A method and device for testing the function of a capacitive screen

Abstract

The present invention belongs to the technical field of capacitive screens, and provides a method and device for functional testing of a capacitive screen, the method comprising: building a simulation test scene for testing the capacitive screen, the simulation test scene is used to simulate a user using a finger to perform a touch operation on the capacitive screen; obtaining FOG functional test project data of the capacitive screen, and importing the FOG functional test project data into a test control platform; according to the test control platform, based on the FOG functional test project data, implementing the FOG functional test of the capacitive screen in the simulation test scene. The present invention performs functional testing on the capacitive screen FOG, and performs a comprehensive and accurate test on the FOG function of the capacitive screen by simulating the touch operation of a finger on the surface of the capacitive screen in a real use scenario, thereby improving the efficiency and quality of the test, and ensuring its sensitivity and stability in actual use.

Description

Technical Field

[0001] The present invention relates to the technical field of capacitive screens, and in particular to a method and device for testing the function of a capacitive screen. Background Art

[0002] FOG in the capacitive touch screen production process refers to the glass structure bound to the flexible circuit board. There are multiple circuits in the FOG of the capacitive touch screen. The function of the capacitive screen is directly related to the quality of the circuits. The glass structure of the flexible circuit board is bound to the capacitive touch screen, and the position between the flexible circuit board and the functional chip is fixed by glue, and then a functional test is performed to ensure that the circuit on the functional chip is normal and avoid circuit breaks on the capacitive screen.

[0003] During the FOG binding process of the capacitive touch screen, the binding may not be firm enough or the line connection may not be tight enough. Functional testing is required after the binding is completed. In traditional functional testing, the testing methods mostly use manual multimeter testing and probe testing technology. These technologies are difficult to comprehensively and systematically test the functions of the capacitive touch screen, and will also cause certain damage to the gold fingers at the interface of the flexible circuit board, causing certain adverse effects on subsequent processes, and the inspection efficiency is not high enough.

[0004] Therefore, it is necessary to provide a method and device for testing the function of a capacitive screen. Summary of the invention

[0005] The present invention provides a functional testing method and device for a capacitive screen, which performs a functional test on a capacitive screen FOG. By simulating the touch operation of a finger on the surface of the capacitive screen in a real usage scenario, the FOG function of the capacitive screen is comprehensively and accurately tested, thereby improving the efficiency and quality of the test and ensuring its sensitivity and stability in actual use.

[0006] The present invention provides a method for testing the function of a capacitive touch screen, comprising:

[0007] Build a simulation test scene for testing the capacitive screen. The simulation test scene is used to simulate the user's touch operation on the capacitive screen with his finger;

[0008] Obtain the FOG function test project data of the capacitive screen, and import the FOG function test project data into the test control platform;

[0009] According to the test control platform, based on the FOG functional test project data, the FOG functional test of the capacitive screen is implemented in the simulated test scenario.

[0010] Furthermore, a simulation test scenario for testing the capacitive screen is built, including:

[0011] A workbench and a test mechanism are constructed, and a simulated finger is configured, and a connection is established between the workbench, the test structure and the simulated finger; wherein the workbench is electrically connected to the test mechanism, and the workbench is network-connected to the simulated finger; the workbench is used to place the capacitive screen to be tested, and the simulated finger is configured to perform a touch operation on the capacitive screen to be tested, and the test mechanism includes a pressure sensor and a charge sensor, which are used to obtain functional test data generated by the touch operation.

[0012] Furthermore, the FOG function test project data of the capacitive screen is obtained, including:

[0013] According to the FOG function test specification standard and FOG function test requirements of the capacitive screen, the FOG function test project data of the capacitive screen is obtained.

[0014] Further, the FOG function test project data of the capacitive screen is obtained, and the FOG function test project data is imported into the test control platform, including:

[0015] According to the FOG function test standard of the capacitive screen, the FOG function test standard is parsed, and the FOG function test standard is divided into multiple data units according to the data type;

[0016] Mark the data unit according to the functional test project template to generate FOG functional test project data;

[0017] Using the data import program, the FOG functional test project data is imported into the data table in the pre-set test control platform.

[0018] Further, according to the test control platform, based on the FOG function test project data, the FOG function test of the capacitive screen is implemented in the simulated test scenario, including:

[0019] Generate the corresponding FOG function test project program according to the FOG function test project data;

[0020] Generate corresponding FOG functional test commands according to the requirements of FOG functional test projects;

[0021] Based on the FOG functional test command, the corresponding FOG functional test project program is called to control the workbench, test mechanism and simulated finger in the simulated test scene to perform the FOG functional test and obtain the functional test data;

[0022] Use the set functional test report template to generate a functional test report based on the functional test data.

[0023] Further, based on the FOG functional test command, the corresponding FOG functional test project program is called to control the workbench, test mechanism and simulated finger in the simulated test scene to perform the FOG functional test and obtain functional test data, including:

[0024] Generate functional test process according to FOG functional test project procedure;

[0025] According to the stage data and node data in the functional test process, a decision tree model is used to generate multiple automated test sub-models; the automated test model includes a control sub-model, a data processing sub-model and a coordination sub-model;

[0026] According to multiple automated test sub-models, the workbench, test mechanism and simulated finger in the simulated test scenario are controlled to perform FOG functional test and obtain functional test data.

[0027] Furthermore, according to the FOG functional test project procedure, a functional test process is generated, including:

[0028] According to the FOG functional test project procedure, determine the test configuration file corresponding to the project to be tested;

[0029] Generate an automated test script using a script generation file according to the test duration, the motion path of the simulated finger, the touch screen pressure of the simulated finger, and the touch screen position of the simulated finger in the test configuration file;

[0030] An automated test script is used to send several groups of test control signals to the capacitive screen, and a functional test process is generated based on the sending sequence of the several groups of test control signals.

[0031] Furthermore, according to the multiple automated test sub-models, the workbench, the test mechanism and the simulated finger in the simulated test scene are controlled to perform the FOG functional test and obtain the functional test data, including:

[0032] According to the control sub-model, the simulated finger is controlled to perform touch screen operation according to the set touch test program;

[0033] According to the data processing sub-model, the test organization is controlled to obtain and process the electrical data of the FOG function test of the capacitive screen and the touch screen pressure data of the simulated finger;

[0034] Coordinate the coordination between the simulated finger action and the response action of the test mechanism according to the coordination sub-model;

[0035] The electrical data and the touch screen pressure data are used to construct a matching relationship data pair according to the correspondence between the set finger action and the capacitive screen response;

[0036] Several matching relationship data pairs are combined to form functional detection data.

[0037] Furthermore, it also includes analyzing the functional test results, specifically:

[0038] Based on the normal correspondence between finger movements and capacitive screen responses, a standard matching relationship data pair of normal electrical data and touch screen pressure data is set;

[0039] Using the supervised contrast learning model in deep learning, training and learning are performed based on the pre-acquired historical functional test data and standard matching relationship data pairs to generate a functional test data contrast model;

[0040] Using the function detection data comparison model, the matching relationship data pairs in the function detection data are compared with the standard matching relationship data pairs to obtain the comprehensive comparison loss and the classification comparison loss;

[0041] Based on the comprehensive contrast loss and the classification contrast loss, the comprehensive data similarity and the classification data similarity between the matching relationship data pair and the standard matching relationship data pair are obtained;

[0042] Based on the set comprehensive data similarity threshold, determining a first difference between the comprehensive data similarity and the comprehensive data similarity threshold;

[0043] Based on the set classification data similarity threshold, determining a second difference between the classification data similarity and the classification data similarity threshold;

[0044] According to the magnitude of the first difference and the second difference, it is determined whether the single electrical property data corresponding to the FOG functional test item in the matching data pair is normal, and it is determined whether all electrical property data corresponding to the FOG functional test item in the matching data pair is normal.

[0045] A functional testing device for a capacitive screen, comprising:

[0046] A test scenario building module is used to build a simulated test scenario for testing a capacitive screen. The simulated test scenario is used to simulate a user performing a touch operation on the capacitive screen with a finger.

[0047] A test item acquisition module is used to acquire the FOG function test item data of the capacitive screen and import the FOG function test item data into the test control platform;

[0048] The test implementation module is used to implement the FOG function test of the capacitive screen in a simulated test scenario according to the test control platform and based on the FOG function test project data.

[0049] Compared with the prior art, the present invention has the following advantages and beneficial effects: the present invention performs functional testing on the capacitive screen FOG, and performs a comprehensive and accurate test on the FOG function of the capacitive screen by simulating the touch operation of a finger on the surface of the capacitive screen in a real usage scenario, thereby improving the efficiency and quality of the test and ensuring its sensitivity and stability in actual use.

[0050] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0051] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0053] Figure 1 A schematic diagram of the steps of a functional test method for a capacitive screen;

[0054] Figure 2 A schematic diagram of the method steps for importing FOG functional test project data into the test control platform;

[0055] Figure 3 The figure is a schematic diagram of the structure of a functional testing device for a capacitive screen. DETAILED DESCRIPTION

[0056] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0057] The present invention provides a method for testing the function of a capacitive touch screen. Figure 1 As shown, it includes: building a simulation test scene for testing the capacitive screen, the simulation test scene is used to simulate the user using a finger to perform a touch operation on the capacitive screen;

[0058] Obtain the FOG function test project data of the capacitive screen, and import the FOG function test project data into the test control platform;

[0059] According to the test control platform, based on the FOG functional test project data, the FOG functional test of the capacitive screen is implemented in the simulated test scenario.

[0060] The working principle of the above technical solution is: in order to realize the test of the capacitive screen, the present invention first builds a simulation test scene for testing the capacitive screen, and the simulation test scene is used to simulate the user using a finger to perform a touch operation on the capacitive screen; then obtains the FOG function test project data of the capacitive screen, and imports the FOG function test project data into the test control platform; finally, according to the test control platform, based on the FOG function test project data, implements the FOG function test of the capacitive screen in the simulation test scene.

[0061] The beneficial effect of the above technical solution is: by adopting the solution provided in this embodiment, the present invention performs functional testing on the capacitive screen FOG, and performs a comprehensive and accurate test on the FOG function of the capacitive screen by simulating the touch operation of a finger on the surface of the capacitive screen in a real usage scenario, thereby improving the efficiency and quality of the test and ensuring its sensitivity and stability in actual use.

[0062] In one embodiment, a simulation test scenario for testing a capacitive screen is constructed, including:

[0063] A workbench and a test mechanism are constructed, and a simulated finger is configured, and a connection is established between the workbench, the test structure and the simulated finger; wherein the workbench is electrically connected to the test mechanism, and the workbench is network-connected to the simulated finger; the workbench is used to place the capacitive screen to be tested, and the simulated finger is configured to perform a touch operation on the capacitive screen to be tested, and the test mechanism includes a pressure sensor and a charge sensor, which are used to obtain functional test data generated by the touch operation.

[0064] The working principle of the above technical solution is: in order to build a simulated test scenario for testing a capacitive screen, the present invention first builds a workbench and a test mechanism, and configures a simulated finger, and then establishes a connection between the workbench, the test structure and the simulated finger; wherein the workbench is electrically connected to the test mechanism, and the workbench is network-connected to the simulated finger; the workbench is used to place the capacitive screen to be tested, the simulated finger is configured to perform a touch operation on the capacitive screen to be tested, and the test mechanism includes a pressure sensor and a charge sensor, which are used to obtain functional test data generated by the touch operation.

[0065] The beneficial effect of the above technical solution is: by adopting the solution provided in this embodiment, by building a simulated test scene for testing the capacitive screen, the necessary conditions and basis are provided for the subsequent FOG function test of the capacitive screen.

[0066] In one embodiment, obtaining FOG function test item data of a capacitive screen includes:

[0067] According to the FOG function test specification standard and FOG function test requirements of the capacitive screen, the FOG function test project data of the capacitive screen is obtained.

[0068] The working principle of the above technical solution is: according to the FOG function test specification standard and FOG function test requirements of the capacitive screen, the FOG function test project data of the capacitive screen is obtained.

[0069] The beneficial effect of the above technical solution is: by adopting the solution provided in this embodiment, the FOG function test project data of the capacitive screen is obtained according to the FOG function test specification standard and FOG function test requirements, so as to ensure the standardization of the acquisition of the FOG function test project data.

[0070] In one embodiment, the FOG function test project data of the capacitive screen is obtained, and the FOG function test project data is imported into the test control platform, such as Figure 2 As shown, including:

[0071] According to the FOG function test standard of the capacitive screen, the FOG function test standard is parsed, and the FOG function test standard is divided into multiple data units according to the data type;

[0072] Mark the data unit according to the functional test project template to generate FOG functional test project data;

[0073] Using the data import program, the FOG functional test project data is imported into the data table in the pre-set test control platform.

[0074] The working principle of the above technical solution is as follows: in processing the FOG function test item data of the capacitive screen, the present invention first parses the FOG function test standard according to the FOG function test standard of the capacitive screen, and divides the FOG function test standard into multiple data units according to the data type; then the data unit is marked according to the function test item template to generate FOG function test item data; finally, the FOG function test item data is imported into the data table in the pre-set test control platform by using the data import program.

[0075] The beneficial effect of the above technical solution is: by adopting the solution provided in this embodiment, by processing and storing the FOG function test item data of the capacitive screen, a basis can be provided for the subsequent test implementation.

[0076] In one embodiment, according to the test control platform, based on the FOG function test project data, the FOG function test of the capacitive screen is implemented in the simulated test scenario, including:

[0077] Generate the corresponding FOG function test project program according to the FOG function test project data;

[0078] Generate corresponding FOG functional test commands according to the requirements of FOG functional test projects;

[0079] Based on the FOG functional test command, the corresponding FOG functional test project program is called to control the workbench, test mechanism and simulated finger in the simulated test scene to perform the FOG functional test and obtain the functional test data;

[0080] Use the set functional test report template to generate a functional test report based on the functional test data.

[0081] The working principle of the above technical solution is: in order to implement the FOG functional test of the capacitive screen in the simulated test scenario, the present invention first generates a corresponding FOG functional test project program according to the FOG functional test project data; then generates a corresponding FOG functional test command according to the FOG functional test project requirements; finally, based on the FOG functional test command, the corresponding FOG functional test project program is called to control the workbench, test mechanism and simulated finger in the simulated test scenario to perform the FOG functional test and obtain functional test data; and uses the set functional test report template to generate a functional test report according to the functional test data.

[0082] The beneficial effect of the above technical solution is: by adopting the solution provided in this embodiment, by calling the corresponding FOG functional test project program based on the FOG functional test command, the workbench, test mechanism and simulated finger in the simulated test scene are controlled to perform the FOG functional test, and the functional test data is obtained, thereby ensuring the accuracy of the acquisition of the functional test data.

[0083] In one embodiment, based on the FOG functional test command, the corresponding FOG functional test project program is called to control the workbench, the test mechanism and the simulated finger in the simulated test scene to perform the FOG functional test and obtain the functional test data, including:

[0084] Generate functional test process according to FOG functional test project procedure;

[0085] According to the stage data and node data in the functional test process, a decision tree model is used to generate multiple automated test sub-models; the automated test model includes a control sub-model, a data processing sub-model and a coordination sub-model;

[0086] According to multiple automated test sub-models, the workbench, test mechanism and simulated finger in the simulated test scenario are controlled to perform FOG functional test and obtain functional test data.

[0087] The working principle of the above technical scheme is as follows: in order to obtain functional test data, the present invention first generates a functional test process according to the FOG functional test project program; then, according to the stage data and node data in the functional test process, a decision tree model is used to generate multiple automated test sub-models; the automated test model includes a control sub-model, a data processing sub-model and a coordination sub-model; finally, according to the multiple automated test sub-models, the workbench, test mechanism and simulated finger in the simulated test scene are controlled to perform the FOG functional test to obtain functional test data.

[0088] The beneficial effect of the above technical solution is: by adopting the solution provided in this embodiment, by generating a functional test process according to the FOG functional test project program, and then generating multiple automated test sub-models, the workbench, test mechanism and simulated fingers in the simulated test scene are controlled to perform FOG functional testing, thereby ensuring that comprehensive functional test data is obtained.

[0089] In one embodiment, according to the FOG functional test project procedure, a functional test process is generated, including:

[0090] According to the FOG functional test project procedure, determine the test configuration file corresponding to the project to be tested;

[0091] Generate an automated test script using a script generation file according to the test duration, the motion path of the simulated finger, the touch screen pressure of the simulated finger, and the touch screen position of the simulated finger in the test configuration file;

[0092] An automated test script is used to send several groups of test control signals to the capacitive screen, and a functional test process is generated based on the sending sequence of the several groups of test control signals.

[0093] The working principle of the above technical scheme is: in order to obtain the FOG functional test project program and generate a functional test process, the present invention first determines the test configuration file corresponding to the item to be tested according to the FOG functional test project program; then generates an automated test script using a script generation file according to the test duration, the motion path of the simulated finger, the touch screen pressure of the simulated finger, and the touch screen position point of the simulated finger in the test configuration file; finally, uses the automated test script to send several groups of test control signals to the capacitive screen, and generates a functional test process based on the sending order of the several groups of test control signals.

[0094] The beneficial effect of the above technical solution is: by adopting the solution provided in this embodiment, by generating a configuration file, generating a test script according to the configuration file, and using an automated test script to send several groups of test control signals to the capacitive screen, the scientific nature of the functional test process generation can be guaranteed.

[0095] In one embodiment, according to a plurality of automated test sub-models, a workbench, a test mechanism, and a simulated finger in a simulated test scenario are controlled to perform a FOG functional test and obtain functional test data, including:

[0096] According to the control sub-model, the simulated finger is controlled to perform touch screen operation according to the set touch test program;

[0097] According to the data processing sub-model, the test organization is controlled to obtain and process the electrical data of the FOG function test of the capacitive screen and the touch screen pressure data of the simulated finger;

[0098] Coordinate the coordination between the simulated finger action and the response action of the test mechanism according to the coordination sub-model;

[0099] The electrical data and the touch screen pressure data are used to construct a matching relationship data pair according to the correspondence between the set finger action and the capacitive screen response;

[0100] Several matching relationship data pairs are combined to form functional detection data.

[0101] The working principle of the above technical scheme is: in order to achieve efficient acquisition of functional detection data, the present invention controls the simulated finger to perform touch screen operation according to the set touch test program according to the control sub-model; according to the data processing sub-model, controls the test mechanism to obtain and process the electrical data of the FOG functional test of the capacitive screen and the touch screen pressure data of the simulated finger; according to the coordination sub-model, coordinates the coordination between the simulated finger movement and the response action of the test mechanism; then, the electrical data and the touch screen pressure data are constructed into matching relationship data pairs according to the corresponding relationship between the set finger movement and the capacitive screen response; finally, a number of matching relationship data pairs are combined into functional detection data.

[0102] The beneficial effect of the above technical solution is: by adopting the solution provided in this embodiment, by utilizing several sub-models, controlling the operation of the simulated finger and the test mechanism, and coordinating the cooperation between the simulated finger movement and the response movement of the test mechanism, accurate functional detection data can be obtained.

[0103] In one embodiment, the functional test results are analyzed, specifically:

[0104] Based on the normal correspondence between finger movements and capacitive screen responses, a standard matching relationship data pair of normal electrical data and touch screen pressure data is set;

[0105] Using the supervised contrast learning model in deep learning, training and learning are performed based on the pre-acquired historical functional test data and standard matching relationship data pairs to generate a functional test data contrast model;

[0106] Using the function detection data comparison model, the matching relationship data pairs in the function detection data are compared with the standard matching relationship data pairs to obtain the comprehensive comparison loss and the classification comparison loss;

[0107] Based on the comprehensive contrast loss and the classification contrast loss, the comprehensive data similarity and the classification data similarity between the matching relationship data pair and the standard matching relationship data pair are obtained;

[0108] Based on the set comprehensive data similarity threshold, determining a first difference between the comprehensive data similarity and the comprehensive data similarity threshold;

[0109] Based on the set classification data similarity threshold, determining a second difference between the classification data similarity and the classification data similarity threshold;

[0110] According to the magnitude of the first difference and the second difference, it is determined whether the single electrical property data corresponding to the FOG functional test item in the matching data pair is normal, and it is determined whether all electrical property data corresponding to the FOG functional test item in the matching data pair is normal.

[0111] The working principle of the above technical solution is as follows: in order to analyze the function test results so as to distinguish whether the tested function is normal or not, the present invention first sets the standard matching relationship data pairs of normal electrical data and touch screen pressure data based on the normal corresponding relationship between finger movements and capacitive screen responses; then uses the supervised contrast learning model in deep learning to perform training and learning based on the pre-acquired historical function test data and standard matching relationship data pairs to generate a function detection data comparison model; uses the function detection data comparison model to compare the matching relationship data pairs in the function detection data with the standard matching relationship data pairs to obtain comprehensive comparison loss and classification comparison loss; and then uses the supervised contrast learning model in deep learning to perform training and learning based on the pre-acquired historical function test data and standard matching relationship data pairs to generate a function detection data comparison model. Based on the comprehensive comparison loss and the classification comparison loss, the comprehensive data similarity and the classification data similarity between the matching relationship data pair and the standard matching relationship data pair are obtained; based on the set comprehensive data similarity threshold, a first difference between the comprehensive data similarity and the comprehensive data similarity threshold is judged; based on the set classification data similarity threshold, a second difference between the classification data similarity and the classification data similarity threshold is judged; finally, according to the size of the first difference and the second difference, whether the single electrical data corresponding to the FOG functional test items in the matching relationship data pair is normal, and whether all the electrical data corresponding to the FOG functional test items in the matching relationship data pair are normal.

[0112] The beneficial effect of the above technical solution is: by adopting the solution provided in this embodiment, by utilizing the supervised contrast learning model, the matching relationship data pairs in the functional detection data are compared with the standard matching relationship data pairs, and the comprehensive contrast loss and the classification contrast loss are obtained. By analyzing the comprehensive contrast loss and the classification contrast loss, it is possible to improve the judgment basis for whether all electrical data corresponding to the FOG functional test items are normal, or whether the single electrical data corresponding to the FOG functional test items is normal.

[0113] A functional test device for a capacitive screen, such as Figure 3 As shown, including:

[0114] A test scenario building module is used to build a simulated test scenario for testing a capacitive screen. The simulated test scenario is used to simulate a user performing a touch operation on the capacitive screen with a finger.

[0115] A test item acquisition module is used to acquire the FOG function test item data of the capacitive screen and import the FOG function test item data into the test control platform;

[0116] The test implementation module is used to implement the FOG function test of the capacitive screen in a simulated test scenario according to the test control platform and based on the FOG function test project data.

[0117] The working principle of the above technical solution is: in order to realize the functional testing device of the capacitive screen, the present invention sets a test scene construction module for building a simulation test scene for testing the capacitive screen, and the simulation test scene is used to simulate the user's touch operation on the capacitive screen with his fingers; a test item acquisition module is set to obtain the FOG functional test item data of the capacitive screen, and import the FOG functional test item data into the test control platform; a test implementation module is set to implement the FOG functional test of the capacitive screen in the simulation test scene based on the test control platform and the FOG functional test item data.

[0118] The beneficial effect of the above technical solution is: by adopting the solution provided in this embodiment, a functional test is performed on the capacitive screen FOG, and the FOG function of the capacitive screen is comprehensively and accurately tested by simulating the touch operation of a finger on the surface of the capacitive screen in a real usage scenario, thereby improving the efficiency and quality of the test and ensuring its sensitivity and stability in actual use.

[0119] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A functional testing method for a capacitive screen, characterized in that: include: Build a simulation test scene for testing the capacitive screen. The simulation test scene is used to simulate the user's touch operation on the capacitive screen with his finger; Obtain the FOG function test project data of the capacitive screen, and import the FOG function test project data into the test control platform; According to the test control platform, based on the FOG function test project data, the FOG function test of the capacitive screen is implemented in the simulated test scenario; According to the test control platform, based on the FOG function test project data, the FOG function test of the capacitive screen is implemented in the simulated test scenario, including: Generate the corresponding FOG function test project program according to the FOG function test project data; Generate corresponding FOG functional test commands according to the requirements of FOG functional test projects; Based on the FOG functional test command, the corresponding FOG functional test project program is called to control the workbench, test mechanism and simulated finger in the simulated test scene to perform the FOG functional test and obtain the functional test data; Generate a functional test report based on the functional test data using the set functional test report template; Based on the FOG functional test command, call the corresponding FOG functional test project program, control the workbench, test mechanism and simulated finger in the simulated test scene to perform the FOG functional test, and obtain functional test data, including: Generate functional test process according to FOG functional test project procedure; According to the stage data and node data in the functional test process, a decision tree model is used to generate multiple automated test sub-models; the automated test model includes a control sub-model, a data processing sub-model and a coordination sub-model; According to multiple automated test sub-models, control the workbench, test mechanism and simulated finger in the simulated test scene to perform FOG functional test and obtain functional test data; According to multiple automated test sub-models, the workbench, test mechanism and simulated finger in the simulated test scenario are controlled to perform FOG functional tests and obtain functional test data, including: According to the control sub-model, the simulated finger is controlled to perform touch screen operation according to the set touch test program; According to the data processing sub-model, the test organization is controlled to obtain and process the electrical data of the FOG function test of the capacitive screen and the touch screen pressure data of the simulated finger; Coordinate the coordination between the simulated finger action and the response action of the test mechanism according to the coordination sub-model; The electrical data and the touch screen pressure data are used to construct a matching relationship data pair according to the correspondence between the set finger action and the capacitive screen response; Combining several matching relationship data pairs into functional detection data; It also includes analysis of functional test results, specifically: Based on the normal correspondence between finger movements and capacitive screen responses, a standard matching relationship data pair of normal electrical data and touch screen pressure data is set; Using the supervised contrast learning model in deep learning, training and learning are performed based on the pre-acquired historical functional test data and standard matching relationship data pairs to generate a functional test data contrast model; Using the function detection data comparison model, the matching relationship data pairs in the function detection data are compared with the standard matching relationship data pairs to obtain the comprehensive comparison loss and the classification comparison loss; Based on the comprehensive contrast loss and the classification contrast loss, the comprehensive data similarity and the classification data similarity between the matching relationship data pair and the standard matching relationship data pair are obtained; Based on the set comprehensive data similarity threshold, determining a first difference between the comprehensive data similarity and the comprehensive data similarity threshold; Based on the set classification data similarity threshold, determining a second difference between the classification data similarity and the classification data similarity threshold; According to the magnitude of the first difference and the second difference, it is determined whether the single electrical property data corresponding to the FOG functional test item in the matching data pair is normal, and it is determined whether all electrical property data corresponding to the FOG functional test item in the matching data pair is normal.

2. A functional testing method for a capacitive screen according to claim 1, characterized in that: Build a simulated test scenario for testing capacitive screens, including: A workbench and a test mechanism are constructed, and a simulated finger is configured, and a connection is established between the workbench, the test structure and the simulated finger; wherein the workbench is electrically connected to the test mechanism, and the workbench is network-connected to the simulated finger; the workbench is used to place the capacitive screen to be tested, and the simulated finger is configured to perform a touch operation on the capacitive screen to be tested, and the test mechanism includes a pressure sensor and a charge sensor, which are used to obtain functional test data generated by the touch operation.

3. A functional testing method for a capacitive screen according to claim 1, characterized in that: Get the FOG function test project data of the capacitive screen, including: According to the FOG function test specification standard and FOG function test requirements of the capacitive screen, the FOG function test project data of the capacitive screen is obtained.

4. The functional testing method of a capacitive screen according to claim 2, characterized in that: Obtain the FOG function test project data of the capacitive screen and import the FOG function test project data into the test control platform, including: According to the FOG function test standard of the capacitive screen, the FOG function test standard is parsed, and the FOG function test standard is divided into multiple data units according to the data type; Mark the data unit according to the functional test project template to generate FOG functional test project data; Using the data import program, the FOG functional test project data is imported into the data table in the pre-set test control platform.

5. The functional testing method of a capacitive screen according to claim 1, characterized in that: According to the FOG functional test project procedure, generate the functional test process, including: According to the FOG functional test project procedure, determine the test configuration file corresponding to the project to be tested; Generate an automated test script using a script generation file according to the test duration, the motion path of the simulated finger, the touch screen pressure of the simulated finger, and the touch screen position of the simulated finger in the test configuration file; An automated test script is used to send several groups of test control signals to the capacitive screen, and a functional test process is generated based on the sending sequence of the several groups of test control signals.

6. A functional test device for a capacitive screen, characterized in that: include: A test scenario building module is used to build a simulated test scenario for testing a capacitive screen. The simulated test scenario is used to simulate a user performing a touch operation on the capacitive screen with a finger. A test item acquisition module is used to acquire the FOG function test item data of the capacitive screen and import the FOG function test item data into the test control platform; A test implementation module is used to implement the FOG function test of the capacitive screen in a simulated test scenario according to the test control platform and based on the FOG function test project data; According to the test control platform, based on the FOG function test project data, the FOG function test of the capacitive screen is implemented in the simulated test scenario, including: Generate the corresponding FOG function test project program according to the FOG function test project data; Generate corresponding FOG functional test commands according to the requirements of FOG functional test projects; Based on the FOG functional test command, the corresponding FOG functional test project program is called to control the workbench, test mechanism and simulated finger in the simulated test scene to perform the FOG functional test and obtain the functional test data; Generate a functional test report based on the functional test data using the set functional test report template; Based on the FOG functional test command, call the corresponding FOG functional test project program, control the workbench, test mechanism and simulated finger in the simulated test scene to perform the FOG functional test, and obtain functional test data, including: Generate functional test process according to FOG functional test project procedure; According to the stage data and node data in the functional test process, a decision tree model is used to generate multiple automated test sub-models; the automated test model includes a control sub-model, a data processing sub-model and a coordination sub-model; According to multiple automated test sub-models, control the workbench, test mechanism and simulated finger in the simulated test scene to perform FOG functional test and obtain functional test data; According to multiple automated test sub-models, the workbench, test mechanism and simulated finger in the simulated test scenario are controlled to perform FOG functional tests and obtain functional test data, including: According to the control sub-model, the simulated finger is controlled to perform touch screen operation according to the set touch test program; According to the data processing sub-model, the test organization is controlled to obtain and process the electrical data of the FOG function test of the capacitive screen and the touch screen pressure data of the simulated finger; Coordinate the coordination between the simulated finger action and the response action of the test mechanism according to the coordination sub-model; The electrical data and the touch screen pressure data are used to construct a matching relationship data pair according to the correspondence between the set finger action and the capacitive screen response; Combining several matching relationship data pairs into functional detection data; It also includes analysis of functional test results, specifically: Based on the normal correspondence between finger movements and capacitive screen responses, a standard matching relationship data pair of normal electrical data and touch screen pressure data is set; Using the supervised contrast learning model in deep learning, training and learning are performed based on the pre-acquired historical functional test data and standard matching relationship data pairs to generate a functional test data contrast model; Using the function detection data comparison model, the matching relationship data pairs in the function detection data are compared with the standard matching relationship data pairs to obtain the comprehensive comparison loss and the classification comparison loss; Based on the comprehensive contrast loss and the classification contrast loss, the comprehensive data similarity and the classification data similarity between the matching relationship data pair and the standard matching relationship data pair are obtained; Based on the set comprehensive data similarity threshold, determining a first difference between the comprehensive data similarity and the comprehensive data similarity threshold; Based on the set classification data similarity threshold, determining a second difference between the classification data similarity and the classification data similarity threshold; According to the magnitude of the first difference and the second difference, it is determined whether the single electrical property data corresponding to the FOG functional test item in the matching data pair is normal, and it is determined whether all electrical property data corresponding to the FOG functional test item in the matching data pair is normal.

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