A method, apparatus, and device for debugging and configuring a capacitive touchscreen.

Abstract

This application relates to the field of repair and debugging technology for capacitive touchscreens, specifically to a debugging and configuration method, apparatus, and device for capacitive touchscreens. Specifically, it includes: acquiring the capacitive signals of the capacitive touchscreen during repair and debugging; constructing a comprehensive display interference degree based on the proportion of noise energy in the spectrum of the capacitive signals and the peak intensity of the capacitive signals; smoothing the comprehensive display interference degree at all times; constructing a touch environment disturbance degree based on the difference between the data before and after smoothing and the degree of instability of the smoothed data; integrating the touch environment disturbance degree into the filter coefficient update formula to improve the filter; and using the filtered capacitive signals for the repair and debugging of the capacitive touchscreen. This avoids the problem of filter response lag or failure when noise changes drastically due to the use of fixed parameters in the filter coefficient update formula, thereby improving the touch stability, positioning accuracy, and anti-interference robustness of the capacitive touchscreen in complex electromagnetic environments.

Description

Technical Field

[0001] This application relates to the field of repair and debugging technology for capacitive touch screens, specifically to a debugging and configuration method, apparatus, and equipment for a capacitive touch screen. Background Technology

[0002] In the repair of computers and auxiliary equipment, configuring and adjusting capacitive touchscreens is crucial for ensuring successful offline repair. With the rise of smartphones, manufacturing processes have evolved from simple single-layer wiring to sophisticated multi-layer sensor arrays using ITO and silver nanowires, significantly increasing the difficulty of capacitive touchscreen configuration. This process requires simultaneous adjustments to capacitance reference, filtering algorithms, and coordinate mapping, while also avoiding electromagnetic interference and accidental touches. This substantial increase in technical complexity underscores the evolution of computer and auxiliary equipment repair from mechanical to fully solid-state electronic methods, and represents a core step in offline capacitive touchscreen repair.

[0003] Due to the uncertainty and complexity of the environment at the disassembly and debugging site for capacitive touchscreens, the starting and stopping of high-power electrical appliances and the operation of switching power supplies near the disassembly and debugging site can generate common-mode or differential-mode noise of unstable intensity. This makes it difficult to establish a stable signal baseline during the debugging process of capacitive touchscreens, further causing touch response delays and accidental touches. Existing technologies usually add shielding layers and filtering circuits to the debugging hardware and configure digital filters during software debugging to suppress noise interference in the environment. However, the static fixed parameters of the filters in the above methods, such as step size parameters, are difficult to effectively suppress complex and ever-changing environments and cannot adapt to sudden or non-periodic changes in environmental noise. Summary of the Invention

[0004] To address the aforementioned technical problems, the purpose of this application is to provide a method, apparatus, and device for debugging and configuring a capacitive touchscreen. The specific technical solution adopted is as follows: In a first aspect, embodiments of this application provide a debugging and configuration method for a capacitive touchscreen, the method comprising the following steps: Acquire timing data of capacitance signals from the sensor channels of the capacitive touchscreen; The peak level of the capacitor signal in the historical local time period at each moment is evaluated, and the energy proportion of the noise interference band in the spectrum of the capacitor signal in the local time period is calculated to determine the comprehensive screen display interference at each moment. The time-series data of comprehensive screen interference in historical local time periods at each moment are smoothed, and the touch environment perturbation degree at each moment is constructed based on the residual of the smoothed data and the degree of data change disorder. The filter coefficient update formula is adjusted based on the touch environment perturbation degree, and the filter is combined to perform capacitor signal filtering. The filtered capacitor signal is used for touch recognition and coordinate calculation of the capacitive touch screen.

[0005] In one embodiment, the peak level of the capacitor signal within the historical local time period at each moment is: the peak-to-average power ratio of the capacitor signal time sequence within the historical local time period at each moment.

[0006] In one embodiment, the calculation process for the energy proportion of the noise interference frequency band in the spectrum is as follows: By setting an interference frequency band, the ratio of the energy of the signal within the interference frequency band to the total energy of the spectrum in the historical local time period of the capacitor signal at each moment is calculated to obtain the energy ratio.

[0007] In one embodiment, the overall screen display interference is: the positive fusion value of the peak level of the capacitor signal and the energy ratio within a historical local time period at each moment.

[0008] In one embodiment, the process of obtaining the touch environment perturbation degree is as follows: Calculate the mean residual of all the smoothed data within the historical local time period; calculate the information entropy of all the smoothed data within the historical local time period using the histogram method; determine the touch environment perturbation degree at each time based on the mean residual and the information entropy, wherein the touch environment perturbation degree is positively correlated with the mean residual and the information entropy, respectively.

[0009] In one embodiment, the touch environment perturbation degree is the product of the residual mean and the information entropy.

[0010] In one embodiment, the process of adjusting the filter coefficients at each time step is as follows: The step size parameter in the original filter coefficient update formula is adjusted by the touch environment perturbation degree at each time step to obtain the adjusted filter coefficient update formula, and the filter parameters at each time step are updated using the adjusted filter coefficient update formula.

[0011] In one embodiment, the adjusted filter coefficient update formula is: In the formula, , These are the filter coefficients at the (n+1)th and nth acquisition times, respectively; This is the normalization function; This is the step size parameter; The perturbation degree of the touch environment at the nth acquisition time; This is the input signal at the nth acquisition time. This is the error signal at the nth acquisition time.

[0012] Secondly, embodiments of this application also provide a debugging and configuration device for a capacitive touchscreen, wherein the device stores a computer program, and when the computer program is executed by a processor, it implements the steps of the method described in the first aspect above.

[0013] Thirdly, embodiments of this application also provide a debugging and configuration device for a capacitive touchscreen, including a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the computer program to implement the steps of the method described in the first aspect above.

[0014] The embodiments of this application have at least the following beneficial effects: This application collects capacitive signals from a capacitive touchscreen during repair and debugging. It constructs a comprehensive display interference level by analyzing the proportion of noise energy in the signal spectrum and the peak intensity of the signal, reflecting the combined characteristics of continuous steady-state noise and sudden impulse noise in the environment. This solves the problem that traditional single-frequency or time-domain analysis methods cannot comprehensively quantify the impact of composite noise. The comprehensive display interference level at all times is smoothed, and the touch environment perturbation level is constructed by analyzing the differences before and after smoothing and the degree of instability in the smoothed data, characterizing the dynamic instability and unpredictability of noise. The touch environment perturbation level is integrated into the filter coefficient update formula to improve the filter, avoiding the problem of filter response lag or failure when noise changes drastically due to fixed parameters in the filter coefficient update formula. This achieves intelligent coupling between filter behavior and noise status. Furthermore, the filtered capacitive signal is used for touch recognition and coordinate calculation of the capacitive touchscreen, significantly improving the touch stability, positioning accuracy, and anti-interference robustness of the capacitive touchscreen in complex electromagnetic environments, while balancing response speed and filtering effect. Attached Figure Description

[0015] To more clearly illustrate the technical solutions and advantages in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 A flowchart illustrating the steps of a debugging and configuration method for a capacitive touchscreen according to an embodiment of this application; Figure 2 A flowchart illustrating the steps of a debugging and configuration method for a capacitive touchscreen; Figure 3 This is a schematic diagram illustrating the process of obtaining the perturbation degree of the touch environment. Detailed Implementation

[0017] To further illustrate the technical means and effects adopted by this application to achieve the intended purpose of the invention, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a capacitive touchscreen debugging and configuration method, apparatus, and device proposed in this application. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0019] The following description, in conjunction with the accompanying drawings, details a specific scheme for the debugging and configuration method, apparatus, and equipment of a capacitive touchscreen provided in this application.

[0020] Please see Figure 1 The diagram illustrates a flowchart of a debugging and configuration method for a capacitive touchscreen according to an embodiment of this application. The method includes the following steps: Step S1: Acquire the timing data of the capacitance signal of the sensor channel of the capacitive touch screen.

[0021] During the repair and debugging of a capacitive touchscreen, a high-precision differential ADC module is installed at the output of the XY electrode channels of the touchscreen sensor array to acquire the analog capacitance signal of each sensing channel. The ADC module samples the capacitance signal at a frequency of 1 kHz, meaning that the voltage of the capacitor is measured instantaneously every 1 millisecond, and this analog quantity is converted into a digital quantity to obtain the capacitance signal at each acquisition moment. The acquired capacitance signal is then normalized using the maximum value normalization method. It should be noted that the sampling frequency of the capacitance signal can be set by the implementer according to the actual situation; this application does not impose specific restrictions.

[0022] The sequence of capacitance signals from all acquisition times within a historical local time period at each acquisition time, arranged chronologically, is recorded as the historical capacitance signal sequence for each acquisition time. This sequence reflects the continuous change of capacitance signals over time. In this embodiment, the historical local time period for each acquisition time is the period within the first second of that acquisition time. In other embodiments of this application, the implementer can set the duration of the historical local time period according to actual conditions.

[0023] Step S2: Evaluate the peak level of the capacitor signal in the historical local time period at each moment, and count the energy proportion of the noise interference frequency band in the spectrum of the capacitor signal in the local time period to determine the comprehensive screen display interference at each moment.

[0024] During the debugging and configuration of capacitive touchscreens, the repair and debugging environment contains complex electromagnetic interference sources. These interferences cause severe fluctuations in the capacitive signal baseline, leading to malfunctions such as sluggish touch response and coordinate positioning drift during the repair and debugging of capacitive touchscreens.

[0025] Therefore, using the historical capacitance signal sequence at each acquisition moment as input, a Short-Time Fourier Transform (STFT) is used. A Hanning window function with a window length of 256 sampling points is set to balance frequency resolution and temporal locality. An overlap rate of 75% is set to observe the change of the noise spectrum over time. The output is the time-frequency spectrum matrix of the historical capacitance signal sequence at that acquisition moment, thus visualizing the time-frequency distribution of noise energy and identifying specific frequency band interference that intermittently occurs during the repair and debugging of capacitive touchscreens. This provides intuitive diagnostic information for capacitive touchscreen repair and debugging personnel. The Short-Time Fourier Transform (STFT) is a well-known technique, and its specific process will not be elaborated further.

[0026] Subsequently, an interference frequency band is set. In this embodiment, the interference frequency band is 50Hz~1kHz. This band covers the two most common noise sources: 50Hz power frequency and its harmonics, and switching power supply noise in the range of several hundred hertz to 1kHz. In other embodiments of this application, the implementer can set the interference frequency band according to the actual situation. Further, the average energy value of the interference frequency band and the average energy value of the complete frequency range in the time-spectrum matrix corresponding to each acquisition time are obtained respectively, and are recorded as noise energy value and total energy value. Specifically, in this embodiment, the process of obtaining noise energy value and total energy value is as follows: The sum of energy within the interference frequency bands corresponding to each Hanning window in the time-spectrum matrix is ​​calculated, and the average of the sums of energy within the interference frequency bands corresponding to all Hanning windows in the time-spectrum matrix is ​​calculated to obtain the average energy value of the interference frequency bands in the time-spectrum matrix, which is denoted as the noise energy value in the time-spectrum matrix. Similarly, the sum of energy between 0 and the Nyquist frequency is calculated within each Hanning window's corresponding time period, and the average of the sums of energy between 0 and the Nyquist frequency within the time-spectrum matrix corresponding to all Hanning windows in the time-spectrum matrix is ​​calculated to obtain the average energy value between 0 and the Nyquist frequency in the time-spectrum matrix, which is denoted as the total energy value in the time-spectrum matrix. The acquisition of energy in the time-spectrum is a well-known process, and the specific process will not be elaborated further. In other embodiments of this application, the implementer may also use other methods to calculate the noise energy and total energy in the time-spectrum matrix.

[0027] Furthermore, the ratio of the noise energy value to the total energy value in the time-spectrum matrix at each time point is calculated to obtain the energy proportion of the interference frequency band.

[0028] Because impulse noise has a short period and a wide spectral distribution, it is difficult to accurately express the instantaneous impact level using only frequency domain methods such as STFT. To address this issue, a sliding window is set in the historical capacitance signal sequence at each acquisition moment, and the peak-to-average power ratio (PAR) is calculated in each sliding window. The PAR can reflect the peak characteristics of the signal and quantify the suddenness of the signal's peak characteristics. In this embodiment, the sliding window length is set to 10ms to match the typical pulse width. In other embodiments of this application, the implementer can set the sliding window length according to the actual situation. The calculation of the PAR is a well-known technique, and the specific process will not be described in detail.

[0029] Based on the above analysis, a comprehensive display interference degree for the capacitive touchscreen at each data acquisition moment is constructed. Taking any acquisition moment as the current moment, preferably, in this embodiment, the expression for the comprehensive display interference degree is: In the formula, A represents the overall screen display interference at the current moment; , These are the noise energy value and total energy value in the time-spectrum matrix of the historical capacitance signal sequence at the current moment, respectively. It is the mean of the peak-to-average ratio (PAPR) within all sliding windows in the historical capacitance signal sequence at the current moment; This is an adjustment factor, used to prevent the denominator from being zero. In this embodiment, it will... The value is set to In other embodiments of this application, the implementer may set the parameters according to the actual situation. The value of .

[0030] Short-Time Fourier Transform (STFT) can effectively separate and quantize the signal energy of different frequency bands by performing time-frequency analysis on the signal, including the average energy of the interference band. A higher value indicates stronger steady-state, continuous electromagnetic interference in the signal, including power frequency interference and switching power supply noise. On the other hand, the sliding window peak-to-average power ratio (PAR) measures the ratio of the instantaneous peak value to the average level of the signal. A higher value indicates more transient and pulse-type electromagnetic interference in the signal, and a higher degree of suddenness. Based on the above analysis, touch failures in capacitive touchscreens can be caused by either continuous noise that leads to signal baseline drift or pulse noise that causes momentary mis-touches or response interruptions. Therefore, this solution integrates the frequency domain energy index for evaluating continuous noise and the time domain suddenness index for evaluating pulse noise, and... and The multiplication constructs a comprehensive screen interference degree A, which can simultaneously capture and quantify the combined effects of two main noise sources in the electromagnetic environment on capacitive signals, thus providing a comprehensive and intuitive criterion for interference intensity judgment for capacitive touch screen repair and debugging personnel.

[0031] Step S3: Smooth the time-series data of the comprehensive screen interference degree in the historical local time period at each moment, and construct the touch environment perturbation degree at each moment based on the residual of the smoothed data and the degree of data change disorder.

[0032] Because the disassembly and repair of capacitive touchscreens are carried out in an environment with high electromagnetic interference, and this interference is time-varying and sudden, the traditional static debugging method cannot correct the changing noise in real time, causing faults such as touch signal baseline drift and coordinate position offset, which reduces the efficiency of disassembly and repair of capacitive touchscreens and the product's anti-interference ability.

[0033] Based on the above analysis, taking the current moment as an example, the comprehensive display interference degree A calculated from all acquisition moments within 1 second prior to the current moment is sorted chronologically, and the resulting sequence is denoted as the display interference sequence at the current moment. Then, the display interference sequence at each acquisition moment is used as the input to the exponentially weighted moving average algorithm. The smoothing factor of the exponentially weighted moving average algorithm is set to 0.3 to give higher weight to recent data, further ensuring that the exponentially weighted moving average algorithm can more quickly capture the changing trend of noise during the disassembly, repair, and debugging of capacitive touchscreens, and finally output a smoothed sequence. The smoothing factor can be set by the implementer according to the actual situation; this application does not impose specific restrictions. This smoothed sequence represents the comprehensive display interference degree after filtering out random fluctuations. Then, the mean residual between the smoothed sequence and the display interference sequence is calculated as the mean absolute error S. S quantifies the information loss of the EWMA smoothing filter; a larger value indicates a large number of violent, instantaneous fluctuations in the original noise signal. The exponentially weighted moving average algorithm is a known technique, and its specific process will not be elaborated further.

[0034] It should be noted that this application provides only one smoothing method for smoothing the screen display interference sequence. There are many existing smoothing methods, and implementers may also use other smoothing algorithms to smooth the screen display interference sequence. This application does not impose any specific restrictions.

[0035] Knowing only the average noise level is insufficient to determine whether its variation pattern is controllable; sudden and irregular noise jumps place higher demands on system adaptability. To address this issue, the information entropy of the smoothed sequence output by EWMA is calculated using the histogram method. Specifically, the elements in the smoothed sequence output by EWMA are normalized to the [0,1] interval using the maximum-minimum normalization method, and divided into M equally spaced intervals. The frequency of data falling into each interval is counted as the probability, and the information entropy of the probabilities of all intervals is calculated. This value represents the uncertainty or disorder of the noise change direction. The higher the entropy value, the more unpredictable the noise fluctuations, and the more robust adaptive strategies are needed to maintain touch stability during the disassembly and repair of capacitive touchscreens. In this embodiment, the value of M is set to 20. In other embodiments of this application, the implementer can set the value of M according to the actual situation.

[0036] Based on the above analysis, the touch environment perturbation degree B is constructed for each data acquisition moment. Preferably, in this embodiment, the expression for the touch environment perturbation degree is: In the formula, B is the perturbation degree of the touch environment at the current moment; S is the mean absolute error at the current moment, which is the mean of the residuals between the original sequence and the EWMA smoothed sequence; E is the information entropy of the elements in the smoothed sequence of the screen display interference sequence at the current moment.

[0037] Mean absolute error (SEE) measures the average deviation between a prediction or smoothing model and the original data. A larger S value indicates that the EWMA smoothing process filters out more instantaneous and drastic fluctuations, meaning there are many high-amplitude sudden jumps in the original noise signal. On the other hand, in existing technologies, information entropy is a core indicator in information theory used to quantify the uncertainty of random variables. A larger E value indicates a more chaotic and irregular change pattern in the smoothed noise sequence, meaning the dynamic behavior of the noise is more unpredictable. Based on the above analysis, a noisy environment that seriously threatens touch stability requires not only sudden jumps in noise amplitude but also unpredictable changes. Therefore, this solution integrates the error index for assessing the deviation of fluctuation amplitude with the uncertainty index for assessing the chaos of change patterns. S and E are multiplied to construct the touch environment perturbation degree B, which can comprehensively characterize the dynamic instability of electromagnetic interference in the disassembly and repair environment of capacitive touchscreens.

[0038] Step S4: Adjust the filter coefficient update formula based on the touch environment perturbation degree, and combine it with the filter to perform capacitor signal filtering. The filtered capacitor signal is used for touch recognition and coordinate calculation of the capacitive touch screen.

[0039] During the repair and debugging of capacitive touch screens, the electromagnetic environment is constantly changing. The start-up and shutdown of high-power equipment or the presence of a large number of high-frequency wireless signals can generate sudden and irregular large noise interference. This causes the originally set filter with fixed parameters to be unable to change its parameters to match the changing noise spectrum, resulting in touch signal baseline drift, coordinate offset, and a large number of false triggers, which seriously affect the touch accuracy.

[0040] Therefore, based on the disturbance level of the touch environment, an algorithm for dynamically adjusting the digital filter parameters needs to be designed for use throughout the entire maintenance and debugging process of capacitive touchscreens, starting from the initial repair and debugging phase. Specifically, this involves using intelligent methods to adaptively adjust parameter values ​​to cope with interference of varying strengths. The design method for dynamically adjusting the digital filter parameters is as follows: In the initial stage of repairing and debugging the capacitive touchscreen, an adaptive filter based on the Least Mean Square (LMS) algorithm is used. The capacitive signal is used as input, and a dual-rate processing mechanism is employed: signal filtering is performed in real-time at high frequency, while the touch environment perturbation degree B is updated once at a low frequency (at each data acquisition interval). During operation, the LMS filter locks the latest B value as a parameter until the next B value update, thus balancing computational overhead and response speed.

[0041] Filter coefficients in an LMS filter The original update formula is The filter coefficient update formula after improvement by touch environment perturbation degree is: In the formula, , These are the filter coefficients at the (n+1)th and nth acquisition times, respectively; This is the normalization function; The step size parameter is used to control the convergence speed. It is usually set to a value between 0.01 and 0.1. In this embodiment, the value is 0.01. The perturbation degree of the touch environment at the nth acquisition time; This is the input signal at the nth acquisition time. Let be the error signal at the nth acquisition time, which is the difference between the desired signal and the filter output signal. , and Both are vectors.

[0042] In this embodiment, the normalized value of the touch environment perturbation degree at the nth acquisition time is obtained by normalizing the maximum and minimum values ​​of the touch environment perturbation degree within T seconds before the nth acquisition time. There are many existing normalization functions, and implementers can also use other normalization functions to normalize the touch environment perturbation degree at each acquisition time. This application does not impose any specific restrictions.

[0043] The core of the Least Mean Square (LMS) adaptive filter lies in its coefficient update mechanism, its standard form Dependent on a fixed step size Through error signal With input signal The correlation is used to iteratively adjust the filter coefficients to minimize the mean square error. The fixed step size... The value needs to be balanced between convergence speed and steady-state error. Based on the above analysis, during the repair and debugging of capacitive touchscreens, the touch environment perturbation degree B characterizes the comprehensive intensity and unpredictability of environmental electromagnetic interference in real time. Therefore, this scheme makes a key improvement to the classic LMS algorithm by introducing the global evaluation index B as the step size. The real-time modulation factor. When a high disturbance B value is detected in the touch environment, it indicates a severe and rapidly changing electromagnetic environment. In this case, the effective adaptive step size must be increased. To improve the filter's noise tracking speed and suppression capability, and avoid system response hysteresis; conversely, when the B value is low, the effective step size is automatically reduced to ensure the filter's steady-state accuracy and prevent overshoot. This design intelligently correlates the filter's adaptive behavior with the severity and dynamic characteristics of actual interference at the repair and commissioning site, thereby realizing a more robust parameter adjustment strategy deeply coupled with noise situational awareness.

[0044] The acquired capacitance signal is used as input to the LMS filter for real-time filtering. The filter parameter update formula is adjusted based on the touch environment perturbation, and the filter parameters are updated at each acquisition time. The filtered capacitance signal is directly used for touch recognition and coordinate calculation of the capacitive touchscreen. Through a dynamic adaptive filtering process, the filter parameters can be intelligently adjusted according to the real-time assessed touch environment perturbation, thereby achieving targeted noise suppression and improving the signal-to-noise ratio and stability.

[0045] The flowchart of the above method is as follows Figure 2 As shown; a schematic diagram of the process for obtaining the perturbation degree of the touch environment is shown below. Figure 3 As shown.

[0046] Based on the same inventive concept as the above method, this application embodiment also provides a debugging and configuration device for a capacitive touch screen. The device stores a computer program, and when the computer program is executed by a processor, it implements the steps of any one of the above-described debugging and configuration methods for a capacitive touch screen.

[0047] Based on the same inventive concept as the above method, this application embodiment also provides a debugging and configuration device for a capacitive touch screen, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any one of the above-described debugging and configuration methods for a capacitive touch screen.

[0048] In summary, this application provides a debugging and configuration method for a capacitive touchscreen. By collecting the capacitive signals of the touchscreen during repair and debugging, a comprehensive screen interference degree is constructed based on the proportion of noise energy in the spectrum of the capacitive signals and the peak intensity of the capacitive signals. This reflects the composite characteristics of continuous steady-state noise and sudden impulse noise in the environment, solving the problem that traditional single frequency domain or time domain analysis methods cannot fully quantify the impact of composite noise. The comprehensive screen interference degree at all times is smoothed, and the touch environment perturbation degree is constructed based on the difference between the data before and after smoothing and the degree of instability of the smoothed data, characterizing the dynamic instability and unpredictability of noise. The touch environment perturbation degree is integrated into the filter coefficient update formula to improve the filter, avoiding the problem of filter response lag or failure when noise changes drastically due to the use of fixed parameters in the filter coefficient update formula. This achieves intelligent coupling between filter behavior and noise status. Furthermore, the filtered capacitive signals are used for touch recognition and coordinate calculation of the capacitive touchscreen, significantly improving the touch stability, positioning accuracy, and anti-interference robustness of the capacitive touchscreen in complex electromagnetic environments, while balancing response speed and filtering effect.

[0049] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, the above description focuses on specific embodiments of this application. Additionally, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are possible or may be advantageous.

[0050] The various embodiments in this application are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0051] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the principles of this application should be included within the protection scope of this application.

Claims

1. A method for debugging and configuring a capacitive touchscreen, characterized in that, The method includes the following steps: Acquire timing data of capacitance signals from the sensor channels of the capacitive touchscreen; The peak level of the capacitor signal in the historical local time period at each moment is evaluated, and the energy proportion of the noise interference band in the spectrum of the capacitor signal in the local time period is calculated to determine the comprehensive screen display interference at each moment. The time-series data of comprehensive screen interference in historical local time periods at each moment are smoothed, and the touch environment perturbation degree at each moment is constructed based on the residual of the smoothed data and the degree of data change disorder. The filter coefficient update formula is adjusted based on the touch environment perturbation degree, and the filter is combined to perform capacitor signal filtering. The filtered capacitor signal is used for touch recognition and coordinate calculation of the capacitive touch screen.

2. The debugging and configuration method for a capacitive touchscreen as described in claim 1, characterized in that, The peak level of the capacitor signal within the historical local time period at each time point is: the peak-to-average power ratio of the capacitor signal time sequence within the historical local time period at each time point.

3. The debugging and configuration method for a capacitive touchscreen as described in claim 1, characterized in that, The calculation process for the energy proportion of the noise interference frequency band in the spectrum is as follows: By setting an interference frequency band, the ratio of the energy of the signal within the interference frequency band to the total energy of the spectrum in the historical local time period of the capacitor signal at each moment is calculated to obtain the energy ratio.

4. The debugging and configuration method for a capacitive touchscreen as described in claim 1, characterized in that, The overall screen interference is: the positive fusion value of the peak level of the capacitor signal and the energy ratio within a historical local time period at each moment.

5. The debugging and configuration method for a capacitive touchscreen as described in claim 1, characterized in that, The process of obtaining the touch environment perturbation degree is as follows: Calculate the mean residual of all the smoothed data within the historical local time period; The information entropy of all the smoothed data within the historical local time period is calculated using the histogram method; the touch environment perturbation degree at each time point is determined based on the residual mean and the information entropy, and the touch environment perturbation degree is positively correlated with the residual mean and the information entropy, respectively.

6. The debugging and configuration method for a capacitive touchscreen as described in claim 5, characterized in that, The perturbation degree of the touch environment is the product of the residual mean and the information entropy.

7. The debugging and configuration method for a capacitive touchscreen as described in claim 1, characterized in that, The process of adjusting the filter coefficients at each time point is as follows: The step size parameter in the original filter coefficient update formula is adjusted by the touch environment perturbation degree at each time step to obtain the adjusted filter coefficient update formula, and the filter parameters at each time step are updated using the adjusted filter coefficient update formula.

8. The debugging and configuration method for a capacitive touchscreen as described in claim 7, characterized in that, The adjusted filter coefficient update formula is as follows: In the formula, , These are the filter coefficients at the (n+1)th and nth acquisition times, respectively; This is the normalization function; This is the step size parameter; The perturbation degree of the touch environment at the nth acquisition time; This is the input signal at the nth acquisition time. This is the error signal at the nth acquisition time.

9. A debugging and configuration device for a capacitive touchscreen, the device storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the debugging and configuration method for a capacitive touchscreen as described in any one of claims 1-8.

10. A debugging and configuration device for a capacitive touchscreen, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the debugging and configuration method for a capacitive touchscreen as described in any one of claims 1-8.

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