the coupling coefficient between the pins. The goal of the optimization process is: ; in, is the physical distance between pins, is the calculated coupling coefficient, and is the index of the signal source, Indicates the signal source and Not the same.

[0010] Preferably, the transmission path selection of the pin signal is optimized by a multi-objective optimization algorithm, and the optimization algorithm is implemented by particle swarm optimization (PSO). The particle swarm optimization update formula is: ; in, and Respectively represent The particle in The speed at the kth and kth iterations, and Respectively represent The particle in Second and The position at the iteration, W is the inertia weight, and is the learning factor, and is a random number between [0,1], is the i-th particle in the The personal best position at iteration , is the global best position.

[0011] Preferably, the quality monitoring of the pin signal is implemented by a Kalman filter, and the update formula of the Kalman filter is: ; ; in, is the state variable of the signal, The system is at time The state vector of is the state transfer matrix, is the control input matrix, is the control input, is the process noise, is the observed value, is the observation matrix, To measure noise.

[0012] Preferably, the total loss of the pin signal transmission path is: ; in, is the integral value of the function on the path, is a path, indicating that the integral is performed along this path, is on the path The function defined above, represents a small change in the path, Is the path A variable on .

[0013] Preferably, the position and size of the dummy pad are dynamically adjusted according to the electromagnetic field simulation results and the signal interference intensity, specifically: The size of the dummy pad is optimized according to the signal strength and frequency of the pin signal area; The position of the dummy pad is determined by calculating the electric field distribution and electromagnetic coupling coefficient of each signal area to determine its optimal position in the signal area; The dummy pad can adjust the position and size in real time according to different interference environments to ensure the stability of signal transmission.

[0014] Preferably, the dynamically monitoring the quality of the pin signal and adjusting the signal transmission path according to the real-time feedback includes: The dynamic monitoring module evaluates the signal quality by real-time sampling of current, voltage and electromagnetic field parameters on the signal transmission path; When the signal quality decreases, the signal strength and transmission mode of the transmission path are automatically adjusted through the feedback mechanism; The feedback adjustment process is based on a Kalman filter algorithm and a dynamic correction model of signal strength, combined with external environmental data, to optimize the signal path and control signal attenuation and interference in real time.

[0015] The present invention also provides a partition correction system based on the pin signal of the touch display module, comprising the following modules: Multiple signal areas, each signal area is responsible for a specific signal transmission task, and the signal areas include a display drive signal area, a touch signal area, and a system control signal area; A physical isolation module, used to set physical isolation measures between the signal areas, including adjustment of pin spacing and setting of a shielding layer; Signal monitoring module, used to dynamically monitor signal quality and estimate and correct signal status in real time in combination with Kalman filter; Signal path optimization module, which optimizes the signal transmission path through variational method and multi-objective optimization algorithm to minimize signal loss and interference; Intelligent feedback module, which identifies signal interference patterns through deep learning algorithms and optimizes signal transmission parameters in real time based on historical data.

[0016] The present invention provides a partition correction method and system based on the pin signal of a touch display module, which has the following beneficial effects: 1. The present invention adopts a technical solution of signal area division and physical isolation. By reasonably dividing the display drive signal area, the touch signal area and the system control signal area, and taking pin spacing adjustment and shielding layer setting, different signal areas are effectively isolated; the technical effect of reducing interference between signals and optimizing signal transmission quality is achieved. Compared with the solution in the prior art with unclear signal areas and large interference, the problem of unstable transmission and poor signal quality caused by signal interference is solved.

[0017] 2. The present invention adopts a solution that combines the Kalman filter with the dynamic signal monitoring technology. By estimating and correcting the signal state in real time, it can accurately monitor the quality of the signal and make rapid adjustments. It achieves the technical effect of ensuring stable transmission of the signal in a complex environment. Compared with the existing technology in which signal monitoring is not accurate enough and interference is difficult to eliminate in real time, it solves the problems of signal distortion and large fluctuations.

[0018] 3. The present invention adopts the variational method and multi-objective optimization algorithm to optimize the signal path, and dynamically adjusts the signal transmission path by considering multi-dimensional objectives such as signal strength, delay and power consumption; it achieves the technical effect of achieving the best balance among multiple objectives. Compared with the solution of only optimizing a single objective in the prior art, it solves the technical problems of insufficient signal path optimization and the inability to take into account multiple objectives at the same time.

[0019] 4. The present invention adopts an intelligent feedback mechanism, which uses a deep learning algorithm to identify signal interference patterns in real time and optimize signal transmission parameters, thereby enhancing the system's adaptive adjustment capability. It achieves the technical effect of responding to environmental changes in real time during signal transmission. Compared with the prior art solutions that rely on static optimization, it solves the problem of being unable to respond flexibly to complex and dynamic environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 is a flow chart of the method steps of the present invention; Figure 2 It is a system architecture diagram of the present invention. DETAILED DESCRIPTION

[0021] The following will be combined with the drawings in the specification of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] Please refer to the attached Figure 1 The embodiment of the present invention provides a partition correction method based on the pin signal of the touch display module, which solves the problems of signal interference, signal attenuation and transmission delay by signal area division, physical isolation, signal monitoring and path optimization, combined with multi-objective optimization algorithm and intelligent feedback mechanism. The method includes the following steps: S1. Divide the pin signals of the touch display module into multiple functional areas, including a display drive signal area, a touch signal area, and a system control signal area; S2. Physical isolation measures are set between multiple functional areas, and the physical isolation measures reduce the signal coupling effect by increasing the pin spacing and setting a shielding layer; S3. Deploy dummy pads in the functional area, wherein the dummy pads do not participate in signal transmission and can effectively absorb excess signal energy; S4. Calculate the coupling coefficient between the functional areas based on physical field simulation and adjust the layout of the pin signal area; S5. Dynamically monitor the quality of the pin signal, and adjust the transmission path, strength and frequency according to the quality results of the monitored pin signal to optimize the stability and response speed of the pin signal.

[0023] For step S1, in this embodiment, the pin signal of the touch display module is first divided into multiple functional areas, each area only processes a specific type of signal. Generally, the signal partition will include a display drive signal area, a touch signal area and a system control signal area. The display drive signal area is responsible for image transmission related to the display, the touch signal area is specifically responsible for receiving touch input signals, and the system control signal area processes other control signals to ensure stable operation of the system. This partition design can avoid cross-interference of different signals in the same area and reduce the influence of coupling effects on signal quality.

[0024] Specifically, the design of signal partitioning should take into account the signal strength, frequency and other electrical characteristics. Display signals and touch signals usually have different electrical characteristics. They differ in frequency and signal strength. In order to ensure effective signal transmission and avoid cross-interference, these signals are divided into different areas, and physical isolation measures are set between areas, which can significantly improve the independence of the signals.

[0025] As an option, the functional area division can also be fine-tuned according to the signal power requirements and operating frequency. In some embodiments, the touch signal and the display signal may share the same pin or circuit during operation. Therefore, through further refined partition design, such as separating high-frequency signals from low-frequency signals, or separating high-power signals from low-power signals, signal interference can be further reduced. The pin signal transmission in certain areas may be affected by the external environment. At this time, the layout of the area can be appropriately adjusted to make the signal transmission more stable.

[0026] In some embodiments, in order to improve the anti-interference ability of the system, excess signal energy can be absorbed by setting up dummy pads. The dummy pads do not participate in signal transmission, but by optimizing the layout position of the pads, excess electromagnetic wave energy can be effectively shielded and absorbed, further reducing mutual interference between signals. This approach is particularly suitable for high-frequency signal areas and can prevent high-frequency signals from interfering with surrounding low-frequency signal areas.

[0027] In one possible implementation, the pin signal partition layout is not just about dividing the signal into multiple blocks, but rather making precise plans by conducting a detailed analysis of each area, taking into account the signal's range, working conditions, and the degree of interference with other signal areas in each area. Electromagnetic field simulation and numerical optimization algorithms can be used to simulate and calculate the signal transmission path to ensure that the signal transmission quality in each area is optimized.

[0028] In this embodiment, further signal partitioning design takes into account the physical isolation between signal areas, which is not only achieved through the spacing between pins, but also possible through the setting of a shielding layer to improve the signal transmission quality. The purpose of the shielding layer design is to isolate the electromagnetic fields of different signal areas to avoid cross-interference of electromagnetic waves. In some cases, specific materials can also be used to construct the shielding layer. These materials have strong electromagnetic wave absorption capabilities and can effectively reduce the coupling effect between signals.

[0029] In the implementation process, the layout of each signal area can be adjusted according to the calculated coupling coefficient. Specifically, the coupling coefficient between the pin signal areas is closely related to the physical spacing between the pins and the effectiveness of the shielding layer. By simulating and optimizing these parameters, the interference between signals can be further reduced, and the stability and signal quality of the system can be improved.

[0030] For the calculation formula of the coupling coefficient between different signal areas, we use the following formula to describe the coupling effect between signals: ; in, For pin and pins The coupling coefficient between and Respectively represent pins and The electric field distribution, is the surface of the computational area, is the dielectric constant of vacuum, represents the small area element of the integral, and is the index of the signal source.

[0031] Through this formula, we can get the coupling strength between different signal areas and adjust the physical isolation measures of the areas accordingly (such as adjusting the pin spacing and setting a shielding layer). This coupling coefficient calculation can help us accurately plan the pin layout during design and ensure signal stability.

[0032] In this embodiment, the specific signal area division and layout adjustment can be achieved by the following steps: Based on the electromagnetic field simulation model, we calculate the electromagnetic field distribution between each signal area and obtain the coupling coefficient between signal areas. Through this simulation, we can clearly identify which areas have higher signal interference and make adjustments during the design stage.

[0033] Based on the results of the coupling coefficient, the spacing between pins is dynamically adjusted to increase the physical isolation between signal areas, and appropriate shielding layers are designed and set to further reduce signal interference.

[0034] According to the distribution of signal strength and frequency, dummy pads are deployed in each signal area. The position and size of the pads are determined through electromagnetic field simulation and coupling coefficient calculation to ensure that they can effectively absorb signal interference.

[0035] For step S2, in this embodiment, the setting of physical isolation measures mainly includes the following aspects: first, increase the pin spacing between signal areas to reduce the coupling strength between signal paths, and appropriately set a shielding layer to further isolate the signal area to prevent electromagnetic interference between different signals. The setting of the shielding layer can improve the signal isolation effect through different materials and structural designs, which is particularly important in the transmission process of high-frequency signals. The optimization of physical isolation measures will be dynamically adjusted according to the electromagnetic field simulation results and the calculation results of the signal coupling coefficient to ensure the stability of the signal transmission path and minimize interference.

[0036] Generally speaking, when designing physical isolation, you first need to determine the functional requirements of the signal area, as well as the signal strength, frequency and other parameters between the signal areas. These factors will affect the design of isolation between areas. Touch signals and display signals usually have different operating frequencies, so they need to be properly separated in physical layout. Specifically, the physical spacing between signal areas and the thickness and material of the shielding layer will be adjusted according to these parameters.

[0037] As an option, increasing the pin spacing between signal areas is an effective way of physical isolation. By increasing the spacing between signal areas, the coupling strength between signal paths can be effectively reduced, reducing signal cross-interference. Specifically, the spacing between pins should be designed based on factors such as the signal frequency and the power of signal transmission. For low-frequency signal areas, the pin spacing can be appropriately increased; for high-frequency signal areas, more electromagnetic field influencing factors need to be considered to reasonably determine the spacing.

[0038] In one possible implementation, the design of the shielding layer between signal areas is particularly important. The shielding layer can effectively block the propagation of electromagnetic waves and reduce mutual interference between signals. The design of the shielding layer needs to select appropriate materials based on the electric field distribution and operating frequency of the signal area. Some commonly used high-conductivity materials (such as copper or aluminum) can be used to construct the shielding layer. The thickness and surface shape of the shielding layer will also affect its shielding effect, and the design needs to be optimized according to actual conditions.

[0039] In some embodiments, the physical isolation design can be further optimized through simulation calculations. Through electromagnetic field simulation, the electric field distribution between each signal area is calculated, and combined with the calculation results of the coupling coefficient, the layout and physical spacing of the signal area are adjusted. This process usually involves numerical optimization algorithms and finite element simulation technology to ensure the effectiveness of the design results in practical applications.

[0040] In this embodiment, the optimization of physical isolation measures not only relies on empirical design, but also ensures the independence of each signal area through electromagnetic field simulation and calculation of coupling effect. Specifically, electromagnetic field simulation calculation can help determine the electric field distribution between different signal areas and further calculate the coupling coefficient. Coupling coefficient It can be calculated by the following formula: ; in, For pin and pins The coupling coefficient between and They represent the electric field distribution of pins i and j respectively, is the surface of the calculation area, is the vacuum dielectric constant, represents the small area element of the integral, and is the index of the signal source.

[0041] Specifically, electromagnetic field simulation can be used to analyze the electromagnetic field distribution during signal transmission in detail. Based on the simulation results, the system can dynamically adjust the pin layout and shielding layer design of each signal area. When the coupling coefficient of a certain area is too high, the system will automatically adjust the signal layout of that area, increase the pin spacing or strengthen the shielding layer to reduce interference between signals.

[0042] In the actual implementation process, physical isolation measures are not only completed in the design stage, but can also be adjusted dynamically to further optimize signal transmission. Under different working conditions, the strength and frequency of the signal may change. At this time, the system can adjust the physical isolation design of the signal area based on real-time feedback. By combining electromagnetic field simulation and real-time monitoring data, the system can adaptively adjust the shielding layer and pin layout in different environments to maintain the stability of signal transmission.

[0043] In some embodiments, the physical isolation design can also achieve real-time feedback through sensors and monitoring systems. By monitoring the coupling between signal areas and signal quality in real time, the system can dynamically adjust the signal path and optimize the signal transmission effect. This real-time feedback mechanism can ensure that interference during signal transmission is minimized and the signal quality is always in the best state.

[0044] For step S3, in this embodiment, by real-time sampling of the current, voltage and electromagnetic field parameters of the signal, the system can accurately evaluate the quality of the signal, and based on this evaluation result, dynamically adjust the signal transmission path and signal strength. Specifically, when a decrease in signal quality is detected, the system will automatically adjust the signal path to reduce interference and improve signal stability. This process is not limited to simple path selection, but also involves dynamic correction and optimization during signal transmission to ensure efficient signal transmission.

[0045] Generally speaking, the signal transmission path may be affected by external environmental factors, resulting in signal attenuation or interference. High temperature, humidity changes, electromagnetic environment changes and other factors may lead to a decrease in signal quality. Therefore, real-time monitoring of signal quality and correction is the key to ensuring signal transmission stability.

[0046] As an option, dynamic signal monitoring uses high-frequency sampling technology to sample the signal's strength, frequency, phase, etc. in real time to obtain signal quality parameters. The signal monitoring module can detect signal attenuation, delay, and interference in real time, and evaluate changes in signal quality based on the monitoring results. Signal quality assessment is usually done through current, voltage, electromagnetic field parameters, etc. These parameters can reflect various changes in the signal during transmission, including a decrease in signal strength, an increase in noise, etc. By analyzing these changes, the system can accurately determine the transmission status of the signal.

[0047] In one possible implementation, the monitoring and real-time correction of signal quality is accomplished through a Kalman filter. The Kalman filter can recursively estimate the state of the signal and optimize the signal transmission path based on the real-time measurement results. This process can be described based on the following formula: ; ; in, is the state variable of the signal, The system is at time The state vector of is the state transfer matrix, is the control input matrix, is the control input, is the process noise, is the observed value, is the observation matrix and is the measurement noise. Through this calculation, the Kalman filter can continuously correct the error in the signal path and ensure the stability of the signal transmission process.

[0048] Based on the signal quality monitoring, the next step is to optimize the signal transmission path. Signal path optimization is not just about choosing the shortest path, but also about comprehensively considering factors such as signal strength, transmission delay, signal attenuation and interference. Through the multi-objective optimization algorithm, the system can optimize multiple parameters at the same time and select a comprehensive optimal signal transmission path.

[0049] In this embodiment, the signal path is optimized using a particle swarm optimization (PSO) algorithm, which can search and optimize the signal path in a multi-dimensional space. The PSO algorithm simulates the group behavior of particles to find the optimal solution and has good global search capabilities. Specifically, the update formula of the particle swarm optimization is: ; ; in, and Respectively represent the i-th particle in the Second and The speed at the iteration, and Respectively represent The position of a particle at the k+1th and kth iterations is the inertia weight, and is the learning factor, and is a random number between [0,1], It is The particle in The personal best position at iteration , is the global optimal position. Through continuous iteration, the particle swarm optimization algorithm can find a balance point between multiple objectives, thereby achieving the optimal selection of the signal path.

[0050] During the signal transmission process, the system will provide real-time feedback and adjust the signal transmission path according to changes in signal quality. Specifically, when the signal quality decreases, the feedback mechanism will be activated to automatically adjust the signal transmission path. This adjustment is not only about selecting a new path, but also includes the optimization of signal strength, frequency and other parameters. Through this process, the system can ensure the stability and accuracy of the signal under different working conditions.

[0051] For example, when the system detects that a certain signal path has high attenuation or interference, the feedback mechanism will automatically select a path with less interference and increase the transmission strength of the signal to ensure that the signal can be stably transmitted to the target area. In some embodiments, the feedback adjustment process combines the Kalman filter and real-time monitoring data to ensure that each adjustment can maximize the optimization of signal quality.

[0052] For step S4, in this embodiment, by continuously collecting signal status data and using a deep learning model to identify the changing pattern of signal quality, the signal transmission path is optimized and adjusted. Different from the aforementioned Kalman filter and particle swarm optimization, this step focuses more on intelligent adaptive adjustment, optimizing the transmission path and parameter settings through feedback data to ensure the continuous stability of the signal.

[0053] Generally speaking, during signal transmission, the signal quality may fluctuate due to factors such as temperature, humidity, and electromagnetic interference. At this time, the intelligent feedback mechanism can continuously evaluate the signal quality based on real-time monitoring data and deep learning algorithms, thereby triggering path optimization or parameter adjustment.

[0054] As an option, the feedback mechanism monitors the current, voltage, and electromagnetic field changes of the signal in real time through sensors. By analyzing these real-time sampled data, the system can identify the changing trend of signal quality and make timely adjustments. The adjustment can be to optimize the signal path, enhance the signal strength, or adjust the signal transmission frequency. Specifically, the goal of the feedback mechanism is to dynamically adjust the various transmission parameters of the signal according to the real-time signal quality so that the signal always remains in the optimal state.

[0055] In one possible implementation, deep learning models (such as convolutional neural networks) can be used to perform pattern recognition on signal quality. By training on a large amount of historical data, deep learning models can identify patterns of signal quality degradation and predict the type of interference or signal attenuation trends that may occur. Based on these predictions, the system can make adjustments in advance to reduce signal interference and improve signal stability.

[0056] Specifically, after receiving the feedback signal, the system will make adaptive adjustments based on the monitored signal quality. The adjustment process first analyzes the feedback data through a deep learning algorithm to identify the cause of the signal quality degradation, such as electromagnetic interference, signal path attenuation, or equipment failure. Then, based on the analysis results, the system will automatically select the appropriate optimization strategy for adjustment.

[0057] For example, in some embodiments, when the signal quality is reduced due to environmental interference, the system can compensate for the loss by selecting a more stable transmission path or by increasing the signal transmission strength. If the signal attenuation is caused by a device failure, the system can automatically adjust the device's operating mode or frequency to re-optimize the signal transmission method.

[0058] In some embodiments, feedback adjustment is not limited to optimization of the signal path, but may also involve adjustment of other system parameters. The system can improve signal quality and reduce interference by adjusting the operating frequency, increasing the signal transmission bandwidth, or changing the power output. The system adjusts these parameters in real time according to the feedback signal to ensure that the signal can be transmitted stably and meet the response requirements of the device.

[0059] In this embodiment, the adjustment process of the feedback mechanism is combined with real-time data, and adaptive adjustment based on deep learning and other algorithms is adopted. The deep learning model identifies interference patterns and signal attenuation trends by processing real-time feedback data, and the system uses optimization algorithms (such as particle swarm optimization, Kalman filtering, etc.) to adjust the signal transmission path and related parameters. The deep learning model provides a highly predictive signal quality assessment mechanism in this optimization process, which can predict before the signal quality deteriorates, so as to make adjustments in advance.

[0060] Specifically, the following optimization formula may be used in the signal quality adjustment process: ; ; in, is the state variable of the signal, The system is at time The state vector of is the state transfer matrix, is the control input matrix, is the control input, is the process noise, is the observation value, is the observation matrix, To measure noise, the Kalman filter is combined with a feedback mechanism to ensure real-time optimization of signal quality by continuously updating the state variables of the signal.

[0061] During the signal transmission process, the combination of feedback mechanism and path optimization algorithm can ensure that the signal transmission path is always in the best state. When the system detects attenuation or increased interference in the signal path, the feedback mechanism will trigger dynamic adjustment of the path; and optimization algorithms such as particle swarm optimization or Kalman filtering will ensure that the adjusted path can effectively reduce signal interference and improve transmission stability under multi-objective optimization.

[0062] For step S5, in this embodiment, a multi-objective optimization algorithm such as particle swarm optimization (PSO) is applied to optimize the signal path under multi-dimensional objectives. The particle swarm optimization algorithm is an algorithm that simulates the foraging behavior of bird flocks in nature and can perform a global search in a multi-dimensional space to find the optimal solution. In the selection of the signal transmission path, the PSO algorithm optimizes based on multiple factors such as signal strength, transmission delay, and interference level to ensure the best transmission path for the signal in a complex environment.

[0063] Generally, during signal transmission, multiple factors need to be considered, such as signal strength, transmission delay, power consumption, interference minimization, etc. Traditional optimization algorithms usually only consider a single goal, while the multi-objective optimization algorithm used in the present invention can optimize multiple goals at the same time to ensure the overall performance of signal transmission.

[0064] Specifically, in this embodiment, the optimization goal of the signal path is not only to minimize interference, but also to comprehensively consider factors such as signal strength, delay, power consumption, etc. As an option, the signal strength should be kept high during the transmission process to ensure the clarity and accuracy of the signal; while the signal delay and power consumption should be minimized to improve the response speed and energy efficiency of the system.

[0065] In this multi-objective optimization, the particle swarm optimization algorithm (PSO) plays an important role. The PSO algorithm simulates how a flock of birds cooperates in the process of finding food to achieve the optimal goal, and can find the optimal solution in a complex signal environment. In the optimization process, a particle represents a possible solution, and the algorithm continuously adjusts the position of each particle to eventually find the optimal solution.

[0066] In one possible implementation, the update formula of particle swarm optimization is: ; ; in, and Respectively represent The particle in The speed at the kth and kth iterations, and denote the number of particles in the first and second The position at the iteration, W is the inertia weight, and is the learning factor, and is a random number between [0,1], It is The particle in The personal best position at iteration , is the global best position.

[0067] In this embodiment, the optimization objectives include the following aspects: Minimize signal interference: Ensure efficient signal transmission by minimizing coupling and interference between signals.

[0068] Maximize signal strength: While ensuring signal quality, enhance signal transmission strength to avoid signal attenuation during transmission.

[0069] Minimize transmission delay: optimize path selection, reduce signal transmission delay, and improve response speed.

[0070] Minimize power consumption: Under the premise of signal strength and path optimization, reduce power consumption as much as possible to improve the energy efficiency of the system. These optimization goals can be combined by weight to obtain a comprehensive optimization objective function. In some embodiments, the expression of the objective function is: ; in, is the objective function, which represents the minimization target of the optimization problem. are multiple objective functions, representing different optimization objectives. The decision variable vector represents all variables that affect system performance. During the optimization process, the PSO algorithm searches for the optimal path and signal parameters based on the combination of objective functions to achieve a balance between multiple objectives.

[0071] Specifically, through the PSO algorithm system, it can balance multiple objectives and select the optimal signal transmission path. In high-frequency signal transmission, the system will reduce attenuation by adjusting path selection and enhancing signal strength, while reducing signal interference and delay by optimizing path design.

[0072] In some embodiments, the optimization results of the PSO algorithm can find the global optimal solution in a relatively short time, improve the transmission efficiency of the signal, and reduce signal loss and errors. In addition, through particle swarm optimization, the system can adaptively adjust the signal transmission parameters so that the signal transmission can achieve the best effect in different environments.

[0073] The partition correction system based on the touch display module pin signal described below and the partition correction method based on the touch display module pin signal described above can be referred to each other.

[0074] Please refer to the attached Figure 2 The present invention also provides a partition correction system based on the pin signal of the touch display module. The system can realize accurate partitioning, effective isolation, real-time monitoring, dynamic optimization and intelligent adjustment of the pin signal in the touch display module through a signal area partition module, a physical isolation module, a signal monitoring module, a signal path optimization module and an intelligent feedback module, thereby achieving the effect of significantly reducing signal interference, improving signal transmission quality, reducing signal delay and power consumption. The system can maintain signal stability and transmission accuracy in a complex electromagnetic environment, ensure the response speed of the device and user experience, and has high adaptability and scalability.

[0075] Multiple signal areas refer to the division of pin signals into different areas in the touch display module according to signal type and functional requirements, and each area is responsible for processing specific signal transmission tasks.

[0076] The display drive signal area is responsible for the transmission of display-related signals, including image display, brightness adjustment and other tasks. The signal strength and frequency of the display drive signal area are usually high, and the stability and clarity of the signal transmission need to be ensured.

[0077] The touch signal area is used to receive touch input signals, including touch position, pressure and other data. These signals need to be transmitted very accurately, so the design of this area needs to reduce interference and ensure fast signal response.

[0078] The system control signal area processes the system control signals of the equipment, such as power control, system status indication, etc. Such signals usually do not involve high-frequency signals, so the stability and electromagnetic compatibility of the system are the key considerations during design.

[0079] For physically isolated modules, physical means are used to reduce mutual interference between signal areas, including the following measures: By reasonably increasing the pin spacing between signal areas, the interference caused by electromagnetic coupling during signal transmission can be reduced. The physical spacing between signal areas can be dynamically adjusted according to the signal type and frequency to ensure that each signal area can work independently and stably.

[0080] To further improve the signal isolation effect, a shielding layer is set between signal areas. The shielding layer can effectively absorb and block the propagation of electromagnetic waves, thereby avoiding mutual interference between different signal areas. The material and thickness of the shielding layer can be selected according to specific application requirements to provide stronger electromagnetic shielding capabilities.

[0081] For the signal monitoring module, the signal quality is monitored in real time and the signal state is estimated and corrected in combination with the Kalman filter.

[0082] Through sensors and sampling circuits, the signal parameters such as current, voltage, frequency and phase are monitored in real time to evaluate the quality and stability of the signal. When the signal quality decreases, it can be discovered in time and corresponding corrective measures can be taken.

[0083] The application of Kalman filter in the signal monitoring module can recursively estimate the signal state. It corrects the signal error in real time by combining the actual observation value with the system model prediction value. The Kalman filter can effectively eliminate the noise in the signal, enhance the stability of the signal, and provide a more accurate signal transmission quality assessment.

[0084] For the signal path optimization module, the signal transmission path is optimized by variational method and multi-objective optimization algorithm to minimize signal loss and interference.

[0085] The calculus of variations is a mathematical method commonly used to optimize paths. In signal path optimization, the calculus of variations is used to minimize the total loss on the signal path, thereby obtaining the optimal transmission path. This method is particularly suitable for multi-path signal transmission scenarios and can find the best path between multiple signal areas.

[0086] The multi-objective optimization algorithm can find the best balance between multiple optimization objectives (such as signal strength, transmission delay, power consumption and interference). In the signal path optimization module, algorithms such as particle swarm optimization (PSO) are used to adjust the signal transmission path and transmission parameters, comprehensively consider the weights and priorities of different objectives, and select the most suitable path.

[0087] For the intelligent feedback module, a deep learning algorithm is used to identify signal interference patterns and optimize signal transmission parameters in real time based on historical data.

[0088] Deep learning algorithms can learn interference patterns and signal quality change patterns in signal transmission by training on a large amount of historical data. In the real-time feedback process, deep learning models can predict signal quality change trends, identify possible interference sources, and make adaptive adjustments based on the prediction results.

[0089] Based on the output of the deep learning algorithm, the intelligent feedback module can optimize the signal transmission path, signal strength, frequency and other parameters in real time to ensure that the signal maintains optimal performance under changing environmental conditions. This intelligent feedback mechanism can effectively improve the system's adaptive and anti-interference capabilities, ensuring that the signal is always in a stable state under complex working conditions.

[0090] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A partition correction method based on a touch display module pin signal, characterized in that: The following steps are involved: Divide the pin signals of the touch display module into multiple functional areas, including a display drive signal area, a touch signal area, and a system control signal area; Physical isolation measures are provided between multiple functional areas, wherein the physical isolation measures reduce signal coupling effects by increasing pin spacing and providing a shielding layer; Deploy dummy pads in the functional area, wherein the dummy pads do not participate in signal transmission and are used to absorb excess signal energy; Calculate the coupling coefficient between functional areas based on physical field simulation and adjust the layout of the pin signal area; Dynamically monitor the quality of pin signals, and adjust the transmission path, strength and frequency according to the quality results of the monitored pin signals to optimize the stability and response speed of the pin signals.

2. The partition correction method based on the touch display module pin signal according to claim 1 is characterized in that: The physical isolation measures include the following steps: Increase the spacing between signal areas by properly designing the pin layout; Isolate interference between signals by setting a shielding layer between different signal areas; According to the electromagnetic field simulation results and the calculation of the signal coupling coefficient, the design parameters of the pin spacing and the shielding layer are dynamically adjusted.

3. The partition correction method based on the touch display module pin signal according to claim 2 is characterized in that: The design of the pin spacing and the shielding layer is optimized by physical field simulation and signal coupling effect calculation. The electromagnetic field simulation calculation is based on the electromagnetic field simulation model to calculate the coupling coefficient between the pin signal areas, and the design parameters of the pin spacing and the shielding layer are determined according to the simulation results. The calculation formula of the coupling coefficient is: ; in, For pin and pins The coupling coefficient between and Respectively represent pins and The electric field distribution, is the surface of the computational area, is the dielectric constant of vacuum, represents the small area element of the integral, and is the index of the signal source.

4. The partition correction method based on the touch display module pin signal according to claim 2 is characterized in that: The signal coupling effect is further adjusted based on the electromagnetic field simulation results, and the pin layout and shielding layer design are designed to optimize the signal transmission path and signal interference. The pin layout is optimized by minimizing the coupling coefficient between pins. The goal of the optimization process is: ; in, is the physical distance between pins, is the calculated coupling coefficient, and is the index of the signal source, Indicates the signal source and Not the same.

5. The partition correction method based on the touch display module pin signal according to claim 1, characterized in that: The transmission path selection of the pin signal is optimized by a multi-objective optimization algorithm, and the optimization algorithm is implemented by particle swarm optimization. The particle swarm optimization update formula is: ; ; in, and Respectively represent The particle in Second and The speed at the iteration, and Respectively represent The particle in Second and The position at the iteration, is the inertia weight, and is the learning factor, and is a random number between [0,1], It is The particle in The personal best position at iteration , is the global best position.

6. The partition correction method based on the touch display module pin signal according to claim 1, characterized in that: The quality monitoring of the pin signal is achieved through a Kalman filter, and the update formula of the Kalman filter is: ; ; in, is the state variable of the signal, The system is at time The state vector of is the state transfer matrix, is the control input matrix, is the control input, is the process noise, is the observed value, is the observation matrix, To measure noise.

7. The partition correction method based on the touch display module pin signal according to claim 1, characterized in that: The total loss of the pin signal transmission path is: ; in, Is the path Upper function The integral value of is a path, indicating that the integral is performed along this path, is on the path The function defined above, represents a small change in the path, Is the path A variable on .

8. The partition correction method based on the touch display module pin signal according to claim 1, characterized in that: The position and size of the dummy pad are dynamically adjusted according to the electromagnetic field simulation results and the signal interference intensity, specifically: The size of the dummy pad is optimized according to the signal strength and frequency of the pin signal area; The position of the dummy pad is determined by calculating the electric field distribution and electromagnetic coupling coefficient of each signal area to determine its optimal position in the signal area; The dummy pad can adjust the position and size in real time according to different interference environments to ensure the stability of signal transmission.

9. The partition correction method based on the touch display module pin signal according to claim 1, characterized in that: The method of dynamically monitoring the quality of the pin signal and adjusting the signal transmission path according to the real-time feedback includes: The dynamic monitoring module evaluates the signal quality by real-time sampling of current, voltage and electromagnetic field parameters on the signal transmission path; When the signal quality decreases, the signal strength and transmission mode of the transmission path are automatically adjusted through the feedback mechanism; The feedback adjustment process is based on a Kalman filter algorithm and a dynamic correction model of signal strength, combined with external environmental data, to optimize the signal path and control signal attenuation and interference in real time.

10. A partition correction system based on a touch display module pin signal, applied to a partition correction method based on a touch display module pin signal according to any one of claims 1 to 9, characterized in that: Includes the following modules: Multiple signal areas, each signal area is responsible for a specific signal transmission task, and the signal areas include a display drive signal area, a touch signal area, and a system control signal area; A physical isolation module, used to set physical isolation measures between the signal areas, including adjustment of pin spacing and setting of a shielding layer; Signal monitoring module, used to dynamically monitor signal quality and combine Kalman filter to estimate and correct signal status in real time; Signal path optimization module, which optimizes the signal transmission path through variational method and multi-objective optimization algorithm to minimize signal loss and interference; Intelligent feedback module, which identifies signal interference patterns through deep learning algorithms and optimizes signal transmission parameters in real time based on historical data.

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