Processing intelligent evaluation method and system based on mobile phone connector

Abstract

The invention discloses an intelligent processing evaluation method and system based on a mobile phone connector. For a target batch of mobile phone connectors, test schemes under K temperature conditions are set, temperature control and operation parameters are recorded, data fitting and multi-dimensional parameter evaluation are carried out, and an operation state equation is established. And adopting a Bayesian optimization algorithm to obtain a first temperature control optimization parameter in local optimal and global optimal search. A test period is divided into a plurality of time periods, and correlation time periods in which temperature control parameters and operation parameter result values are significantly correlated are screened out through linear change evaluation and Pearson's correlation coefficient analysis. And extracting temperature control data corresponding to the associated time periods, performing effective time node screening in combination with the first temperature control optimization parameters, and formulating an optimization test evaluation scheme in combination with the first temperature control optimization parameters and the effective time nodes, so that efficient test and optimization evaluation of the connector are realized, and the quality and reliability of the mobile phone connector are improved.

Description

Technical Field

[0001] The present invention relates to the field of connector processing analysis, and more specifically, to a processing intelligent evaluation method and system based on a mobile phone connector. Background Art

[0002] As a key component in electronic devices, the quality and performance of mobile phone connectors directly affect the overall performance of the equipment. Traditional evaluation methods mostly rely on manual inspection and experimental verification, which is not only time-consuming and labor-intensive, but also difficult to fully and accurately reflect the actual working status of the connector. In addition, the traditional processing flow of mobile phone connectors often lacks effective processing tests, and the processing tests are often based on simple connection tests, without considering the impact of the basic temperature of the mobile phone or the temperature changes of the mobile phone itself, resulting in unsatisfactory processing test results and difficulty in accurately controlling the quality control of connector processing. Therefore, there is an urgent need for an intelligent processing evaluation method for mobile phone connectors. Summary of the invention

[0003] The present invention overcomes the defects of the prior art and proposes a processing intelligent evaluation method and system based on a mobile phone connector.

[0004] The first aspect of the present invention provides a processing intelligent evaluation method based on a mobile phone connector, comprising: Based on a target batch of mobile phone connectors, set a test plan under K temperature conditions, record the temperature control and operating parameters in each test plan, and obtain the temperature control parameters and the operating parameters of the mobile phone connector; During the test cycle, the temperature control parameters and the operating parameters are fitted with data in the time dimension, the operating parameters are evaluated in multiple dimensions, the operating state equation is set, and based on the Bayesian optimization algorithm, the temperature control parameters and the operating parameters are used as decision variables, and the operating state equation is used as the objective function to perform local optimal and global optimal searches to obtain the first temperature control optimization parameters; Based on the test cycle, multiple time periods are divided; Based on the time dimension, the temperature control parameters and operating parameters are evaluated for linear changes in the time dimension. The linear change evaluation of the operating parameters is based on the result value of the operating state equation. The Pearson correlation coefficient is used to analyze and calculate the correlation between the temperature control parameters and the result value in each time period. By judging the correlation coefficient, multiple time periods with correlation are screened out and marked as associated time periods. During the test cycle, the temperature control parameters corresponding to the associated time period are extracted to obtain associated temperature control data, the associated temperature control data is determined to be matched with the first temperature control optimization parameter, and the associated time period corresponding to the successfully matched data is marked as a valid time node; Through the first temperature control optimization parameter and the effective time node, an optimization test evaluation plan for the mobile phone connector is set.

[0005] In this scheme, the test scheme based on a target batch of mobile phone connectors is set under K temperature conditions, and temperature control and operating parameter records are performed in each test scheme to obtain temperature control parameters and operating parameters of the mobile phone connector, specifically: Based on a target batch of mobile phone connectors, a test plan is set under K temperature conditions, and the K temperature conditions are continuously changing temperatures with the same change range; In each test plan, the data transmission operation test of the connector is carried out based on the set temperature conditions, and the temperature control and operation parameters are recorded and integrated to obtain the temperature control parameters and the operation parameters of the mobile phone connector; The temperature control parameters include the temperature change value of the connector and the set temperature condition value; the operating parameters include the data transmission rate, data loss rate, and transmission power fluctuation value.

[0006] In this solution, during the test cycle, the temperature control parameters and the operating parameters are fitted with data in the time dimension, the operating parameters are evaluated in multiple dimensions, the operating state equation is set, and based on the Bayesian optimization algorithm, the temperature control parameters and the operating parameters are used as decision variables, and the operating state equation is used as the objective function to perform local optimal and global optimal searches to obtain the first temperature control optimization parameters, which are specifically: Set the test cycle, and based on the time dimension, perform data fitting on the temperature control parameters and the operating parameters in the time dimension to form a continuous change curve; Perform multi-dimensional parameter evaluation on the operating parameters, and perform linear fitting based on the three dimensions of transmission rate, data loss rate, and transmission power fluctuation value as independent variables. The dependent variable of the fitting equation is marked as the result value, and the fitting equation is used as the operating state equation; Based on the Bayesian optimization algorithm, the temperature control parameters and operating parameters are used as decision variables, the operating state equation is used as the objective function, and the objective function takes the minimization of the result value of the operating state equation as the optimization goal. The temperature control parameters and operating parameters are limited to the safe working parameter range as constraints, and local and global optimal searches are performed to generate the optimal decision variables based on the temperature control parameters. A first temperature control optimization parameter is set based on the optimal decision variable.

[0007] In this solution, based on the time dimension, the temperature control parameters and the operating parameters are evaluated for linear changes in the time dimension. The linear change evaluation of the operating parameters is evaluated based on the result value of the operating state equation. The correlation between the temperature control parameters and the result value in each time period is analyzed and calculated by the Pearson correlation coefficient. By judging the correlation coefficient, multiple time periods with correlation are screened out and marked as associated time periods, specifically: Based on the time dimension, the temperature control parameters and operating parameters are evaluated for linear changes in the time dimension. For the evaluation process of the operating parameters, the result value of the operating state equation is used for linear change analysis; In each time period, the same time variable is set, the linear change relationship between the temperature control parameters and the result value is analyzed, and the Pearson correlation coefficient between the two is calculated to obtain multiple correlation coefficients; It is determined whether the correlation coefficient is within a preset coefficient range. If so, it is determined that there is correlation, and multiple time periods with correlation are screened out and marked as associated time periods.

[0008] In this solution, during the test cycle, the temperature control parameters corresponding to the associated time period are extracted to obtain the associated temperature control data, and the associated temperature control data is judged to match the data with the first temperature control optimization parameter, and the associated time period corresponding to the successfully matched data is marked as a valid time node, specifically: Based on the test cycle, the temperature control parameters corresponding to the associated time period are extracted to obtain the associated temperature control data; Serialize the associated temperature control data to form a temperature control subsequence; Sequencing the first temperature control optimization parameter to obtain an optimized temperature control sequence; A temperature control subsequence is matched with the optimized temperature control sequence. Specifically, the data matching process is as follows: a sequence length D of a temperature control subsequence is calculated, a continuous sequence segment with a sequence length of D is intercepted from the optimized temperature control sequence, and marked as an intermediate comparison sequence. The difference between the intermediate comparison sequence and the values ​​corresponding to each sequence position in the temperature control subsequence is calculated, and the average difference is calculated based on the sequence length. If the average difference is less than the preset difference, it means a successful match, and the associated time period corresponding to the temperature control subsequence is marked as a valid time node; If an intermediate comparison sequence that meets the expected preset difference cannot be intercepted from the optimized temperature control sequence, it means that the data matching fails; Analyze the associated temperature control data corresponding to all time periods and filter out multiple valid time nodes.

[0009] In this solution, the intervals between each of the multiple time periods are consistent.

[0010] In this solution, the associated time period includes at least one.

[0011] In this solution, the optimization test evaluation scheme of the mobile phone connector is set by using the first temperature control optimization parameter and the effective time node, specifically: Based on the first temperature control optimization parameter, the basic test temperature control parameter is set, and for multiple valid time nodes, the temperature control change parameter is set to form an optimization test evaluation plan; Apply the optimized test evaluation scheme to the target batch of mobile phone connectors.

[0012] The second aspect of the present invention further provides a processing intelligent evaluation system based on a mobile phone connector, the system comprising: a memory, a processor, the memory comprising a processing intelligent evaluation program based on a mobile phone connector, the processing intelligent evaluation program based on a mobile phone connector being executed by the processor to implement the following steps: Based on a target batch of mobile phone connectors, set a test plan under K temperature conditions, record the temperature control and operating parameters in each test plan, and obtain the temperature control parameters and the operating parameters of the mobile phone connector; During the test cycle, the temperature control parameters and the operating parameters are fitted with data in the time dimension, the operating parameters are evaluated in multiple dimensions, the operating state equation is set, and based on the Bayesian optimization algorithm, the temperature control parameters and the operating parameters are used as decision variables, and the operating state equation is used as the objective function to perform local optimal and global optimal searches to obtain the first temperature control optimization parameters; Based on the test cycle, multiple time periods are divided; Based on the time dimension, the temperature control parameters and operating parameters are evaluated for linear changes in the time dimension. The linear change evaluation of the operating parameters is based on the result value of the operating state equation. The Pearson correlation coefficient is used to analyze and calculate the correlation between the temperature control parameters and the result value in each time period. By judging the correlation coefficient, multiple time periods with correlation are screened out and marked as associated time periods. During the test cycle, the temperature control parameters corresponding to the associated time period are extracted to obtain associated temperature control data, the associated temperature control data is determined to be matched with the first temperature control optimization parameter, and the associated time period corresponding to the successfully matched data is marked as a valid time node; Through the first temperature control optimization parameter and the effective time node, an optimization test evaluation plan for the mobile phone connector is set.

[0013] The third aspect of the present invention also provides a computer-readable storage medium, which includes a processing intelligence assessment program based on a mobile phone connector. When the processing intelligence assessment program based on a mobile phone connector is executed by a processor, the steps of the processing intelligence assessment method based on a mobile phone connector as described in any one of the above items are implemented.

[0014] The present invention discloses a processing intelligent evaluation method and system based on mobile phone connectors. For a target batch of mobile phone connectors, set a test scheme under K temperature conditions, record the temperature control and operating parameters, perform data fitting and multi-dimensional parameter evaluation, and establish an operating state equation. A Bayesian optimization algorithm is used to obtain the first temperature control optimization parameter in the local optimal and global optimal search. The test cycle is divided into multiple time periods, and the associated time periods in which the temperature control parameters and the operating parameter result values ​​are significantly correlated are screened out through linear change evaluation and Pearson correlation coefficient analysis. The temperature control data corresponding to these associated time periods are extracted, and the effective time nodes are screened in combination with the first temperature control optimization parameter. In combination with the first temperature control optimization parameter and the effective time node, an optimized test evaluation scheme is formulated to achieve efficient testing and optimization evaluation of the connector, and improve the quality and reliability of the mobile phone connector. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 A flow chart of a processing intelligent evaluation method based on a mobile phone connector of the present invention is shown; Figure 2 The flowchart of obtaining the temperature control parameters and the operating parameters of the present invention is shown; Figure 3 A block diagram of a processing intelligent evaluation system based on a mobile phone connector of the present invention is shown. DETAILED DESCRIPTION

[0016] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0017] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0018] Figure 1 A flow chart of a processing intelligent evaluation method based on a mobile phone connector of the present invention is shown.

[0019] like Figure 1 As shown, the first aspect of the present invention provides a processing intelligent evaluation method based on a mobile phone connector, comprising: S102, based on a target batch of mobile phone connectors, setting a test scheme under K temperature conditions, performing temperature control and operating parameter recording in each test scheme, and obtaining temperature control parameters and operating parameters of the mobile phone connector; S104, during the test period, performing data fitting on the temperature control parameters and the operating parameters in the time dimension, performing multi-dimensional parameter evaluation on the operating parameters, setting the operating state equation, and performing local optimal and global optimal searches based on the Bayesian optimization algorithm with the temperature control parameters and the operating parameters as decision variables and the operating state equation as the objective function to obtain the first temperature control optimization parameter; S106, dividing a plurality of time periods based on the test cycle; S108, based on the time dimension, the temperature control parameters and the operating parameters are evaluated for linear changes in the time dimension. The linear change evaluation of the operating parameters is evaluated based on the result value of the operating state equation. The correlation between the temperature control parameters and the result value in each time period is analyzed and calculated by the Pearson correlation coefficient. By judging the correlation coefficient, multiple time periods with correlation are screened out and marked as associated time periods. S110, within the test cycle, extracting the temperature control parameters corresponding to the associated time period to obtain associated temperature control data, determining the associated temperature control data and performing data matching with the first temperature control optimization parameter, and marking the associated time period corresponding to the successfully matched data as a valid time node; S112, setting an optimization test evaluation plan for the mobile phone connector through the first temperature control optimization parameter and the effective time node.

[0020] It should be noted that traditional mobile phone connectors often lack effective processing tests, and processing tests are often based on simple connection tests, without considering the impact of the basic temperature of the mobile phone or the temperature change of the mobile phone itself, resulting in unsatisfactory processing test results, and connector processing quality control is difficult to accurately control, and lacks consideration of the impact of temperature control and data operation transmission, resulting in difficulty in achieving accurate testing and reasonable evaluation and screening of product processing. The embodiments of the present invention can effectively solve the above problems.

[0021] Figure 2 The flowchart of obtaining the temperature control parameters and the operating parameters of the present invention is shown; According to an embodiment of the present invention, the mobile phone connector based on a target batch is set to test under K temperature conditions, and temperature control and operating parameter records are performed in each test scheme to obtain temperature control parameters and operating parameters of the mobile phone connector, specifically: S202, based on a target batch of mobile phone connectors, setting a test plan under K temperature conditions, the K temperature conditions are continuously changing temperatures, and the change intervals are consistent; S204, in each test scheme, performing a data transmission operation test of the connector based on the set temperature conditions, recording and integrating the temperature control and operation parameters, and obtaining the temperature control parameters and the operation parameters of the mobile phone connector; S206, the temperature control parameters include the temperature change value of the connector and the set temperature condition value, and the operation parameters include the data transmission rate, the data loss rate, and the transmission power fluctuation value.

[0022] It should be noted that the K temperature conditions are continuously changing temperatures, and the change interval is consistent, that is, K temperatures are set from low to high, and the temperature change in the interval is consistent. It is specifically used to simulate the operation of the connector at different temperatures. For example, K is 3, corresponding to 3 conditions: 10°C, 20°C, and 30°C.

[0023] According to an embodiment of the present invention, in the test cycle, data fitting is performed on the temperature control parameters and the operating parameters in the time dimension, multi-dimensional parameter evaluation is performed on the operating parameters, and the operating state equation is set. Based on the Bayesian optimization algorithm, the temperature control parameters and the operating parameters are used as decision variables, and the operating state equation is used as the objective function to perform local optimal and global optimal searches to obtain the first temperature control optimization parameters, which are specifically: Set the test cycle, and based on the time dimension, perform data fitting on the temperature control parameters and the operating parameters in the time dimension to form a continuous change curve; Perform multi-dimensional parameter evaluation on the operating parameters, and perform linear fitting based on the three dimensions of transmission rate, data loss rate, and transmission power fluctuation value as independent variables. The dependent variable of the fitting equation is marked as the result value, and the fitting equation is used as the operating state equation; Based on the Bayesian optimization algorithm, the temperature control parameters and operating parameters are used as decision variables, the operating state equation is used as the objective function, and the objective function takes the minimization of the result value of the operating state equation as the optimization goal. The temperature control parameters and operating parameters are limited to the safe working parameter range as constraints, and local and global optimal searches are performed to generate the optimal decision variables based on the temperature control parameters. A first temperature control optimization parameter is set based on the optimal decision variable.

[0024] It should be noted that the data fitting of the temperature control parameters and the operating parameters in the time dimension can fit the discontinuous data under multiple temperature controls and generate continuous data for analysis, improve the accuracy of data analysis, and achieve effective prediction of data. The operating state equation is a state equation that is fitted based on multiple dimensions in the operating parameters. The result value (dependent variable) of the equation is used to reflect the final performance state value. The performance state is effectively evaluated by fitting the state equation, and the temperature control parameters are subsequently optimized. In addition, the final performance state value is set as the minimum optimization in the objective function optimal analysis, that is, the worst performance parameter performance is used as the objective function result, so as to screen out the temperature control change parameters that can effectively test the connector in a harsh temperature environment, and set an effective test plan or scheme, so as to efficiently evaluate the processing performance and optimize the processing.

[0025] The optimal decision variables include various temperature control parameters.

[0026] According to an embodiment of the present invention, based on the time dimension, the temperature control parameters and the operating parameters are evaluated for linear changes in the time dimension, and the linear change evaluation of the operating parameters is evaluated based on the result value of the operating state equation. The correlation between the temperature control parameters and the result value in each time period is analyzed and calculated by the Pearson correlation coefficient. By judging the correlation coefficient, multiple time periods with correlation are screened out and marked as associated time periods, specifically: Based on the time dimension, the temperature control parameters and operating parameters are evaluated for linear changes in the time dimension. For the evaluation process of the operating parameters, the result value of the operating state equation is used for linear change analysis; In each time period, the same time variable is set, the linear change relationship between the temperature control parameters and the result value is analyzed, and the Pearson correlation coefficient between the two is calculated to obtain multiple correlation coefficients; It is determined whether the correlation coefficient is within a preset coefficient range. If so, it is determined that there is correlation, and multiple time periods with correlation are screened out and marked as associated time periods.

[0027] It should be noted that the traditional technology has poor analysis capabilities for the correlation between connector performance and temperature control, and is often based on manual inspection and analysis and manual warning, which is not very practical and difficult to achieve an automated testing process. However, the embodiment of the present invention can set a correlation evaluation process based on correlation analysis to effectively solve the above problems.

[0028] According to an embodiment of the present invention, during the test cycle, the temperature control parameters corresponding to the associated time period are extracted to obtain associated temperature control data, the associated temperature control data is determined to be matched with the first temperature control optimization parameter, and the associated time period corresponding to the successfully matched data is marked as a valid time node, specifically: Based on the test cycle, the temperature control parameters corresponding to the associated time period are extracted to obtain the associated temperature control data; Serialize the associated temperature control data to form a temperature control subsequence; Sequencing the first temperature control optimization parameter to obtain an optimized temperature control sequence; A temperature control subsequence is matched with the optimized temperature control sequence. Specifically, the data matching process is as follows: a sequence length D of a temperature control subsequence is calculated, a continuous sequence segment with a sequence length of D is intercepted from the optimized temperature control sequence, and marked as an intermediate comparison sequence. The difference between the intermediate comparison sequence and the values ​​corresponding to each sequence position in the temperature control subsequence is calculated, and the average difference is calculated based on the sequence length. If the average difference is less than the preset difference, it means a successful match, and the associated time period corresponding to the temperature control subsequence is marked as a valid time node; If an intermediate comparison sequence that meets the expected preset difference cannot be intercepted from the optimized temperature control sequence, it means that the data matching fails; Analyze the associated temperature control data corresponding to all time periods and filter out multiple valid time nodes.

[0029] It should be noted that the test evaluation of traditional connectors lacks correlation analysis of performance temperature control, and lacks efficient temperature control and efficient test solution optimization for different time nodes of the overall test solution. Therefore, it is difficult to achieve precise test optimization.

[0030] In the present invention, serialization is set for data matching, and an efficient test time node can be analyzed based on the first temperature control optimization parameter, and through the time node, it is applied to the existing test plan, so as to set the temperature control change time node for the target batch of connectors, and then applied to the test plan in the future to achieve efficient and accurate test evaluation, and quickly evaluate and screen the processing quality of connector products. Each time period corresponds to an associated temperature control data, and also corresponds to a temperature control subsequence.

[0031] According to the embodiment of the present invention, the interval between each time period in the multiple time periods is consistent.

[0032] According to an embodiment of the present invention, the associated time period includes at least one.

[0033] It should be noted that the associated time period generally includes multiple ones.

[0034] According to an embodiment of the present invention, the optimization test evaluation scheme of the mobile phone connector is set by using the first temperature control optimization parameter and the effective time node, specifically: Based on the first temperature control optimization parameter, the basic test temperature control parameter is set, and for multiple valid time nodes, the temperature control change parameter is set to form an optimization test evaluation plan; Apply the optimized test evaluation scheme to the target batch of mobile phone connectors.

[0035] It should be noted that the first temperature control optimization parameter includes multiple temperature control parameters, and for the test temperature control change time period, the temperature control change application needs to be performed within the effective time node to generate a test evaluation plan for the target batch.

[0036] According to an embodiment of the present invention, the valid time node further includes: Based on the time dimension, the temperature control parameters and operating parameters are evaluated for linear changes in the time dimension; For each time period, the linear change rate, the maximum parameter value and the minimum parameter value of the temperature control parameter are calculated, and a temperature control feature vector is generated based on the linear change rate, the maximum parameter value and the minimum parameter value; According to multiple time periods, the generated multiple temperature control feature vectors are used as clustering inputs for density clustering grouping to form multiple temperature control feature groups; Calculating the linear change rate, maximum parameter value and minimum parameter value of the first temperature control optimization parameter and generating an optimization feature vector; For a temperature control feature group, cyclically select a temperature control feature vector in the group and perform vector distance calculation and similarity analysis with the optimized feature vector. If the distance value is lower than a preset distance, the temperature control feature group is marked as a valid feature group. Based on the valid feature group, the corresponding time period is marked as a valid time node.

[0037] It should be noted that the density clustering may adopt a clustering algorithm such as DBSCAN. In the vector distance calculation and similarity analysis, the standard Euclidean distance is used for calculation, and the distance value reflects the vector similarity.

[0038] In the present invention, intercepting and matching to select effective time nodes (or effective time periods) is suitable for a solution optimization process with a short test cycle and low requirements on the computing power of the test platform. Optionally, for test solutions with short time periods or large-scale batch test tasks, clustering analysis of temperature control data can improve the rapid generation of test optimization solutions and improve the applicability of optimization solutions.

[0039] According to an embodiment of the present invention, it also includes: Based on the test evaluation scheme applied to the target batch of mobile phone connectors, for each valid time node, the real-time temperature control parameters and real-time operating parameters of the connectors are recorded; The real-time temperature control parameters are serialized to form real-time sequence segments, and the real-time sequence segments are modeled and predicted based on the LSTM network model to obtain predicted temperature control sequence data; For real-time operation parameters, the corresponding result values ​​are calculated using the operation state equation, and the result values ​​are serialized and combined with the LSTM network model for data domain measurement to generate prediction result data; Compare the predicted temperature control sequence data and the predicted result data with the test expected sequence to generate a deviation rate; Based on multiple effective time nodes, multiple deviation rates are generated for test evaluation, processing early warning and processing quality control.

[0040] It should be noted that, through the above scheme, the actual test connector temperature data of the relevant nodes is used for prediction, forming multiple prediction data, realizing test warning and processing quality evaluation, and at the same time, it can realize fast and accurate analysis of test results and efficient product screening. The test expected sequence is the test result sequence under ideal conditions, including the ideal numerical range of the result value corresponding to the temperature control sequence and the running state equation.

[0041] Figure 3 A block diagram of a processing intelligent evaluation system based on a mobile phone connector of the present invention is shown.

[0042] The second aspect of the present invention further provides a processing intelligent evaluation system 3 based on a mobile phone connector, the system comprising: a memory 31, a processor 32, the memory 31 comprising a processing intelligent evaluation program based on a mobile phone connector, the processing intelligent evaluation program based on a mobile phone connector when executed by the processor 32 implements the following steps: Based on a target batch of mobile phone connectors, set a test plan under K temperature conditions, record the temperature control and operating parameters in each test plan, and obtain the temperature control parameters and the operating parameters of the mobile phone connector; During the test cycle, the temperature control parameters and the operating parameters are fitted with data in the time dimension, the operating parameters are evaluated in multiple dimensions, the operating state equation is set, and based on the Bayesian optimization algorithm, the temperature control parameters and the operating parameters are used as decision variables, and the operating state equation is used as the objective function to perform local optimal and global optimal searches to obtain the first temperature control optimization parameters; Based on the test cycle, multiple time periods are divided; Based on the time dimension, the temperature control parameters and operating parameters are evaluated for linear changes in the time dimension. The linear change evaluation of the operating parameters is based on the result value of the operating state equation. The Pearson correlation coefficient is used to analyze and calculate the correlation between the temperature control parameters and the result value in each time period. By judging the correlation coefficient, multiple time periods with correlation are screened out and marked as associated time periods. During the test cycle, the temperature control parameters corresponding to the associated time period are extracted to obtain associated temperature control data, the associated temperature control data is determined to be matched with the first temperature control optimization parameter, and the associated time period corresponding to the successfully matched data is marked as a valid time node; Through the first temperature control optimization parameter and the effective time node, an optimization test evaluation plan for the mobile phone connector is set.

[0043] It should be noted that traditional mobile phone connectors often lack effective processing tests, and processing tests are often based on simple connection tests, without considering the impact of the basic temperature of the mobile phone or the temperature change of the mobile phone itself, resulting in unsatisfactory processing test results, and connector processing quality control is difficult to accurately control, and lacks consideration of the impact of temperature control and data operation transmission, resulting in difficulty in achieving accurate testing and reasonable evaluation and screening of product processing. The embodiments of the present invention can effectively solve the above problems.

[0044] According to an embodiment of the present invention, the mobile phone connector based on a target batch is set to test under K temperature conditions, and temperature control and operating parameter records are performed in each test scheme to obtain temperature control parameters and operating parameters of the mobile phone connector, specifically: Based on a target batch of mobile phone connectors, a test plan is set under K temperature conditions, and the K temperature conditions are continuously changing temperatures with the same change range; In each test plan, the data transmission operation test of the connector is carried out based on the set temperature conditions, and the temperature control and operation parameters are recorded and integrated to obtain the temperature control parameters and the operation parameters of the mobile phone connector; The temperature control parameters include the temperature change value of the connector and the set temperature condition value; the operating parameters include the data transmission rate, data loss rate, and transmission power fluctuation value.

[0045] It should be noted that the K temperature conditions are continuously changing temperatures, and the change interval is consistent, that is, K temperatures are set from low to high, and the temperature change in the interval is consistent. It is specifically used to simulate the operation of the connector at different temperatures. For example, K is 3, corresponding to 3 conditions: 10°C, 20°C, and 30°C.

[0046] According to an embodiment of the present invention, in the test cycle, data fitting is performed on the temperature control parameters and the operating parameters in the time dimension, multi-dimensional parameter evaluation is performed on the operating parameters, and the operating state equation is set. Based on the Bayesian optimization algorithm, the temperature control parameters and the operating parameters are used as decision variables, and the operating state equation is used as the objective function to perform local optimal and global optimal searches to obtain the first temperature control optimization parameters, which are specifically: Set the test cycle, and based on the time dimension, perform data fitting on the temperature control parameters and the operating parameters in the time dimension to form a continuous change curve; Perform multi-dimensional parameter evaluation on the operating parameters, and perform linear fitting based on the three dimensions of transmission rate, data loss rate, and transmission power fluctuation value as independent variables. The dependent variable of the fitting equation is marked as the result value, and the fitting equation is used as the operating state equation; Based on the Bayesian optimization algorithm, the temperature control parameters and operating parameters are used as decision variables, the operating state equation is used as the objective function, and the objective function takes the minimization of the result value of the operating state equation as the optimization goal. The temperature control parameters and operating parameters are limited to the safe working parameter range as constraints, and local and global optimal searches are performed to generate the optimal decision variables based on the temperature control parameters. A first temperature control optimization parameter is set based on the optimal decision variable.

[0047] It should be noted that the data fitting of the temperature control parameters and the operating parameters in the time dimension can fit the discontinuous data under multiple temperature controls and generate continuous data for analysis, improve the accuracy of data analysis, and achieve effective prediction of data. The operating state equation is a state equation that is fitted based on multiple dimensions in the operating parameters. The result value (dependent variable) of the equation is used to reflect the final performance state value. The performance state is effectively evaluated by fitting the state equation, and the temperature control parameters are subsequently optimized. In addition, the final performance state value is set as the minimum optimization in the objective function optimal analysis, that is, the worst performance parameter performance is used as the objective function result, so as to screen out the temperature control change parameters that can effectively test the connector in a harsh temperature environment, and set an effective test plan or scheme, so as to efficiently evaluate the processing performance and optimize the processing.

[0048] The optimal decision variables include various temperature control parameters.

[0049] According to an embodiment of the present invention, based on the time dimension, the temperature control parameters and the operating parameters are evaluated for linear changes in the time dimension, and the linear change evaluation of the operating parameters is evaluated based on the result value of the operating state equation. The correlation between the temperature control parameters and the result value in each time period is analyzed and calculated by the Pearson correlation coefficient. By judging the correlation coefficient, multiple time periods with correlation are screened out and marked as associated time periods, specifically: Based on the time dimension, the temperature control parameters and operating parameters are evaluated for linear changes in the time dimension. For the evaluation process of the operating parameters, the result value of the operating state equation is used for linear change analysis; In each time period, the same time variable is set, the linear change relationship between the temperature control parameters and the result value is analyzed, and the Pearson correlation coefficient between the two is calculated to obtain multiple correlation coefficients; It is determined whether the correlation coefficient is within a preset coefficient range. If so, it is determined that there is correlation, and multiple time periods with correlation are screened out and marked as associated time periods.

[0050] It should be noted that the traditional technology has poor analysis capabilities for the correlation between connector performance and temperature control, and is often based on manual inspection and analysis and manual warning, which is not very practical and difficult to achieve an automated testing process. However, the embodiment of the present invention can set a correlation evaluation process based on correlation analysis to effectively solve the above problems.

[0051] According to an embodiment of the present invention, during the test cycle, the temperature control parameters corresponding to the associated time period are extracted to obtain associated temperature control data, the associated temperature control data is determined to be matched with the first temperature control optimization parameter, and the associated time period corresponding to the successfully matched data is marked as a valid time node, specifically: Based on the test cycle, the temperature control parameters corresponding to the associated time period are extracted to obtain the associated temperature control data; Serialize the associated temperature control data to form a temperature control subsequence; Sequencing the first temperature control optimization parameter to obtain an optimized temperature control sequence; A temperature control subsequence is matched with the optimized temperature control sequence. Specifically, the data matching process is as follows: a sequence length D of a temperature control subsequence is calculated, a continuous sequence segment with a sequence length of D is intercepted from the optimized temperature control sequence, and marked as an intermediate comparison sequence. The difference between the intermediate comparison sequence and the values ​​corresponding to each sequence position in the temperature control subsequence is calculated, and the average difference is calculated based on the sequence length. If the average difference is less than the preset difference, it means a successful match, and the associated time period corresponding to the temperature control subsequence is marked as a valid time node; If an intermediate comparison sequence that meets the expected preset difference cannot be intercepted from the optimized temperature control sequence, it means that the data matching fails; Analyze the associated temperature control data corresponding to all time periods and filter out multiple valid time nodes.

[0052] It should be noted that the test evaluation of traditional connectors lacks correlation analysis of performance temperature control, and lacks efficient temperature control and efficient test solution optimization for different time nodes of the overall test solution. Therefore, it is difficult to achieve precise test optimization.

[0053] In the present invention, serialization is set for data matching, and an efficient test time node can be analyzed based on the first temperature control optimization parameter, and through the time node, it is applied to the existing test plan, so as to set the temperature control change time node for the target batch of connectors, and then applied to the test plan in the future to achieve efficient and accurate test evaluation, and quickly evaluate and screen the processing quality of connector products. Each time period corresponds to an associated temperature control data, and also corresponds to a temperature control subsequence.

[0054] According to the embodiment of the present invention, the interval between each time period in the multiple time periods is consistent.

[0055] According to an embodiment of the present invention, the associated time period includes at least one.

[0056] It should be noted that the associated time period generally includes multiple ones.

[0057] According to an embodiment of the present invention, the optimization test evaluation scheme of the mobile phone connector is set by using the first temperature control optimization parameter and the effective time node, specifically: Based on the first temperature control optimization parameter, the basic test temperature control parameter is set, and for multiple valid time nodes, the temperature control change parameter is set to form an optimization test evaluation plan; Apply the optimized test evaluation scheme to the target batch of mobile phone connectors.

[0058] It should be noted that the first temperature control optimization parameter includes multiple temperature control parameters, and for the test temperature control change time period, the temperature control change application needs to be performed within the effective time node to generate a test evaluation plan for the target batch.

[0059] The third aspect of the present invention also provides a computer-readable storage medium, which includes a processing intelligence assessment program based on a mobile phone connector. When the processing intelligence assessment program based on a mobile phone connector is executed by a processor, the steps of the processing intelligence assessment method based on a mobile phone connector as described in any one of the above items are implemented.

[0060] The present invention discloses a processing intelligent evaluation method and system based on mobile phone connectors. For a target batch of mobile phone connectors, set a test scheme under K temperature conditions, record the temperature control and operating parameters, perform data fitting and multi-dimensional parameter evaluation, and establish an operating state equation. A Bayesian optimization algorithm is used to obtain the first temperature control optimization parameter in the local optimal and global optimal search. The test cycle is divided into multiple time periods, and the associated time periods in which the temperature control parameters and the operating parameter result values ​​are significantly correlated are screened out through linear change evaluation and Pearson correlation coefficient analysis. The temperature control data corresponding to these associated time periods are extracted, and the effective time nodes are screened in combination with the first temperature control optimization parameter. In combination with the first temperature control optimization parameter and the effective time node, an optimized test evaluation scheme is formulated to achieve efficient testing and optimization evaluation of the connector, and improve the quality and reliability of the mobile phone connector.

[0061] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0062] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0063] In addition, all functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as a unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0064] A person of ordinary skill in the art can understand that: all or part of the steps of implementing the above method embodiment can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above method embodiment; and the aforementioned storage medium includes: a mobile storage device, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and other media that can store program codes.

[0065] Alternatively, if the above-mentioned integrated unit of the present invention is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present invention can be essentially or partly reflected in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, magnetic disks or optical disks.

[0066] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A processing intelligent evaluation method based on mobile phone connectors, characterized in that: include: Based on a target batch of mobile phone connectors, set a test plan under K temperature conditions, record the temperature control and operating parameters in each test plan, and obtain the temperature control parameters and the operating parameters of the mobile phone connector; During the test cycle, the temperature control parameters and the operating parameters are fitted with data in the time dimension, the operating parameters are evaluated in multiple dimensions, the operating state equation is set, and based on the Bayesian optimization algorithm, the temperature control parameters and the operating parameters are used as decision variables, and the operating state equation is used as the objective function to perform local optimal and global optimal searches to obtain the first temperature control optimization parameters; Based on the test cycle, multiple time periods are divided; Based on the time dimension, the temperature control parameters and operating parameters are evaluated for linear changes in the time dimension. The linear change evaluation of the operating parameters is based on the result value of the operating state equation. The Pearson correlation coefficient is used to analyze and calculate the correlation between the temperature control parameters and the result value in each time period. By judging the correlation coefficient, multiple time periods with correlation are screened out and marked as associated time periods. During the test cycle, the temperature control parameters corresponding to the associated time period are extracted to obtain associated temperature control data, the associated temperature control data is determined to be matched with the first temperature control optimization parameter, and the associated time period corresponding to the successfully matched data is marked as a valid time node; Through the first temperature control optimization parameter and the effective time node, an optimization test evaluation plan for the mobile phone connector is set.

2. According to claim 1, a processing intelligent evaluation method based on a mobile phone connector is characterized in that: The test scheme based on a target batch of mobile phone connectors is set under K temperature conditions, and temperature control and operating parameter records are performed in each test scheme to obtain temperature control parameters and operating parameters of the mobile phone connector, specifically: Based on a target batch of mobile phone connectors, a test plan is set under K temperature conditions, and the K temperature conditions are continuously changing temperatures with the same change range; In each test plan, the data transmission operation test of the connector is carried out based on the set temperature conditions, and the temperature control and operation parameters are recorded and integrated to obtain the temperature control parameters and the operation parameters of the mobile phone connector; The temperature control parameters include the temperature change value of the connector and the set temperature condition value; the operating parameters include the data transmission rate, data loss rate, and transmission power fluctuation value.

3. According to claim 2, a processing intelligent evaluation method based on a mobile phone connector is characterized in that: In the test cycle, the temperature control parameters and the operating parameters are fitted with data in the time dimension, the operating parameters are evaluated in multiple dimensions, the operating state equation is set, and based on the Bayesian optimization algorithm, the temperature control parameters and the operating parameters are used as decision variables, and the operating state equation is used as the objective function to perform local optimal and global optimal searches to obtain the first temperature control optimization parameters, which are specifically: Set the test cycle, and based on the time dimension, perform data fitting on the temperature control parameters and the operating parameters in the time dimension to form a continuous change curve; Perform multi-dimensional parameter evaluation on the operating parameters, and perform linear fitting based on the three dimensions of transmission rate, data loss rate, and transmission power fluctuation value as independent variables. The dependent variable of the fitting equation is marked as the result value, and the fitting equation is used as the operating state equation; Based on the Bayesian optimization algorithm, the temperature control parameters and operating parameters are used as decision variables, the operating state equation is used as the objective function, and the objective function takes the minimization of the result value of the operating state equation as the optimization goal. The temperature control parameters and operating parameters are limited to the safe working parameter range as constraints, and local and global optimal searches are performed to generate the optimal decision variables based on the temperature control parameters. A first temperature control optimization parameter is set based on the optimal decision variable.

4. According to claim 1, a processing intelligent evaluation method based on a mobile phone connector is characterized in that: Based on the time dimension, the temperature control parameters and the operating parameters are evaluated for linear changes in the time dimension. The linear change evaluation of the operating parameters is evaluated based on the result value of the operating state equation. The correlation between the temperature control parameters and the result value in each time period is analyzed and calculated by the Pearson correlation coefficient. By judging the correlation coefficient, multiple time periods with correlation are screened out and marked as associated time periods, specifically: Based on the time dimension, the temperature control parameters and operating parameters are evaluated for linear changes in the time dimension. For the evaluation process of the operating parameters, the result value of the operating state equation is used for linear change analysis; In each time period, the same time variable is set, the linear change relationship between the temperature control parameters and the result value is analyzed, and the Pearson correlation coefficient between the two is calculated to obtain multiple correlation coefficients; It is determined whether the correlation coefficient is within a preset coefficient range. If so, it is determined that there is correlation, and multiple time periods with correlation are screened out and marked as associated time periods.

5. The processing intelligent evaluation method based on mobile phone connector according to claim 1 is characterized in that: In the test cycle, the temperature control parameters corresponding to the associated time period are extracted to obtain the associated temperature control data, the associated temperature control data is judged to match the data with the first temperature control optimization parameter, and the associated time period corresponding to the successfully matched data is marked as a valid time node, specifically: Based on the test cycle, the temperature control parameters corresponding to the associated time period are extracted to obtain the associated temperature control data; Serialize the associated temperature control data to form a temperature control subsequence; Sequencing the first temperature control optimization parameter to obtain an optimized temperature control sequence; A temperature control subsequence is matched with the optimized temperature control sequence. Specifically, the data matching process is as follows: a sequence length D of a temperature control subsequence is calculated, a continuous sequence segment with a sequence length of D is intercepted from the optimized temperature control sequence, and marked as an intermediate comparison sequence. The difference between the intermediate comparison sequence and the values ​​corresponding to each sequence position in the temperature control subsequence is calculated, and the average difference is calculated based on the sequence length. If the average difference is less than the preset difference, it means a successful match, and the associated time period corresponding to the temperature control subsequence is marked as a valid time node; If an intermediate comparison sequence that meets the expected preset difference cannot be intercepted from the optimized temperature control sequence, it means that the data matching fails; Analyze the associated temperature control data corresponding to all time periods and filter out multiple valid time nodes.

6. The processing intelligent evaluation method based on mobile phone connector according to claim 1 is characterized in that: Among the multiple time periods, each time period has a consistent interval.

7. The processing intelligent evaluation method based on mobile phone connector according to claim 1 is characterized in that: The associated time period includes at least one.

8. The processing intelligent evaluation method based on mobile phone connector according to claim 1 is characterized in that: The optimization test evaluation scheme of the mobile phone connector is set by using the first temperature control optimization parameter and the effective time node, specifically: Based on the first temperature control optimization parameter, the basic test temperature control parameter is set, and for multiple valid time nodes, the temperature control change parameter is set to form an optimization test evaluation plan; Apply the optimized test evaluation scheme to the target batch of mobile phone connectors.

9. A processing intelligent evaluation system based on mobile phone connectors, characterized in that: The system includes: a memory and a processor, wherein the memory includes a processing intelligent evaluation program based on a mobile phone connector, and when the processing intelligent evaluation program based on a mobile phone connector is executed by the processor, the following steps are implemented: Based on a target batch of mobile phone connectors, set a test plan under K temperature conditions, record the temperature control and operating parameters in each test plan, and obtain the temperature control parameters and the operating parameters of the mobile phone connector; During the test cycle, the temperature control parameters and the operating parameters are fitted with data in the time dimension, the operating parameters are evaluated in multiple dimensions, the operating state equation is set, and based on the Bayesian optimization algorithm, the temperature control parameters and the operating parameters are used as decision variables, and the operating state equation is used as the objective function to perform local optimal and global optimal searches to obtain the first temperature control optimization parameters; Based on the test cycle, multiple time periods are divided; Based on the time dimension, the temperature control parameters and operating parameters are evaluated for linear changes in the time dimension. The linear change evaluation of the operating parameters is based on the result value of the operating state equation. The Pearson correlation coefficient is used to analyze and calculate the correlation between the temperature control parameters and the result value in each time period. By judging the correlation coefficient, multiple time periods with correlation are screened out and marked as associated time periods. During the test cycle, the temperature control parameters corresponding to the associated time period are extracted to obtain associated temperature control data, the associated temperature control data is determined to be matched with the first temperature control optimization parameter, and the associated time period corresponding to the successfully matched data is marked as a valid time node; Through the first temperature control optimization parameter and the effective time node, an optimization test evaluation plan for the mobile phone connector is set.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a processing intelligence assessment program based on a mobile phone connector. When the processing intelligence assessment program based on a mobile phone connector is executed by a processor, the steps of the processing intelligence assessment method based on a mobile phone connector as described in any one of claims 1 to 8 are implemented.

Images