A test method, device and electronic device thereof

Abstract

The embodiment of the present application discloses a test method applied to automatic test equipment, the test method comprises the following steps: configuring the ID of a clamp and corresponding test items, so that the test item configuration corresponding to the ID is loaded by reading the ID of the clamp; obtaining corresponding first judgment value and second judgment value according to the corresponding test data of each test item of a reference sample; setting the first judgment value and the second judgment value as the lower limit threshold and the upper limit threshold of the corresponding test item of the automatic test equipment respectively; and making the automatic test equipment test the product to be tested according to the test item configuration to obtain corresponding test data. In the above manner, the embodiment of the present application can automatically configure the test range and automatically load the test items, thereby improving the test efficiency of the automatic test equipment. Moreover, the defective products can be automatically tested and classified, the test efficiency is improved, and the error of the manual test result is avoided.

Description

TECHNICAL FIELD

[0001] The embodiments of the present application relate to the field of automatic testing, and in particular, to a testing method, device and electronic equipment thereof. BACKGROUND

[0002] Automatic test equipment is an automated system designed to perform electrical, thermal, and physical tests without direct human intervention. Generally, automatic test equipment systems are used to speed up testing, perform repetitive tasks, or enhance the repeatability and consistency of a test system. The purpose of designing an automatic test equipment system is to accomplish all of the above tasks. If all testing were performed manually, the cost of the final component could be significantly increased by the cost of the performance, quality, functionality, and even environmental variable stress testing of the device.

[0003] However, in the case of applying different models of automatic test equipment, different input voltages, input currents, output voltages, output currents, and test items need to be configured, and the test software also needs to be modified. In this case, the test items are numerous, and manually configuring the test range is tedious and not objective. In addition, after the current test system is tested, engineers need to manually retest and classify defective products, and only after statistics are obtained will the factory be fed back for improvement, which is low in efficiency and prone to errors. SUMMARY

[0004] To solve the above technical problems, one technical solution adopted by the embodiments of the present application is to provide a testing method applied to automatic test equipment, the testing method comprising: configuring the ID of a clamp and corresponding test items, so that by reading the ID of the clamp, the test item configuration corresponding to the ID is loaded; calculating a first judgment value and a second judgment value according to the corresponding test data of each test item of a reference sample; setting the first judgment value and the second judgment value as the lower threshold value and the upper threshold value of the corresponding test item of the automatic test equipment, respectively; and causing the automatic test equipment to test a product to be tested according to the test item configuration to obtain corresponding test data.

[0005] In some embodiments, the testing method further comprises: judging defective products according to the corresponding test data, counting the number and proportion of item defective products in defective products to obtain statistical data; generating a fault analysis model through machine learning according to the statistical data; inputting the test data of defective products into the fault analysis model to judge the fault cause and severity of the defective products and give corresponding repair suggestions.

[0006] In some embodiments, the testing method further comprises: when performing product comparison testing, sequentially testing each product according to the set test items to obtain test results; and generating a product comparison report according to the test results.

[0007] In some embodiments, the method of calculating the corresponding first judgment value and the second judgment value based on the corresponding test data of each test item of the reference sample includes: entering the corresponding test data of each test item of the reference sample; calculating the first center value and the standard deviation of the corresponding test data respectively; subtracting 3 times the standard deviation from the first center value to obtain a first screening value; adding 3 times the standard deviation to the first center value to obtain a second screening value; eliminating data smaller than the first screening value and data larger than the second screening value in the test data; calculating the second center value, minimum value and maximum value of the remaining test data; and calculating the first absolute value according to the following formula:

[0008] X1=XM-(Xmin-σ),

[0009] Wherein, X1 is the first absolute value, XM is the second center value, Xmin is the minimum value, and σ is the standard deviation. The second absolute value is calculated according to the following formula:

[0010] X2=(Xmax+σ)-XM,

[0011] Wherein, X2 is the second absolute value, and Xmax is the maximum value; the maximum value between the first absolute value and the second absolute value is calculated to obtain an error value; the error value is subtracted from the second center value to obtain the first judgment value; and the error value is added to the second center value to obtain the second judgment value.

[0012] In some embodiments, setting the first judgment value and the second judgment value as the lower limit threshold and the upper limit threshold of the corresponding test item of the automatic testing equipment respectively includes: setting the first judgment value as the lower limit threshold of the corresponding test item of the automatic testing equipment, and if the corresponding test data of the product to be tested is less than the first judgment value, determining that the product to be tested is a defective product; setting the second judgment value as the upper limit threshold of the corresponding test item of the automatic testing equipment, and if the corresponding test data of the product to be tested is greater than the second judgment value, determining that the product to be tested is a defective product.

[0013] In some embodiments, the test items include input voltage, output voltage, input current, output current, input power, output power, power loss, and power efficiency.

[0014] In some embodiments, the failure causes of the defective product include no output voltage, power loss greater than a preset loss threshold, input current exceeding a preset current threshold, output voltage lower than a preset voltage threshold, and unstable output current.

[0015] To solve the above technical problems, another technical solution adopted by the embodiment of the present application is to provide a test device applied to automatic test equipment, the test device comprising: a loading module configured to configure the ID of a clamp and corresponding test items, so that by reading the ID of the clamp, the test item corresponding to the ID is loaded; a calculation module configured to calculate a first judgment value and a second judgment value according to the corresponding test data of each test item of a reference sample; a setting module configured to set the first judgment value and the second judgment value as the lower limit threshold and the upper limit threshold of the corresponding test item of the automatic test equipment respectively; a first test module configured to make the automatic test equipment test a product to be tested according to the test item configuration to obtain corresponding test data; a statistical module configured to judge defective products according to the corresponding test data, count the number and proportion of item defective products in defective products, and obtain statistical data; a model generation module configured to generate a fault analysis model through machine learning according to the statistical data; a judgment module configured to input the test data of defective products into the fault analysis model to judge the fault cause and severity of the defective products and give corresponding maintenance suggestions; a second test module configured to test each product according to the set test items in turn to obtain test results when performing product comparison test; and a report generation module configured to generate a product comparison report according to the test results.

[0016] To solve the above technical problems, another technical solution adopted by the embodiment of the present application is to provide an electronic device, comprising: at least one processor; and a memory in communication connection with the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the test method as described above.

[0017] To solve the above technical problems, another technical solution adopted by the embodiment of the present application is to provide a non-volatile computer storage medium, the computer storage medium storing computer executable instructions, the computer executable instructions being executed by one or more processors, so that the one or more processors perform the test method as described above.

[0018] The embodiment of the present application has the beneficial effect that, unlike the prior art, the embodiment of the present application can automatically configure the test range and automatically load the test items, thereby improving the test efficiency of the automatic test equipment. Moreover, the defective products can be automatically tested and classified, thereby improving the test efficiency and avoiding the error of manual test results. BRIEF DESCRIPTION OF DRAWINGS

[0019] Figure 1is a flowchart of a test method provided by an embodiment of the present application;

[0020] Figure 2 is a flowchart of a process of calculating a corresponding first judgment value and a second judgment value according to corresponding test data of each test item of a reference sample provided by an embodiment of the present application;

[0021] Figure 3 is a flowchart of a process of setting the first judgment value and the second judgment value as lower limit threshold and upper limit threshold of corresponding test items of an automatic test equipment respectively provided by an embodiment of the present application;

[0022] Figure 4 is a structural diagram of a test device provided by an embodiment of the present application;

[0023] Figure 5 is a structural diagram of an electronic device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0024] Automatic test equipment (ATE) is an automated system, which is used for electrical, thermal and physical tests without direct human intervention. Generally, automatic test equipment system is used for accelerating tests, performing repetitive tasks or enhancing repeatability and consistency of test system. The purpose of designing automatic test equipment system is to complete all the above tasks.

[0025] In the case of testing different models of modules by using automatic test equipment, different input voltage, input current, output voltage, output current and test items need to be configured, and the test software also needs to be modified. Moreover, in the case of a large number of test items, it is too tedious and not objective to manually configure the test range. To solve the above problems, an embodiment of the present application provides a test method applied to the automatic test equipment, which comprises the following steps:

[0026] Step S100: configuring the ID of the fixture and corresponding test items, so that the test item configuration corresponding to the ID is loaded by reading the ID of the fixture.

[0027] The automatic test equipment does not need direct human intervention in the use process, and generally needs to be operated through a computer system before using the automatic test equipment for testing. The operator selects test items through a tabular human-machine interface combined with the characteristics of different modules of the automatic test equipment. Customized test requirements based on a unified interface are realized.

[0028] In the embodiment, each fixture is matched with each module type of the automatic test equipment, each fixture has a respective ID, and by configuring the ID of the fixture and the corresponding test item, the automatic test equipment automatically loads the test item configuration corresponding to the ID when reading the ID of the fixture.

[0029] The automatic test equipment can read the ID of the fixture in a wireless or wired manner. Specifically, the wireless reading of the ID includes Radio Frequency Identification (RFID), Bluetooth Low Energy (BLE), Near Field Communication (NFC), etc. The ID is related to the test item setting. That is, the automatic test equipment matched with different fixtures can automatically load the related test item setting.

[0030] In the embodiment, the test items include, but are not limited to, input voltage, output voltage, input current, output current, input power, output power, power loss, power efficiency, peak-to-peak value, and root mean square value, etc.

[0031] Step S200: According to the corresponding test data of each test item of the reference sample, a first judgment value and a second judgment value are obtained.

[0032] In some embodiments, step S200 specifically includes the following steps, and a flowchart thereof is shown in Figure 2

[0033] Step S2100: The corresponding test data of each test item of the reference sample is inputted.

[0034] Specifically, the corresponding test data of each test item of the reference sample is collected in advance, and the collected corresponding test data is inputted. The corresponding test data includes input voltage, output voltage, input current, output current, input power, output power, power loss, power efficiency, peak-to-peak value, and root mean square value, etc.

[0035] Step S2200: The first central value and the standard deviation of the corresponding test data are calculated respectively.

[0036] The central value refers to the numerical value showing the central tendency of the data. Specifically, the first central value and the standard value of the test data of input voltage, output voltage, input current, output current, input power, output power, power loss, power efficiency, peak-to-peak value, and root mean square value, etc. are calculated respectively.

[0037] Step S2300: The first central value is subtracted by 3 times the standard deviation to obtain the first screening value.

[0038] ​Specifically, the first screening value is obtained by calculation through the following formula:

[0039] Xa = Xmiddle - 3σ,

[0040] wherein Xa is the first screening value, Xmiddle is the first central value, and σ is the standard deviation. σ

[0041] Step S2400: obtaining the second screening value by adding 3 times of the standard deviation to the first central value.

[0042] Specifically, the second screening value is obtained by calculation through the following formula:

[0043] Xb = Xmiddle + 3σ,

[0044] wherein Xb is the second screening value, Xmiddle is the first central value, and σ is the standard deviation.

[0045] Step S2500: eliminating the data less than the first screening value and the data greater than the second screening value in the test data.

[0046] Specifically, in the corresponding test data, the data less than the corresponding first screening value X a and the data greater than the corresponding second screening value X b are eliminated. Taking the test data of the input voltage as an example, after obtaining the first screening value and the second screening value of the input voltage, the data less than the first screening value of the input voltage and the data greater than the second screening value of the input voltage are eliminated from the test data of the input voltage.

[0047] Step S2600: calculating the second central value, the minimum value and the maximum value of the remaining test data.

[0048] After eliminating the data outside 3 times of the standard deviation in the corresponding test data, the second central value, the minimum value and the maximum value in the remaining test data are calculated. For example, after eliminating the data less than the first screening value of the input voltage and the data greater than the second screening value of the input voltage from the test data of the input voltage, the second central value, the minimum value and the maximum value in the remaining test data of the input voltage are calculated.

[0049] Step S2700: calculating the first absolute value.

[0050] Specifically, the first absolute value of the corresponding test data is obtained by calculation through the following formula:

[0051] X1 = XM - (Xmin - σ),

[0052] wherein X1 is the first absolute value, XM is the second central value, Xmin is the minimum value, and σ is the standard deviation.

[0053] ​Step S2800: calculating the second absolute value.

[0054] Specifically, the second absolute value of the corresponding test data is calculated by the following formula:

[0055] X2 = (Xmax + σ) - XM,

[0056] wherein X2 is the second absolute value, Xmax is the maximum value;

[0057] Step S2900: calculating the maximum value of the first absolute value and the second absolute value, and obtaining the error value.

[0058] Specifically, the first absolute value and the second absolute value of the corresponding test data are compared, and the larger one of the two is taken as the error value of the corresponding test data. For example, after the first absolute value and the second absolute value of the test data of the input voltage are calculated, the first absolute value of the input voltage and the second absolute value of the input voltage are compared. If the first absolute value of the input voltage is greater than the second absolute value of the input voltage, the first absolute value of the input voltage is taken as the error value of the input voltage; if the second absolute value of the input voltage is greater than the first absolute value of the input voltage, the second absolute value of the input voltage is taken as the error value of the input voltage.

[0059] Step S2110: subtracting the error value from the second center value to obtain the first judgment value.

[0060] Specifically, the second center value of the corresponding test data is subtracted by the error value of the corresponding test data to obtain the first judgment value of the corresponding test data. The first judgment value is the lower limit threshold of the corresponding test item. For example, the second center value of the test data of the input voltage is subtracted by the error value thereof to obtain the first judgment value of the test data of the input voltage.

[0061] Different test items have a corresponding first judgment value.

[0062] Step S2120: adding the error value to the second center value to obtain the second judgment value.

[0063] Specifically, the second center value of the corresponding test data is added by the error value of the corresponding test data to obtain the second judgment value of the corresponding test data. The second judgment value is the upper limit threshold of the corresponding test item. For example, the second center value of the test data of the input voltage is added by the error value thereof to obtain the second judgment value of the test data of the input voltage.

[0064] Different test items have a corresponding second judgment value.

[0065] Through step S200, before using the automatic test equipment, without manually inputting the test judgment parameters, through reading the test data of the reference sample, performing operation, and automatically setting to meet the test judgment parameters of the mass product. In this way, a large amount of time and workload is saved, and the objectivity of the test judgment parameters is improved.

[0066] Step S300: setting the first judgment value and the second judgment value as the lower limit threshold value and the upper limit threshold value of the corresponding test item of the automatic test equipment respectively.

[0067] In some embodiments, step S300 specifically includes the following steps, a flowchart thereof is shown in Figure 3

[0068] Step S3100: setting the first judgment value as the lower limit threshold value of the corresponding test item of the automatic test equipment, and if the corresponding test data of the product to be tested is less than the first judgment value, determining that the product to be tested is a defective product.

[0069] Step S3200: setting the second judgment value as the upper limit threshold value of the corresponding test item of the automatic test equipment, and if the corresponding test data of the product to be tested is greater than the second judgment value, determining that the product to be tested is a defective product.

[0070] Step S400: making the automatic test equipment test the product to be tested according to the test item configuration to obtain corresponding test data.

[0071] After the test judgment parameters and the test item configuration are pre-set through the above steps, the automatic test equipment tests the product to be tested by reading the ID of the fixture, loading the test item corresponding to the fixture ID, and obtains the test data of the corresponding test item.

[0072] Step S500: judging the defective product according to the corresponding test data, counting the number and proportion of the project defective product of the corresponding test item in the defective product, and obtaining statistical data.

[0073] Specifically, the test judgment parameters of the corresponding test item, i.e., the first judgment value and the second judgment value, are used to judge whether the product to be tested is a defective product. For example, the input voltage of the product to be tested is obtained through the above test, and it is judged whether the input voltage is less than the first judgment value of the input voltage or greater than the second judgment value of the input voltage. If yes, it is determined that the input voltage of the product to be tested is unqualified, and the product to be tested is a defective product.

[0074] Subsequently, the number and proportion of the project defective product of the corresponding test item in the defective product, i.e., the number and proportion of the defective product of each test item, are counted to obtain statistical data.

[0075] ​It should be noted that the same batch of products to be tested can be tested for multiple test items. For any product to be tested, if the test data of any test item exceeds the test judgment parameter, the product to be tested is determined to be a defective product.

[0076] Step S600: According to the statistical data, a fault analysis model is generated by machine learning.

[0077] Specifically, the statistical data is used as training data to generate a fault analysis model by machine learning. In this embodiment, the type of machine learning is supervised learning. The specific implementation means of machine learning is prior art, which is not described here.

[0078] Step S700: The test data of the defective product is input into the fault analysis model to judge the fault cause and severity of the defective product and give corresponding maintenance suggestions.

[0079] After obtaining the fault analysis model, by inputting the test data of the defective product into the fault analysis model, the fault cause and severity of the defective product can be obtained. In this embodiment, the fault cause analysis of the fault analysis model for the defective product includes no output voltage, power loss greater than a preset loss threshold, input current exceeding a preset current threshold, output voltage lower than a preset voltage threshold, and unstable output current.

[0080] Step S800: When performing product comparison test, test each product according to the set test item in turn to obtain test results.

[0081] In addition, when performing product comparison test on similar products, each product can be tested according to the set test item in turn to obtain test results.

[0082] Step S900: Generate a product comparison report according to the test results.

[0083] Unlike the prior art, the embodiment of the present application can automatically configure the test range and automatically load the test items, thereby improving the test efficiency of the automatic test equipment. Moreover, it can also automatically test and classify defective products, thereby improving the test efficiency and avoiding the error of manual test results.

[0084] Based on the above test method, the embodiment of the present application further provides a test device, a structure diagram of which is shown in Figure 4 The device comprises a loading module 100, a calculation module 200, a setting module 300, a first test module 400, a statistical module 500, a model generation module 600, a judgment module 700, a second test module 800 and a report generation module 900, wherein,

[0085] The loading module 100 is configured to read the ID of the clamp to load a test item corresponding to the clamp; the calculation module 200 is configured to calculate a first judgment value and a second judgment value according to corresponding test data of each test item of a reference sample; the setting module 300 is configured to set the first judgment value and the second judgment value as a lower limit threshold value and an upper limit threshold value of a corresponding test item of the automatic test device respectively; the first test module 400 is configured to make the automatic test device test a product to be tested according to the test item configuration to obtain corresponding test data; the statistical module 500 is configured to judge defective products according to the corresponding test data, count the number and proportion of item defective products in the defective products, and obtain statistical data; the model generation module 600 is configured to generate a fault analysis model through machine learning according to the statistical data; the judgment module 700 is configured to input test data of the defective products into the fault analysis model to judge the fault cause and severity of the defective products and give corresponding maintenance suggestions; the second test module 800 is configured to test each product according to a set test item in sequence when performing product comparison test to obtain test results; and the report generation module 900 is configured to generate a product comparison report according to the test results.

[0086] Please refer to Figure 5 , Figure 5 A structural schematic diagram of an electronic device provided by an embodiment of the present application, the electronic device 1000 comprises:

[0087] One or more processors 1100 and memories 1200, Figure 5 For example, taking one processor 1100 as an example.

[0088] The processor 1100 and the memory 1200 can be connected through a bus or other means, Figure 5 For example, taking connection through a bus as an example.

[0089] The memory 1200 is a kind of nonvolatile computer readable storage medium, and can be used to store nonvolatile software programs, nonvolatile computer executable programs and modules.The processor 1100 is by running the nonvolatile software program, instruction and unit stored in the memory 1200, thereby executing the various functions of the electronic device and data processing, i.e.

[0090] The memory 1200 can include a program storage area and a data storage area, where the program storage area can store an operating system, at least one application required by a function, and the data storage area can store data created according to the use of the electronic device, and the like. In addition, the memory 1200 can include a high-speed random access memory, and can further include a non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory 1200 can optionally include a memory disposed remotely from the processor 1100, which can be connected to the electronic device through a network. Examples of the above network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0091] The one or more units are stored in the memory 1200, and when executed by the one or more processors 1100, perform a test method of any of the above method embodiments, for example, perform the method steps S100 to S900 in the above-described method Figure 1 Figure 4 The functions of each module in the device in

[0092] The above electronic device can perform a test method provided by the embodiments of the present application, has the corresponding program modules and beneficial effects of performing the method. Technical details not described in detail in the electronic device embodiment can refer to the test method provided by the embodiments of the present application.

[0093] The embodiments of the present application also provide a non-volatile computer readable storage medium, which can be included in the device described in the above embodiments; or can exist separately and not be assembled into the device. The above non-volatile computer readable storage medium carries one or more programs, when the one or more programs are executed, the method of the embodiments of the present disclosure is realized.

[0094] The above only describes the embodiments of the present application, and does not limit the patent scope of the present application, any equivalent structure or equivalent process transformation made by using the content of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.​

Claims

1. A testing method, applied to automatic testing equipment, characterized in that: include: Configure the fixture ID and the corresponding test item, so that by reading the fixture ID, the test item configuration corresponding to the ID is loaded; Calculating and obtaining corresponding first judgment values ​​and second judgment values ​​according to corresponding test data of each test item of the reference sample; Setting the first judgment value and the second judgment value as the lower threshold and the upper threshold of the corresponding test items of the automatic test equipment respectively; The automatic test equipment is configured to test the product to be tested according to the test items to obtain corresponding test data; Determine defective products based on the corresponding test data, count the number and proportion of defective products of corresponding test items among the defective products, and obtain statistical data; generating a fault analysis model through machine learning based on the statistical data; Inputting the test data of the defective product into the fault analysis model to determine the cause and severity of the failure of the defective product and provide corresponding repair suggestions; The step of calculating the corresponding first judgment value and the second judgment value based on the corresponding test data of each test item of the reference sample includes: Enter the corresponding test data of each test item of the reference sample; Calculate the first central value and standard deviation of the corresponding test data respectively; Subtract 3 times the standard deviation from the first center value to obtain a first screening value; Add 3 times the standard deviation to the first central value to obtain a second screening value; Eliminate data smaller than the first screening value and data larger than the second screening value in the test data; Calculate the second center value, minimum value and maximum value of the remaining test data; The first absolute value is calculated according to the following formula: X1=|XM - (X min -s)|, Among them, X1 is the first absolute value, X M is the second center value, X min is the minimum value, σ is the standard deviation; The second absolute value is calculated according to the following formula: X2=|(X max +σ)-XM|, Wherein, X2 is the second absolute value, X max is the maximum value; Calculating the maximum value of the first absolute value and the second absolute value to obtain an error value; Subtract the error value from the second center value to obtain the first judgment value; The second center value is added to the error value to obtain the second judgment value.

2. The method according to claim 1, characterized in that Also includes: When conducting product comparison tests, each product is tested in turn according to the set test items to obtain the test results; A product comparison report is generated based on the test results.

3. The method according to claim 2, characterized in that The step of setting the first judgment value and the second judgment value as the lower threshold and the upper threshold of the corresponding test item of the automatic test equipment respectively comprises: Setting the first judgment value as the lower limit threshold of the corresponding test item of the automatic test equipment, and determining that the product to be tested is a defective product if the corresponding test data of the product to be tested is less than the first judgment value; The second judgment value is set as the upper limit threshold of the corresponding test item of the automatic test equipment. If the corresponding test data of the product to be tested is greater than the second judgment value, the product to be tested is determined to be a defective product.

4. The method according to any one of claims 1 to 3, characterized in that The test items include input voltage, output voltage, input current, output current, input power, output power, power loss and power efficiency.

5. The method according to claim 4, characterized in that The failure causes of the defective products include no output voltage, power loss greater than a preset loss threshold, input current exceeding a preset current threshold, output voltage lower than a preset voltage threshold, and unstable output current.

6. A test device, applied to automatic test equipment, characterized in that: include: A loading module is used to configure the fixture ID and the corresponding test items, so that the test item configuration corresponding to the ID is loaded by reading the fixture ID; The calculation module is used to calculate the corresponding first judgment value and second judgment value based on the corresponding test data of each test item of the reference sample, including: Enter the corresponding test data of each test item of the reference sample; Calculate the first central value and standard deviation of the corresponding test data respectively; Subtract 3 times the standard deviation from the first center value to obtain a first screening value; Add 3 times the standard deviation to the first central value to obtain a second screening value; Eliminate data smaller than the first screening value and data larger than the second screening value in the test data; Calculate the second center value, minimum value and maximum value of the remaining test data; The first absolute value is calculated according to the following formula: X1=|XM - (X min -s)|, Among them, X1 is the first absolute value, X M is the second center value, X min is the minimum value, σ is the standard deviation; The second absolute value is calculated according to the following formula: X2=|(X max +σ)-XM|, Wherein, X2 is the second absolute value, X max is the maximum value; Calculating the maximum value of the first absolute value and the second absolute value to obtain an error value; Subtract the error value from the second center value to obtain the first judgment value; Add the second center value to the error value to obtain the second judgment value; A setting module, configured to set the first judgment value and the second judgment value as a lower threshold and an upper threshold of a corresponding test item of the automatic test equipment, respectively; A first testing module is configured to enable the automatic testing equipment to test the product to be tested according to the test item configuration to obtain corresponding test data; A statistics module is used to determine defective products based on the corresponding test data, count the number and proportion of defective products of corresponding test items among the defective products, and obtain statistical data; A model generation module, configured to generate a fault analysis model through machine learning based on the statistical data; A judgment module, configured to input the test data of defective products into the fault analysis model to determine the cause and severity of the failure of the defective products and provide corresponding repair suggestions; The second test module is used to test each product in turn according to the set test items when performing product comparison testing to obtain test results; A report generation module is used to generate a product comparison report based on the test results.

7. An electronic device, characterized in that: include: at least one processor; as well as, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform a testing method according to any one of claims 1 to 6.

8. A non-volatile computer storage medium, characterized in that The computer storage medium stores computer-executable instructions, which are executed by one or more processors, enabling the one or more processors to execute a testing method according to any one of claims 1 to 6.

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