Component detection method and device, electronic equipment and storage medium

Abstract

The invention relates to an element detection method and device, electronic equipment and a storage medium, and the method comprises the steps: carrying out at least two times of function testing on candidate to-be-evaluated elements in to-be-tested equipment under the condition that a test event for the to-be-tested equipment is triggered; determining the candidate to-be-evaluated element passing the at least two times of function tests as a target to-be-evaluated element; determining a current index parameter corresponding to the target to-be-evaluated element based on retest data obtained by performing at least two function tests on the target to-be-evaluated element; wherein the current index parameter is related to the current stability and consistency of the target to-be-evaluated element, so that the stability and consistency of the to-be-tested equipment can be dynamically identified, abnormal shutdown is avoided, and the production efficiency and the productivity are improved.

Description

Technical Field

[0001] The present disclosure relates to the field of Internet of Things, and in particular to a component detection method and device, electronic equipment, and storage medium. Background Art

[0002] Equipment consistency and stability are basic requirements of the production process, but factories currently lack the means to monitor equipment consistency and stability. As a result, equipment problems are not discovered in a timely manner, resulting in poor equipment stability and reliability.

[0003] In related technologies, through analysis and monitoring methods such as Complex Process Capability index (CPK) and Statistical Process Control (SPC), the production process can be monitored in real time and quality problems can be discovered in advance. However, due to the many factors that affect equipment quality, the above methods cannot accurately locate equipment stability and consistency problems, and field engineers need to stop the line for analysis. Field engineers can only perform indicator tests manually, but since the testing process is time-consuming, it is easy to cause production capacity loss. Summary of the invention

[0004] In order to overcome the problems existing in the related art, the present disclosure provides a component detection method and device, an electronic device, and a storage medium to overcome the problem in the prior art that the stability and consistency of the device to be tested cannot be dynamically identified, resulting in downtime losses and reduced production efficiency.

[0005] According to a first aspect of an embodiment of the present disclosure, there is provided a component detection method, comprising:

[0006] In case of triggering a test event for the device to be tested, performing at least two functional tests on the candidate components to be evaluated in the device to be tested;

[0007] Determine the candidate component to be evaluated that has passed at least two of the functional tests as a target component to be evaluated;

[0008] Determining a current index parameter corresponding to the target component to be evaluated based on retest data obtained by performing at least two functional tests on the target component to be evaluated;

[0009] Wherein, the current indicator parameter is related to the current stability and consistency of the target component to be evaluated. In some embodiments, the method further includes:

[0010] When the current index parameter is greater than the standard index parameter, determining that the target component to be evaluated is in a state to be repaired;

[0011] When the current indicator parameter is less than or equal to the standard indicator parameter, the re-measurement data continues to be collected.

[0012] In some embodiments, determining the current indicator parameter corresponding to the target component to be evaluated based on the retest data obtained by performing the functional test on the target component to be evaluated at least twice includes:

[0013] Determine a total indicator deviation value of the device to be tested based on all the retest data corresponding to the device to be tested;

[0014] Determining a consistency deviation value of the device to be tested based on the re-test data corresponding to each of the target components to be evaluated and the number of the target components to be evaluated;

[0015] Determining a stability deviation value of the device to be tested based on the re-test data and a grouping result obtained by grouping the target components to be evaluated;

[0016] Based on the consistency deviation value, the stability deviation value and the total indicator deviation value, the current indicator parameter is determined.

[0017] In some embodiments, determining the current indicator parameter based on the consistency deviation value, the stability deviation value and the total indicator deviation value includes:

[0018] Performing weighted processing on the consistency deviation value based on a first weighted value to obtain a first weighted deviation value;

[0019] Performing weighted processing on the stability deviation value based on a second weighted value to obtain a second weighted deviation value;

[0020] determining a sum of the first weighted deviation value and the second weighted deviation value;

[0021] The current indicator parameter is determined based on a ratio between the sum value and the total indicator deviation value.

[0022] In some embodiments, determining the total indicator deviation value of the device to be tested based on all the retest data corresponding to the device to be tested includes:

[0023] Determine a first average value of all the retest data corresponding to the device to be tested;

[0024] Determine a first indicator deviation value corresponding to each re-measured data based on a difference between each re-measured data corresponding to the device to be tested and the first average value;

[0025] Based on each of the first indicator deviation values, a total indicator deviation value is determined.

[0026] In some embodiments, determining the consistency deviation value of the device to be tested based on the re-test data corresponding to each of the target components to be evaluated and the number of the target components to be evaluated includes:

[0027] respectively determining a second average value of all the re-measured data corresponding to each of the target components to be evaluated;

[0028] Determine a second indicator deviation value corresponding to the target component to be evaluated based on a difference between each of the second average values ​​and a first average value of all the re-test data corresponding to the device to be tested;

[0029] Determining the component index deviation value based on the second index deviation value and the number of the target components to be evaluated;

[0030] Based on the component index deviation value and the total index deviation value, a consistency deviation value of the device to be tested is determined.

[0031] In some embodiments, determining the stability deviation value of the device to be tested based on the re-test data and the grouping result obtained by grouping the target components to be evaluated includes:

[0032] Grouping the target components to be evaluated to obtain a target component group to be evaluated;

[0033] Determine a third average value of all the re-measured data corresponding to the target to-be-evaluated component group;

[0034] The stability deviation value is determined based on the difference between each of the re-test data corresponding to the device under test and the third average value.

[0035] In some embodiments, the method further comprises:

[0036] During the functional test of the device to be tested, generating a test data set according to the test results corresponding to the device to be tested;

[0037] Preprocessing the test data set to extract test data of the target component to be evaluated;

[0038] The test data of the target component to be evaluated is determined as the re-test data.

[0039] In some embodiments, the method further comprises:

[0040] When a test event for the device to be tested is triggered, obtaining historical component parameters of each component in the device to be tested;

[0041] Based on the historical component parameters, determining whether each of the components in the device to be tested is in a repaired state and / or an abnormality occurs during the test process;

[0042] The components that have been repaired and / or have abnormalities during the test are determined as the candidate components to be evaluated.

[0043] According to a second aspect of an embodiment of the present disclosure, there is provided a component detection device, comprising:

[0044] A testing module, configured to perform at least two functional tests on a candidate to-be-evaluated component in the device to be tested when a test event for the device to be tested is triggered;

[0045] A first determination module is configured to determine the candidate to-be-evaluated component that has passed at least two of the functional tests as a target to-be-evaluated component;

[0046] A second determination module is configured to determine a current indicator parameter corresponding to the target component to be evaluated based on retest data obtained by performing at least two functional tests on the target component to be evaluated;

[0047] The current index parameter is related to the current stability and consistency of the target component to be evaluated.

[0048] In some embodiments, the component detection device further includes:

[0049] A third determination module is configured to determine that the target component to be evaluated is in a state to be repaired when the current index parameter is greater than the standard index parameter;

[0050] The collection module is configured to continue collecting the remeasurement data when the current indicator parameter is less than or equal to the standard indicator parameter.

[0051] In some embodiments, the second determining module includes:

[0052] A first submodule is configured to determine a total indicator deviation value of the device to be tested based on all the retest data corresponding to the device to be tested;

[0053] A second submodule is configured to determine a consistency deviation value of the device to be tested based on the re-test data corresponding to each of the target components to be evaluated and the number of the target components to be evaluated;

[0054] A third submodule is configured to determine a stability deviation value of the device to be tested based on the re-test data and a grouping result obtained by grouping the target components to be evaluated;

[0055] The fourth submodule is configured to determine the current indicator parameter based on the consistency deviation value, the stability deviation value and the total indicator deviation value.

[0056] In some embodiments, the fourth submodule includes:

[0057] A first weighting module is configured to perform weighted processing on the consistency deviation value based on a first weighted value to obtain a first weighted deviation value;

[0058] a second weighting module, configured to perform weighted processing on the stability deviation value based on a second weighted value to obtain a second weighted deviation value;

[0059] a summing module configured to determine a sum between the first weighted deviation value and the second weighted deviation value;

[0060] A ratio module is configured to determine the current indicator parameter based on a ratio between the sum value and the total indicator deviation value.

[0061] In some embodiments, the first submodule includes:

[0062] A first calculation module is configured to determine a first average value of all the retest data corresponding to the device to be tested;

[0063] A second calculation module is configured to determine a first indicator deviation value corresponding to each re-test data based on a difference between each re-test data corresponding to the device to be tested and the first average value;

[0064] The third calculation module is configured to determine a total indicator deviation value based on each of the first indicator deviation values.

[0065] In some embodiments, the second submodule includes:

[0066] A fourth calculation module is configured to respectively determine a second average value of all the re-measured data corresponding to each of the target components to be evaluated;

[0067] A fifth calculation module is configured to determine a second indicator deviation value corresponding to the target component to be evaluated based on a difference between each of the second average values ​​and a first average value of all the re-test data corresponding to the device to be tested;

[0068] a sixth calculation module, configured to determine the component index deviation value based on the second index deviation value and the number of the target components to be evaluated;

[0069] A seventh calculation module is configured to determine a consistency deviation value of the device to be tested based on the component index deviation value and the total index deviation value.

[0070] In some embodiments, the third submodule includes:

[0071] an eighth calculation module, configured to group the target components to be evaluated to obtain a target component group to be evaluated;

[0072] A ninth calculation module, configured to determine a third average value of all the re-measured data corresponding to the target to-be-evaluated component group;

[0073] The tenth calculation module is configured to determine the stability deviation value based on the difference between each of the re-measured data corresponding to the device to be tested and the third average value.

[0074] In some embodiments, the component detection device further includes:

[0075] A generating module, configured to generate a test data set according to the test result corresponding to the device to be tested during a function test on the device to be tested;

[0076] A preprocessing module is configured to preprocess the test data set to extract test data of the target component to be evaluated;

[0077] The fourth determining module is configured to determine the test data of the target component to be evaluated as the retest data.

[0078] In some embodiments, the component detection device further includes:

[0079] An acquisition module, configured to acquire historical component parameters of each component in the device to be tested when a test event for the device to be tested is triggered;

[0080] A fifth determination module is configured to determine, based on the historical component parameters, whether each of the components in the device to be tested is in a repaired state and / or an abnormality occurs during the test process;

[0081] The sixth determination module is configured to determine the component that has been repaired and / or has an abnormality during the test process as the candidate component to be evaluated.

[0082] According to a third aspect of an embodiment of the present disclosure, there is provided an electronic device, including:

[0083] processor;

[0084] a memory for storing processor-executable instructions;

[0085] Wherein, the processor is configured to: when executing the executable command, implement the steps in any one of the component detection methods in the first aspect above.

[0086] According to a fourth aspect of an embodiment of the present disclosure, a non-transitory computer-readable storage medium is provided, including:

[0087] When the instructions in the storage medium are executed by a processor of an electronic device, the steps in any one of the component detection methods in the first aspect are implemented.

[0088] The technical solution provided by the embodiments of the present disclosure may have the following beneficial effects:

[0089] In the embodiment of the present disclosure, when a test event for the device to be tested is triggered, at least two functional tests are performed on the candidate components to be evaluated in the device to be tested; the candidate components to be evaluated that have passed at least two of the functional tests are determined as target components to be evaluated; based on the retest data obtained by performing at least two functional tests on the target components to be evaluated, the current index parameters corresponding to the target components to be evaluated are determined; wherein the current index parameters are related to the current stability and consistency of the target components to be evaluated. In this way, the embodiment of the present disclosure can dynamically calculate the current index parameters corresponding to the target components to be evaluated based on the retest data, thereby being able to dynamically identify the consistency and stability of the device to be tested, reduce the losses caused by abnormal downtime due to problems with the device to be tested, and help improve production efficiency.

[0090] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0091] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0092] Figure 1 is a schematic diagram of a component detection method according to an exemplary embodiment Figure 1 ;

[0093] Figure 2 is a schematic diagram of a related technology device detection method according to an exemplary embodiment;

[0094] Figure 3 is a schematic diagram of a component detection method according to an exemplary embodiment Figure 2 ;

[0095] Figure 4 is a schematic diagram of a component detection method according to an exemplary embodiment Figure 3 ;

[0096] Figure 5is a block diagram of a component detection device according to an exemplary embodiment;

[0097] Figure 6 A hardware structure frame of an electronic device according to an exemplary embodiment is shown Figure 1 ;

[0098] Figure 7 A hardware structure frame of an electronic device according to an exemplary embodiment is shown Figure 2 . DETAILED DESCRIPTION

[0099] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0100] Figure 1 is a schematic diagram of a component detection method according to an exemplary embodiment Figure 1 ,like Figure 1 As shown, the component detection method mainly includes the following steps:

[0101] In step 101, when a test event for a device under test is triggered, at least two functional tests are performed on candidate components to be evaluated in the device under test;

[0102] In step 102, the candidate component to be evaluated that has passed at least two functional tests is determined as a target component to be evaluated;

[0103] In step 103, based on the retest data obtained by performing the functional test on the target component to be evaluated at least twice, a current index parameter corresponding to the target component to be evaluated is determined;

[0104] The current index parameter is related to the current stability and consistency of the target component to be evaluated.

[0105] It should be noted that the component detection method proposed in the present disclosure can be applied to electronic devices. Here, the electronic device may include: terminal devices, for example, mobile terminals or fixed terminals. Among them, mobile terminals may include: mobile phones, tablet computers, laptop computers, wearable electronic devices and other devices. Fixed terminals may include: desktop computers, smart TVs, vehicle-mounted devices, etc. In other embodiments, the component detection method can also be applied to applications installed on electronic devices.

[0106] In other embodiments, the component detection method in the embodiment of the present disclosure may be configured in a component detection device, and the component detection device may be provided in an electronic device, and the embodiment of the present disclosure does not limit this. It should be noted that the execution subject of the embodiment of the present disclosure may be a central processing unit (CPU) in an electronic device in terms of hardware, and may be a related background service in the electronic device in terms of software, and this is not limited.

[0107] It can be understood that, in order to determine the target component to be evaluated, when a test event for the device to be tested is triggered, it is necessary to perform at least two functional tests on the candidate components to be evaluated in the device to be tested.

[0108] It should be explained that the device under test refers to an object or system that can perform a specific function. The device under test is usually composed of multiple components, and the function of the device under test is achieved through the coordinated work of these components. Therefore, the function and performance of the device under test usually depends on the quality and performance of the components contained in the device under test.

[0109] Here, the device to be tested may be a mechanical device, such as an airplane, a car, a machine tool, etc.; the device to be tested may also be an electronic device, such as a mobile phone, a television, a computer, etc., which is not limited in the embodiments of the present disclosure.

[0110] It should be noted that functional testing is to verify the functions of candidate components to be evaluated. According to the functional test cases, each candidate component to be evaluated is tested item by item to check whether it meets the functions required by the user. It is mainly based on the characteristics, operation description and user scheme of the candidate component to be evaluated, and the characteristics and operable behaviors of each candidate component to be evaluated are tested to determine whether the candidate component to be evaluated meets the design requirements.

[0111] Here, the functional tests of different candidate components to be evaluated may be the same or different, and this is not limited in the embodiments of the present disclosure.

[0112] In some embodiments, if the device to be tested is a mobile phone, the candidate components to be evaluated may be a mobile phone motherboard (i.e., the main circuit board in the mobile phone) and a sensor, etc. When a test event for the mobile phone is triggered, at least two functional tests need to be performed on the mobile phone motherboard and at least two functional tests need to be performed on the sensor.

[0113] It is understandable that the functional test results of the candidate to-be-evaluated component include but are not limited to the test results of passing one functional test and failing one functional test, the test results of passing two functional tests, and the test results of failing two functional tests.

[0114] It should be noted that, in order to determine the target component to be evaluated, it is necessary to determine the candidate components to be evaluated that pass both functional tests based on the functional test results of each candidate component to be evaluated.

[0115] Here, the target component to be evaluated may be one or more, which is not limited in the embodiment of the present disclosure.

[0116] In some embodiments, in order to improve the efficiency of screening the functional test results that pass both times of the candidate components to be evaluated, a database query language (such as Structured Query Language, SQL) can be used, specifically: connect to the database, open the query tool, then write a query statement, specify the conditions to be screened, and finally execute the query language to screen out the test results that pass both times from multiple functional test results.

[0117] It can be understood that the target component to be evaluated is a candidate component to be evaluated that has passed both functional tests, and therefore, the test data corresponding to the target component to be evaluated is retest data that has passed both functional tests. After determining the retest data obtained by performing at least two functional tests on the target component to be evaluated, the current index parameter corresponding to the target component to be evaluated can be determined.

[0118] In some embodiments, the current index parameter may be a Gauge Repeatability and Reproducibility (GRR) index, which is used to evaluate the ability of the device to be tested to stably and accurately reproduce the same results. It is usually used to evaluate the reliability of the device to be tested, the inspection method, and the operator. In the GRR index, repeatability refers to the stability of the results obtained by the same operator performing multiple inspections on the same device to be tested in a short period of time under the same conditions; reproducibility refers to the consistency of the results obtained by different operators performing multiple inspections on the same device to be tested under the same conditions.

[0119] In related technologies, in order to detect the reliability and stability of the equipment to be tested, it is necessary to idle the equipment to be tested, suspend the current production process, and arrange three testers to test multiple components respectively. Each component needs to be tested more than twice. After collecting the data required to calculate the GRR index, it is necessary to calculate the GRR index offline. Then the engineer compares the calculated GRR index value with the standard GRR threshold to determine whether the equipment to be tested is stable, and then determine whether to shut down for maintenance or continue production. Therefore, the above process is very time-consuming, easily affects production capacity, and is not conducive to improving production efficiency.

[0120] For example, Figure 2is a schematic diagram of a related technology device detection method according to an exemplary embodiment. Figure 2 As shown, three persons, A, B and C, are arranged to respectively test component 1 of the device under test twice, component 2 of the device under test twice, component 3 of the device under test twice, component 4 of the device under test twice, and component 5 of the device under test twice.

[0121] In another related technology, although the production process can be monitored in real time through CPK, SPC and other analysis and monitoring methods to discover quality problems of the equipment to be tested in advance, due to the many factors that affect the quality problems of the equipment to be tested, it is impossible to accurately locate the stability and consistency problems of the equipment to be tested, and on-site engineers are still required to stop the line for analysis, thereby increasing production capacity losses.

[0122] The disclosed embodiment can improve the accuracy and reliability of the detection of the equipment to be tested by dynamically acquiring the current indicator parameters (i.e., the above-mentioned GRR indicators) corresponding to the re-test data, and then analyzing the current indicator parameters, which is beneficial to improving the quality of candidate components to be evaluated and the process control capability of each equipment to be tested in the factory, thereby solving the problem of the inability to dynamically identify the stability and consistency of the equipment to be tested in the related technology. At the same time, the entry step of the line body review in the related technology can be cancelled, thereby shortening the line change time and reducing time loss.

[0123] It should be noted that, since the current index parameter is related to the current stability and consistency of the target component to be evaluated, and the performance of the target component to be evaluated is related to the performance of the device to be tested, the current index parameter is related to the stability and consistency of the device to be tested.

[0124] In some embodiments, if the current indicator parameter is the GRR indicator, the smaller the value of the GRR indicator is, the higher the stability and consistency of the device to be tested is.

[0125] In the embodiment of the present disclosure, when a test event for the device to be tested is triggered, at least two functional tests are performed on the candidate components to be evaluated in the device to be tested; the candidate components to be evaluated that have passed at least two of the functional tests are determined as target components to be evaluated; based on the retest data obtained by performing at least two functional tests on the target components to be evaluated, the current index parameters corresponding to the target components to be evaluated are determined; wherein the current index parameters are related to the current stability and consistency of the target components to be evaluated. In this way, the embodiment of the present disclosure can dynamically calculate the current index parameters corresponding to the target components to be evaluated based on the retest data, thereby being able to dynamically identify the consistency and stability of the device to be tested, reduce the losses caused by abnormal downtime due to problems with the device to be tested, and help improve production efficiency.

[0126] In some embodiments, the method further comprises:

[0127] When the current index parameter is greater than the standard index parameter, determining that the target component to be evaluated is in a state to be repaired;

[0128] When the current indicator parameter is less than or equal to the standard indicator parameter, the re-measurement data continues to be collected.

[0129] It should be explained that in order to reduce the number of abnormal shutdowns caused by problems with the equipment to be tested and improve production efficiency, after determining the current indicator parameters corresponding to the target component to be evaluated, standard indicator parameters can be set, and based on the comparison results between the current indicator parameters and the standard indicator parameters, it is determined whether the equipment to be tested needs to be shut down for maintenance.

[0130] It can be understood that the current index parameter is negatively correlated with the current stability and consistency of the target component to be evaluated, that is, the larger the current index parameter, the worse the current stability and consistency of the target component to be evaluated; the smaller the current index parameter, the better the current stability and consistency of the target component to be evaluated. When the current index parameter is greater than the standard index parameter, it can be determined that the stability and consistency of the target component to be evaluated are poor, and it can be judged that the target component to be evaluated is in a state to be repaired, so that the target component to be evaluated can be repaired in time to avoid causing greater losses; when the current index parameter is less than or equal to the standard index parameter, it can be determined that the stability and consistency of the target component to be evaluated are good, and the re-test data can continue to be collected, so that the current index parameter can be dynamically calculated to improve the detection efficiency of the equipment to be tested.

[0131] Here, the standard indicator parameters may be determined by the tester according to the working conditions of the device to be tested, or may be determined based on the judgment criteria of the GRR indicator, and the embodiments of the present disclosure are not limited to this.

[0132] In the embodiment of the present disclosure, when the current index parameter is greater than the standard index parameter, it is determined that the target component to be evaluated is in a state to be repaired; when the current index parameter is less than or equal to the standard index parameter, the retest data continues to be collected. In this way, the embodiment of the present disclosure can dynamically determine whether the current index parameter reaches the standard index parameter, and when the current index parameter is greater than the standard index parameter, the target component to be evaluated is repaired in a timely manner; when the current index parameter is less than or equal to the standard index parameter, the retest data is continuously collected and the GRR index is recalculated, which is conducive to reducing the number of abnormal shutdowns caused by problems with the device to be tested. At the same time, this process does not require intervention by testers, thereby reducing labor costs.

[0133] In some embodiments, determining the current indicator parameter corresponding to the target component to be evaluated based on the retest data obtained by performing the functional test on the target component to be evaluated at least twice includes:

[0134] Determine a total indicator deviation value of the device to be tested based on all the retest data corresponding to the device to be tested;

[0135] Determining a consistency deviation value of the device to be tested based on the re-test data corresponding to each of the target components to be evaluated and the number of the target components to be evaluated;

[0136] Determining a stability deviation value of the device to be tested based on the re-test data and a grouping result obtained by grouping the target components to be evaluated;

[0137] Based on the consistency deviation value, the stability deviation value and the total indicator deviation value, the current indicator parameter is determined.

[0138] It should be noted that the current indicator parameters present the relationship between the consistency deviation value, the stability deviation value and the total indicator deviation value. Therefore, it is necessary to calculate the consistency deviation value corresponding to the device to be tested, the stability deviation value corresponding to the device to be tested and the total indicator deviation value corresponding to the device to be tested respectively.

[0139] It can be understood that the total indicator deviation value represents the deviation of all re-test data corresponding to the device under test. Therefore, the total indicator deviation value needs to be calculated based on all re-test data corresponding to the device under test.

[0140] It should be explained that the consistency deviation value of the device under test corresponds to the functional reproducibility of the target component under evaluation. Therefore, it is necessary to obtain the retest data corresponding to each target component under evaluation and the number of target components under evaluation respectively to calculate the consistency deviation value.

[0141] It should be noted that the stability deviation value of the device to be tested corresponds to the functional repeatability of the target component to be evaluated. Therefore, the stability deviation value needs to be calculated based on the retest data and the grouping result obtained by grouping the target component to be evaluated.

[0142] In the disclosed embodiment, based on all re-test data of the device to be tested, a total index deviation value of the device to be tested is determined; based on the re-test data corresponding to each of the target components to be evaluated and the number of the target components to be evaluated, a consistency deviation value of the device to be tested is determined; based on the re-test data and the grouping results obtained by grouping the target components to be evaluated, a stability deviation value of the device to be tested is determined; finally, based on the consistency deviation value, the stability deviation value and the total index deviation value, the current index parameter is determined, so that the current index parameter is dynamically calculated based on the re-test data, without the need for testers to intervene in the calculation, which is beneficial to reducing manpower loss and production costs.

[0143] In some embodiments, determining the current indicator parameter based on the consistency deviation value, the stability deviation value and the total indicator deviation value includes:

[0144] Performing weighted processing on the consistency deviation value based on a first weighted value to obtain a first weighted deviation value;

[0145] Performing weighted processing on the stability deviation value based on a second weighted value to obtain a second weighted deviation value;

[0146] determining a sum of the first weighted deviation value and the second weighted deviation value;

[0147] The current indicator parameter is determined based on a ratio between the sum value and the total indicator deviation value.

[0148] It should be noted that, in order to improve the accuracy of calculating the current index parameter, a first weighted value and a second weighted value may be set for the consistency deviation value and the stability deviation value, respectively. The consistency deviation value is weighted based on the first weighted value to obtain a first weighted deviation value; the stability deviation value is weighted based on the second weighted value to obtain a second weighted deviation value.

[0149] Here, the first weighted value and the second weighted value may be equal or unequal, and this is not limited in the embodiment of the present disclosure.

[0150] It needs to be explained that the current indicator parameters reflect the proportional relationship between the consistency deviation value, the stability deviation value and the total indicator deviation value. Therefore, in order to facilitate the calculation of the current indicator parameters, the consistency deviation value and the total indicator deviation value can be summed up first.

[0151] In the embodiment of the present disclosure, after obtaining the first weighted deviation value and the second weighted deviation value, the sum of the first weighted deviation value and the second weighted deviation value may be determined to further calculate the current indicator parameter.

[0152] Exemplarily, the calculation formula for the sum of the first weighted deviation value and the second weighted deviation value may be as follows:

[0153] SS GRR =α*SS reproduct +β*SS error (1);

[0154] In formula (1), SS GRR represents the sum of the first weighted deviation value and the second weighted deviation value, α represents the first weighted value, β represents the second weighted value, SS reproduct Indicates the consistency deviation value, SS error Indicates the stability deviation value.

[0155] In some embodiments, if the first weighted value and the second weighted value are both set to 1, formula (1) can be transformed into formula (2):

[0156] SS GRR =SS reproduct +SS error (2);

[0157] In formula (2), SS GRR Represents the sum of the first weighted deviation value and the second weighted deviation value, SS reproduct Indicates the consistency deviation value, SS error Indicates the stability deviation value.

[0158] It can be understood that after the sum value is determined, the current index parameter corresponding to the target component to be evaluated can be obtained by calculating the ratio between the sum value and the total index deviation value.

[0159] Exemplarily, the calculation formula of the current index parameter corresponding to the target component to be evaluated may be as follows:

[0160]

[0161] In formula (3), GRR represents the current index parameter corresponding to the target component to be evaluated, SS GRR Represents the sum of the first weighted deviation value and the second weighted deviation value, SS total Indicates the total indicator deviation value.

[0162] In some embodiments, if the current indicator parameter is the GRR indicator, the GRR indicator includes the percentage of GRR, which can represent the proportional relationship between the consistency deviation and stability deviation of the target component to be evaluated and the total deviation of the device to be tested. Usually, when GRR% is less than 10%, it can be determined that the consistency and stability of the device to be tested are good.

[0163] In the embodiment of the present disclosure, a first weighted value and a second weighted value are set, the first weighted value is used to perform weighted processing on the consistency deviation value to obtain a first weighted deviation value, and then the second weighted value is used to perform weighted processing on the stability deviation value to obtain a second weighted deviation value; then the sum of the first weighted deviation value and the second weighted deviation value is determined; finally, based on the ratio between the sum and the total index deviation value, the current index parameter is determined, thereby improving the accuracy of the current index parameter calculation and further improving the accuracy and reliability of detecting the equipment to be tested.

[0164] In some embodiments, determining the total indicator deviation value of the device to be tested based on all the retest data corresponding to the device to be tested includes:

[0165] Determine a first average value of all the retest data corresponding to the device to be tested;

[0166] Determine a first indicator deviation value corresponding to each re-measured data based on a difference between each re-measured data corresponding to the device to be tested and the first average value;

[0167] Based on each of the first indicator deviation values, a total indicator deviation value is determined.

[0168] It should be explained that after obtaining all retest data corresponding to the device under test, the number and value corresponding to the retest data are determined, and based on the number and the value corresponding to each retest data, the first average value of all retest data corresponding to the device under test is calculated.

[0169] Exemplarily, the calculation formula of the first average value of all the retest data corresponding to the device to be tested may be as follows:

[0170]

[0171] In formula (4), represents the first average value of all retest data corresponding to the device under test, n represents the number of all retest data corresponding to the device under test, x1, x2…x i Indicates the value of all retest data corresponding to the device under test.

[0172] It can be understood that after determining the first average value, the deviation of each re-measured data from the first average value can be determined based on the difference between each re-measured data of the device to be tested and the first average value, and the first indicator deviation value corresponding to each re-measured data can be calculated.

[0173] Exemplarily, the calculation formula of the first indicator deviation value corresponding to each re-measurement data may be as follows:

[0174]

[0175] In formula (5), x q Indicates the deviation value of the first indicator corresponding to the retest data, Indicates the first average value of all retest data corresponding to the device under test, x i Indicates the numerical value corresponding to the re-measured data.

[0176] It should be explained that after calculating each first indicator deviation value, the first indicator deviation values ​​are summed to obtain a total indicator deviation value.

[0177] For example, the calculation formula of the total index deviation value may be as follows:

[0178]

[0179] In formula (6), SS total Indicates the total indicator deviation value, Indicates the first average value of all retest data corresponding to the device under test, x i represents the numerical value corresponding to the re-measured data, Indicates that the deviation values ​​of the first indicators are accumulated.

[0180] In the embodiment of the present disclosure, by determining a first average value of all re-measured data corresponding to the device to be tested; and then determining a first indicator deviation value corresponding to each re-measured data based on a difference between each re-measured data corresponding to the device to be tested and the first average value; and finally determining a total indicator deviation value based on each first indicator deviation value, the accuracy of calculating the total indicator deviation value can be improved. This process does not require intervention by testers, which is beneficial to saving labor costs.

[0181] In some embodiments, determining the consistency deviation value of the device to be tested based on the re-test data corresponding to each of the target components to be evaluated and the number of the target components to be evaluated includes:

[0182] respectively determining a second average value of all the re-measured data corresponding to each of the target components to be evaluated;

[0183] Determine a second indicator deviation value corresponding to the target component to be evaluated based on a difference between each of the second average values ​​and a first average value of all the re-test data corresponding to the device to be tested;

[0184] Determining the component index deviation value based on the second index deviation value and the number of the target components to be evaluated;

[0185] Based on the component index deviation value and the total index deviation value, a consistency deviation value of the device to be tested is determined.

[0186] It can be understood that after determining the number of all re-measured data corresponding to each target component to be evaluated and the value of the re-measured data, the second average value corresponding to each target component to be evaluated can be calculated.

[0187] Exemplarily, the calculation formula of the second average value of all the re-measured data corresponding to each target component to be evaluated may be as follows:

[0188]

[0189] In formula (7), represents the second average value corresponding to the target component w to be evaluated, w represents the number of re-measured data corresponding to the target component w to be evaluated, x 11 、x 12 …x 1w Indicates the value of the re-measured data corresponding to the target component w to be evaluated.

[0190] It should be explained that after determining each second average value, the deviation of each second average value from the first average value can be determined based on the difference between each second average value and the first average value of all the re-measured data corresponding to the device to be tested, and the second indicator deviation value corresponding to the target component to be evaluated can be calculated.

[0191] Exemplarily, the calculation formula of the first indicator deviation value corresponding to each re-measurement data may be as follows:

[0192]

[0193] In formula (8), x e Indicates the deviation value of the second indicator corresponding to the retest data. Indicates the first average value of all retest data corresponding to the device under test. Represents each second average value corresponding to each of the target components to be evaluated.

[0194] It can be understood that by determining each second indicator deviation value and the number of target components to be evaluated, the component indicator deviation value can be determined.

[0195] Exemplarily, the calculation formula of the component index deviation value may be as follows:

[0196]

[0197] In formula (9), SS parts represents the component index deviation value, p represents the number of target components to be evaluated, Represents the accumulation of the second indicator deviation values ​​corresponding to the p target components to be evaluated.

[0198] It should be noted that the consistency deviation value of the device to be tested is determined by the difference between the total index deviation value and the component index deviation value.

[0199] Exemplarily, the calculation formula of the consistency deviation value of the device to be tested can be as follows:

[0200] SS reproduct =SS total -SS parts (10);

[0201] In formula (10), SS reproduct Indicates the consistency deviation value of the device to be tested, SS parts Indicates the component index deviation value, SS total Indicates the total indicator deviation value.

[0202] In the disclosed embodiment, the second average values ​​of all re-measured data corresponding to each target component to be evaluated are determined respectively; based on the difference between each second average value and the first average value of all re-measured data corresponding to the device to be tested, the second index deviation value corresponding to the target component to be evaluated is determined; then based on the second index deviation value and the number of the target components to be evaluated, the component index deviation value is determined; finally, based on the component index deviation value and the total index deviation value, the consistency deviation value of the device to be tested is determined, so that the consistency deviation value can be dynamically calculated, and this process does not require manual intervention, reducing manpower loss.

[0203] In some embodiments, determining the stability deviation value of the device to be tested based on the re-test data and the grouping result obtained by grouping the target components to be evaluated includes:

[0204] Grouping the target components to be evaluated to obtain a target component group to be evaluated;

[0205] Determine a third average value of all the re-measured data corresponding to the target to-be-evaluated component group;

[0206] The stability deviation value is determined based on the difference between each of the re-test data corresponding to the device under test and the third average value.

[0207] It should be noted that the number of groups of each target component group to be evaluated is set by the tester according to requirements, and the embodiment of the present disclosure does not limit this.

[0208] Here, the number of target components to be evaluated in each target component to be evaluated group may be the same or different, and this is not limited in the embodiment of the present disclosure.

[0209] It can be understood that, based on the number of each target component to be evaluated in the target component to be evaluated group and all re-measurement data corresponding to each target component to be evaluated, a third average value corresponding to the target component to be evaluated group can be calculated.

[0210] Exemplarily, the calculation formula of the third average value of all the re-test data corresponding to the target component group to be evaluated may be as follows:

[0211]

[0212]

[0213] In formula (11), represents the mean value of the first target component group to be evaluated, x m1 、x m2 …x mm represents the re-measurement data corresponding to each target component to be evaluated in the first target component to be evaluated group, and m represents the number of target components to be evaluated in the first target component to be evaluated group.

[0214] In formula (12), represents the third average value corresponding to the target component group to be evaluated, represents the mean value corresponding to each target component group to be evaluated, and k represents the number of target component groups to be evaluated.

[0215] It should be noted that the stability deviation value may be determined based on the difference between each of the re-measured data corresponding to the device to be tested and the third average value.

[0216] Exemplarily, the calculation formula of the stability deviation value may be as follows:

[0217]

[0218] In formula (13), SS error represents the stability deviation value, n represents the number of all retest data corresponding to the device to be tested, k represents the number of target component groups to be evaluated, and x i represents the values ​​of all the retest data corresponding to the device under test, Indicates the third average value corresponding to the target component group to be evaluated.

[0219] In the disclosed embodiment, the target components to be evaluated are grouped to obtain a target component group to be evaluated; then a third average value of all the re-measured data corresponding to the target component group to be evaluated is determined; finally, based on the difference between each re-measured data corresponding to the device to be tested and the third average value, the stability deviation value is determined, so that the stability deviation value can be dynamically calculated. This process does not require manual intervention, which is conducive to reducing manpower loss.

[0220] In some embodiments, the method further comprises:

[0221] During the functional test of the device to be tested, generating a test data set according to the test results corresponding to the device to be tested;

[0222] Preprocessing the test data set to extract test data of the target component to be evaluated;

[0223] The test data of the target component to be evaluated is determined as the re-test data.

[0224] It should be noted that the test data set is a test result set obtained by performing functional tests on all components of the device to be tested. Therefore, the test data set at least includes functional test data of candidate components to be evaluated and functional test data of target components to be evaluated.

[0225] Here, the functional test data of the target component to be evaluated includes at least the test results of the target component to be evaluated passing the functional test once, failing the functional test once, failing the functional test twice, and passing the functional test twice.

[0226] It should be explained that in order to reflect the correspondence between each test data and each component in the test data set, during the functional test of the device to be tested, it is necessary to obtain the test data and attach the identification of the corresponding component to the test data. Since each component is functionally tested at least twice in the embodiment of the present disclosure, each component should correspond to at least two test data.

[0227] In some embodiments, the test data of the device to be tested during the functional test can be collected in real time through the Internet of Things Platform (IOT), and a test data set can be generated based on the test data.

[0228] It is understandable that in order to improve the efficiency of extracting the test data of the target component to be evaluated, the test data in the test data set may be preprocessed so as to extract the test data of the target component to be evaluated from the test data set.

[0229] Here, preprocessing includes but is not limited to data cleaning, data conversion, data reduction, and data aggregation, etc., which are not limited in the embodiments of the present disclosure.

[0230] In some embodiments, data cleaning refers to processing and processing data to make the data more suitable for analysis and modeling. Data cleaning is an important step in data processing, which can eliminate data errors and noise and improve the accuracy of analysis and modeling. Data cleaning includes operations such as removing duplicate data, filling missing values, processing outliers, and converting data formats to improve the accuracy and reliability of data.

[0231] Here, removing duplicate data means removing duplicate records in a data set, which can be achieved by comparing identifiers or key fields in the records; filling missing values ​​means filling missing values ​​in a data set, which can be achieved using methods such as interpolation, average or median; processing outliers means detecting and processing outliers in a data set, which can be converted into acceptable values ​​by deletion or replacement; converting data formats means converting the format of data, such as converting a text format date into a date format.

[0232] It should be noted that, since the current index parameters are calculated based on the retest data, the present disclosure preprocesses the test data set and extracts test data in which the target component to be evaluated passes two functional tests from the data set as the retest data.

[0233] For example, Figure 3 is a schematic diagram of a component detection method according to an exemplary embodiment Figure 2 ,like Figure 3 As shown, after the device to be tested SN01 is delivered to station A, it is necessary to perform a functional test on the components in the device to be tested SN01 at station A, and based on the test results, determine whether the test results pass. If the test results fail, the Manufacturing Execution System (MES) is required to perform special control on the components whose test results fail the test, and force the components that fail the test to be retested for the first time, and perform a second functional test at station A. If the second functional test passes, the component needs to be retested for the second time, and a third functional test is performed at station A.

[0234] Based on the results of the two functional retests, it is determined whether the two functional retests are both passed. If the two functional retest results of the component are both passed, the device to be tested SN01 can be transported to station B; if the two functional retest results of the component are not both passed, it is determined that the device to be tested SN01 is a defective device.

[0235] In the disclosed embodiment, during the functional test of the device to be tested, a test data set is generated according to the test results corresponding to the device to be tested; the test data set is preprocessed to extract the test data of the target component to be evaluated; the test data of the target component to be evaluated is determined as the retest data, which is conducive to selecting the test data of the target component to be evaluated from the test data set (i.e., the test data that passed two functional tests), and determining the test data as the retest data, which is conducive to improving the accuracy of calculating the current indicator parameters.

[0236] In some embodiments, the method further comprises:

[0237] When a test event for the device to be tested is triggered, obtaining historical component parameters of each component in the device to be tested;

[0238] Based on the historical component parameters, determining whether each of the components in the device to be tested is in a repaired state and / or an abnormality occurs during the test process;

[0239] The components that have been repaired and / or have abnormalities during the test are determined as the candidate components to be evaluated.

[0240] It should be noted that in order to improve the detection efficiency of the device to be tested, it is necessary to obtain the historical component parameters of each component in the device to be tested when a test event for the device to be tested is triggered, so as to obtain the historical working status of each component.

[0241] Here, the historical component parameter may be a historical current parameter, a historical voltage parameter, or any parameter that can characterize the working state of the component, and the present disclosure does not limit this.

[0242] It is understandable that, through the historical component parameters of each component, it is possible to determine whether each component is in a repaired state and / or has an abnormality during the test process. Since the performance of the component is related to the performance of the device to be tested, the components that are in a repaired state and / or have an abnormality during the test process need to be determined as the candidate components to be evaluated for subsequent functional testing.

[0243] In some embodiments, in order to improve the efficiency of determining candidate components to be evaluated, the test data of each component in the device to be tested can also be input into the detection model of bad components, wherein the detection model of bad components is a data network model established based on the historical bad data training of multiple dimensions of the device. The detection model of bad components analyzes the data of the component to determine whether the component is a bad component. The detection model of bad components extracts the features of the component data, classifies the features of the component data, determines whether the features of the component data are features of bad component data, and when it is determined that the features of the component data belong to the features of bad component data, determines that the component is a candidate component to be evaluated; if it is determined that the features of the component data do not belong to the features of bad component data, determines that the component is not a candidate component to be evaluated.

[0244] In the embodiment of the present disclosure, when a test event is triggered for the device to be tested, historical component parameters of each component in the device to be tested are obtained to determine whether the device to be tested is in a repaired state and / or an abnormality occurs during the test process; and the components that are in a repaired state and / or an abnormality occurs during the test process are determined as candidate components to be evaluated, so that the candidate components to be evaluated can be accurately located, the detection efficiency of the device to be tested is improved, and the production efficiency is further improved.

[0245] Figure 4 is a schematic diagram of a component detection method according to an exemplary embodiment Figure 3 ,like Figure 4 As shown, based on the retest data obtained by performing at least two functional tests on the target component to be evaluated, the current index parameter corresponding to the target component to be evaluated is determined. The method mainly includes the following steps:

[0246] In step 301, a test data set of a device to be tested is collected.

[0247] Here, during the functional test of the device to be tested, the IOT platform can be used to collect the test results corresponding to the device to be tested and generate a test data set.

[0248] In step 302, the test data set is preprocessed.

[0249] Here, after the test data set is acquired, the test data set may be preprocessed to extract the test data of the target component to be evaluated.

[0250] In step 303, retest data is obtained.

[0251] Here, after extracting the test data of the target component to be evaluated, the test data of the target component to be evaluated may be determined as the re-test data.

[0252] In step 304, a total index deviation value is calculated.

[0253] Here, the first average value of all the re-measured data corresponding to the device to be tested can be determined first; then, based on the difference between each re-measured data corresponding to the device to be tested and the first average value, the first indicator deviation value corresponding to each re-measured data can be determined; finally, based on each of the first indicator deviation values, the total indicator deviation value can be determined.

[0254] In step 305, the component index deviation value is calculated.

[0255] Here, the second average values ​​of all the re-measured data corresponding to each of the target components to be evaluated can be determined respectively; then, based on the difference between each of the second average values ​​and the first average values ​​of all the re-measured data corresponding to the device to be tested, the second indicator deviation value corresponding to the target component to be evaluated can be determined; finally, based on the second indicator deviation value and the number of the target components to be evaluated, the component indicator deviation value can be determined.

[0256] In step 306, a consistency deviation value is calculated.

[0257] Here, after the component index deviation value is determined, the consistency deviation value of the device to be tested is determined based on the component index deviation value and the total index deviation value.

[0258] In step 307 , a stability deviation value is calculated.

[0259] Here, the target components to be evaluated may be grouped to obtain a target component group to be evaluated; then a third average value of all the re-measured data corresponding to the target component group to be evaluated is determined; and finally, the stability deviation value is determined based on the difference between each re-measured data corresponding to the device to be tested and the third average value.

[0260] In step 308, current indicator parameters are calculated.

[0261] Here, the consistency deviation value can be weighted based on the first weighted value to obtain a first weighted deviation value; the stability deviation value can be weighted based on the second weighted value to obtain a second weighted deviation value; then the sum of the first weighted deviation value and the second weighted deviation value is determined; finally, the current indicator parameter is determined based on the ratio between the sum and the total indicator deviation value.

[0262] In step 309, it is determined whether it is greater than a standard indicator parameter.

[0263] Here, it is to judge whether the current index parameter is greater than the standard index parameter. If the current index parameter is greater than the standard index parameter, it is determined that the target component to be evaluated is in a state to be repaired; if the current index parameter is less than or equal to the standard index parameter, the re-measurement data is continued to be collected.

[0264] Exemplarily, as shown in Table 1, Table 1 is a comparison table of the effects of the method disclosed herein and the related technical methods. In terms of time consumption, compared with the related technology, the method disclosed herein reduces the access time for line audit, and at the same time, does not occupy production time, reducing time loss; in terms of manpower loss, compared with the related technology, the method disclosed herein does not require testers, saving 3 testers; in terms of timeliness, compared with the related technology, the method disclosed herein can dynamically identify the stability and consistency of the equipment to be tested.

[0265] Table 1 Comparison of the effects of the disclosed method and related technical methods

[0266]

[0267]

[0268] In the embodiment of the present disclosure, when a test event for the device to be tested is triggered, at least two functional tests are performed on the candidate components to be evaluated in the device to be tested; the candidate components to be evaluated that have passed at least two of the functional tests are determined as target components to be evaluated; based on the retest data obtained by performing at least two functional tests on the target components to be evaluated, the current index parameters corresponding to the target components to be evaluated are determined; wherein the current index parameters are related to the current stability and consistency of the target components to be evaluated. In this way, the embodiment of the present disclosure can dynamically calculate the current index parameters corresponding to the target components to be evaluated based on the retest data, thereby being able to dynamically identify the consistency and stability of the device to be tested, reduce the losses caused by abnormal downtime due to problems with the device to be tested, and help improve production efficiency.

[0269] Figure 5 is a block diagram of a component detection device according to an exemplary embodiment. Figure 5 As shown, the component detection device 400 includes:

[0270] The testing module 401 is configured to perform at least two functional tests on the candidate components to be evaluated in the device to be tested when a test event for the device to be tested is triggered;

[0271] A first determining module 402 is configured to determine the candidate to-be-evaluated component that has passed at least two functional tests as a target to-be-evaluated component;

[0272] The second determination module 403 is configured to determine the current index parameter corresponding to the target component to be evaluated based on the retest data obtained by performing the functional test on the target component to be evaluated at least twice;

[0273] The current index parameter is related to the current stability and consistency of the target component to be evaluated.

[0274] In some embodiments, the component detection device 400 further includes:

[0275] A third determination module is configured to determine that the target component to be evaluated is in a state to be repaired when the current index parameter is greater than the standard index parameter;

[0276] The collection module is configured to continue collecting the remeasurement data when the current indicator parameter is less than or equal to the standard indicator parameter.

[0277] In some embodiments, the second determining module 403 includes:

[0278] A first submodule is configured to determine a total indicator deviation value of the device to be tested based on all the retest data corresponding to the device to be tested;

[0279] A second submodule is configured to determine a consistency deviation value of the device to be tested based on the re-test data corresponding to each of the target components to be evaluated and the number of the target components to be evaluated;

[0280] A third submodule is configured to determine a stability deviation value of the device to be tested based on the re-test data and a grouping result obtained by grouping the target components to be evaluated;

[0281] The fourth submodule is configured to determine the current indicator parameter based on the consistency deviation value, the stability deviation value and the total indicator deviation value.

[0282] In some embodiments, the fourth submodule includes:

[0283] A first weighting module is configured to perform weighted processing on the consistency deviation value based on a first weighted value to obtain a first weighted deviation value;

[0284] a second weighting module, configured to perform weighted processing on the stability deviation value based on a second weighted value to obtain a second weighted deviation value;

[0285] a summing module configured to determine a sum between the first weighted deviation value and the second weighted deviation value;

[0286] A ratio module is configured to determine the current indicator parameter based on a ratio between the sum value and the total indicator deviation value.

[0287] In some embodiments, the first submodule includes:

[0288] A first calculation module is configured to determine a first average value of all the retest data corresponding to the device to be tested;

[0289] A second calculation module is configured to determine a first indicator deviation value corresponding to each re-test data based on a difference between each re-test data corresponding to the device to be tested and the first average value;

[0290] The third calculation module is configured to determine a total indicator deviation value based on each of the first indicator deviation values.

[0291] In some embodiments, the second submodule includes:

[0292] A fourth calculation module is configured to respectively determine a second average value of all the re-measured data corresponding to each of the target components to be evaluated;

[0293] A fifth calculation module is configured to determine a second indicator deviation value corresponding to the target component to be evaluated based on a difference between each of the second average values ​​and a first average value of all the re-test data corresponding to the device to be tested;

[0294] a sixth calculation module, configured to determine the component index deviation value based on the second index deviation value and the number of the target components to be evaluated;

[0295] A seventh calculation module is configured to determine a consistency deviation value of the device to be tested based on the component index deviation value and the total index deviation value.

[0296] In some embodiments, the third submodule includes:

[0297] an eighth calculation module, configured to group the target components to be evaluated to obtain a target component group to be evaluated;

[0298] A ninth calculation module, configured to determine a third average value of all the re-measured data corresponding to the target to-be-evaluated component group;

[0299] The tenth calculation module is configured to determine the stability deviation value based on the difference between each of the re-measured data corresponding to the device to be tested and the third average value.

[0300] In some embodiments, the component detection device 400 further includes:

[0301] A generating module, configured to generate a test data set according to the test result corresponding to the device to be tested during a function test on the device to be tested;

[0302] A preprocessing module is configured to preprocess the test data set to extract test data of the target component to be evaluated;

[0303] The fourth determining module is configured to determine the test data of the target component to be evaluated as the retest data.

[0304] In some embodiments, the component detection device 400 further includes:

[0305] An acquisition module, configured to acquire historical component parameters of each component in the device to be tested when a test event for the device to be tested is triggered;

[0306] A fifth determination module is configured to determine, based on the historical component parameters, whether each of the components in the device to be tested is in a repaired state and / or an abnormality occurs during the test process;

[0307] The sixth determination module is configured to determine the component that has been repaired and / or has an abnormality during the test process as the candidate component to be evaluated.

[0308] Regarding the device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0309] Figure 6 A hardware structure frame of an electronic device according to an exemplary embodiment is shown Figure 1 For example, the apparatus 800 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, etc.

[0310] Reference Figure 6 , the device 800 may include one or more of the following components: a processing component 802 , a memory 804 , a power component 806 , a multimedia component 808 , an audio component 810 , an input / output (I / O) interface 812 , a sensor component 814 , and a communication component 816 .

[0311] The processing component 802 generally controls the overall operation of the device 800, such as operations associated with display, phone calls, data communications, camera operations, and recording operations. The processing component 802 may include one or more processors 820 to execute instructions to complete all or part of the steps of the above-mentioned method. In addition, the processing component 802 may include one or more modules to facilitate the interaction between the processing component 802 and other components. For example, the processing component 802 may include a multimedia module to facilitate the interaction between the multimedia component 808 and the processing component 802.

[0312] The memory 804 is configured to store various types of data to support operations on the device 800. Examples of such data include instructions for any application or method operating on the device 800, contact data, phone book data, messages, pictures, videos, etc. The memory 804 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0313] The power supply component 806 provides power to the various components of the device 800. The power supply component 806 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the device 800.

[0314] The multimedia component 808 includes a screen that provides an output interface between the device 800 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundaries of the touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 808 includes a front camera and / or a rear camera. When the device 800 is in an operating mode, such as a shooting mode or a video mode, the front camera and / or the rear camera may receive external multimedia data. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.

[0315] The audio component 810 is configured to output and / or input audio signals. For example, the audio component 810 includes a microphone (MIC), and when the device 800 is in an operating mode, such as a call mode, a recording mode, and a speech recognition mode, the microphone is configured to receive an external audio signal. The received audio signal can be further stored in the memory 804 or sent via the communication component 816. In some embodiments, the audio component 810 also includes a speaker for outputting audio signals.

[0316] I / O interface 812 provides an interface between processing component 802 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include but are not limited to: a home button, a volume button, a start button, and a lock button.

[0317] The sensor assembly 814 includes one or more sensors for providing various aspects of the status assessment of the device 800. For example, the sensor assembly 814 can detect the open / closed state of the device 800, the relative positioning of components, such as the display and keypad of the device 800, and the sensor assembly 814 can also detect the position change of the device 800 or a component of the device 800, the presence or absence of user contact with the device 800, the orientation or acceleration / deceleration of the device 800, and the temperature change of the device 800. The sensor assembly 814 may include a proximity sensor configured to detect the presence of a nearby object without any physical contact. The sensor assembly 814 may also include an optical sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 814 may also include an accelerometer, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

[0318] The communication component 816 is configured to facilitate wired or wireless communication between the device 800 and other devices. The device 800 can access a wireless network based on a communication standard, such as WiFi, 4G or 5G, or a combination thereof. In an exemplary embodiment, the communication component 816 receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 816 also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

[0319] In an exemplary embodiment, the apparatus 800 may be implemented by one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors or other electronic components to perform the above method.

[0320] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 804 including instructions, and the instructions can be executed by the processor 820 of the device 800 to perform the above method. For example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0321] A non-transitory computer-readable storage medium, when instructions in the storage medium are executed by a processor of an electronic device, enables the electronic device to perform a component detection method, the method comprising:

[0322] In case of triggering a test event for the device to be tested, performing at least two functional tests on the candidate components to be evaluated in the device to be tested;

[0323] Determine the candidate component to be evaluated that has passed at least two of the functional tests as a target component to be evaluated;

[0324] Determining a current index parameter corresponding to the target component to be evaluated based on retest data obtained by performing at least two functional tests on the target component to be evaluated;

[0325] The current index parameter is related to the current stability and consistency of the target component to be evaluated. Figure 7 A hardware structure frame of an electronic device according to an exemplary embodiment is shown Figure 2 For example, the apparatus 1900 may be provided as a server. Figure 7 , the apparatus 1900 includes a processing component 1922, which further includes one or more processors, and a memory resource represented by a memory 1932 for storing instructions executable by the processing component 1922, such as an application. The application stored in the memory 1932 may include one or more modules each corresponding to a set of instructions. In addition, the processing component 1922 is configured to execute instructions to perform the above method:

[0326] In case of triggering a test event for the device to be tested, performing at least two functional tests on the candidate components to be evaluated in the device to be tested;

[0327] Determine the candidate component to be evaluated that has passed at least two of the functional tests as a target component to be evaluated;

[0328] Determining a current index parameter corresponding to the target component to be evaluated based on retest data obtained by performing at least two functional tests on the target component to be evaluated;

[0329] The current indicator parameter is related to the current stability and consistency of the target component to be evaluated. The device 1900 may also include a power supply component 1926 configured to perform power management of the device 1900, a wired or wireless network interface 1950 configured to connect the device 1900 to the network, and an input / output (I / O) interface 1958. The device 1900 may operate based on an operating system stored in the memory 1932, such as Windows ServerTM, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM or the like.

[0330] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. The present disclosure is intended to cover any variations, uses or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The description and examples are to be considered exemplary only, and the true scope and spirit of the present disclosure are indicated by the following claims.

[0331] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A component detection method, characterized in that: The method comprises: In case of triggering a test event for the device to be tested, performing at least two functional tests on the candidate components to be evaluated in the device to be tested; Determine the candidate component to be evaluated that has passed at least two of the functional tests as a target component to be evaluated; Determining a current index parameter corresponding to the target component to be evaluated based on retest data obtained by performing at least two functional tests on the target component to be evaluated; The current index parameter is related to the current stability and consistency of the target component to be evaluated.

2. The method according to claim 1, characterized in that The method further comprises: When the current index parameter is greater than the standard index parameter, determining that the target component to be evaluated is in a state to be repaired; When the current indicator parameter is less than or equal to the standard indicator parameter, the re-measurement data continues to be collected.

3. The method according to claim 1, characterized in that The determining the current index parameter corresponding to the target component to be evaluated based on the retest data obtained by performing at least two functional tests on the target component to be evaluated comprises: Determine a total indicator deviation value of the device to be tested based on all the retest data corresponding to the device to be tested; Determining a consistency deviation value of the device to be tested based on the re-test data corresponding to each of the target components to be evaluated and the number of the target components to be evaluated; Determining a stability deviation value of the device to be tested based on the re-test data and a grouping result obtained by grouping the target components to be evaluated; Based on the consistency deviation value, the stability deviation value and the total indicator deviation value, the current indicator parameter is determined.

4. The method according to claim 3, characterized in that The determining the current indicator parameter based on the consistency deviation value, the stability deviation value and the total indicator deviation value includes: Performing weighted processing on the consistency deviation value based on a first weighted value to obtain a first weighted deviation value; Performing weighted processing on the stability deviation value based on a second weighted value to obtain a second weighted deviation value; determining a sum of the first weighted deviation value and the second weighted deviation value; The current indicator parameter is determined based on a ratio between the sum value and the total indicator deviation value.

5. The method according to claim 3, characterized in that: The determining the total indicator deviation value of the device to be tested based on all the retest data corresponding to the device to be tested includes: Determine a first average value of all the retest data corresponding to the device to be tested; Determine a first indicator deviation value corresponding to each re-measured data based on a difference between each re-measured data corresponding to the device to be tested and the first average value; Based on each of the first indicator deviation values, a total indicator deviation value is determined.

6. The method according to claim 3, characterized in that The determining the consistency deviation value of the device to be tested based on the re-test data corresponding to each of the target components to be evaluated and the number of the target components to be evaluated includes: respectively determining a second average value of all the re-measured data corresponding to each of the target components to be evaluated; Determine a second indicator deviation value corresponding to the target component to be evaluated based on a difference between each of the second average values ​​and a first average value of all the re-test data corresponding to the device to be tested; Determining the component index deviation value based on the second index deviation value and the number of the target components to be evaluated; Based on the component index deviation value and the total index deviation value, a consistency deviation value of the device to be tested is determined.

7. The method according to claim 3, characterized in that The determining the stability deviation value of the device to be tested based on the re-test data and the grouping result obtained by grouping the target components to be evaluated includes: Grouping the target components to be evaluated to obtain a target component group to be evaluated; Determine a third average value of all the re-measured data corresponding to the target to-be-evaluated component group; The stability deviation value is determined based on the difference between each of the re-test data corresponding to the device under test and the third average value.

8. The method according to any one of claims 1 to 7, characterized in that: The method further comprises: During the functional test of the device to be tested, generating a test data set according to the test results corresponding to the device to be tested; Preprocessing the test data set to extract test data of the target component to be evaluated; The test data of the target component to be evaluated is determined as the re-test data.

9. The method according to any one of claims 1 to 7, characterized in that: The method further comprises: When a test event for the device to be tested is triggered, obtaining historical component parameters of each component in the device to be tested; Based on the historical component parameters, determining whether each of the components in the device to be tested is in a repaired state and / or an abnormality occurs during the test process; The components that have been repaired and / or have abnormalities during the test are determined as the candidate components to be evaluated.

10. A component detection device, characterized in that: The device comprises: A testing module, configured to perform at least two functional tests on a candidate to-be-evaluated component in the device to be tested when a test event for the device to be tested is triggered; A first determination module is configured to determine the candidate to-be-evaluated component that has passed at least two of the functional tests as a target to-be-evaluated component; A second determination module is configured to determine a current indicator parameter corresponding to the target component to be evaluated based on retest data obtained by performing at least two functional tests on the target component to be evaluated; The current index parameter is related to the current stability and consistency of the target component to be evaluated.

11. An electronic device, characterized in that: include: processor; a memory for storing processor-executable instructions; Wherein, the processor is configured to: implement the steps in the component detection method according to any one of claims 1 to 9 when executing the executable command. 12 . A non-transitory computer-readable storage medium, when instructions in the storage medium are executed by a processor of an electronic device, the steps in the component detection method according to any one of claims 1 to 9 are implemented.

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