Orthogonal test method, device, electronic device and computer readable storage medium

Abstract

The present application proposes an orthogonal test method, device, electronic device and computer-readable storage medium, the method comprising: obtaining multiple performance indicators, multiple factors and corresponding levels of each factor of the product to be tested, and selecting an orthogonal table with blank columns from a preset orthogonal table library; obtaining the index values ​​of each performance indicator of the product to be tested at different times after the preset accelerated test, so as to obtain a test data set; obtaining a change curve of the preset key parameter change rate at different times according to the test data set; determining the performance stability parameter according to the change curve and the preset algorithm; determining the influence of each factor on each performance indicator according to the orthogonal table with blank columns and the performance stability parameter, and screening out the performance indicator with a greater degree of influence as the target performance indicator; obtaining a comprehensive indicator according to the target performance indicator to determine the optimal level value of each factor. The present application simplifies the number of orthogonal tests, which is of great significance for the design of product reliability tests.

Description

Technical Field

[0001] The present application relates to the technical field of experimental design and data processing, and in particular to an orthogonal experimental method, device, electronic device and computer-readable storage medium. Background Art

[0002] In product testing, product manufacturing parameters can generally be represented by the level values ​​of each manufacturing factor, and in most cases they are determined by the corresponding multiple performances and their reliability in the service process. In real life, product manufacturing parameters correspond to multiple factors, and the levels related to the factors are often numerous. If a comprehensive test of single performance is conducted on each level parameter of each factor, the number of tests is already extremely large. If multiple performances of the product need to be considered, the number of tests will increase by multiples of the number of performances. Furthermore, if the stability of product performance needs to be considered, the number of tests will increase by multiples of the number of test time points on the original basis. Therefore, determining the optimal level values ​​of multiple time, multiple indicators, multiple factors, and multiple levels is a very complex problem.

[0003] For multi-index, multi-factor, and multi-level tests, some studies have used orthogonal test designs with "neat comparability and balanced dispersion" to reduce the number of multi-factor and multi-level tests. On this basis, some studies have proposed two methods, the comprehensive balance method and the comprehensive scoring method, to comprehensively consider multiple indicators and obtain the optimal level value under each factor. However, the current orthogonal test design does not take into account the stability of product performance during service, and cannot guarantee the reliability of the product during long-term operation, which is precisely the key to determining the service life of the product. Summary of the invention

[0004] In view of this, the present application proposes an orthogonal test method, device, electronic device and computer-readable storage medium, which expands the traditional multi-indicator, multi-factor and multi-level orthogonal test to multiple time scales, establishes a time-space related orthogonal test, and takes the dimensionality reduction idea as the core to determine the optimal level value from the multi-dimensional orthogonal test, so as to solve the complex problem of determining the optimal level value in multiple factors that need to consider multiple indicators and their stability, greatly simplifies the number of tests, and is of great significance for product reliability test design.

[0005] In a first aspect, an embodiment of the present application provides an orthogonal test method, comprising:

[0006] Obtaining multiple performance indicators, multiple factors and levels corresponding to each of the factors of the product to be tested, and selecting an orthogonal table with blank columns from a preset orthogonal table library according to the multiple factors and the levels corresponding to each of the factors;

[0007] Obtaining the index values ​​of the performance indexes of the product to be tested at different times after the product to be tested passes the preset accelerated test, so as to obtain a test data set;

[0008] Determining the change rate of the preset key parameter at different times according to the test data set to obtain a change curve corresponding to the change rate;

[0009] Determine the performance stability parameter according to the change curve and the preset algorithm;

[0010] Determine the influence degree of each factor on each performance index according to the orthogonal table with blank columns and the performance stability parameter, and select the performance index with the largest influence degree of each factor as the target performance index;

[0011] Performing weighted calculation on the target performance index to obtain a comprehensive index;

[0012] The optimal level value of each factor is determined according to the comprehensive index.

[0013] In one embodiment, the change rate of the preset key parameters at different times is determined based on the test data set to obtain a change curve corresponding to the change rate, including: taking the indicator value of each performance indicator at the initial moment as the standard, setting the indicator value change rate at the initial moment to 0, calculating the indicator value change rate of each performance indicator at the different times after the initial moment, and determining the corresponding change curve based on the indicator value change rate.

[0014] In one embodiment, determining the optimal level value of each of the factors based on the comprehensive index includes: calculating the k value and range of the comprehensive index in an orthogonal table containing multiple factors and the levels corresponding to each of the factors, so as to determine the optimal level value of each of the factors.

[0015] In one embodiment, the change rate of the preset key parameter at different times is determined according to the test data set to obtain the change curve corresponding to the change rate, including: calculating the k value of each factor at each level corresponding to the single performance indicator, and taking the k value at the initial moment as the standard, setting the k value change rate at the initial moment to 0, so as to calculate the k value change rate at different times after the initial moment, and determining the corresponding change curve according to the k value change rate.

[0016] In one embodiment, determining the optimal level value of each of the factors according to the comprehensive indicators includes: determining the optimal level value of each of the factors according to the smallest comprehensive indicator among the comprehensive indicators.

[0017] In one embodiment, determining the performance stability parameter corresponding to each performance indicator according to the change curve and a preset algorithm includes: calculating the area enclosed by the change curve and the time axis at different times, and obtaining the performance stability parameter through a normalization algorithm.

[0018] In one embodiment, the method of determining the degree of influence of each of the factors on each of the performance indicators based on the orthogonal table with blank columns and the performance stability parameter, and selecting the performance indicators that are more influenced by each of the factors as target performance indicators, includes: using the orthogonal table with blank columns and taking the performance stability parameter as an indicator to calculate the range of the performance stability parameter corresponding to each of the performance indicators under each of the factors under a single performance indicator and the range of the performance stability parameter corresponding to each of the performance indicators under the blank column; comparing the range of the performance stability parameter corresponding to each of the performance indicators under each of the factors and the range of the performance stability parameter corresponding to each of the performance indicators under the blank column, determining the degree of influence of each of the factors on each of the performance indicators, and selecting the performance indicators that are more influenced by each of the factors as target performance indicators.

[0019] In a second aspect, an embodiment of the present application provides an orthogonal test device, comprising: an orthogonal table acquisition module, used to obtain multiple performance indicators, multiple factors and the levels corresponding to each of the factors of the product to be tested, and select an orthogonal table with blank columns from a preset orthogonal table library according to the multiple factors and the levels corresponding to each of the factors; a test data acquisition module, used to obtain the index value of each of the performance indicators of the product to be tested at different times after the preset accelerated test, so as to obtain a test data set; a change curve acquisition module, used to determine the change rate of the preset key parameters at different times according to the test data set, so as to obtain the change curve corresponding to the change rate; a stability parameter calculation module, used to determine the performance stability parameter according to the change curve and a preset algorithm; a performance indicator screening module, used to determine the influence of each of the factors on each of the performance indicators according to the orthogonal table with blank columns and the performance stability parameter, and screen out the performance indicators with a greater influence of each of the factors as target performance indicators; a comprehensive indicator calculation module, used to perform weighted operation on the target performance indicator to obtain a comprehensive indicator; an optimal level value determination module, used to determine the optimal level value of each of the factors according to the comprehensive indicator.

[0020] In a third aspect, an embodiment of the present application provides an electronic device, comprising a processor and a memory, wherein the memory is used to store instructions, and the processor is used to call the instructions in the memory so that the electronic device executes the orthogonal test method described in the first aspect.

[0021] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions. When the computer instructions are executed on an electronic device, the electronic device executes the orthogonal test method as described in the first aspect.

[0022] The orthogonal test method, device, electronic device and computer-readable storage medium provided in the embodiments of the present application expand the traditional multi-indicator, multi-factor and multi-level orthogonal test to multiple time scales, establish a time-space related orthogonal test, and use the dimensionality reduction idea as the core to determine the optimal level value from the multi-dimensional orthogonal test to solve the complex problem of determining the optimal level value in multiple factors that need to consider multiple indicators and their stability, which greatly simplifies the number of tests and is of great significance for product reliability test design. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 Schematic diagram of the steps of an orthogonal test method according to an embodiment of the present application.

[0024] Figure 2 Schematic diagram of the steps of an orthogonal test method according to an embodiment of the present application.

[0025] Figure 3 Schematic diagram of the steps of an orthogonal test method according to an embodiment of the present application.

[0026] Figure 4 Schematic diagram of functional modules of an orthogonal test device according to an embodiment of the present application.

[0027] Figure 5 It is a schematic diagram of the structure of an electronic device according to an embodiment of the present application.

[0028] Main component symbols

[0029] Orthogonal test device 10

[0030] Orthogonal table acquisition module 11

[0031] Test data acquisition module 12

[0032] Change curve acquisition module 13

[0033] Stability parameter calculation module 14

[0034] Performance index screening module 15

[0035] Comprehensive indicator calculation module 16

[0036] Optimal level value determination module 17

[0037] Electronic devices 20

[0038] Processor 21

[0039] Memory 22

[0040] The following specific implementation methods will further illustrate the present application in conjunction with the above-mentioned drawings. DETAILED DESCRIPTION

[0041] The technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments.

[0042] It should be noted that, in the embodiments of the present application, "at least one" refers to one or more, and "more" refers to two or more. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art in the present application. The terms used in the specification of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application.

[0043] It should be noted that, in the embodiments of the present application, words such as "first" and "second" are only used for the purpose of distinguishing descriptions, and cannot be understood as indicating or implying relative importance, nor can they be understood as indicating or implying order. Features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a concrete way.

[0044] To further illustrate the implementation manner of the present application, the embodiments of the present application are described in detail below by taking the silicone rubber used in external insulation as the product to be tested.

[0045] See also Figure 1 , is a schematic diagram of the step flow of the orthogonal test method provided in one embodiment of the present application.

[0046] Specifically, the orthogonal test method of this embodiment may include:

[0047] S100, obtaining multiple performance indicators of silicone rubber, multiple factors and levels corresponding to each factor, and selecting an orthogonal table with blank columns from a preset orthogonal table library according to the multiple factors and the levels corresponding to each factor.

[0048] Specifically, silicone rubber for external insulation plays the role of mechanical support and electrical insulation, and mechanical properties such as hardness, tensile strength, tear strength and electrical properties such as volume resistivity, breakdown field strength, dielectric loss tangent value, and dielectric constant are quite important. Therefore, hardness, tensile strength, tear strength, volume resistivity, breakdown field strength, dielectric loss tangent value, and dielectric constant are determined as performance indicators.

[0049] The vulcanization conditions of silicone rubber are mainly controlled by three factors (temperature, time, and pressure). The vulcanization temperature of silicone rubber is generally between 160°C and 190°C, the vulcanization time is usually between 10min and 20min, and the vulcanization pressure is generally between 8Mpa and 12Mpa. Therefore, 60°C, 170°C, and 180°C are selected as the three levels of the vulcanization temperature factor, 10min, 15min, and 20min are selected as the three levels of the vulcanization time factor, and 8MPa, 10MPa, and 12MPa are selected as the three levels of the vulcanization pressure factor. Therefore, the three-factor three-level orthogonal experiment L9 (3 4 ) as the vulcanization scheme, as shown in Table 1.

[0050] Table 1 Based on three-factor three-level orthogonal test L9(3 4 ) of different sample vulcanization schemes

[0051]

[0052]

[0053] S200, obtaining index values ​​of various performance indexes of the silicone rubber at different times after the silicone rubber passes a preset accelerated test, so as to obtain a test data set.

[0054] Specifically, silicone rubber for external insulation needs to operate outdoors for a long time and is affected by ultraviolet radiation and ages. Therefore, the ultraviolet aging accelerated experiment is selected as the preset accelerated experiment. Taking the standard 1000h ultraviolet aging as an example, 0h, 500h, and 1000h are selected as the test time of the performance indicators in each orthogonal table, and the ultraviolet aging accelerated experiment is carried out to test the indicator values ​​of each sample with different aging time, and complete the data collection of multi-time, multi-indicator, multi-factor, and multi-level orthogonal experiments, as shown in Table 2.

[0055] Table 2 Multi-time, multi-index, multi-factor, multi-level orthogonal test table

[0056]

[0057]

[0058] S300, determining the change rate of the preset key parameter at different times according to the test data set to obtain a change curve corresponding to the change rate.

[0059] Specifically, the preset key parameter may be an indicator value, for example, Figure 2 The orthogonal test method shown in FIG. 1 is based on the idea of ​​reducing the time dimension of the indicator. It can also be the k value of each level under a single performance indicator. For example, Figure 3 The orthogonal experimental method shown is based on the idea of ​​dimensionality reduction of the k-value time dimension.

[0060] S400, determining a performance stability parameter according to the change curve and a preset algorithm.

[0061] Specifically, the area enclosed by the change curve and the time axis at different times is calculated, and the performance stability parameter is obtained through a normalization algorithm.

[0062] S500, determining the influence of each factor on each performance indicator according to the orthogonal table with blank columns and the performance stability parameter, and selecting the performance indicator with the largest influence of each factor as the target performance indicator.

[0063] Specifically, first, using an orthogonal table with blank columns, taking the performance stability parameter as an indicator, the range of the performance stability parameter corresponding to each performance indicator under each factor under a single performance indicator and the range of the performance stability parameter corresponding to each performance indicator under a blank column are calculated. Then, the range of the performance stability parameter corresponding to each performance indicator under each factor and the range of the performance stability parameter corresponding to each performance indicator under a blank column are compared to determine the degree of influence of each factor on each performance indicator, and screen out the performance indicators that are most affected by each factor.

[0064] S600, performing weighted calculation on the target performance index to obtain a comprehensive index.

[0065] The screened target performance indicators are weighted according to their importance, and weighted operations are performed on them according to the weights of the target performance indicators to obtain the comprehensive indicators of silicone rubber.

[0066] S700, determining the optimal level value of each factor according to the comprehensive index.

[0067] Specifically, the preset key parameters in step S300 are selected differently, and the method of determining the optimal level value of each factor is also different.

[0068] Further integration Figure 2 As shown in the figure, the orthogonal test method with the idea of ​​reducing the time dimension of indicators as the core can include:

[0069] S10, obtaining multiple performance indicators of silicone rubber, multiple factors and the levels corresponding to each factor, and selecting an orthogonal table with blank columns from a preset orthogonal table library according to the multiple factors and the levels corresponding to each factor.

[0070] Specifically, in combination with the details of step S100 in the above embodiment, a three-factor three-level orthogonal experiment L9 (3 4 ) as the vulcanization scheme, as shown in Table 1 of the above embodiment.

[0071] S11, obtaining index values ​​of various performance indexes of the silicone rubber at different aging times after the accelerated aging test, so as to obtain a test data set.

[0072] Specifically, in combination with the detailed contents shown in step S200 of the above embodiment, the ultraviolet aging accelerated experiment is selected as the preset accelerated experiment to complete the data collection of the multi-time, multi-index, multi-factor, and multi-level orthogonal experiment, as shown in Table 2 of the above embodiment.

[0073] S12, taking the index value of each performance index at the initial moment as the standard, setting the index value change rate at the initial moment to 0, calculating the index value change rate of each performance index at different aging times after the initial moment, and determining the corresponding change curve according to the index value change rate.

[0074] Specifically, the index value of each performance index at the initial moment is used as the standard, and the change rate at the initial moment is set to 0. For example, the hardness value of sample 1 at the initial moment is 63, and the change rate of the hardness value at 500h is (65-63) / 63=0.03175. Similarly, an orthogonal test table of the index value change rate of samples at multiple times can be obtained, as shown in Table 3, and the change curve of the index value change rate can be determined according to the index value change rate.

[0075] Table 3 Orthogonal test table of index value change rate of samples at multiple times

[0076]

[0077] S13, determining the performance stability parameters corresponding to each performance indicator according to the change curve and the preset algorithm.

[0078] Specifically, the area enclosed by the change curve of the index value change rate and the time axis of different aging times is calculated as the performance stability parameter, as shown in Table 4.

[0079] Table 4 Orthogonal test table of performance stability parameters of samples at multiple times

[0080]

[0081] S14, performance stability parameter of each sample under normalized single performance index.

[0082] Specifically, the performance stability parameters of each sample under the normalized single performance index are shown in Table 5.

[0083] Table 5 Performance stability parameter normalization table

[0084]

[0085]

[0086] S15, using an orthogonal table containing blank columns and taking the normalized performance stability parameter as an indicator, calculate the range of each factor under a single performance indicator and the range of the blank column, compare the values ​​of the two, determine the degree of influence of each factor on the performance indicator, and select the performance indicator with a greater degree of influence as the target performance indicator.

[0087] Specifically, as shown in Table 6, the influence of each factor on the target performance index is calculated, where italics indicate factors that have a significant influence on a certain performance index. Taking the blank column range as the benchmark, it is found that the sulfidation factor has a more significant influence on hardness, volume resistivity, breakdown field strength, and dielectric constant, that is, hardness, volume resistivity, breakdown field strength, and dielectric constant are the target performance indicators.

[0088] Table 6 Influence of vulcanization factors on performance indicators

[0089]

[0090] S16, determining the weight of the target performance indicator according to the importance of the screened target performance indicator.

[0091] Specifically, the target performance indicators screened are hardness, volume resistivity, breakdown field strength, and dielectric constant. Among them, hardness is more important to the service of insulators, while volume resistivity, breakdown field strength, and dielectric constant are less important to the service of insulators. Therefore, the hardness is assigned a weight of 0.7, and the other three performance indicators are each assigned a weight of 0.1.

[0092] S17, performing weighted calculation on the target performance index to obtain a comprehensive index of each sample.

[0093] Specifically, weighted calculations were performed on the screened target performance indicators of hardness, volume resistivity, breakdown field strength, and dielectric constant to obtain comprehensive indicators of each sample, as shown in Table 7.

[0094] Table 7 Comprehensive index calculation table

[0095]

[0096]

[0097] S18, calculating the k value and the range of the comprehensive index in an orthogonal table containing multiple factors and the levels corresponding to each factor, so as to determine the optimal level value of each factor.

[0098] Specifically, the lower the comprehensive index, the more stable it is and the better the aging resistance. Temperature and time have a significant impact on the performance index. From Table 8, it can be seen that when the temperature is 170°C and the time is 15 minutes, the performance reaches the best. The range of pressure is lower than the blank column, indicating that it has no significant impact on the comprehensive index, so the optimal level of pressure is no longer important.

[0099] Table 8 Optimal level values ​​of each factor

[0100] temperature time pressure blank Level 1 0.132916 0.10397 0.116481 0.106288 Level 2 0.099761 0.095344 0.110118 0.103132 Level 3 0.100656 0.134019 0.106735 0.123914 Very bad 0.099465 0.116027 0.029237 0.062346

[0101] In this embodiment, for the time dimension reduction of the indicator, the time change rate of the single performance indicator corresponding to the single sample and the area of ​​the time axis of different aging times are calculated, and the dimension reduction in the time dimension is formed to form the performance stability parameter under the single performance indicator. Then, after weighted operation, the performance indicators with significant influence are further reduced in dimension to propose a comprehensive indicator. On this basis, the optimal level value of each factor is determined using the traditional orthogonal table.

[0102] Further integration Figure 3 As shown in the figure, the orthogonal test method based on the idea of ​​k-value time dimension reduction can include:

[0103] S20, obtaining multiple performance indicators of silicone rubber, multiple factors and the levels corresponding to each factor, and selecting an orthogonal table with blank columns from a preset orthogonal table library according to the multiple factors and the levels corresponding to each factor.

[0104] Specifically, in combination with the details of step S100 in the above embodiment, a three-factor three-level orthogonal experiment L9 (3 4 ) as the vulcanization scheme, as shown in Table 1 of the above embodiment.

[0105] S21, obtaining the index values ​​of various performance indexes of the silicone rubber at different aging times after the accelerated aging test, so as to obtain a test data set.

[0106] Specifically, in combination with the detailed contents shown in step S200 of the above embodiment, the ultraviolet aging accelerated experiment is selected as the preset accelerated experiment to complete the data collection of the multi-time, multi-index, multi-factor, and multi-level orthogonal experiment, as shown in Table 2 of the above embodiment.

[0107] S22, calculate the k value of each factor at each corresponding level under a single performance indicator.

[0108] Specifically, the traditional orthogonal table is used to calculate the k value of each level under the single performance index, as shown in Table 9.

[0109] Table 9 k value table for each level

[0110]

[0111]

[0112]

[0113] S23, taking the k value at the initial moment as a standard, setting the k value change rate at the initial moment to 0, calculating the k value change rate at different aging times after the initial moment, and determining the corresponding change curve according to the k value change rate.

[0114] Specifically, taking the k value at the initial moment as the standard, the k value change rate at the initial moment is set to 0, the k value change rate of the subsequent aging time is calculated, as shown in Table 10, and the change curve of the k value change rate is determined according to the k value change rate.

[0115] Table 10 Change rate of k value at each level

[0116]

[0117]

[0118] S24, determining performance stability parameters according to the change curve and a preset algorithm.

[0119] Specifically, the area enclosed by the change curve of the k value change rate and the time axis of different aging times are calculated, and the area corresponding to each level is normalized to obtain the performance stability parameters, as shown in Table 11.

[0120] Table 11 Performance stability parameters of each level

[0121]

[0122]

[0123] S25, determining the influence of each factor on each performance indicator according to the orthogonal table with blank columns and the performance stability parameter, and selecting the performance indicator with the largest influence of each factor as the target performance indicator.

[0124] Specifically, the range of the performance stability parameters of each factor and the blank column under a single performance index is calculated, and the numerical values ​​of the two are compared to determine the degree of influence of each factor on the performance index, and the performance index that is significantly affected is selected as the target performance index, as shown in Table 12, where italics indicate factors that have a significant impact on a certain performance index. Therefore, hardness, volume resistivity, breakdown field strength, and dielectric constant are selected as target performance indicators.

[0125] Table 12 Influence of vulcanization factors on indicators

[0126] temperature time pressure Blank Column hardness 0.088 0.180 0.088 0.052 Tensile Strength 0.165 0.298 0.316 0.535 Tear strength 0.056 0.019 0.075 0.189 Volume resistivity 0.295 0.113 0.161 0.193 Breakdown field strength 0.749 0.288 0.341 0.463 Dielectric constant 0.556 0.328 0.165 0.353 Dielectric loss 0.435 0.410 0.402 0.618

[0127] S26, determining the weight of the target performance indicator according to the importance of the target performance indicator.

[0128] Specifically, the target performance indicators after screening are hardness, volume resistivity, breakdown field strength, and dielectric constant. Among them, hardness is more important to the service of insulators, while volume resistivity, breakdown field strength, and dielectric constant are less important to the service of insulators. Therefore, the hardness is assigned a weight of 0.7, and the other three performance indicators are each assigned a weight of 0.1.

[0129] S27, performing weighted calculation on the target performance index to obtain comprehensive indexes at each level.

[0130] The screened target performance indicators hardness, volume resistivity, breakdown field strength, and dielectric constant are weighted and calculated to obtain comprehensive indicators at each level, as shown in Table 13.

[0131] Table 13 Comprehensive index calculation table

[0132]

[0133] S28, determining the optimal level value of each factor according to the smallest comprehensive index among the comprehensive indicators.

[0134] Specifically, it can be seen from Table 13 that the performance is optimal when the temperature is 170°C, the time is 15 min, and the pressure is 12 MPa.

[0135] In this embodiment, for the k-value time dimension reduction, the k-value is first calculated using a traditional orthogonal table, and the k-value change rate and the area surrounded by the time axis of different aging times are calculated to reduce the dimension in the time dimension to form the performance stability parameters at each level. After weighted calculation, the performance indicators with significant impact are further reduced in dimension, and a comprehensive indicator is proposed to directly determine the optimal level value of each factor.

[0136] Further integration Figure 4As shown, an orthogonal test device 10 provided by an embodiment of the present application includes: an orthogonal table acquisition module 11, which is used to obtain multiple performance indicators, multiple factors and the corresponding levels of each factor of the product to be tested, and select an orthogonal table with blank columns from a preset orthogonal table library according to the multiple factors and the corresponding levels of each factor; a test data acquisition module 12, which is used to obtain the index values ​​of each performance indicator of the product to be tested at different times after the preset accelerated test, so as to obtain a test data set; a change curve acquisition module 13, which is used to determine the change rate of the preset key parameter at different times according to the test data set, so as to obtain a change curve corresponding to the change rate; a stability parameter calculation module 14, which is used to determine the performance stability parameter according to the change curve and a preset algorithm; a performance indicator screening module 15, which is used to determine the influence of each factor on each performance indicator according to the orthogonal table with blank columns and the performance stability parameter, and screen out the performance indicator with a greater influence of each factor as the target performance indicator; a comprehensive indicator calculation module 16, which is used to perform weighted operation on the target performance indicator to obtain a comprehensive indicator; an optimal level value determination module 17, which is used to determine the optimal level value of each factor according to the comprehensive indicator.

[0137] See also Figure 5 , Figure 5 This is a diagram of the architecture of an electronic device 20 provided in an embodiment of the present application.

[0138] Specifically, the electronic device 20 includes a processor 21 and a memory 22. The memory 22 is used to store computer instructions, and the processor 21 is used to call the computer instructions in the memory 22 so that the electronic device 20 executes the steps of the orthogonal test method in the above embodiment.

[0139] Exemplarily, the computer instruction may be divided into one or more modules / units, one or more modules / units are stored in the memory 22 and executed by the processor 21. One or more modules / units may be a series of computer instruction segments that can perform specific functions, and the instruction segments are used to describe the execution process of the computer instruction in the electronic device 20. For example, it may be divided into Figure 4 The orthogonal table acquisition module 11, the test data acquisition module 12, the change curve acquisition module 13, the stability parameter calculation module 14, the performance index screening module 15, the comprehensive index calculation module 16, and the optimal level value determination module 17 are shown.

[0140] The electronic device 20 may be a computing device such as a desktop computer, a notebook, a PDA, an industrial computer, a tablet computer, a server, etc. Those skilled in the art will appreciate that the schematic diagram is merely an example of the electronic device 20 and does not constitute a limitation on the electronic device 20. The electronic device 20 may include more or fewer components than shown in the figure, or may combine certain components, or different components. For example, the electronic device 20 may also include input and output devices, network access devices, buses, etc.

[0141] The processor 21 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor, a single-chip microcomputer, or the processor 21 may also be any conventional processor, etc.

[0142] The memory 22 can be used to store computer instructions and / or modules / units. The processor 21 implements various functions of the electronic device 20 by running or executing the computer instructions and / or modules / units stored in the memory 22 and calling the data stored in the memory 22. The memory 22 can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area can store data (such as audio data) created according to the use of the electronic device 20, etc. In addition, the memory 22 can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (FlashCard), at least one disk storage device, a flash memory device, or other non-volatile solid-state storage devices.

[0143] The present application also discloses a computer-readable storage medium, which stores computer instructions. When the computer instructions are executed on the electronic device 20, the electronic device 20 executes the steps of the orthogonal test method in the above embodiment. The storage medium can be a U disk, a mobile hard disk, a ROM, a RAM, a magnetic disk, or an optical disk, etc., which can store program codes.

[0144] The orthogonal test method, system, electronic device and computer-readable storage medium provided in the embodiments of the present application comprehensively consider multiple indicators and their stability to determine the optimal level value among multiple factors. The multi-indicator, multi-factor and multi-level orthogonal test is extended to multiple time scales to establish a time-space related orthogonal test. With the idea of ​​dimensionality reduction as the core, the optimal level value is determined from the multi-dimensional orthogonal test.

[0145] Those skilled in the art should recognize that the above embodiments are only used to illustrate the present application and are not intended to be limiting of the present application. As long as they are within the spirit and scope of the present application, appropriate changes and modifications to the above embodiments are within the scope of protection claimed in the present application.

Claims

1. An orthogonal test method, characterized in that: include: Obtaining multiple performance indicators, multiple factors and levels corresponding to each of the factors of the product to be tested, and selecting an orthogonal table with blank columns from a preset orthogonal table library according to the multiple factors and the levels corresponding to each of the factors; Obtaining the index values ​​of the performance indexes of the product to be tested at different times after the product to be tested passes the preset accelerated test, so as to obtain a test data set; Determining the change rate of the preset key parameter at different times according to the test data set to obtain a change curve corresponding to the change rate; Determine the performance stability parameter according to the change curve and the preset algorithm; Determine the degree of influence of each of the factors on each of the performance indicators according to the orthogonal table with blank columns and the performance stability parameter, and select the performance indicators that are greatly influenced by each of the factors as target performance indicators, including: using the orthogonal table with blank columns and taking the performance stability parameter as an indicator, calculating the range of the performance stability parameter corresponding to each of the performance indicators under each of the factors under a single performance indicator and the range of the performance stability parameter corresponding to each of the performance indicators under the blank column; comparing the range of the performance stability parameter corresponding to each of the performance indicators under each of the factors and the range of the performance stability parameter corresponding to each of the performance indicators under the blank column, determine the degree of influence of each of the factors on each of the performance indicators, and select the performance indicators that are greatly influenced by each of the factors as target performance indicators; Performing weighted calculation on the target performance index to obtain a comprehensive index; The optimal level value of each factor is determined according to the comprehensive index.

2. The orthogonal test method according to claim 1, characterized in that: The method of determining the change rate of the preset key parameters at different times based on the test data set to obtain the change curve corresponding to the change rate includes: taking the indicator value of each performance indicator at the initial moment as the standard, setting the indicator value change rate at the initial moment to 0, calculating the indicator value change rate of each performance indicator at the different times after the initial moment, and determining the corresponding change curve according to the indicator value change rate.

3. The orthogonal test method according to claim 2, characterized in that: Determining the optimal level value of each factor according to the comprehensive index includes: calculating the k value and range of the comprehensive index in an orthogonal table containing multiple factors and the levels corresponding to each factor, so as to determine the optimal level value of each factor.

4. The orthogonal test method according to claim 1, characterized in that: The method of determining the change rate of the preset key parameter at different times according to the test data set to obtain the change curve corresponding to the change rate includes: calculating the k value of each factor at the corresponding level under the single performance indicator, and taking the k value at the initial moment as the standard, setting the k value change rate at the initial moment to 0, calculating the k value change rate at different times after the initial moment, and determining the corresponding change curve according to the k value change rate.

5. The orthogonal test method according to claim 4, characterized in that: Determining the optimal level value of each of the factors according to the comprehensive indicators includes: determining the optimal level value of each of the factors according to the smallest comprehensive indicator among the comprehensive indicators.

6. The orthogonal test method according to claim 1, characterized in that: Determining the performance stability parameter corresponding to each of the performance indicators according to the change curve and a preset algorithm includes: calculating the area enclosed by the change curve and the time axis at different times, and obtaining the performance stability parameter through a normalization algorithm.

7. An orthogonal test device, characterized in that: include: An orthogonal table acquisition module is used to acquire multiple performance indicators, multiple factors and the levels corresponding to each of the factors of the product to be tested, and select an orthogonal table with blank columns from a preset orthogonal table library according to the multiple factors and the levels corresponding to each of the factors; A test data acquisition module, used to obtain the index value of each performance index at different times after the product to be tested passes the preset accelerated test, so as to obtain a test data set; A change curve acquisition module, used to determine the change rate of the preset key parameter at different times according to the test data set, so as to obtain a change curve corresponding to the change rate; A stability parameter calculation module, used to determine the performance stability parameter according to the change curve and a preset algorithm; A performance index screening module, used for determining the influence degree of each of the factors on each of the performance indicators according to the orthogonal table with blank columns and the performance stability parameter, and screening out the performance indicators with a greater influence degree of each of the factors as target performance indicators, including: using the orthogonal table with blank columns and taking the performance stability parameter as an indicator, calculating the range of the performance stability parameter corresponding to each of the performance indicators under each of the factors under a single performance indicator and the range of the performance stability parameter corresponding to each of the performance indicators under the blank column; comparing the range of the performance stability parameter corresponding to each of the performance indicators under each of the factors and the range of the performance stability parameter corresponding to each of the performance indicators under the blank column, determining the influence degree of each of the factors on each of the performance indicators, and screening out the performance indicators with a greater influence degree of each of the factors as target performance indicators; A comprehensive index calculation module, used to perform weighted calculation on the target performance index to obtain a comprehensive index; The optimal level value determination module is used to determine the optimal level value of each factor according to the comprehensive index.

8. An electronic device, characterized in that: The electronic device comprises a processor and a memory, wherein the memory is used to store instructions, and the processor is used to call the instructions in the memory, so that the electronic device executes the orthogonal test method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and when the computer instructions are executed on an electronic device, the electronic device executes the orthogonal test method according to any one of claims 1 to 6.

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