Incell glass specification data matching debugging method and system

Abstract

The application relates to the technical field of glass debugging, and discloses an InCell glass specification data matching and debugging method and system. The method comprises the following steps: determining a driving code through a unique identifier of a target material; configuring the driving code as a driving basis of a probe to control the target material to enter a lighting working state; monitoring brightness distribution and a current waveform in the lighting working state, and generating a state ready signal when the brightness distribution and the current waveform meet preset state rules; in response to the state ready signal, synchronously collecting a line image and an electrical signal, extracting a topological contour and a time-frequency domain feature to generate line morphology and line electrical data; matching a corresponding parameter compensation scheme from a historical debugging library; and adjusting the driving code according to the parameter compensation scheme to obtain a debugging driving code. The application can improve the efficiency of InCell glass specification data matching and debugging.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of display debugging, and in particular to an InCell glass specification data matching debugging method and system. BACKGROUND

[0002] In the InCell glass specification data matching debugging process, the prior art has significant deficiencies in the drive code matching and probe driver configuration links. The prior art is difficult to accurately locate the adaptive drive code through the unique identifier of the target material, and relies more on manual screening or general code templates, resulting in a lack of effective verification of the compatibility of the drive code and the corresponding probe of the target material, and often the drive parameters and probe logic drive context do not match, which further causes the target material to frequently appear start-up abnormalities, brightness fluctuations and other problems when it enters the lighting working state. At the same time, the monitoring of the brightness distribution and current waveform under the lighting state lacks systematicness, only local area data can be obtained and the abnormality determination standard is ambiguous, which cannot accurately identify abnormal brightness areas and abnormal waveform sections, and it is difficult to reliably generate a state ready signal, directly affecting the accuracy and promotion efficiency of the subsequent debugging process.

[0003] The efficiency of the prior art in the data acquisition, feature extraction and parameter compensation scheme matching link is also poor. When responding to the ready signal, the prior art cannot realize the synchronous acquisition of the line image and the electrical signal, resulting in the misalignment of the time stamps of the two types of data, and the edge features are prone to breakage when extracting the line image topological profile. In the process of analyzing the time-frequency domain features of the electrical signal, key frequency components are easily lost, and the accuracy of the generated line shape and line electrical data is insufficient. In addition, when matching the parameter compensation scheme from the historical debugging library, the prior art only matches according to a single structural feature or impedance characteristic, without combining the topological structure of the line shape and the impedance characteristic of the line electrical data to carry out comprehensive analysis, resulting in poor adaptability of the matched compensation scheme, and still requiring multiple repeated debugging after adjusting the drive code, greatly increasing the debugging time and cost, and being difficult to meet the needs of efficient debugging of InCell glass. Therefore, how to improve the efficiency of InCell glass specification data matching debugging has become a problem to be solved. SUMMARY

[0004] The present application provides an InCell glass specification data matching debugging method and system to solve the problems raised in the background art.

[0005] To achieve the above-mentioned purpose, the present application provides an InCell glass specification data matching debugging method, which comprises:

[0006] S1, determining the drive code of the target material through the unique identifier of the target material;

[0007] S2, configure the driving code as a driving basis of the probe corresponding to the target material to control the target material to enter a lighting working state;

[0008] S3, monitor a brightness distribution and a current waveform of the target material in the lighting working state, and generate a state ready signal of the target material when the brightness distribution and the current waveform meet a preset state rule;

[0009] S4, in response to the state ready signal, synchronously collect a line image and an electrical signal of the target material, extract a topological contour of the line image and a time-frequency domain feature of the electrical signal to generate line morphology and line electrical data of the target material;

[0010] S5, according to the topological structure of the line morphology and the impedance characteristic of the line electrical data, match a corresponding parameter compensation scheme from a historical debugging library of the target material;

[0011] S6, adjust the driving code according to the parameter compensation scheme to obtain a debugging driving code of the target material.

[0012] In a preferred embodiment, the driving code is configured as a driving basis of the probe corresponding to the target material to control the target material to enter a lighting working state, comprising:

[0013] extracting driving parameters and timing control instructions in the driving code to obtain structured driving configuration data of the driving code;

[0014] verifying compatibility of the structured driving configuration data and the probe corresponding to the target material to obtain verified driving parameters of the structured driving configuration data;

[0015] binding the verified driving parameters and a logical driving context of the probe to obtain a driving configuration mapping relationship of the target material;

[0016] triggering an initialization sequence according to the driving configuration mapping relationship to activate the driving capability of the probe and control the target material to enter a lighting working state.

[0017] In a preferred embodiment, the verified driving parameters and the logical driving context of the probe are bound to obtain a driving configuration mapping relationship of the target material, comprising:

[0018] constructing a logical driving context template of the probe according to a communication protocol type and a timing parameter in a communication interface feature of the probe;

[0019] The verified driving parameters are organized hierarchically to obtain a hierarchical parameter configuration table of the verified driving parameters;

[0020] Allocate a parameter storage area in the logic driving context template, input the parameters in the hierarchical parameter configuration table into the parameter storage area, and obtain a parameterized template instance of the logic driving context template;

[0021] Based on the association between parameter identifiers in the parameterized template instance, the logical dependencies between the parameters are analyzed, and the logical dependencies are used as the driving configuration mapping relationship of the target material.

[0022] In a preferred embodiment, monitoring the brightness distribution and current waveform of the target material under the illumination working state, and generating a state-ready signal for the target material when the brightness distribution and current waveform meet a preset state rule, includes:

[0023] The display area of ​​the target material is divided into a brightness sampling area, and test access points are specified at the key circuit nodes of the probe to obtain the current monitoring nodes of the probe.

[0024] The pixel distribution of illumination points in the brightness sampling region is structured using a feature tensor to obtain the brightness distribution matrix of the brightness sampling region.

[0025] The high-frequency signal of the current monitoring node is reconstructed to obtain the current waveform sequence of the high-frequency signal;

[0026] Based on the brightness distribution matrix, abnormal brightness areas in the display area are identified;

[0027] Based on the anomaly determination criteria in the preset state rules, the abnormal waveform segment in the current waveform sequence is located.

[0028] The spatial distribution density of the abnormal brightness region and the temporal distribution frequency of the abnormal waveform segment are statistically analyzed to obtain the distribution parameters of the target material;

[0029] When the distribution parameters satisfy the stability condition in the state rule, a state ready signal for the target material is generated.

[0030] In a preferred embodiment, the formula for calculating the spatial distribution density is as follows: ;

[0031] In the formula, The spatial distribution density, This refers to the number of regions with abnormal brightness. For the first The area of ​​each abnormal brightness region an average luminance value of the first abnormal luminance region, a preset luminance threshold value, a total area of the display region, an absolute value.

[0032] In a preferred embodiment, the line image and the electrical signal of the target material are synchronously collected in response to the state ready signal, the topological profile of the line image and the time-frequency domain feature of the electrical signal are extracted to generate the line morphology and the line electrical data of the target material, including:

[0033] The state ready signal is encoded as a synchronous control instruction of the target material;

[0034] The image data collection and the electrical signal collection under the guidance of the synchronous control instruction are implemented to obtain a line image set and an electrical signal set of the target material;

[0035] The edge features in the line image set are geometrically reconstructed to obtain topological profile data of the edge features;

[0036] The time-frequency components in the electrical signal set are deconstructed to obtain time-frequency feature descriptions of the time-frequency components;

[0037] The topological profile data are fused to obtain the line morphology of the target material;

[0038] The time-frequency feature descriptions and the topological profile data are coupled and analyzed to obtain the line electrical data of the target material.

[0039] In a preferred embodiment, the topological profile data are fused to obtain the line morphology of the target material, including:

[0040] Discrete profile segments in the topological profile data are associated to obtain a profile segment association relationship of the topological profile data;

[0041] The topological profile data are topologically synthesized with the profile segment association relationship as a connection path to obtain a line topological structure diagram of the target material;

[0042] Connected paths in the line topological structure diagram are output as the line morphology of the target material.

[0043] In a preferred embodiment, the corresponding parameter compensation scheme is matched from a historical debugging library of the target material according to the topological structure of the line morphology and the impedance characteristics of the line electrical data, including:

[0044] ​screening a key geometric element in a topology of the line form to obtain a structural feature of the line form;

[0045] extracting a change mode in an impedance characteristic of the line electrical data to obtain an impedance feature of the line electrical data;

[0046] tensor synthesizing the structural feature and the impedance feature to obtain a joint feature quantity of the target material;

[0047] inputting the joint feature quantity into a historical debugging library of the target material to select a parameter compensation scheme suitable for a current scene in the historical debugging library.

[0048] In a preferred embodiment, the adjusting the driving code according to the parameter compensation scheme to obtain the debugging driving code of the target material comprises:

[0049] parsing a configuration parameter in the parameter compensation scheme to obtain a parameter adjustment instruction of the driving code;

[0050] injecting the parameter adjustment instruction into the driving code to obtain a preliminary adjusted driving code of the target material;

[0051] reconstructing a logic structure of the preliminary adjusted driving code and verifying functional integrity of the reconstructed driving code to obtain the debugging driving code of the target material.

[0052] In order to solve the above problems, the application further provides an InCell glass specification data matching debugging system, the system comprises:

[0053] a driving code retrieval module configured to determine the driving code of the target material through a unique identifier of the target material;

[0054] a probe driving configuration module configured to configure the driving code as a driving basis of a probe corresponding to the target material to control the target material to enter a lighting working state;

[0055] a state monitoring and signal generation module configured to monitor a brightness distribution and a current waveform of the target material in the lighting working state, and generate a state ready signal of the target material when the brightness distribution and the current waveform meet a preset state rule;

[0056] a data acquisition and feature extraction module configured to synchronously acquire a line image and electrical signals of the target material in response to the state ready signal, extract a topological contour of the line image and a time-frequency domain feature of the electrical signals, and generate line form and line electrical data of the target material;

[0057] A parameter compensation matching module is configured to match a corresponding parameter compensation scheme from a historical debugging library of the target material according to a topology of the line pattern and impedance characteristics of the line electrical data.

[0058] A driving code adjustment module is configured to adjust the driving code according to the parameter compensation scheme to obtain a post-debugging driving code of the target material.

[0059] Compared with the prior art, the present application has the following beneficial effects:

[0060] 1. The present application accurately determines the corresponding driving code through the unique identifier of the target material, configures it as the driving basis of the probe corresponding to the target material, ensures the adaptability of the driving parameters and the probe logic driving context, and reliably controls the target material to enter the lighting working state; at the same time, the brightness distribution and current waveform in the lighting state are monitored, the abnormal area and section are identified according to the preset state rule, and the state readiness signal is stably generated, which provides a stable precondition for subsequent debugging and improves the reliability and efficiency of the early preparation link of debugging.

[0061] 2. The present application synchronously collects the line image and electrical signal in response to the state readiness signal, extracts the line image topology contour and electrical signal time-frequency domain features, generates accurate line pattern and line electrical data; then, the driving code is adjusted by matching the adaptive parameter compensation scheme from the historical debugging library in combination with the line pattern topology structure and the line electrical data impedance characteristics, which improves the parameter compensation accuracy, reduces the invalid debugging link, significantly improves the InCell glass specification data matching debugging efficiency, and guarantees the performance stability of the post-debugging InCell glass. BRIEF DESCRIPTION OF DRAWINGS

[0062] Figure 1 A flowchart of an InCell glass specification data matching debugging method provided by an embodiment of the present application is shown;

[0063] Figure 2 A functional module diagram of an InCell glass specification data matching debugging system provided by an embodiment of the present application is shown;

[0064] The implementation, functional features and advantages of the present application will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION

[0065] It should be understood that the specific embodiments described herein are only used to explain the present application and do not limit the present application.

[0066] The embodiment of the application provides an InCell glass specification data matching debugging method. The execution subject of the InCell glass specification data matching debugging method includes but is not limited to at least one of electronic devices such as a server and a terminal, which can be configured to execute the method provided by the embodiment of the application. In other words, the InCell glass specification data matching debugging method can be executed by software or hardware installed in a terminal device or a server device. The server includes but is not limited to a single server, a server cluster, a cloud server or a cloud server cluster, etc. The server can be a stand-alone server, or a cloud server providing cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content distribution networks (CDN), and basic cloud computing services such as big data and artificial intelligence platforms.

[0067] Referring to Figure 1 FIG. 1 is a flowchart of an InCell glass specification data matching debugging method provided by an embodiment of the application. In the embodiment, the InCell glass specification data matching debugging method includes the following steps.

[0068] In the embodiment of the application, S1, the driving code of the target material is determined through the unique identifier of the target material.

[0069] The unique identifier of the target material is obtained, which is a unique code preset for each InCell glass when it is manufactured. The unique identifier can be read in two ways. If the identifier is marked on the edge of the target material in the form of laser engraving, a high-definition code scanning device is used to approach the code area, and the device converts the code pattern into digital text through optical recognition technology. If the identifier is stored in the electronic tag built-in the target material, a radio frequency identification reader is used to approach the target material, and the digital code stored in the electronic tag is read through wireless radio frequency signals, so as to finally obtain the unique identifier text of the target material.

[0070] The obtained unique identifier is used as a search keyword, and a database system storing the driving code is accessed. The database is pre-stored in the corresponding relationship of "unique identifier-driving code", and each unique identifier is bound to a driving code file adapted to the specification of the corresponding InCell glass. The unique identifier text is input in the database search interface, the accurate matching search function of the database is triggered, all stored entries in the database are automatically traversed, the entry completely consistent with the input identifier is located, and the driving code file basic information associated with the entry is called.

[0071] The actual file corresponding to the retrieved driving code file basic information is matched and verified, the driving code file is opened, the material specification parameters recorded in the file are extracted, the actual specification parameters of the target material are obtained through a measuring tool, and the specification parameters are compared one by one to confirm that all parameters are completely consistent, and it is determined that the driving code is adapted to the target material.

[0072] After confirming the adaptation, the driving code file is downloaded from the corresponding storage path of the database, the file is saved to the "driving code temporary storage area" of the debugging system, and a file retrieval record is generated, the process of determining the driving code of the target material through the unique identifier of the target material is completed, and finally the product obtained is the driving code of the target material.

[0073] The beneficial effects are that the driving code is accurately positioned through the exclusive unique identifier, the identifier reading accuracy is ensured through optical or radio frequency identification, the driving code adaptability is verified through specification parameter comparison, the driving code mismatch problem is avoided, the compatibility of the subsequent probe driving configuration and the target material is ensured, a reliable premise is provided for the target material to smoothly enter the lighting working state, the time consumption of driving code searching and confirming is shortened, and the efficiency of the early preparation link of debugging is improved.

[0074] S2, the driving code is configured as the driving basis of the probe corresponding to the target material, so as to control the target material to enter the lighting working state;

[0075] In the embodiment of the application, the driving code is configured as the driving basis of the probe corresponding to the target material, so as to control the target material to enter the lighting working state, comprising:

[0076] The driving parameters and timing control instructions in the driving code are extracted to obtain the structured driving configuration data of the driving code;

[0077] The compatibility of the structured driving configuration data and the probe corresponding to the target material is verified to obtain the verified driving parameters of the structured driving configuration data;

[0078] The verified driving parameters are bound to the logical driving context of the probe to obtain the driving configuration mapping relationship of the target material;

[0079] According to the driving configuration mapping relationship, an initialization sequence is triggered to activate the driving capability of the probe and control the target material to enter the lighting working state.

[0080] The verified driving parameters are bound to the logical driving context of the probe to obtain the driving configuration mapping relationship of the target material, comprising:

[0081] According to the communication protocol type and timing parameter in the communication interface feature of the probe, a logical drive context template of the probe is constructed;

[0082] The verified drive parameters are hierarchically organized to obtain a hierarchical parameter configuration table of the verified drive parameters;

[0083] A parameter storage area is allocated in the logical drive context template, and parameters in the hierarchical parameter configuration table are input into the parameter storage area to obtain a parameterized template instance of the logical drive context template;

[0084] According to the association relationship between parameter identifiers in the parameterized template instance, logical dependencies between the parameters are analyzed, and the logical dependencies are taken as a drive configuration mapping relationship of the target material.

[0085] The drive code file of the determined target material is opened, and the code content is read line by line, the field marked as "drive parameter" in the code is identified, including specific numerical information such as voltage value, current value, signal frequency required for the target material to work, and the "timing control instruction" in the code for controlling the action sequence of the probe is screened out, such as probe start instruction, signal sending interval instruction, and sleep trigger instruction. The extracted drive parameters are arranged in the format of "parameter name-parameter value-parameter purpose", and the timing control instructions are arranged in the format of "instruction name-execution condition-execution sequence", and the two types of information are integrated into a unified table form, which is the structured drive configuration data of the drive code.

[0086] The specification of the probe corresponding to the target material is obtained, and the maximum voltage, minimum current, adaptive signal frequency range, and compatible timing instruction type supported by the probe are extracted. Each drive parameter in the structured drive configuration data is compared with the corresponding compatibility index of the probe, if the value of the drive parameter is within the range supported by the probe, it is determined that the parameter is compatible, if it is out of range, it is marked as incompatible. At the same time, it is checked whether the timing control instruction in the structured drive configuration data is in the list of instructions that the probe can respond to, and the instructions that the probe can respond to are marked as compatible, and the instructions that the probe cannot respond to are marked as incompatible. All drive parameters and timing control instructions marked as incompatible are removed, and compatible drive parameters are retained, which are the verified drive parameters of the structured drive configuration data.

[0087] By consulting the hardware manual of the probe, the communication protocol type of the probe communication interface is determined, such as USB protocol, SPI protocol or I2C protocol, etc., and the timing parameters of data transmission under the communication protocol are recorded, including data bit width, transmission rate, synchronization signal duration, data interval time, etc. Based on these information, a logical drive context template is constructed, the "communication protocol type" field is set in the template for filling in the determined protocol name, the "timing parameter" field is set for filling in the specific timing information such as data bit width, transmission rate, etc., and the "parameter association area" is reserved for subsequent association of drive parameters, forming a probe logical drive context template containing a fixed field structure.

[0088] According to the functional use of the verified drive parameters, they are divided into three levels: the first level is "basic running parameters", including voltage values, current values and the like for maintaining the basic work of the probe; the second level is "communication control parameters", including signal frequency, data transmission format and the like matched with the probe communication interface; and the third level is "protection mechanism parameters", including parameter values corresponding to the probe overcurrent protection threshold, overheat protection trigger temperature and the like. In the table, according to the column structure of "parameter level-parameter name-parameter value-parameter function description", all the verified drive parameters are filled in the corresponding positions one by one, forming a hierarchical parameter configuration table of the verified drive parameters.

[0089] In the "parameter association area" of the logical drive context template, the corresponding storage areas are divided according to the parameter levels, i.e. "basic running parameter storage area", "communication control parameter storage area" and "protection mechanism parameter storage area" are set respectively. From the hierarchical parameter configuration table, the parameters of each level are extracted in turn, and all the parameters and their values under the "basic running parameter" level are filled into the "basic running parameter storage area", the "communication control parameters" are filled into the "communication control parameter storage area", and the "protection mechanism parameters" are filled into the "protection mechanism parameter storage area", so as to ensure that the name and value of each parameter are stored correspondingly in the template. The logical drive context template after parameter input is the parameterized template instance of the logical drive context template.

[0090] Each parameter in the parameterized template instance has a unique parameter identifier, such as "basic running parameter-voltage", "communication control parameter-signal frequency", etc. These parameter identifiers are checked one by one to identify parameter pairs that exist in association, for example, "basic running parameter-voltage" needs to reach a preset value before "communication control parameter-signal frequency" can take effect at a set value, and there is an association relationship between the two, i.e. "voltage meets the standard → frequency takes effect"; when "protection mechanism parameter-overcurrent threshold" is triggered, "basic running parameter-current" needs to be immediately reduced to a safe value, and there is an association relationship between the two, i.e. "overcurrent trigger → current down". All the identified association relationships are arranged in the form of "trigger parameter-response parameter-association rule", and these association relationships are the drive configuration mapping relationship of the target material.

[0091] Following the association rules in the driver configuration mapping relationship, an initialization sequence is generated: First, an instruction to load "basic operating parameters" is sent to the probe, transmitting parameters such as voltage and current to the probe's hardware circuitry, enabling the probe to meet basic operating conditions. Next, based on the association rules between "communication control parameters" and "basic operating parameters," after the voltage and current meet the requirements, parameters such as signal frequency and data transmission format are loaded to activate the probe's communication function. Finally, "protection mechanism parameters" are enabled to ensure that the probe can trigger protection actions under abnormal conditions. During the execution of the initialization sequence, the probe's driving capability is gradually activated. The probe sends a lighting control signal to the target material according to the driver configuration mapping relationship. Upon receiving the signal, the target material's display area begins to illuminate, entering the lighting working state.

[0092] The beneficial effects are as follows: by extracting structured driver configuration data and verifying compatibility, the driver parameters are ensured to be compatible with the probe; by constructing a logical driver context template, hierarchically organizing parameters, and analyzing logical dependencies, the relationship between parameters is clarified; finally, the initialization sequence is triggered based on the driver configuration mapping relationship, which reliably activates the probe driving capability and puts the target material into the lighting working state. The entire process has accurate parameter matching and clear step logic, effectively avoiding debugging failures caused by parameter incompatibility or chaotic association, and improving the stability and efficiency of the target material lighting process.

[0093] S3. Monitor the brightness distribution and current waveform of the target material under the illumination working state. When the brightness distribution and the current waveform meet the preset state rules, generate the state ready signal of the target material.

[0094] In this embodiment of the invention, the step of monitoring the brightness distribution and current waveform of the target material under the illumination working state, and generating a state-ready signal for the target material when the brightness distribution and the current waveform satisfy a preset state rule, includes:

[0095] The display area of ​​the target material is divided into a brightness sampling area, and test access points are specified at the key circuit nodes of the probe to obtain the current monitoring nodes of the probe.

[0096] The pixel distribution of illumination points in the brightness sampling region is structured using a feature tensor to obtain the brightness distribution matrix of the brightness sampling region.

[0097] The high-frequency signal of the current monitoring node is reconstructed to obtain the current waveform sequence of the high-frequency signal;

[0098] Based on the brightness distribution matrix, abnormal brightness areas in the display area are identified;

[0099] Based on the anomaly determination criteria in the preset state rules, the abnormal waveform segment in the current waveform sequence is located.

[0100] The spatial distribution density of the abnormal brightness region and the temporal distribution frequency of the abnormal waveform segment are statistically analyzed to obtain the distribution parameters of the target material;

[0101] When the distribution parameters satisfy the stability condition in the state rule, a state ready signal for the target material is generated.

[0102] The formula for calculating the spatial distribution density is as follows: ;

[0103] In the formula, The spatial distribution density, This refers to the number of regions with abnormal brightness. For the first The area of ​​each abnormal brightness region For the first The average brightness value of each abnormal brightness area The preset brightness threshold, The total area of ​​the display area. To take the absolute value.

[0104] First, use high-precision calipers to measure the total horizontal and vertical lengths of the target material display area. Divide both sides into 20 equal parts and draw dividing lines. The intersection of these lines forms 400 identical rectangular areas, each representing the brightness sampling area. Consult the probe's hardware specifications to identify the three key circuit nodes: power input, signal output, and ground. Solder 5cm test leads to the metal pins of each key circuit node. Connect the other end of the test leads to the signal input terminal of the current monitoring device. These key circuit nodes with soldered test leads are the probe's current monitoring nodes.

[0105] Fix the brightness acquisition camera 30 cm directly in front of the target material. Adjust the camera parameters to ensure a complete image of the display area and clear pixel identification in each brightness sampling area. Start the camera to acquire the pixel brightness values ​​of all illuminated points within each brightness sampling area. Set the horizontal arrangement of the brightness sampling areas as rows and the vertical arrangement as columns in the matrix. Calculate the average brightness value of all pixels within each brightness sampling area and use this average value as the element value at the intersection of the corresponding row and column. If any individual pixel brightness value within a sampling area is abnormally high or low, use the average brightness value of all pixels within that area as the element value. Fill all rows and columns of the matrix sequentially, resulting in a two-dimensional numerical table of 400 elements, which is the brightness distribution matrix of the brightness sampling area.

[0106] Clamp the current probe of the oscilloscope on the test lead of the current monitoring node, set the sampling frequency of the oscilloscope to 100MHz, the sampling duration to 10 seconds, click the "acquisition" button of the oscilloscope to start collecting the current signal at the current monitoring node. Select the "high frequency reconstruction" function in the signal processing interface of the oscilloscope, which will automatically filter the low frequency interference components in the collected signal with a frequency lower than 1MHz, and retain the high frequency current signal with a frequency in the range of 1MHz-50MHz. According to the time sequence of the oscilloscope sampling, extract the current value at each 0.01 second time point from the reconstructed high frequency signal, arrange these values in time sequence, and form an ordered list containing 1000 values, which is the current waveform sequence of the high frequency signal.

[0107] The brightness determination threshold is called from the preset state rule document, which specifies that the upper limit of brightness is 500cd / m² and the lower limit of brightness is 100cd / m². The average brightness value of each element in the brightness distribution matrix is read one by one, and compared with the brightness determination threshold. If the average brightness value of an element is greater than 500cd / m² or less than 100cd / m², the brightness sampling area corresponding to the element in the matrix is marked as an abnormal brightness area, and the horizontal and vertical coordinate ranges of each abnormal brightness area in the display area are recorded.

[0108] The current waveform abnormality determination criteria are obtained by opening the preset state rule document: the current peak value range is 50mA-100mA, the current waveform fluctuation amplitude upper limit is 20mA, and the current continuous stable time lower limit is 0.5 seconds. According to the standard of 0.5 seconds as a section, the current waveform sequence is divided into 20 waveform sections, and the current peak value, fluctuation amplitude and continuous stable time of each waveform section are calculated. If the current peak value of a waveform section is greater than 100mA or less than 50mA, or the fluctuation amplitude is greater than 20mA, or the continuous stable time is less than 0.5 seconds, the waveform section is marked as an abnormal waveform section, and the start and end time points of each abnormal waveform section are recorded.

[0109] The number of abnormal brightness areas is the total number of abnormal areas marked when identifying abnormal brightness areas; the area of the first abnormal brightness area is obtained by multiplying the horizontal length and vertical length of each abnormal area read by the image measurement tool; the area of the second abnormal brightness area is obtained by multiplying the horizontal length and vertical length of each abnormal area read by the image measurement tool; and so on. ​The average luminance value of the abnormal luminance area is the element value corresponding to the abnormal area in the luminance distribution matrix; the preset luminance threshold value is the luminance determination standard value called from the preset state rule document; and the total area of the display area is the product of the total length in the horizontal direction and the total length in the vertical direction of the display area measured by a high-precision caliper before the luminance sampling area is divided. When calculating the spatial distribution density, first, the area of each abnormal luminance area is multiplied by the absolute value of the difference between the average luminance value of the area and the preset luminance threshold value, and then all the results are added to obtain the numerator; the total area of the display area is multiplied by the preset luminance threshold value to obtain the denominator; and the result of the numerator divided by the denominator is the spatial distribution density of the abnormal luminance area. This calculation can comprehensively consider the size of the abnormal area and the severity of the luminance abnormality, and provide a quantitative basis for subsequent judgment. The total number of abnormal waveform sections in the current waveform sequence is counted, and the total number of abnormal waveform sections is divided by the total sampling duration of the current waveform sequence to obtain the time distribution frequency of the abnormal waveform section. The spatial distribution density and the time distribution frequency are arranged as a set of associated data, and the set of data is the distribution parameter of the target material.

[0110] The stable condition threshold value is extracted from the preset state rule document: the maximum allowed value of the spatial distribution density is 5%, and the maximum allowed value of the time distribution frequency is 0.2 times per second. The spatial distribution density in the distribution parameter is compared with 5%, and the time distribution frequency is compared with 0.2 times per second. If the spatial distribution density is less than or equal to 5%, and the time distribution frequency is less than or equal to 0.2 times per second, it is determined that the distribution parameter meets the stable condition. The signal generation module in the debugging system is started, which outputs a high-level signal with a voltage of 3.3V. The high-level signal is the state ready signal of the target material, and the specific time stamp of the signal generation is recorded in the log of the debugging system.

[0111] The beneficial effects are that the luminance sampling area is scientifically divided and the current monitoring node is accurately specified to ensure the comprehensiveness and pertinence of luminance and current data collection; the accuracy of the luminance distribution matrix and the current waveform sequence is improved through the feature tensor structuring and high-frequency signal reconstruction to provide reliable data basis for abnormal identification; the stable state of the target material is accurately judged and the ready signal is generated through the explicit abnormality determination standard, the spatial distribution density calculation combined with the parameter source and the quantitative meaning, and the time distribution frequency statistics, which effectively avoids the subsequent debugging deviation caused by state misjudgment, ensures the timing accuracy of synchronously collecting the line image and the electrical signal, and improves the stability and efficiency of the InCell glass specification data matching debugging as a whole.

[0112] S4, in response to the state ready signal, synchronously collecting the line image and the electrical signal of the target material, extracting the topological contour of the line image and the time-frequency domain feature of the electrical signal to generate the line morphology and the line electrical data of the target material;

[0113] In the embodiment of the present application, the line image and the electrical signal of the target material are synchronously collected in response to the state ready signal, the topological profile of the line image and the time-frequency domain feature of the electrical signal are extracted to generate the line morphology and the line electrical data of the target material, comprising:

[0114] The state ready signal is encoded as the synchronous control instruction of the target material;

[0115] The image data collection and the electrical signal collection under the guidance of the synchronous control instruction are implemented to obtain the line image set and the electrical signal set of the target material;

[0116] The edge features in the line image set are geometrically reconstructed to obtain the topological profile data of the edge features;

[0117] The time-frequency components in the electrical signal set are deconstructed to obtain the time-frequency feature description of the time-frequency components;

[0118] The topological profile data are fused to obtain the line morphology of the target material;

[0119] The time-frequency feature description and the topological profile data are coupled and analyzed to obtain the line electrical data of the target material.

[0120] The topological profile data are fused to obtain the line morphology of the target material, comprising:

[0121] The discrete profile segments in the topological profile data are associated to obtain the profile segment association relationship of the topological profile data;

[0122] The topological profile data are topologically synthesized with the profile segment association relationship as the connection path to obtain the line topological structure diagram of the target material;

[0123] The connected path in the line topological structure diagram is output as the line morphology of the target material.

[0124] The state ready signal is a 3.3V high-level signal output by the debugging system, and the debugging system is built-in with an encoding module which converts the high-level signal into binary code: first, the "start image collection" instruction is encoded as "0011", and the "start electrical signal collection" instruction is encoded as "1100"; then, the binary codes of the two instructions are spliced in the order of "image collection instruction + electrical signal collection instruction" to form an 8-bit binary synchronous control instruction "00111100", and a check bit "1" is added to the instruction, and finally a 9-bit binary instruction containing the check bit is obtained as the synchronous control instruction of the target material.

[0125] The synchronization control instruction is transmitted to the high-definition industrial camera and the digital oscilloscope through the data line. After receiving the instruction, the camera and the oscilloscope will start collecting at the same time within 0.1 seconds. The camera is fixed 20 centimeters above the target material, with the lens vertically aligned with the line area. Ten line images are continuously collected, and the 10 images are named in the order of collection time as "Img1-Img10" to form a line image set of the target material. The probe of the oscilloscope is connected to the signal output node of the probe, and 10 groups of electrical signals are synchronously collected. Each group of signals is named in the order of collection as "Sig1-Sig10" to form an electrical signal set of the target material.

[0126] Open each image in the line image set, convert the color image to a grayscale image using the image grayscale processing tool, set the grayscale threshold to 150, extract the line and background intersection pixel points in each image, and record the two-dimensional coordinates of each edge feature point. For each edge feature point of each image, arrange them in the order of increasing x-axis coordinates. If the difference in y-axis coordinates between adjacent feature points is less than 2 pixels, connect the two points with a straight line. If the difference is greater than 2 pixels, mark it as a discrete edge segment. Process all edge feature points in turn to obtain the edge coordinate sequence of each image. Integrate the edge coordinate sequences of the 10 images to form the topological contour data of the edge features.

[0127] Open each group of signals in the electrical signal set, and select the "component decomposition" function in the time-frequency analysis interface of the oscilloscope. This function will decompose each electrical signal into sinusoidal components of different frequencies. Record the key information of each frequency component: frequency value, amplitude value, phase value, and duration. Organize the time-frequency component information of each group of signals in the format "frequency-amplitude-phase-duration". The organization results of the 10 groups of signals together form the time-frequency feature description of the time-frequency components.

[0128] Extract all discrete contour segments from the topological contour data, number each discrete contour segment, and record the starting coordinates (x1, y1) and ending coordinates (x2, y2) of each discrete contour segment. Calculate the distance between the endpoints of any two discrete contour segments: if the straight-line distance between the ending coordinates (x2, y2) of segment S1 and the starting coordinates (x3, y3) of segment S2 is less than 0.1 millimeter, then it is determined that S1 and S2 have a correlation relationship, marked as "S1→S2"; if the distance between the ending coordinates of segment S2 and the starting coordinates of segment S3 is also less than 0.1 millimeter, then it is marked as "S2→S3". Traverse all discrete contour segments in turn, record all correlation relationships, and form the contour segment correlation relationship of the topological contour data.

[0129] In the drawing software, create a canvas with the same scale as the target material line area, and draw the discrete contour segments in the order of contour segment association: first draw S1, then draw S2 from the end coordinates of S1, then draw S3 from the end coordinates of S2, and complete the drawing of a connected line; similarly, draw the connected line of S4→S5. In the drawing process, mark the intersection nodes of the line with different colors, and mark the number of each node with text. The final graph formed on the canvas, which contains all the connected lines, nodes and annotation information, is the line topology structure diagram of the target material.

[0130] From the line topology structure diagram, identify all independent connected paths. For each connected path, extract the maximum and minimum values of the x-axis and y-axis of all coordinate points to determine the spatial range of the path; record the direction and number of line segments of the path. Organize the spatial range, direction, number of line segments and complete coordinate sequence of each connected path in the format of "path number-spatial range-direction-number of line segments-coordinate sequence", for example, "path 1-(x0-x10, y0-y5)-horizontal as the main-3 line segments-coordinate (0, 0), (5, 0), (5, 3), (10, 3)". The organization results of all paths together form the line pattern of the target material.

[0131] From the time-frequency feature description, extract the main frequency components of each group of signals, and extract the line edge segment information corresponding to the collection time from the topology contour data. Analyze the correspondence between the main frequency components and the edge segments: if an edge segment S1 corresponds to a line length of 5mm in the image, the main frequency of the electrical signal at the collection time is 5MHz, and the amplitude is 3V, then record "S1-frequency 5MHz-amplitude 3V"; if the edge segment S2 corresponds to a line length of 3mm, the main frequency of the electrical signal at the collection time is 5MHz, and the amplitude is 2.8V, then record "S2-frequency 5MHz-amplitude 2.8V". At the same time, analyze the electrical signal characteristics at the line intersection nodes, record the node number, corresponding frequency and amplitude, and organize the correspondence between all edge segments, nodes and electrical characteristics into a table. This table is the line electrical data of the target material.

[0132] The beneficial effects are: by encoding the state ready signal as a synchronous control instruction, ensuring the time consistency of image and electrical signal collection, avoiding data misplacement; by edge feature geometric reconstruction, time-frequency component decomposition and contour segment association, accurately extracting line topology contour and signal time-frequency feature, providing reliable data for line pattern generation; by topology synthesis and coupling analysis, deeply associating line geometric information and electrical characteristics, obtaining accurate line pattern and line electrical data, providing comprehensive and accurate basis for subsequent matching parameter compensation scheme, effectively improving the accuracy and efficiency of InCell glass specification data matching and debugging.

[0133] S5. Based on the topology of the line configuration and the impedance characteristics of the line electrical data, match the corresponding parameter compensation scheme from the historical debugging library of the target material.

[0134] In this embodiment of the invention, the step of matching a corresponding parameter compensation scheme from the historical debugging library of the target material based on the topology of the line configuration and the impedance characteristics of the line electrical data includes:

[0135] By filtering the key geometric elements in the topology of the line morphology, the structural features of the line morphology are obtained;

[0136] The impedance characteristics of the line electrical data are obtained by extracting the variation patterns in the impedance characteristics.

[0137] Tensor synthesis is performed on the structural features and the impedance features to obtain the joint characteristic quantities of the target material;

[0138] The joint feature quantity is input into the historical debugging library of the target material, and a parameter compensation scheme suitable for the current scenario is selected from the historical debugging library.

[0139] Key geometric elements in the topology of the described line form are selected to obtain its structural characteristics. All geometric elements are extracted from the line form, including the width, length, and bending angle of each connected path, as well as the number and spacing of line intersections. The "Geometric Element-Impedance Influence Correlation Table" recorded in the historical debugging database is consulted to identify elements that significantly affect impedance characteristics: line width, line length, bending angle, number of intersections, and node spacing. The specific values ​​of these key elements are recorded, for example, "Line segment S1: width 0.08mm, length 12mm, bending angle 120 degrees, number of intersections 3, node spacing 2mm." These values ​​are then organized in the format of "Line segment - key element - specific value" to form the structural characteristics of the line form.

[0140] The impedance characteristics of the line electrical data are obtained by extracting the variation patterns of the impedance characteristics. Impedance measurements of each line segment at different frequencies are extracted from the line electrical data and arranged in ascending order of frequency, forming an impedance-frequency data sequence for each line segment. The variation pattern of each sequence is analyzed: whether the impedance increases or decreases linearly with increasing frequency, fluctuates non-linearly, or exhibits abrupt changes; the trend is recorded. If abrupt changes occur, the corresponding frequency value and impedance change amplitude are recorded. Simultaneously, the impedance difference between different line segments at the same frequency is calculated. These variation patterns are organized in the format of "frequency range - variation trend - abrupt change characteristic - impedance difference" to form the impedance characteristics of the line electrical data.

[0141] Tensor synthesis is performed on the structural features and the impedance features to obtain the joint characteristic quantity of the target material. First, the key elements in the structural features are organized into one-dimensional ordered data in a fixed order: line width → line length → bending angle → number of intersection nodes → node spacing, for example, "0.08mm, 12mm, 120 degrees, 3 nodes, 2mm". Then, the variation patterns in the impedance features are organized into another-dimensional ordered data in a fixed order: frequency range → variation trend → abrupt change frequency → abrupt change increase → impedance difference, for example, "1-5MHz, linear decrease, 5MHz, 50%, 0.5Ω". These two-dimensional ordered data are then concatenated in the order of "structural feature ordered data + impedance feature ordered data" to form a complete ordered data set containing all key structural information and impedance variation information. This set is the joint characteristic quantity of the target material, for example, "0.08mm, 12mm, 120 degrees, 3 nodes, 2mm; 1-5MHz, linear decrease, 5MHz, 50%, 0.5Ω".

[0142] The joint characteristic quantity is input into the historical debugging library of the target material, and a parameter compensation scheme suitable for the current scenario is selected from the historical debugging library. The historical debugging library pre-stores a large number of corresponding entries for "joint characteristic quantity - parameter compensation scheme", and each entry contains compensation measures that match the joint characteristic quantity. The current joint characteristic quantity is compared item by item with the joint characteristic quantity in all entries in the library: first, the structural characteristic part is compared, requiring that the numerical error of key elements such as line width, length, and bending angle is less than 10%; then, the impedance characteristic part is compared, requiring that the changing trend, abrupt change frequency, and other patterns are completely consistent. The entry with the highest similarity that meets the above conditions is found, and the parameter compensation scheme corresponding to that entry is retrieved, for example, "adjust the driving voltage from 3.3V to 3.5V, optimize the signal frequency to 4.8MHz, and increase the impedance matching resistor by 0.3Ω". It is confirmed that the application scenario of this scheme is consistent with the current target material scenario, and this scheme is the selected parameter compensation scheme suitable for the current scenario.

[0143] The beneficial effects are as follows: by screening key geometric elements that significantly affect impedance to form structural features, the targeted nature of feature extraction is ensured; by extracting the core change patterns of impedance characteristics to form impedance features, key information on electrical performance is accurately captured; by tensor synthesis, multi-dimensional features are integrated into joint feature quantities, achieving the unification of structural and electrical information; and finally, based on the joint feature quantities, a suitable parameter compensation scheme is matched from the historical debugging library, which greatly improves the matching accuracy of the compensation scheme, reduces invalid debugging attempts, and effectively improves the efficiency and reliability of InCell glass specification data matching and debugging.

[0144] S6. Adjust the driving code according to the parameter compensation scheme to obtain the debugged driving code for the target material.

[0145] In the embodiment of the present application, the adjusting the driving code according to the parameter compensation scheme comprises:

[0146] parsing the configuration parameters in the parameter compensation scheme to obtain parameter adjustment instructions of the driving code;

[0147] injecting the parameter adjustment instructions into the driving code to obtain a preliminary adjusted driving code of the target material;

[0148] reconstructing the logical structure of the preliminary adjusted driving code and verifying the functional integrity of the reconstructed driving code to obtain the debugged driving code of the target material.

[0149] Parsing the configuration parameters in the parameter compensation scheme to obtain parameter adjustment instructions of the driving code. Open the parameter compensation scheme document and read the configuration parameters recorded in the document line by line. These parameters include driving voltage target value, signal frequency adjustment value, impedance matching resistance parameter, etc. According to the parameter definition manual of the driving code, determine the corresponding parameter identifier of each configuration parameter in the driving code, for example, "driving voltage" corresponds to "V_Drive" in the code, and "signal frequency" corresponds to "F_Signal" in the code. Generate parameter adjustment instructions in the format of "parameter identifier + adjustment type + target value", for example, "V_Drive-up-3.5V", "F_Signal-optimize-4.8MHz", "R_Match-add-0.3Ω", and arrange all generated instructions according to the appearance order of parameters in the driving code to form a parameter adjustment instruction set of the driving code.

[0150] Injecting the parameter adjustment instructions into the driving code to obtain a preliminary adjusted driving code of the target material. Open the original driving code file of the target material with a professional code editing tool, and search for the corresponding parameter definition line in the code according to the "parameter identifier" in the parameter adjustment instruction set, for example, find the line "V_Drive=3.3V". Modify the parameter value according to the "adjustment type" and "target value" in the instruction, change "V_Drive=3.3V" to "V_Drive=3.5V", and similarly modify "F_Signal" and "R_Match" parameters. After completing the modification of each parameter, mark the modification time and the instruction number according to which the modification is made in the code comment bar, for example, " / / 2024-10-01 modification, according to instruction 1: V_Drive is up to 3.5V". After all parameter adjustments are completed, save the modified driving code file, which is the preliminary adjusted driving code of the target material.

[0151] Reconstruct the logical structure of the preliminary adjusted driving code, and verify the functional integrity of the reconstructed driving code to obtain the debugged driving code of the target material. Analyze the logical structure of the preliminary adjusted driving code, sort out the parameter calling sequence, conditional judgment statement, and loop execution process, integrate the parameter calling statements related to the driving voltage and signal frequency into the same code module, optimize the logical branches in the conditional judgment, and make the code execution process more coherent. After reconstruction is completed, load the code into the simulation running environment of the debugging system, start the simulation running: first check whether the code can be compiled normally, then simulate the probe driving process, observe whether the system can output the control signal to make the virtual target material enter the lighting state, and monitor whether the simulated brightness distribution and current waveform meet the preset standard. If the compilation is passed and the function simulation is normal, it is determined that the reconstructed driving code is functionally complete, and the code is the debugged driving code of the target material; if there is a problem, return to the reconstruction step to correct the logic and reverify until the function is complete.

[0152] The beneficial effects are that accurate parameter adjustment instructions are generated by analyzing the parameter compensation scheme line by line, ensuring that the driving code parameter modification has a clear basis; accurate injection of instructions is achieved by locating the parameter position and marking the modification information, avoiding incorrect or missed parameter modification; through optimization of the logical structure and simulation running verification, the driving code logic is clear and functionally complete, and finally the debugged driving code adapted to the target material is obtained, effectively reducing the debugging rework caused by abnormal driving code, and improving the final effect and efficiency of InCell glass specification data matching debugging.

[0153] As shown in Figure 2 FIG. 1 is a functional module diagram of an InCell glass specification data matching debugging system according to an embodiment of the present application.

[0154] The InCell glass specification data matching debugging system 100 can be installed in an electronic device. According to the functions implemented, the InCell glass specification data matching debugging system 100 includes a driving code retrieval module 101, a probe driving configuration module 102, a state monitoring and signal generation module 103, a data acquisition and feature extraction module 104, a parameter compensation matching module 105, and a driving code adjustment module 106. The modules of the present application can also be referred to as units, which refer to a series of computer program segments that can be executed by an electronic device processor and can complete a fixed function, stored in the memory of the electronic device.

[0155] In this embodiment, the functions of each module / unit are as follows:

[0156] The driving code retrieval module 101 is used to determine the driving code of the target material through the unique identifier of the target material.

[0157] The probe driving configuration module 102 is configured to configure the driving code as driving basis of the probe corresponding to the target material, so as to control the target material to enter the lighting working state.

[0158] The state monitoring and signal generation module 103 is configured to monitor the brightness distribution and the current waveform of the target material in the lighting working state, and generate a state ready signal of the target material when the brightness distribution and the current waveform meet a preset state rule.

[0159] The data acquisition and feature extraction module 104 is configured to synchronously acquire a line image and an electrical signal of the target material in response to the state ready signal, extract a topological contour of the line image and a time-frequency domain feature of the electrical signal, so as to generate line morphology and line electrical data of the target material.

[0160] The parameter compensation matching module 105 is configured to match a corresponding parameter compensation scheme from a historical debugging library of the target material according to a topological structure of the line morphology and an impedance characteristic of the line electrical data.

[0161] The driving code adjustment module 106 is configured to adjust the driving code according to the parameter compensation scheme, so as to obtain a debugging driving code of the target material.

[0162] In several embodiments provided in the present application, it should be understood that the disclosed method and system can be implemented in other ways. For example, the system embodiments described above are merely illustrative, for example, the division of the modules is only a logical function division, and another division mode can be used in actual implementation.

[0163] The modules described as separate components can or can not be physically separated, and the components displayed as modules can or can not be physical units, that is, they can be located in one place or distributed on multiple network units. Part or all of the modules can be selected to achieve the purpose of the embodiment according to actual needs.

[0164] In addition, each functional module in each embodiment of the present application can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of hardware plus software functional modules.

[0165] It is obvious for those skilled in the art that the present application is not limited to the details of the above exemplary embodiments, and the present application can be implemented in other specific forms without departing from the spirit or essential characteristics of the present application.

[0166] The embodiments of the present application can acquire and process related data based on artificial intelligence technology. Artificial intelligence is a theory, method, technology and application system for simulating, extending and expanding human intelligence by using a digital computer or a machine controlled by a digital computer, perceiving an environment, acquiring knowledge and using the knowledge to obtain optimal results.

[0167] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application and are not limiting. Although the present application has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solutions of the present application can be modified or replaced equivalently without departing from the spirit and scope of the technical solutions of the present application.

Claims

1. An InCell glass specification data matching debugging method, characterized by, The method comprises: S1, determining the driving code of the target material through the unique identifier of the target material; S2, configuring the driving code as the driving basis of the probe corresponding to the target material to control the target material to enter the lighting working state; S3, monitoring the brightness distribution and current waveform of the target material in the lighting working state, and generating a state readiness signal of the target material when the brightness distribution and the current waveform meet the preset state rule, comprising: dividing the display area of the target material into a brightness sampling area, and specifying a test access point at a key circuit node of the probe to obtain a current monitoring node of the probe; performing feature tensor structuring on the pixel distribution of the light points in the brightness sampling area to obtain a brightness distribution matrix of the brightness sampling area; reconstructing the high-frequency signal of the current monitoring node to obtain a current waveform sequence of the high-frequency signal; identifying an abnormal brightness area in the display area according to the brightness distribution matrix; locating an abnormal waveform section in the current waveform sequence based on an abnormality judgment criterion in the preset state rule; statistically analyzing the spatial distribution density of the abnormal brightness area and the time distribution frequency of the abnormal waveform section to obtain the distribution parameters of the target material; generating a state readiness signal of the target material when the distribution parameters meet the stability condition in the state rule; S4, in response to the state readiness signal, synchronously collecting the line image and electrical signal of the target material, extracting the topological contour of the line image and the time-frequency domain features of the electrical signal to generate the line morphology and line electrical data of the target material, comprising: encoding the state readiness signal as a synchronous control instruction of the target material; implementing image data acquisition and electrical signal acquisition under the guidance of the synchronous control instruction to obtain a line image set and an electrical signal set of the target material; geometrically reconstructing the edge features in the line image set to obtain topological contour data of the edge features; deconstructing the time-frequency components in the electrical signal set to obtain time-frequency feature descriptions of the time-frequency components; fusing the topological contour data to obtain the line morphology of the target material; coupling analyzing the time-frequency feature descriptions and the topological contour data to obtain the line electrical data of the target material; S5, according to the topological structure of the line morphology and the impedance characteristics of the line electrical data, matching a corresponding parameter compensation scheme from a historical debugging library of the target material; S6, adjusting the driving code according to the parameter compensation scheme to obtain the debugging driving code of the target material.

2. The InCell glass specification data matching debugging method of claim 1, wherein, The configuration of the driving code as the driving basis of the probe corresponding to the target material to control the target material to enter the lighting working state comprises: extracting the driving parameters and timing control instructions in the driving code to obtain structured driving configuration data of the driving code; verifying the compatibility of the structured driving configuration data and the probe corresponding to the target material to obtain the verified driving parameters of the structured driving configuration data; binding the verified driving parameter with a logical driving context of the probe to obtain a driving configuration mapping relationship of the target material; triggering an initialization sequence according to the driving configuration mapping relationship to activate the driving capability of the probe and control the target material to enter a lighting working state.

3. The InCell glass specification data matching debugging method of claim 2, wherein, The binding of the verified driving parameter with the logical driving context of the probe to obtain the driving configuration mapping relationship of the target material comprises: constructing a logical driving context template of the probe according to the communication protocol type and the timing parameter in the communication interface feature of the probe; hierarchically organizing the verified driving parameter to obtain a hierarchical parameter configuration table of the verified driving parameter; allocating a parameter storage area in the logical driving context template, inputting the parameters in the hierarchical parameter configuration table into the parameter storage area to obtain a parameterized template instance of the logical driving context template; analyzing the logical dependency between the parameters according to the association relationship between the parameter identifiers in the parameterized template instance, and taking the logical dependency as the driving configuration mapping relationship of the target material.

4. The InCell glass specification data matching debugging method of claim 1, wherein, The formula for calculating the spatial distribution density is as follows: ; In the formula, The spatial distribution density, This refers to the number of regions with abnormal brightness. For the first The area of ​​each abnormal brightness region For the first The average brightness value of each abnormal brightness area The preset brightness threshold, The total area of ​​the display area. To take the absolute value.

5. The InCell glass specification data matching debugging method of claim 1, wherein, The fusion of the topological contour data to obtain the line form of the target material comprises: associating discrete contour segments in the topological contour data to obtain a contour segment association relationship of the topological contour data; topologically synthesizing the topological contour data with the contour segment association relationship as a connection path to obtain a line topological structure diagram of the target material; outputting the connected path in the line topological structure diagram as the line form of the target material.

6. The InCell glass specification data matching debugging method of claim 1, wherein, The matching of the corresponding parameter compensation scheme from the historical debugging library of the target material according to the topological structure of the line form and the impedance characteristic of the line electrical data comprises: screening key geometric elements in the topological structure of the line form to obtain a structure feature of the line form; extracting a change mode in the impedance characteristic of the line electrical data to obtain an impedance feature of the line electrical data; tensor synthesizing the structure feature and the impedance feature to obtain a joint feature quantity of the target material; inputting the joint feature quantity into the historical debugging library of the target material to select a parameter compensation scheme suitable for the current scene in the historical debugging library.

7. The InCell glass specification data matching debugging method of claim 1, wherein, The adjustment of the driving code according to the parameter compensation scheme to obtain the debugging driving code of the target material comprises: parsing the configuration parameter in the parameter compensation scheme to obtain a parameter adjustment instruction of the driving code; injecting the parameter adjustment instruction into the driving code to obtain a preliminary adjusted driving code of the target material; reconstructing the logical structure of the preliminary adjusted driving code and verifying the functional integrity of the reconstructed driving code to obtain the debugging driving code of the target material.

8. An InCell glass specification data matching debugging system for implementing the InCell glass specification data matching debugging method of claim 1, the system comprising: a driving code retrieval module configured to determine the driving code of the target material through a unique identifier of the target material; The probe driving configuration module is configured to configure the driving code as driving basis of the probe corresponding to the target material to control the target material to enter a lighting working state. The state monitoring and signal generation module is configured to monitor brightness distribution and current waveform of the target material in the lighting working state, and generate a state ready signal of the target material when the brightness distribution and the current waveform meet a preset state rule, including: dividing a display area of the target material into a brightness sampling area, and specifying a test access point at a key circuit node of the probe to obtain a current monitoring node of the probe; performing feature tensor structuring on pixel distribution of an illumination point in the brightness sampling area to obtain a brightness distribution matrix of the brightness sampling area; reconstructing a high-frequency signal of the current monitoring node to obtain a current waveform sequence of the high-frequency signal; identifying an abnormal brightness area in the display area according to the brightness distribution matrix; locating an abnormal waveform section in the current waveform sequence based on an abnormality judgment criterion in the preset state rule; statistically analyzing spatial distribution density of the abnormal brightness area and time distribution frequency of the abnormal waveform section to obtain distribution parameters of the target material; generating the state ready signal of the target material when the distribution parameters meet a stability condition in the state rule; The data acquisition and feature extraction module is configured to, in response to the state ready signal, synchronously acquire a line image and an electrical signal of the target material, extract a topological contour of the line image and a time-frequency domain feature of the electrical signal, and generate line morphology and line electrical data of the target material, including: encoding the state ready signal as a synchronous control instruction of the target material; implementing image data acquisition and electrical signal acquisition under guidance of the synchronous control instruction to obtain a line image set and an electrical signal set of the target material; performing geometric reconstruction on edge features in the line image set to obtain topological contour data of the edge features; deconstructing time-frequency components in the electrical signal set to obtain time-frequency feature descriptions of the time-frequency components; fusing the topological contour data to obtain line morphology of the target material; performing coupling analysis on the time-frequency feature descriptions and the topological contour data to obtain line electrical data of the target material; The parameter compensation matching module is configured to match a corresponding parameter compensation scheme from a historical debugging library of the target material according to a topological structure of the line morphology and an impedance characteristic of the line electrical data. The driving code adjustment module is configured to adjust the driving code according to the parameter compensation scheme to obtain a post-debugging driving code of the target material.

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