Partition correction method and system based on pin signals of a touch display module

Abstract

The present invention relates to the technical field of touch display, and discloses a partition correction method and system based on the pin signals of a touch display module, including the following steps: dividing the pin signals of the touch display module into multiple functional regions, where the functional regions include a display driving signal region, a touch signal region, and a system control signal region; setting physical isolation measures between the multiple functional regions. The present invention also provides a partition correction system based on the pin signals of a touch display module, including: multiple signal regions, each signal region being responsible for a specific signal transmission task, the signal regions including a display driving signal region, a touch signal region, and a system control signal region, and a physical isolation module for setting physical isolation measures between the signal regions. The present invention achieves the technical effect of reducing interference between signals and optimizing the signal transmission quality by reasonably dividing the display driving signal region, the touch signal region, and the system control signal region, and taking measures such as adjusting the pin pitch and setting a shielding layer.

Description

Technical Field

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

[0002] The touch display module is an important component in modern electronic devices and is widely used in fields such as smart phones, tablet computers, smart homes, and car navigation. It not only provides an image display function but also enables response to user touch input. With the continuous development of technology, the functions of touch display modules are becoming increasingly diverse, and the performance requirements are also getting higher and higher. To meet various requirements such as fast response, low power consumption, and high stability, the processing of pin signals of touch display modules has become a crucial link. Especially in the case of multi-signal processing, how to ensure the mutual independence and efficient transmission between different signals has become the key to design optimization.

[0003] Existing touch display modules adopt a method for partition correction of pin signals. By dividing the pin signals into multiple regions according to functions, such as a display drive signal region, a touch signal region, and a system control signal region, each region processes different types of signals to reduce the mutual interference between signals. Some technical solutions also combine physical isolation means, such as adjusting the pin pitch and setting shielding layers, etc., to enhance the isolation effect between signal regions. At the same time, by monitoring the signal quality and performing simple filtering processing, some systems can perform real-time correction on the signals to maintain the stability of signal transmission.

[0004] However, in the existing method for partition correction of pin signals of touch display modules, the division of signal regions is often relatively rough, and the mutual influence between different signals is not fully considered, resulting in the difficulty of effectively controlling signal interference in complex environments. Most of the existing signal monitoring and correction methods only rely on static models and simple filters, and these methods cannot accurately estimate and adjust signals in real time and dynamically. Especially in complex electromagnetic environments or unstable signal quality, the ideal effect cannot be achieved. Moreover, most of the existing signal path optimization technologies only consider a single target, such as signal strength or delay, and lack comprehensive optimization of multiple targets, which makes other factors such as power consumption and signal loss during signal transmission not be effectively balanced. Therefore, the present invention provides a method and system for partition correction based on pin signals of a touch display module to solve the deficiencies existing in the prior art. Summary of the Invention

[0005] Aiming at the deficiencies of the prior art, the present invention provides a method and system for partition correction based on pin signals of a touch display module, which solves the problems that the drainage tube in the drainage device in the prior art is prone to bending and the operation of blocking the drainage tube when replacing the drainage bag is not convenient and stable enough.

[0006] To achieve the above object, the present invention is realized through the following technical solutions: A partition correction method based on the pin signals of a touch display module, comprising the following steps:

[0007] Divide the pin signals of the touch display module into multiple functional areas, and the functional areas include a display driving signal area, a touch signal area, and a system control signal area;

[0008] Set physical isolation measures between multiple functional areas, and the physical isolation measures reduce the signal coupling effect by increasing the pin pitch and setting a shielding layer;

[0009] Deploy dummy pads inside the functional area, and the dummy pads do not participate in signal transmission and are used to absorb excess signal energy;

[0010] Based on physical field simulation, calculate the coupling coefficient between each functional area, and adjust the layout of the pin signal area;

[0011] Dynamically monitor the quality of the pin signals, and adjust the transmission path, intensity, and frequency according to the monitoring results of the pin signal quality to optimize the stability and response speed of the pin signals.

[0012] Preferably, the physical isolation measures include the following steps:

[0013] By reasonably designing the pin layout, increase the distance between signal areas;

[0014] By setting a shielding layer between different signal areas, isolate the interference between signals;

[0015] According to the electromagnetic field simulation results and the calculation of the signal coupling coefficient, dynamically adjust the design parameters of the pin pitch and the shielding layer.

[0016] Preferably, the design of the pin pitch and the shielding layer is optimized through physical field simulation and signal coupling effect calculation. The electromagnetic field simulation calculation is based on an electromagnetic field simulation model, calculates the coupling coefficient between the pin signal areas, and determines the design parameters of the pin pitch and the shielding layer according to the simulation results. The calculation formula of the coupling coefficient is:

[0017]

[0018] Among them, C ij is the coupling coefficient between pin i and pin j, E i and E j respectively represent the electric field distributions of pins i and j, S is the surface of the calculation area, ∈0 is the vacuum permittivity, dA represents the infinitesimal area element of the integral, and i and j are the indices of the signal sources.

[0019] Preferably, based on the electromagnetic field simulation results, the signal coupling effect is further used to adjust the pin layout and shield layer design, optimize the signal transmission path and signal interference degree. The optimization of the pin layout is carried out by minimizing the coupling coefficient between pins. The goal of the optimization process is:

[0020]

[0021] where Δx ij is the physical distance between pins, C ij is the calculated coupling coefficient, and i and j are the indices of the signal sources, with i≠j indicating that signal sources i and j are different.

[0022] Preferably, the transmission path of the pin signal is optimized through a multi-objective optimization algorithm, which is implemented by particle swarm optimization (PSO). The update formula of the particle swarm optimization is:

[0023]

[0024] where and represent the velocities of the i-th particle at the (k + 1)-th and k-th iterations respectively, and represent the positions of the i-th particle at the (k + 1)-th and k-th iterations respectively, w is the inertia weight, c1 and c2 are the learning factors, r1 and r2 are random numbers between [0, 1], is the individual best position of the i-th particle at the k-th iteration, is the global best position.

[0025] Preferably, the quality monitoring of the pin signal is realized by a Kalman filter. The update formula of the Kalman filter is:

[0026] x k = A k x k-1 + B k u k + w k ;

[0027] y k = H k x k + v k ;

[0028] where x k is the state variable of the signal, x k-1 is the state vector of the system at time k - 1, A k is the state transition matrix, B k is the control input matrix, u kFor the control input, w k For the process noise, y k For the observed value, H k For the observation matrix, v k For the measurement noise.

[0029] Preferably, the total loss of the pin signal transmission path is:

[0030] L(γ) = ∫ γ α(x)dx;

[0031] Wherein, L(γ) is the integral value of the function α(x) on the path γ, γ is the path, indicating that the integration is carried out along this path, α(x) is the function defined on the path γ, dx represents the infinitesimal change on the path, and x is a variable on the path γ.

[0032] 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:

[0033] The size of the dummy pad is optimized according to the signal strength and frequency in the pin signal area;

[0034] The position of the dummy pad is determined by calculating the electric field distribution and electromagnetic coupling coefficient in each signal area to determine its optimal position in the signal area;

[0035] The dummy pad can adjust the position and size in real time according to different interference environments to ensure the stability of signal transmission.

[0036] Preferably, the quality of the pin signal is dynamically monitored, and the signal transmission path is adjusted according to the real-time feedback, including:

[0037] The dynamic monitoring module evaluates the signal quality by real-time sampling the current, voltage and electromagnetic field parameters on the signal transmission path;

[0038] When the signal quality deteriorates, the signal strength and transmission mode of the transmission path are automatically adjusted through the feedback mechanism;

[0039] The feedback adjustment process is based on the Kalman filter algorithm and the dynamic correction model of signal strength, combined with external environment data, to optimize the signal path and control the attenuation and interference of the signal in real time.

[0040] The present invention also provides a partition correction system based on the pin signal of the touch display module, including the following modules:

[0041] 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;

[0042] A physical isolation module for setting physical isolation measures between the signal regions, including adjusting the pin pitch and setting a shielding layer;

[0043] A signal monitoring module for dynamically monitoring the signal quality and combining a Kalman filter to perform real-time estimation and correction of the signal state; A signal path optimization module that optimizes the signal transmission path through variational methods and multi-objective optimization algorithms to minimize signal loss and interference;

[0044] An intelligent feedback module that identifies signal interference patterns through deep learning algorithms and optimizes signal transmission parameters in real time based on historical data.

[0045] The present invention provides a partition correction method and system based on the pin signals of a touch display module. It has the following beneficial effects:

[0046] 1. The present invention adopts the technical solutions of signal region division and physical isolation. By reasonably dividing the display driving signal region, touch signal region, and system control signal region, and taking measures such as adjusting the pin pitch and setting a shielding layer, different signal regions are effectively isolated; achieving the technical effect of reducing interference between signals and optimizing the signal transmission quality. Compared with the prior art solutions with unclear signal regions and large interference, it solves the problems of unstable transmission and poor signal quality caused by signal interference.

[0047] 2. The present invention adopts a scheme that combines a Kalman filter and dynamic signal monitoring technology. By real-time estimating and correcting the signal state, it can accurately monitor the signal quality and make rapid adjustments; achieving the technical effect of ensuring stable signal transmission in a complex environment. Compared with the prior art solutions with inaccurate signal monitoring and difficulty in eliminating interference in real time, it solves the problems of signal distortion and large fluctuations.

[0048] 3. The present invention uses variational methods and multi-objective optimization algorithms to optimize the signal path. By considering multi-dimensional objectives such as signal strength, delay, and power consumption, the signal transmission path is dynamically adjusted; achieving the technical effect of achieving the best balance among multiple objectives. Compared with the prior art solutions that only optimize a single objective, it solves the technical problems of insufficient signal path optimization and inability to consider multiple objectives simultaneously.

[0049] 4. The present invention adopts an intelligent feedback mechanism. By using deep learning algorithms to identify signal interference patterns in real time and optimize signal transmission parameters, it enhances the adaptive adjustment ability of the system; achieving the technical effect of coping with environmental changes in real time during signal transmission. Compared with the prior art solutions that rely on static optimization, it solves the deficiency of being unable to flexibly respond under complex and dynamically changing environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 It is a flowchart of the method steps of the present invention;

[0051] Figure 2 This is the system architecture diagram of the present invention; Specific implementation manners

[0052] Next, in conjunction with the accompanying drawings of the present invention specification, the technical solutions in the embodiments of the present invention will be clearly and completely described. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts belong to the scope of protection of the present invention.

[0053] Please refer to the attached Figure 1 , the embodiments of the present invention provide a partition correction method based on the pin signals of a touch display module. By signal region division, physical isolation, signal monitoring and path optimization, combined with a multi-objective optimization algorithm and an intelligent feedback mechanism, problems such as signal interference, signal attenuation and transmission delay are solved. The method includes the following steps:

[0054] S1. Divide the pin signals of the touch display module into multiple functional regions, and the functional regions include a display driving signal region, a touch signal region, and a system control signal region;

[0055] S2. Set physical isolation measures between multiple functional regions, and the physical isolation measures reduce the signal coupling effect by increasing the pin pitch and setting a shielding layer;

[0056] S3. Deploy dummy pads inside the functional regions, and the dummy pads do not participate in signal transmission and can effectively absorb excess signal energy; S4. Calculate the coupling coefficient between each functional region based on physical field simulation and adjust the layout of the pin signal region;

[0057] S5. Dynamically monitor the quality of the pin signals and adjust the transmission path, intensity and frequency according to the monitoring results of the pin signal quality to optimize the stability and response speed of the pin signals.

[0058] For step S1, in this embodiment, the pin signals of the touch display module are first divided into multiple functional regions, and each region only processes specific types of signals. Generally, the signal partition will include a display driving signal region, a touch signal region, and a system control signal region. The display driving signal region is responsible for image transmission related to the display, the touch signal region is specifically responsible for receiving touch input signals, and the system control signal region processes other control signals to ensure the stable operation of the system. This partition design can avoid cross-interference of different signals in the same region and reduce the influence of the coupling effect on the signal quality.

[0059] 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, with differences in frequency and signal strength. To ensure the effective transmission of signals and avoid cross-interference, these signals are divided into different regions, and physical isolation measures are set between the regions, which can significantly enhance the independence of signals.

[0060] As an option, the functional area partitioning can also be finely adjusted according to the power requirements and operating frequencies of the signals. In some embodiments, touch signals and display signals may share the same pins or circuits during operation. Therefore, through further refined partitioning 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 transmission of pin signals 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.

[0061] In some embodiments, to improve the anti-interference ability of the system, dummy pads can also be set to absorb excess signal energy. Dummy pads do not participate in signal transmission, but by optimizing the layout position of the pads, the excess electromagnetic wave energy can be effectively shielded and absorbed, further reducing the mutual interference between signals. This approach is particularly applicable to high-frequency signal regions and can prevent high-frequency signals from interfering with the surrounding low-frequency signal regions.

[0062] In a possible implementation, the partitioning layout of pin signals is not just about dividing the signals into multiple blocks, but through a detailed analysis of each region, considering the scope of action, operating conditions of the signals within each region, and the degree of interference with other signal regions for precise planning. 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 region reaches the optimal level.

[0063] In this embodiment, the further signal partitioning design takes into account the physical isolation between signal regions. This is not only achieved through the spacing between pins, but may also be 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 regions and avoid cross-interference of electromagnetic waves. In some cases, specific materials can also be used to construct the shielding layer, and these materials have strong electromagnetic wave absorption capabilities, which can effectively reduce the coupling effect between signals.

[0064] During the implementation process, according to the calculated coupling coefficients, the layout of each signal region can be adjusted. Specifically, the coupling coefficients between the pin signal regions are closely related to the physical distance 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.

[0065] For the calculation formula of the coupling coefficients between different signal regions, we use the following formula to describe the coupling effect between signals:

[0066]

[0067] Where C ij is the coupling coefficient between pin i and pin j, E i and E j represent the electric field distributions of pins i and j respectively, S is the surface of the calculation region, ∈0 is the vacuum permittivity, dA represents the infinitesimal region element of the integral, and i and j are the indices of the signal sources.

[0068] Through this formula, we can obtain the coupling strength between different signal regions and adjust the physical isolation measures of the regions accordingly (such as adjusting the pin spacing and setting up the shielding layer). This calculation of the coupling coefficients can help us accurately plan the pin layout during the design to ensure the stability of the signals.

[0069] In this embodiment, the specific signal region division and layout adjustment can be achieved through the following steps:

[0070] Based on the electromagnetic field simulation model, calculate the electromagnetic field distribution between each signal region and obtain the coupling coefficients between the signal regions. Through this simulation, we can identify which regions have high signal interference and make adjustments during the design stage.

[0071] According to the results of the coupling coefficients, dynamically adjust the spacing between the pins, increase the physical isolation between the signal regions, design and set up an appropriate shielding layer to further reduce the signal interference.

[0072] According to the distribution of the signal strength and frequency, deploy dummy pads within each signal region. The position and size of the pads are determined through electromagnetic field simulation and coupling coefficient calculation to ensure that they can effectively absorb the signal interference.

[0073] For step S2, in this embodiment, the setting of physical isolation measures mainly includes the following aspects: First, increase the pin pitch between signal regions, thereby reducing the coupling strength between signal paths. Appropriately set the shielding layer to further isolate the signal regions and prevent electromagnetic interference between different signals. The setting of the shielding layer can improve the signal isolation effect through different material and structural designs, which is particularly important during the transmission 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.

[0074] Generally, when conducting physical isolation design, it is first necessary to determine the functional requirements of the signal regions, as well as parameters such as the signal strength and frequency between each signal region. These factors will affect the design scheme of the isolation between regions. Touch signals and display signals usually have different operating frequencies. Therefore, they need to be appropriately separated in the physical layout. Specifically, the physical distance between signal regions and the thickness, material, etc. of the shielding layer will be adjusted according to these parameters.

[0075] As an option, increasing the pin pitch between signal regions is an effective physical isolation method. By expanding the distance between signal regions, the coupling strength between signal paths can be effectively reduced, and signal cross-interference can be minimized. Specifically, the pitch between pins should be designed according to factors such as the signal frequency and the power of signal transmission. For low-frequency signal regions, the pin pitch can be appropriately increased; for high-frequency signal regions, more electromagnetic field influencing factors need to be considered to reasonably determine the pitch.

[0076] In a possible implementation, the shielding layer design between signal regions is particularly important. The shielding layer can effectively block the propagation of electromagnetic waves and reduce the mutual interference between signals. The design of the shielding layer needs to select appropriate materials according to the electric field distribution and operating frequency of the signal regions. Some commonly used highly conductive 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 need to be optimized according to the actual situation.

[0077] In some embodiments, the physical isolation design can be further optimized through simulation calculations. By electromagnetic field simulation, calculate the electric field distribution between each signal region, and combine the calculation results of the coupling coefficient to adjust the layout and physical distance of the signal regions. This process usually involves numerical optimization algorithms and finite element simulation techniques to ensure the effectiveness of the design results in practical applications.

[0078] In this embodiment, the optimization of physical isolation measures not only relies on empirical design, but also ensures the independence of each signal region through electromagnetic field simulation and calculation of coupling effects. Specifically, electromagnetic field simulation calculations can help determine the electric field distribution between different signal regions and further calculate the coupling coefficient. The coupling coefficient C ij can be calculated by the following formula:

[0079]

[0080] where C ij is the coupling coefficient between pin i and pin j, E i and E j represent the electric field distributions of pins i and j respectively, S is the surface of the calculation region, ∈0 is the vacuum permittivity, dA represents the infinitesimal region element of the integral, and i and j are the indices of the signal sources.

[0081] Specifically, through electromagnetic field simulation, the electromagnetic field distribution during signal transmission can be analyzed in detail. According to the simulation results, the system can dynamically adjust the pin layout and shield layer design of each signal region. When the coupling coefficient of a certain region is too high, the system will automatically adjust the signal layout of that region, increase the pin spacing or strengthen the shield layer to reduce interference between signals.

[0082] In the actual implementation process, physical isolation measures are not only completed in the design stage, but can also be further optimized for signal transmission through dynamic adjustment. Under different working conditions, the intensity and frequency of signals may change. At this time, the system can adjust the physical isolation design of the signal region according to real-time feedback. By combining electromagnetic field simulation and real-time monitoring data, the system can adaptively adjust the shield layer and pin layout in different environments to maintain the stability of signal transmission.

[0083] In some embodiments, physical isolation design can also achieve real-time feedback through sensors and monitoring systems. By real-time monitoring the coupling situation and signal quality between signal regions, the system can dynamically adjust the signal path to optimize the signal transmission effect. This real-time feedback mechanism can ensure the minimization of interference during signal transmission and ensure that the signal quality is always in the best state.

[0084] For step S3, in this embodiment, by real-time sampling the current, voltage and electromagnetic field parameters of the signal, the system can accurately evaluate the signal quality, and based on this evaluation result, dynamically adjust the signal transmission path and signal intensity. Specifically, when it is detected that the signal quality deteriorates, 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.

[0085] In general, the signal transmission path may be affected by external environmental factors, resulting in signal attenuation or interference. Factors such as high temperature, humidity changes, and electromagnetic environment changes may all lead to a decline in signal quality. Therefore, real-time monitoring of signal quality and correction are the keys to ensuring signal transmission stability.

[0086] As an option, dynamic signal monitoring uses high-frequency sampling technology to perform real-time sampling of signal intensity, frequency, phase, etc., and 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. The evaluation of signal quality is usually completed through parameters such as current, voltage, and electromagnetic field parameters. These parameters can reflect various changes in the signal during transmission, including a decrease in signal intensity and an increase in noise. By analyzing these changes, the system can accurately judge the signal transmission status.

[0087] In a possible implementation, the monitoring and real-time correction of signal quality are completed through a Kalman filter. The Kalman filter can recursively estimate the state of the signal and optimize the signal transmission path based on real-time measurement results. This process can be described by the following formula:

[0088] x k = A k x k-1 + B k u k + w k ;

[0089] y k = H k x k + v k ;

[0090] where x k is the state variable of the signal, x k-1 is the state vector of the system at time k - 1, A k is the state transition matrix, B k is the control input matrix, u k is the control input, w k is the process noise, y k is the observed value, H k is the observation matrix, and v k is the measurement noise. Through this calculation, the Kalman filter can continuously correct the errors in the signal path and ensure stability during signal transmission.

[0091] Based on signal quality monitoring, the next step is to optimize the signal transmission path. The optimization of the signal path is not just about choosing the shortest path, but rather comprehensively considering factors such as signal strength, transmission delay, signal attenuation, and interference. Through a multi-objective optimization algorithm, the system can simultaneously optimize multiple parameters and select a comprehensively optimal signal transmission path.

[0092] In this embodiment, the optimization of the signal path adopts the Particle Swarm Optimization (PSO) algorithm, which can search for and optimize the signal path in a multi-dimensional space. The PSO algorithm finds the optimal solution by simulating the collective behavior of particles and has good global search ability. Specifically, the update formula for particle swarm optimization is:

[0093]

[0094] where and represent the velocities of the i-th particle at the (k + 1)-th and k-th iterations respectively, and represent the positions of the i-th particle at the (k + 1)-th and k-th iterations respectively, w is the inertia weight, c1 and c2 are learning factors, r1 and r2 are random numbers between [0, 1], is the personal best position of the i-th particle at the k-th iteration, is the global best position. Through continuous iteration, the particle swarm optimization algorithm can find a balance among multiple objectives, thus achieving the optimal selection of the signal path.

[0095] During the signal transmission process, the system will, according to the change in signal quality, provide real-time feedback and adjust the signal transmission path. Specifically, when the signal quality deteriorates, the feedback mechanism will be activated to automatically adjust the signal transmission path. This adjustment is not just about choosing a new path, but also includes optimizing signal strength, frequency, and other parameters. Through this process, the system can ensure the stability and accuracy of the signal under different working conditions.

[0096] For example, when the system detects that there is high attenuation or interference in a certain signal path, the feedback mechanism will automatically select a path with less interference and increase the signal transmission strength to ensure that the signal can be stably transmitted to the target area. In some embodiments, the feedback adjustment process combines a Kalman filter and real-time monitoring data to ensure that each adjustment can optimize the signal quality to the greatest extent.

[0097] For step S4, in this embodiment, by continuously collecting signal status data and using a deep learning model to identify the variation law of signal quality, the signal transmission path is further optimized and adjusted. Different from the aforementioned Kalman filtering 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.

[0098] Generally, during the signal transmission process, 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.

[0099] As an option, the feedback mechanism monitors the changes in the current, voltage, and electromagnetic field of the signal in real time through sensors. By analyzing these real-time sampled data, the system can identify the variation trend of the signal quality and make timely adjustments. Such adjustments can be the optimization of the signal path, the enhancement of the signal strength, or the adjustment of the signal transmission frequency. Specifically, the goal of the feedback mechanism is to dynamically adjust various transmission parameters of the signal according to the real-time signal quality, so that the signal always remains in the optimal state.

[0100] In a possible implementation, a deep learning model (such as a convolutional neural network) can be used for pattern recognition of signal quality. Through training with a large amount of historical data, the deep learning model can identify the patterns of signal quality degradation and predict the possible types of interference or signal attenuation trends. Based on these predictions, the system can make adjustments in advance to reduce signal interference and improve signal stability.

[0101] Specifically, after receiving the feedback signal, the system will make adaptive adjustments according to the monitored signal quality. This adjustment process first analyzes the feedback data through deep learning algorithms to identify the reasons for the signal quality degradation, such as whether it is caused by electromagnetic interference, signal path attenuation, or equipment failure. Then, according to the analysis results, the system will automatically select appropriate optimization strategies for adjustment.

[0102] For example, in some embodiments, when the reason for the signal quality degradation is environmental interference, the system can select a more stable transmission path or compensate for the loss by enhancing the signal transmission intensity. If the signal attenuation is caused by equipment failure, the system can automatically adjust the working mode or frequency of the equipment to re-optimize the signal transmission method.

[0103] In some embodiments, the feedback adjustment is not limited to the optimization of the signal path, but may also involve the adjustment of other system parameters. The system can improve the signal quality and reduce interference by adjusting the operating frequency, increasing the signal transmission bandwidth, or changing the power output, etc. 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.

[0104] In this embodiment, the adjustment process of the feedback mechanism is combined with real-time data, and an adaptive adjustment based on deep learning and other algorithms is adopted. The deep learning model processes the real-time feedback data to identify interference patterns and signal attenuation trends, 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 evaluation mechanism in this optimization process, which can predict before the signal quality deteriorates and thus make adjustments in advance.

[0105] Specifically, the following optimization formula may be used in the signal quality adjustment process:

[0106] x k =A k x k-1 +B k u k +w k ;

[0107] y k =H k x k +v k ;

[0108] Wherein, x k is the state variable of the signal, x k-1 is the state vector of the system at time k-1, A k is the state transition matrix, B k is the control input matrix, u k is the control input, w k is the process noise, y k is the observation value, H k is the observation matrix, v k is the measurement noise. The Kalman filter is combined with the feedback mechanism to continuously update the state variable of the signal to ensure the real-time optimization of the signal quality.

[0109] During the signal transmission process, the combination of the feedback mechanism and the path optimization algorithm can ensure that the signal transmission path is always in the best state. When the system detects an increase in the attenuation or interference of the signal path, the feedback mechanism will trigger the dynamic adjustment of the path; while 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.

[0110] For step S5, in this embodiment, multi-objective optimization algorithms such as Particle Swarm Optimization (PSO) are 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 global search in multi-dimensional space to find the optimal solution. In the selection of signal transmission paths, the PSO algorithm optimizes according to multiple factors such as signal strength, transmission delay, and interference degree to ensure the best transmission path of the signal in a complex environment.

[0111] 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 objective, while the multi-objective optimization algorithm adopted in the present invention can optimize multiple objectives simultaneously to ensure the overall performance of signal transmission.

[0112] Specifically, in this embodiment, the optimization objective of the signal path is not only to minimize interference, but also to comprehensively consider factors such as signal strength, delay, and power consumption. As an option, the signal strength should be kept high during transmission to ensure the clarity and accuracy of the signal; while the signal delay and power consumption should be minimized as much as possible to improve the response speed and energy efficiency of the system.

[0113] Under this multi-objective optimization, the Particle Swarm Optimization (PSO) algorithm plays an important role. The PSO algorithm can find the optimal solution in a complex signal environment by simulating how bird flocks cooperate to achieve the optimal goal during the process of finding food. During the optimization process, particles represent a possible solution, and the algorithm finally finds the optimal solution by continuously adjusting the position of each particle.

[0114] In a possible implementation, the update formula of Particle Swarm Optimization is:

[0115]

[0116] Where, and respectively represent the velocity of the i-th particle at the (k + 1)-th and k-th iterations, and respectively represent the position of the i-th particle at the (k + 1)-th and k-th iterations, w is the inertia weight, c1 and c2 are learning factors, r1 and r2 are random numbers between [0, 1], is the individual best position of the i-th particle at the k-th iteration, is the global best position.

[0117] In this embodiment, the optimization objectives include the following aspects:

[0118] Signal interference minimization: Ensure efficient signal transmission by minimizing the coupling and interference between signals.

[0119] Signal strength maximization: While ensuring signal quality, enhance the transmission strength of the signal to avoid signal attenuation during transmission.

[0120] Transmission delay minimization: Optimize the path selection, reduce the transmission delay of the signal, and improve the response speed.

[0121] Power consumption minimization: On the premise of signal strength and path optimization, minimize the power consumption as much as possible to improve the energy efficiency of the system. These optimization goals can be combined with weights to obtain a comprehensive optimization objective function. In some embodiments, the expression of the objective function is:

[0122] minf(x)=[f1(x),f2(x),…,f m (x)];

[0123] Wherein, minf(x) is the objective function, representing the minimization objective of the optimization problem, [f1(x),f2(x),…,f m (x)] is a plurality of objective functions, representing different optimization goals, and x is the decision variable vector, representing all variables that affect the system performance. During the optimization process, the PSO algorithm searches for the optimal path and signal parameters according to the combination of the objective functions, so as to achieve a balance between multiple objectives.

[0124] Specifically, through the PSO algorithm, the system can weigh between multiple objectives and select the optimal signal transmission path. In high-frequency signal transmission, the system will reduce attenuation by adjusting the path selection and enhancing the signal strength, and at the same time reduce signal interference and delay by optimizing the path design.

[0125] In some embodiments, the optimization result of the PSO algorithm can find the global optimal solution in a short time, improve the signal transmission efficiency, 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.

[0126] The partition correction system based on the touch display module pin signal described below can be correspondingly referred to the partition correction method based on the touch display module pin signal described above.

[0127] Please refer to the appendix Figure 2, the present invention also provides a partition correction system based on the pin signals of the touch display module. Through the signal area partition module, physical isolation module, signal monitoring module, signal path optimization module and intelligent feedback module, this system can achieve precise partitioning, effective isolation, real-time monitoring, dynamic optimization and intelligent adjustment of the pin signals in the touch display module, achieving the effects of significantly reducing signal interference, improving signal transmission quality, reducing signal delay and power consumption. This system can maintain signal stability and transmission accuracy in a complex electromagnetic environment, ensure the response speed and user experience of the device, and has high adaptability and scalability.

[0128] For multiple signal areas, it means that in the touch display module, the pin signals are divided into different areas according to signal types and functional requirements, and each area is responsible for processing specific signal transmission tasks.

[0129] The display drive signal area is responsible for the transmission of display-related signals, including tasks such as image display and brightness adjustment. The signal intensity and frequency in the display drive signal area are usually high, and it is necessary to ensure the stability and clarity of signal transmission.

[0130] The touch signal area is used to receive touch input signals, including data such as touch position and pressure. These signals need to be transmitted very precisely, so the design of this area needs to reduce interference and ensure fast signal response.

[0131] The system control signal area processes the system control signals of the device, such as power control and system status indication. Such signals usually do not involve high-frequency signals, so the stability and electromagnetic compatibility of the system are mainly considered in the design.

[0132] For the physical isolation module, it reduces the mutual interference between signal areas physically, including the following measures: by reasonably increasing the pin spacing between signal areas, reducing the interference caused by electromagnetic coupling during signal transmission. The physical spacing between signal areas can be dynamically adjusted according to different signal types and frequencies to ensure that each signal area can work independently and stably.

[0133] 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, thus avoiding the 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 ability.

[0134] For the signal monitoring module, it monitors the signal quality in real time and combines a Kalman filter to estimate and correct the signal state.

[0135] Through sensors and sampling circuits, parameters such as current, voltage, frequency, and phase of the signal are monitored in real time to evaluate the quality and stability of the signal. When the signal quality deteriorates, it can be detected in a timely manner and corresponding correction measures can be taken.

[0136] The application of the Kalman filter in the signal monitoring module can recursively estimate the signal state. By combining the actual observed values with the predicted values of the system model, it can correct the signal error in real time. The Kalman filter can effectively eliminate the noise in the signal, enhance the signal stability, and provide a more accurate assessment of the signal transmission quality.

[0137] For the signal path optimization module, the variational method and multi-objective optimization algorithms are used to optimize the signal transmission path to minimize signal loss and interference.

[0138] The variational method is a mathematical method commonly used for optimizing paths. In signal path optimization, the variational method is used to solve the minimization of the total loss on the signal path to obtain the optimal transmission path. This method is particularly suitable for scenarios of multi-path signal transmission and can find the best path between multiple signal regions.

[0139] The multi-objective optimization algorithm can find the optimal balance among 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 considering the weights and priorities of different objectives, and selecting the most suitable path.

[0140] For the intelligent feedback module, deep learning algorithms are used to identify signal interference patterns and optimize signal transmission parameters in real time based on historical data.

[0141] Deep learning algorithms can learn the interference patterns and signal quality change rules in signal transmission through training on a large amount of historical data. During the real-time feedback process, the deep learning model can predict the signal quality change trend, identify possible interference sources, and make adaptive adjustments based on the prediction results.

[0142] According to the output of the deep learning algorithm, the intelligent feedback module can optimize parameters such as the signal transmission path, signal strength, and frequency 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 adaptability and anti-interference ability, ensuring that the signal remains in a stable state under complex working conditions.

[0143] Although the embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. 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; 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; Dynamically adjust the design parameters of pin spacing and shielding layer according to the electromagnetic field simulation results and signal coupling coefficient calculation; 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.

2. The partition correction method based on the touch display module pin signal according to claim 1 is characterized in that: The design of the pin spacing and the shielding layer is optimized through 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: Among them, C ij is the coupling coefficient between pin i and pin j, E i and E j They represent the electric field distribution of pins i and j respectively, S is the surface of the calculation area, ∈0 is the vacuum dielectric constant, dA represents the integrated tiny area element, and i and j are the indexes of the signal source.

3. The partition correction method based on the touch display module pin signal according to claim 1 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: Where Δx ij is the physical distance between pins, C ij is the calculated coupling coefficient, where i and j are the indexes of the signal sources, and i≠j means that the signal sources i and j are different.

4. 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 denote the speed of the i-th particle at the k+1th and kth iterations, respectively. and denotes the position of the i-th particle at the k+1th and kth iterations, respectively, w is the inertia weight, c1 and c2 are learning factors, r1 and r2 are random numbers between [0,1], is the individual best position of the ith particle at the kth iteration, is the global best position.

5. 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: x k =A k x k-1 +B k u k +w k ; y k =H k x k +v k ; Among them, x k is the state variable of the signal, x k-1 is the state vector of the system at time k-1, A k is the state transfer matrix, B k is the control input matrix, u k is the control input, w k is the process noise, y k is the observed value, H k is the observation matrix, v k To measure noise.

6. 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: L(γ)=∫ γ α(x)dx; Where L(γ) is the integral value of the function α(x) on the path γ, γ is the path, indicating that the integration is performed along the path, α(x) is the function defined on the path γ, dx represents a small change on the path, and x is a variable on the path γ.

7. 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.

8. 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 7, 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 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.

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