A method and system for constructing test profiles based on measured temperature data

Abstract

The present invention discloses a method and system for constructing a test profile based on measured temperature data. The method comprises the following steps: 1) obtaining measured temperature data of the product's environment over multiple cycles; 2) separating and reconstructing the temperature data to obtain a data periodic component and a data random component; 3) performing a single-cycle fatigue equivalent analysis on the data periodic component to obtain an equivalent value of a daily cycle temperature; performing fatigue damage calculation on the data random component to obtain a unit fatigue damage index and an equivalent cumulative damage index; 4) obtaining an equivalent low temperature and an equivalent high temperature based on the equivalent value of the daily cycle temperature; obtaining an equivalent number of cycles based on the unit fatigue damage index and the equivalent cumulative damage index; and finally, obtaining an equivalent temperature cycle profile within the measured temperature data cycle based on the equivalent number of cycles and the ratio of cold days to hot days. The present invention has the advantages of being simple to operate, ensuring test authenticity, and ensuring product reliability.

Description

Technical Field

[0001] The present invention mainly relates to the field of temperature test technology, and in particular to a test profile construction method and system based on measured temperature data. Background Art

[0002] The existing test conditions (temperature) are all from the standards and cannot truly reflect the environmental conditions of the product during actual use. Testing according to the test conditions in the standards cannot truly reflect the environmental adaptability and reliability of the product. Summary of the Invention

[0003] The technical problem to be solved by the present invention is: in response to the problems existing in the prior art, the present invention provides a method and system for constructing a test profile based on measured temperature data, which is simple to operate and ensures the authenticity and reliability of the test.

[0004] In order to solve the above technical problems, the technical solution proposed by the present invention is:

[0005] A method for constructing a test profile based on measured temperature data comprises the steps of:

[0006] 1) Obtain the measured temperature data of the product environment under multiple cycles;

[0007] 2) Separate and reconstruct the temperature data to obtain the periodic component and random component of the data;

[0008] 3) Performing single-cycle fatigue equivalent analysis and tolerance estimation on the data periodic component to obtain the equivalent value of the daily cycle temperature; performing tolerance estimation and fatigue damage calculation on the data random component to obtain the unit fatigue damage index and equivalent cumulative damage index;

[0009] 4) Based on the equivalent value of the daily cycle temperature, the equivalent low temperature and equivalent high temperature are obtained, where the equivalent low temperature and equivalent high temperature are the lowest and highest temperatures of the test section, and their difference is the temperature cycle amplitude of the test section; the equivalent number of cycles is obtained based on the unit fatigue damage index and the equivalent cumulative damage index; and the equivalent temperature cycle profile within the measured temperature data period is obtained based on the equivalent number of cycles and the ratio of cold days to hot days.

[0010] Preferably, after step 4), the method further includes step 5) of verifying the equivalence of the measured temperature data and the constructed equivalent temperature cycle profile.

[0011] Preferably, in step 5), the finite element simulation method is used for verification, and the specific process is: the solder joint is selected as the simulation object, the measured temperature data and the constructed equivalent temperature cycle profile are applied to the solder joint respectively, the creep amount of the solder joint is calculated, and by comparing the two calculation results, it is verified whether the measured data and the equivalent temperature cycle profile are equivalent.

[0012] Preferably, between step 1) and step 2), data preprocessing is also included to remove extreme stress and random interference signals.

[0013] Preferably, the process of removing the limit stress is:

[0014] Formula (1) is used to determine the limit stress, and then formula (2) is used to eliminate it; formula (1) and formula (2) are respectively:

[0015]

[0016]

[0017] Where T is the measured temperature; represents a day of the year, i = 1, 2, 3, ..., 365; j represents an hour of the day, j = 1, 2, 3, ..., 24.

[0018] Preferably, the sliding filter process is performed using formula (3) to remove random interference signals.

[0019]

[0020] Preferably, in step 3), the specific process of performing single-cycle fatigue equivalent analysis on the data period component is:

[0021] The logarithmic life of the product is linearly related to the inverse of the absolute temperature stress to which the product is subjected, namely:

[0022] lnθ=a+b / T (4)

[0023] Where: θ is a parameter that can characterize the lifespan; a and b are unknown constants, and T represents the absolute temperature;

[0024] dθ=e a+b / T dt (5)

[0025] By using formula (5) to perform life damage equivalence, the equivalent value of daily cycle temperature can be obtained:

[0026]

[0027] Where t equa is the equivalent total time, t equa =(t1+t2+...+t n ); T1, T2...T n Represents the absolute temperature value at each time of the day.

[0028] Preferably, in step 3), the process of performing tolerance estimation and fatigue damage calculation on the random component of the data to obtain the unit fatigue damage index and the equivalent cumulative damage index is:

[0029] Fatigue damage calculation is performed on the temperature change curve, the measured load history is simplified into several load cycles, and the temperature change history is equivalent to several temperature cycles with different amplitudes. There is a linear relationship between the logarithm of the strain amplitude and the logarithm of the number of fatigue load reversals. The linear cumulative damage hypothesis is used to analyze the cumulative fatigue damage of the product, and then the unit fatigue damage index is obtained based on the linear relationship and cumulative fatigue damage. Then, based on the fatigue damage principle, the equivalent cumulative damage index corresponding to the equivalent cyclic stress is obtained.

[0030] The present invention also discloses a test profile construction system based on measured temperature data, comprising:

[0031] The first program module is used to obtain the measured temperature data of the environment in which the product is located under multiple cycles;

[0032] The second program module is used to separate and reconstruct the temperature data to obtain a data periodic component and a data random component;

[0033] The third program module is configured to perform single-cycle fatigue equivalent analysis and tolerance estimation on the data periodic component to obtain an equivalent value of the daily cycle temperature; perform tolerance estimation and fatigue damage calculation on the data random component to obtain a unit fatigue damage index and an equivalent cumulative damage index;

[0034] The fourth program module is used to obtain the equivalent low temperature and equivalent high temperature based on the equivalent value of the daily cycle temperature, where the equivalent low temperature and equivalent high temperature are the lowest and highest temperatures of the test section, and their difference is the temperature cycle amplitude of the test section; the equivalent number of cycles is obtained based on the unit fatigue damage index and the equivalent cumulative damage index; and the equivalent temperature cycle profile within the measured temperature data period is obtained based on the equivalent number of cycles and the ratio of cold days to hot days.

[0035] The present invention further discloses a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the computer program executes the steps of the above-mentioned method for constructing a test profile based on measured temperature data.

[0036] The present invention also discloses a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the computer program is run by the processor, the steps of the test profile construction method based on measured temperature data are executed.

[0037] Compared with the prior art, the advantages of the present invention are:

[0038] The test profile construction method based on measured temperature data of the present invention can faithfully reflect the environmental conditions of the product during actual use by obtaining real-time temperature data of the product under the actual operating environment. The measured temperature data is decomposed and reconstructed into data periodic components and data random components to facilitate subsequent calculations. The temperature of small cycles is then equivalent to achieve simplification of two-dimensional data. The above-mentioned overall method is simple to operate and can ensure the authenticity and reliability of subsequent tests. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 The present invention is a flowchart of an embodiment of the method. DETAILED DESCRIPTION

[0040] The present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0041] like Figure 1 As shown, the method for constructing a test profile based on measured temperature data according to an embodiment of the present invention includes the following steps:

[0042] 1) Select an appropriate data sampling rate based on the actual application environment of the product to obtain the measured temperature data of the product environment under multiple cycles;

[0043] 2) Separate and reconstruct the temperature data to obtain the periodic component and random component of the data;

[0044] 3) Perform single-cycle fatigue equivalent analysis and tolerance estimation on the periodic components of the data to obtain the equivalent value of the daily cycle temperature; perform tolerance estimation and fatigue damage calculation on the random components of the data to obtain the unit fatigue damage index and equivalent cumulative damage index;

[0045] 4) Based on the equivalent value of the daily cycle temperature, the equivalent low temperature and equivalent high temperature are obtained, where the equivalent low temperature and equivalent high temperature are the lowest and highest temperatures of the test section, and their difference is the temperature cycle amplitude of the test section; the equivalent number of cycles is obtained based on the unit fatigue damage index and the equivalent cumulative damage index; and the equivalent temperature cycle profile within the measured temperature data period is obtained based on the equivalent number of cycles and the ratio of cold days to hot days;

[0046] 5) Verify the equivalence of the measured temperature data and the constructed equivalent temperature cycle profile.

[0047] The test profile construction method based on measured temperature data of the present invention can faithfully reflect the environmental conditions of the product during actual use by obtaining real-time temperature data of the product under the actual operating environment. The measured temperature data is decomposed and reconstructed into data periodic components and data random components to facilitate subsequent calculations. The temperature of small cycles is then equivalent to achieve simplification of two-dimensional data. The above-mentioned overall method is simple to operate and can ensure the authenticity and reliability of subsequent tests.

[0048] In one specific embodiment, in step 1), an appropriate data sampling rate is selected based on the actual application environment of the product to record the ambient temperature of the product. Data recording requires collecting data over multiple periods to facilitate statistical analysis. For example, a high-speed train runs from Beijing to Guangzhou daily, operating from 9:00 AM to 5:00 PM. Temperature data is affected by diurnal fluctuations and seasonal changes. Therefore, temperature data should be collected on a daily basis and a yearly basis. Therefore, the ambient temperature data of the high-speed train should be collected on a yearly basis, with temperature data collected for multiple years along the Beijing-Guangzhou high-speed train line.

[0049] In a specific embodiment, between step 1) and step 2), data preprocessing is also included. Specifically, for extreme weather caused by drastic climate changes, which leads to extreme environmental stress, the extreme stress history is relatively short, and its impact on product life is generally not considered. In this regard, formula (1) is used to determine the extreme stress, and then formula (2) is used to eliminate it; wherein formula (1) and formula (2) are respectively:

[0050]

[0051]

[0052] T represents the measured temperature; i represents a day of the year, i = 1, 2, 3, ..., 365; j represents an hour of the day, j = 1, 2, 3, ..., 24;

[0053] For random interference signals introduced during the measurement process due to measurement system errors or human factors, the sliding filter is processed using formula (3):

[0054]

[0055] By preprocessing the above data, extreme temperature conditions and random measurement interference are eliminated.

[0056] In a specific embodiment, in step 2), the measured data is decomposed and the periodic component of the data (periodic temperature variation) and the random component of the data (random temperature variation) are reconstructed by wavelet analysis algorithm or empirical mode decomposition (EMD) or support vector machine method.

[0057] In a specific embodiment, in step 3), the specific processing process of the data period component is:

[0058] a) Single cycle fatigue equivalent

[0059] The logarithmic life of the product is linearly related to the inverse of the absolute temperature stress to which the product is subjected, namely:

[0060] lnθ=a+b / T (4)

[0061] Where: θ is a parameter that can characterize the lifespan; a and b are unknown constants, and T represents the absolute temperature.

[0062] dθ=e a+b / T dt (5)

[0063] By using formula (5) to perform life damage equivalence, the equivalent value of daily cycle temperature can be obtained.

[0064]

[0065] Where t equa is the equivalent total time, t equa =(t1+t2+...+t n ).

[0066] Among them, T1, T2...T n They represent the absolute temperature values at different times of the day. For example, if one data point is collected every hour, there will be 24 absolute temperature data points in a day.

[0067] b) Statistical analysis of data

[0068] When analyzing data statistically, it is expected that the statistical estimator can well envelop more extreme values without completely enveloping the extreme values, which will lead to an overly large estimator. The tolerance estimation method is used to estimate the extreme stress conditions of the annual temperature extreme profile and the annual temperature cycle.

[0069] Assume that the measured temperature data obeys the normal distribution X~N(μ,σ 2 ), by calculation, the upper limit of the unilateral tolerance of the data with probability β under the confidence level γ is:

[0070]

[0071] X H Indicates the upper tolerance limit; represents the mean of the data subsample; S represents the standard deviation of the data subsample; N is the number of samples; f = N-1 represents the degrees of freedom; λ is the noncentrality; t(f,λ) represents the noncentral t distribution with given degrees of freedom f = N-1 and λ as the noncentrality.

[0072] In a specific embodiment, in step 3), the specific processing process of the random component of the data is:

[0073] a) Expand the random component according to the sampling unit time and apply tolerance statistics to obtain the tolerance estimation data of the random component;

[0074] b) Fatigue damage calculation is performed on the temperature change curve, simplifying the measured load history into several load cycles and equating the temperature change history to several temperature cycles with different amplitudes. Research on the mechanism of temperature cycle stress on product failure is still in the stage of understanding low-cycle fatigue damage. It can be assumed that there is a linear relationship between the logarithm of the strain amplitude and the logarithm of the number of fatigue load reversals, so the following formula is obtained:

[0075] SN B =C (8)

[0076] Where: S is the stress amplitude; N is the number of stress cycles; B and C are constants.

[0077] The cumulative fatigue damage of the product is analyzed using the linear cumulative damage hypothesis. Assume that the product is subjected to M alternating stresses with amplitudes of S and i The actual number of cycles for each stress is n i , the total cumulative damage is:

[0078]

[0079] Where N i The product is under cyclic stress S i The number of cycles required to reach failure under the action of force; D is a constant, generally taken as 1.0, 1.5, or 2.0.

[0080] From formula (8) and formula (9), the unit fatigue damage index can be obtained as:

[0081]

[0082] Let S e is the equivalent cyclic stress, according to the fatigue damage principle, and S e The corresponding equivalent cumulative damage index is:

[0083] D e =N p (S e / C) 1 / B (11)

[0084] Where N p is the equivalent number of cycles.

[0085] By performing the equivalence between the periodic component of the data and the random component of the data, the simplification of the two-dimensional data is achieved.

[0086] In a specific embodiment, in step 4), the specific process of constructing the equivalent temperature cycle profile (or temperature test profile) is as follows: the temperature of the annual temperature curve below a certain value is equivalent to a cold day, and the temperature above a certain value is equivalent to a hot day, and the equivalent average time and process time of the cold day and the hot day are obtained respectively; the equivalent low temperature and the equivalent high temperature are obtained using formula (6), and the equivalent low temperature and the equivalent high temperature are the lowest and highest temperatures of the test profile, and the difference between them is the test profile temperature cycle amplitude S e ;

[0087] The equivalent cycle number can be obtained using equations (10) and (11):

[0088]

[0089] The equivalent temperature cycle profile within the measured data period can be obtained by using the number of cycles and the ratio of cold days to hot days.

[0090] In one specific embodiment, in step 5), the verification process specifically includes: using finite element simulation to verify the equivalence of the measured temperature data and the constructed test profile. The verification uses a solder joint as the simulation object, applies the measured temperature data and the constructed test profile to the solder joint, and calculates the creep of the solder joint. By comparing the two calculation results, it can be verified that the measured data and the constructed test profile are equivalent.

[0091] The embodiment of the present invention further discloses a test profile construction system based on measured temperature data, comprising:

[0092] The first program module is used to obtain the measured temperature data of the environment in which the product is located under multiple cycles;

[0093] The second program module is used to separate and reconstruct the temperature data to obtain a data periodic component and a data random component;

[0094] The third program module is configured to perform single-cycle fatigue equivalent analysis and tolerance estimation on the data periodic component to obtain an equivalent value of the daily cycle temperature; perform tolerance estimation and fatigue damage calculation on the data random component to obtain a unit fatigue damage index and an equivalent cumulative damage index;

[0095] The fourth program module is used to obtain the equivalent low temperature and equivalent high temperature based on the equivalent value of the daily cycle temperature, where the equivalent low temperature and equivalent high temperature are the lowest and highest temperatures of the test section, and their difference is the temperature cycle amplitude of the test section; the equivalent number of cycles is obtained based on the unit fatigue damage index and the equivalent cumulative damage index; and the equivalent temperature cycle profile within the measured temperature data period is obtained based on the equivalent number of cycles and the ratio of cold days to hot days.

[0096] The system of the present invention corresponds to the above method and also has the advantages described in the above method.

[0097] The present invention further discloses a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the steps of the method for constructing a test profile based on measured temperature data as described above. The present invention also discloses a computer device, comprising a memory and a processor, wherein the memory has a computer program stored thereon, which, when executed by the processor, performs the steps of the method for constructing a test profile based on measured temperature data as described above. The present invention can implement all or part of the processes in the above-mentioned embodiments by instructing related hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and when executed by the processor, the computer program can implement the steps of each of the above-mentioned method embodiments. The computer program includes computer program code, which can be in source code form, object code form, executable file, or some intermediate form. Computer-readable media can include: any entity or device capable of carrying computer program code, recording medium, USB flash drive, mobile hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium. The memory can be used to store computer programs and / or modules. The processor implements various functions by running or executing the computer programs and / or modules stored in the memory, and calling data stored in the memory. The memory can include high-speed random access memory and non-volatile memory, such as a hard disk, internal memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a flash memory card, at least one disk storage device, a flash memory device, or other volatile solid-state storage device.

[0098] The above are merely preferred embodiments of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions based on the principles of the present invention are within the scope of protection of the present invention. It should be noted that for those skilled in the art, various improvements and modifications that do not depart from the principles of the present invention should be considered within the scope of protection of the present invention.

Claims

1. A method for constructing a test profile based on measured temperature data, characterized in that: Including steps: 1) Obtain the measured temperature data of the product environment under multiple cycles; 2) Separate and reconstruct the temperature data to obtain the periodic component and random component of the data; 3) Performing single-cycle fatigue equivalent analysis and tolerance estimation on the data periodic components to obtain equivalent values of daily cycle temperature; performing tolerance estimation and fatigue damage calculation on the random components of the data to obtain a unit fatigue damage index and an equivalent cumulative damage index; 4) Based on the equivalent value of the daily cycle temperature, the equivalent low temperature and equivalent high temperature are obtained, where the equivalent low temperature and equivalent high temperature are the lowest and highest temperatures of the test section, and their difference is the temperature cycle amplitude of the test section; The equivalent number of cycles is obtained based on the unit fatigue damage index and the equivalent cumulative damage index; then, the equivalent temperature cycle profile within the measured temperature data period is obtained based on the equivalent number of cycles and the ratio of cold days to hot days; In step 3), the specific process of performing single-cycle fatigue equivalent analysis on the data period component is as follows: The logarithmic life of the product is linearly related to the inverse of the absolute temperature stress to which the product is subjected, namely: （4） Where: is a parameter that can characterize the lifespan; a and b are unknown constants, and T represents the absolute temperature; （5） By using formula (5) to perform life damage equivalence, the equivalent value of daily cycle temperature can be obtained: (6) Where t equa is the equivalent total time, ; T1, T2...T n Respectively represent the absolute temperature value at each time of the day; In step 3), the process of performing tolerance estimation and fatigue damage calculation on the random component of the data to obtain the unit fatigue damage index and the equivalent cumulative damage index is as follows: Fatigue damage calculation is performed on the temperature change curve, the measured load history is simplified into several load cycles, and the temperature change history is equivalent to several temperature cycles with different amplitudes. There is a linear relationship between the logarithm of the strain amplitude and the logarithm of the number of fatigue load reversals. The linear cumulative damage hypothesis is used to analyze the cumulative fatigue damage of the product, and then the unit fatigue damage index is obtained based on the linear relationship and cumulative fatigue damage. Then, based on the fatigue damage principle, the equivalent cumulative damage index corresponding to the equivalent cyclic stress is obtained.

2. The method for constructing a test profile based on measured temperature data according to claim 1, characterized in that: After step 4), step 5) is also included to verify the equivalence of the measured temperature data and the constructed equivalent temperature cycle profile.

3. The method for constructing a test profile based on measured temperature data according to claim 2, characterized in that: In step 5), finite element simulation is used for verification. The specific process is as follows: the solder joint is selected as the simulation object, the measured temperature data and the constructed equivalent temperature cycle profile are applied to the solder joint respectively, the creep amount of the solder joint is calculated, and by comparing the two calculation results, it is verified whether the measured data and the equivalent temperature cycle profile are equivalent.

4. The method for constructing a test profile based on measured temperature data according to claim 1, 2 or 3, characterized in that: Between step 1) and step 2), data preprocessing is also included to remove extreme stress and random interference signals.

5. The method for constructing a test profile based on measured temperature data according to claim 4, characterized in that: The process of removing the ultimate stress is: Formula (1) is used to determine the ultimate stress, and then formula (2) is used to eliminate it; formula (1) and formula (2) are respectively: (1) (2)； Where T is the measured temperature; represents a day of the year, i = 1, 2, 3, ..., 365; j represents an hour of the day, j = 1, 2, 3, ..., 24.

6. The method for constructing a test profile based on measured temperature data according to claim 5, characterized in that: Use formula (3) to perform sliding filtering to remove random interference signals. （3）。 7. A test profile construction system based on measured temperature data, used to execute the steps of the test profile construction method based on measured temperature data according to any one of claims 1 to 6, characterized in that: include: The first program module is used to obtain the measured temperature data of the environment in which the product is located under multiple cycles; The second program module is used to separate and reconstruct the temperature data to obtain a data periodic component and a data random component; a third program module, configured to perform single-cycle fatigue equivalent analysis and tolerance estimation on the data periodic component to obtain an equivalent value of the daily cycle temperature; performing tolerance estimation and fatigue damage calculation on the random components of the data to obtain a unit fatigue damage index and an equivalent cumulative damage index; The fourth program module is used to obtain an equivalent low temperature and an equivalent high temperature based on the equivalent value of the daily cycle temperature, wherein the equivalent low temperature and the equivalent high temperature are the lowest and highest temperatures of the test section, and the difference between them is the temperature cycle amplitude of the test section; The equivalent number of cycles is obtained based on the unit fatigue damage index and the equivalent cumulative damage index; then, the equivalent temperature cycle profile within the measured temperature data period is obtained according to the equivalent number of cycles and the ratio of cold days to hot days.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the computer program executes the steps of the method for constructing a test profile based on measured temperature data according to any one of claims 1 to 6.

9. A computer device comprising a memory and a processor, wherein a computer program is stored in the memory, wherein: When the computer program is executed by a processor, the computer program executes the steps of the method for constructing a test profile based on measured temperature data according to any one of claims 1 to 6.

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