Electronic product temperature cycle life test system based on data analysis

Abstract

The application discloses an electronic product temperature cycle life test system based on data analysis and relates to the technical field of electronic product testing, solves the technical problem that the prior art cannot extract a harsh scene and integrate it into a temperature cycle scheme for temperature cycle test in combination with the use scene of an electronic product, and specifically relates to a use scene joint analysis unit which performs life test analysis on an electronic product in combination with the use scene of the electronic product, extracts a harsh scene and integrates it into a temperature cycle scheme for temperature cycle test, and tests the electronic product under a simulated use scene; a material failure analysis unit which performs material failure analysis on the electronic product; a material welding failure risk determination unit which determines the material welding failure risk of the electronic product and controls the material connection of the electronic product in a timely manner; and a micro deformation analysis unit which performs micro deformation analysis on the electronic product and ensures the usability of the connection of the overall material.

Description

Technical Field

[0001] This invention relates to the field of electronic product testing technology, specifically to a data analysis-based electronic product temperature cycle life testing system. Background Technology

[0002] Electronic products refer to a general term for devices that use electronic components (such as chips, resistors, capacitors, sensors, etc.) as their core and are driven by electrical energy to achieve signal processing, data transmission, energy conversion, or functional control. They have deeply penetrated all fields such as production, life, and scientific research, and are the basic carriers of the modern information society. Temperature cycling test is one of the core means of verifying the reliability of electronic products. By simulating extreme temperature alternation environments and applying temperature stress (high temperature, low temperature, temperature change rate), the performance stability, structural integrity, and life limit of the product during temperature cycling are evaluated.

[0003] However, existing technologies cannot combine the usage scenarios of electronic products, extract harsh scenarios and integrate them into temperature cycling solutions for temperature cycling testing, which reduces the accuracy of electronic product testing. At the same time, it is impossible to perform material connection failure analysis and overall material deformation analysis on the electronic products themselves, which reduces the stability of electronic product operation.

[0004] To address the aforementioned technical shortcomings, a solution is proposed. Summary of the Invention

[0005] The purpose of this invention is to solve the problems mentioned above by proposing a data analysis-based temperature cycle life testing system for electronic products.

[0006] The objective of this invention can be achieved through the following technical solutions:

[0007] The electronic product temperature cycle life test system based on data analysis includes a life test platform, which is connected to a usage scenario joint analysis unit, a material failure analysis unit, and a micro deformation analysis unit.

[0008] The usage scenario joint analysis unit analyzes the life test of electronic products by combining the usage scenarios of electronic products, extracts harsh scenarios and integrates them into temperature cycling schemes, conducts temperature cycling tests, and tests electronic products under simulated usage scenarios.

[0009] The material failure analysis unit performs material failure analysis on electronic products; identifies material welding failure risks, and promptly controls material connections in electronic products.

[0010] The micro-deformation analysis unit performs micro-deformation analysis on electronic products to ensure the usability of the overall connecting materials.

[0011] As a preferred embodiment of the present invention, the process of using the scenario joint analysis unit is as follows:

[0012] The system collects usage scenarios set at the factory default of electronic devices and usage scenarios at the location of users of the current type of electronic devices. Temperature data is collected according to the corresponding usage scenarios, and the temperature data is represented as temperature fluctuation frequency and temperature fluctuation amplitude. Any operating parameter of the electronic device is used as a state division parameter. That is, when the value of the state division parameter exceeds the set interval threshold, the device enters the next state. The temperature values ​​within the usage scenario are divided into intervals according to the operating status of the electronic device, and the temperature interval corresponds to each state of the electronic product.

[0013] In a preferred embodiment of the present invention, the probability of the electronic product transitioning from state i to state j, i.e., P, is recorded based on the temperature range of historical usage scenarios. ij Form a transition matrix P with a row sum of 1; i and j are letter substitutions for different states, used to represent the transitions between different states;

[0014] An initial temperature state is set, and the next temperature state is randomly selected based on the probability distribution of the transition matrix. This process is iterated to generate a continuous, non-uniform temperature change sequence, which is then fitted as a curve. The threshold of the thermal expansion coefficient of key materials in electronic products is tested in advance. The temperature change rate is calculated for each moment of the generated dynamic temperature curve. If the temperature change rate corresponding to the thermal expansion coefficient exceeds the set temperature change rate threshold, the corresponding temperature moment is set as a risk point; otherwise, it is marked as a safe point.

[0015] In a preferred embodiment of the present invention, the simulation process of the dynamic temperature curve is traversed, all risk points that trigger material thresholds are marked, risk temperature ranges are constructed, and harsh scenarios are extracted; a temperature cycling scheme is integrated; the current batch of electronic products is tested according to the temperature cycling scheme and the harsh scenarios, and the operating status of the electronic products is inferred based on the current test, and the test results are sent to the life test platform. The life test platform optimizes the material selection and adds temperature control modules to the electronic products based on the test results.

[0016] As a preferred embodiment of the present invention, the process of the material failure analysis unit is as follows:

[0017] Temperature and vibration data of electronic products are collected by sensors. The temperature data is represented as the temperature value changing over time; the vibration data is represented as a triaxial acceleration time history curve.

[0018] Finite element modeling is performed. Electronic products are modeled using CAD, and material data in the model are assigned values, such as temperature-related data: input thermal expansion coefficient and thermal conductivity; vibration-related data: input elastic modulus, Poisson's ratio, density, and fatigue strength of the material; boundary adjustment and division of the model are performed, that is, the temperature field loading data is used as temperature load, and the vibration field loading data is used as acceleration load.

[0019] In the finite element software, enable thermal-structural indirect coupling analysis to output thermal strain energy density and vibration fatigue damage; thermal strain energy density represents the material strain energy caused by temperature change; vibration fatigue damage represents the cumulative damage caused by vibration cycle.

[0020] As a preferred embodiment of the present invention, failure simulation of electronic products is carried out through temperature cycling test, and the critical values ​​of cracking of corresponding solder points of electronic products are recorded: thermal strain energy density threshold and vibration fatigue damage threshold.

[0021] The thermal strain energy density and vibration fatigue damage generated by the finite element method were compared with the thermal strain energy density threshold and the vibration fatigue damage threshold, respectively.

[0022] If the product of thermal strain energy density and vibration fatigue damage exceeds the product of thermal strain energy density threshold, vibration fatigue damage threshold, and safety factor, a failure warning signal will be generated and sent to the life test platform. The life test platform will implement failure protection for the corresponding solder joints of the current batch of electronic products and adjust the soldering process. The safety factor is a manually set coefficient to balance false alarms and missed alarms.

[0023] As a preferred embodiment of the present invention, the process of the micro-deformation analysis unit is as follows:

[0024] Temperature cycling tests are conducted on the current batch of electronic products to obtain the lattice spacing of the soldering material on the surface of the electronic products, and the lattice distortion rate is obtained by comparing the lattice spacing in the initial state. The range of the expansion of the lattice distortion rate of the electronic products during the temperature cycling test and the area ratio of the region where the lattice distortion rate increases in adjacent temperature cycles are obtained and analyzed.

[0025] In a preferred embodiment of the present invention, if the numerical expansion range of the lattice distortion rate of the electronic product exceeds the numerical expansion range threshold during the temperature cycling test, or if the area ratio of the region corresponding to the increase in lattice distortion rate in adjacent temperature cycles exceeds the area ratio threshold, a deformation risk signal is generated and sent to the life test platform; if the numerical expansion range of the lattice distortion rate of the electronic product does not exceed the numerical expansion range threshold during the temperature cycling test, and the area ratio of the region corresponding to the increase in lattice distortion rate in adjacent temperature cycles does not exceed the area ratio threshold, a deformation stabilization signal is generated and sent to the life test platform.

[0026] Compared with the prior art, the beneficial effects of the present invention are:

[0027] 1. In this invention, the life test analysis of electronic products is carried out in combination with the usage scenarios of electronic products. The stability of electronic products is inferred under temperature cycling scenarios. The random temperature fluctuations of real environment are accurately simulated, thereby improving the reliability of electronic product operation and enhancing the durability of electronic devices in areas with drastic temperature differences.

[0028] 2. In this invention, material failure analysis is performed on electronic products. Based on the material failure analysis, design defects can be discovered in advance during the research and development stage, enabling timely material selection and replacement. This reduces the risk of changes in the operating state of electronic products due to hardware material abnormalities in the usage scenario, thereby improving the operational stability of electronic products. Microscopic deformation analysis is also performed on electronic products. The deformation effect of electronic products is inferred through cyclic temperature testing. The deformation effect is used to infer whether the overall material properties of electronic products are suitable for the current usage scenario, thereby improving the operating efficiency and stability of electronic products. Attached Figure Description

[0029] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0030] Figure 1 This is a system principle block diagram of the present invention;

[0031] Figure 2 This is a flowchart of the method of the present invention. Detailed Implementation

[0032] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0033] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0034] Please see Figures 1-2As shown, the electronic product temperature cycle life test system based on data analysis includes a life test platform, which is connected to a usage scenario joint analysis unit, a material failure analysis unit, and a micro-deformation analysis unit.

[0035] The life test platform generates usage scenario joint analysis signals and sends them to the usage scenario joint analysis unit.

[0036] After receiving the usage scenario joint analysis signal, the usage scenario joint analysis unit performs life test analysis on the electronic product in combination with the usage scenario of the electronic product. Under temperature cycling scenario, it infers whether the stability of the electronic product is normal, accurately simulates the random temperature fluctuation of the real environment, thereby improving the reliability of the electronic product and enhancing the durability of electronic devices in areas with drastic temperature differences.

[0037] The system collects the usage scenarios set at the factory for electronic devices and the usage scenarios at the location of the user of the current type of electronic device. Temperature data is collected according to the corresponding usage scenarios, and the temperature data is expressed as the temperature fluctuation frequency and temperature fluctuation amplitude.

[0038] The state division parameters are determined by any operating parameter of the electronic device. When the value of the state division parameter exceeds the set interval threshold, the device enters the next state. For example, the surface temperature of the electronic device. The state development trend is consistent with the characteristic trend of the corresponding state division parameter. The temperature value in the usage scenario is divided into intervals according to the operating state of the electronic device, and the temperature interval corresponds to each state of the electronic product.

[0039] Based on the temperature range of historical usage scenarios, record the probability, P, of the electronic product transitioning from state i to state j. ij Form a transition matrix P with a row sum of 1; i and j are letter substitutions for different states, used to represent the transitions between different states;

[0040] Set an initial temperature state (such as the average initial temperature of the usage scenario), randomly select the next temperature state according to the probability distribution of the transition matrix, iterate cyclically, generate a continuous, non-uniform temperature change sequence, and fit it as a curve;

[0041] The threshold values ​​of the thermal expansion coefficients of key materials in electronic products are pre-tested; and the rate of temperature change is calculated moment by moment from the generated dynamic temperature curve, combined with the material's thermal expansion coefficient formula: α is the coefficient of thermal expansion. Let L0 be the shape variable and L0 be the initial length.

[0042] If the rate of temperature change corresponding to the coefficient of thermal expansion exceeds the set threshold for the rate of temperature change, the corresponding temperature moment is set as a risk point; otherwise, it is marked as a safe point.

[0043] The simulation process iterates through the dynamic temperature curve, marks all risk points that trigger material thresholds, constructs risk temperature segments, and extracts severe scenarios, such as: extreme temperature combinations (e.g., the maximum magnitude of a sudden drop in high temperature or a sudden rise in low temperature); and continuous risk duration (e.g., the duration of high temperature impact).

[0044] The integrated temperature cycling scheme includes: a temperature change sequence within the cycle (accurate to minute-level fluctuations); risk warning points (critical temperature / rate of material failure); and recommended test duration (covering typical failure cycles in the target region, such as extreme environments where electronic products are lost).

[0045] The process of constructing the state transition matrix is ​​as follows:

[0046] The temperature state set S = {s1, s2, ..., s} is obtained. n}, where n represents a natural number;

[0047] Transition matrix P=[P ij ] n×n ;

[0048] in, Nij represents the historical data from s i to s j The number of transfers; For from s i Total number of transfers from the starting point;

[0049] The iterative process for curve generation is as follows:

[0050] Let the temperature state at time t be Xt, and the initial state be X0 = S. i ;

[0051] X t+1 =s j The probability is: ;

[0052] Select s by random sampling (such as roulette). j Repeated execution yields the temperature sequence X0, X1, ..., X. T T represents the temperature symbol, and the interpolation fitting is a continuous curve;

[0053] The current batch of electronic products is tested based on the temperature cycling scheme and harsh scenarios. The operating status of the electronic products is inferred based on the current test conditions, and the test results are sent to the life test platform. The life test platform optimizes the material selection and adds temperature control modules to the electronic products based on the test results.

[0054] After completing the joint analysis of usage scenarios, a material failure analysis signal is generated and sent to the material failure analysis unit.

[0055] After receiving the material failure analysis signal, the material failure analysis unit performs material failure analysis on the electronic product. Based on the material failure analysis, design defects can be discovered in advance during the R&D stage, and materials can be selected and replaced in a timely manner. This reduces the risk of changes in the operating state of the electronic product due to hardware material abnormalities in the usage scenario, and improves the operational stability of the electronic product.

[0056] Temperature and vibration data of electronic products are collected by sensors. The temperature data is represented by T(t), which is the temperature value that changes over time. The vibration data is represented by Z(t), which is the triaxial acceleration time history curve.

[0057] Perform finite element modeling, model the electronic product using CAD, and assign values ​​to the material data in the model, such as temperature-related data: input the coefficient of thermal expansion α(T), a function of temperature, α(T) = α0 + βT, where β is the temperature coefficient; input the thermal conductivity k(T).

[0058] Vibration-related data include the elastic modulus E, Poisson's ratio v, and density of the input material. Fatigue strength P;

[0059] The model is divided into boundary adjustment sections, namely, T(t) collected by temperature field loading is used as temperature load (transient thermal analysis boundary), and Z(t) collected by vibration field loading is used as acceleration load (transient structural analysis boundary).

[0060] In the finite element software, enable thermal-structural indirect coupling analysis (first calculate the temperature field to obtain thermal strain, then use the thermal strain as a load to calculate structural stress), and output the thermal strain energy density w. t (t) and vibration fatigue damage D p (t);

[0061] Thermal strain energy density represents the material strain energy induced by temperature change; vibration fatigue damage represents the cumulative damage caused by vibration cycles.

[0062] Failure simulation of electronic products was carried out through temperature cycling tests, and the critical values ​​for cracking of corresponding solder points of electronic products were recorded: thermal strain energy density threshold and vibration fatigue damage threshold.

[0063] The thermal strain energy density and vibration fatigue damage generated by the finite element method were compared with the thermal strain energy density threshold and the vibration fatigue damage threshold, respectively.

[0064] If the product of thermal strain energy density and vibration fatigue damage exceeds the product of thermal strain energy density threshold, vibration fatigue damage threshold, and safety factor, a failure warning signal is generated and sent to the life test platform. The life test platform will implement failure protection for the corresponding solder joints of the current batch of electronic products and adjust the soldering process. The safety factor is a manually set coefficient to balance false alarms and missed alarms.

[0065] Conversely, a failure stabilization signal is generated and sent to the life test platform;

[0066] The formula for vibration fatigue damage is: ;

[0067] N i (t) represents the current number of vibration cycles (the number of vibrations exceeding the fatigue limit, as statistically derived from the acceleration time history). This represents the fatigue life of the material at the corresponding stress level, which can be found by looking up the SN curve (stress-life curve); for example... , Let b be the stress amplitude and m be the material constants.

[0068] The SN curve fitting process is as follows:

[0069] Multiple sets of stress amplitudes obtained from the test With corresponding fatigue life N f Fitting the SN curve using a power function:

[0070] ;

[0071] Taking the logarithm of both sides yields the linear form:

[0072] ;

[0073] By fitting the experimental data using the least squares method and solving for A and B, the fatigue life N under any stress amplitude can be obtained. f ;

[0074] The thermal strain energy density is calculated as follows:

[0075] Thermal strain energy density is the strain energy generated by a material due to temperature change. Under the assumption of small deformation, the thermal strain Gt is caused by thermal expansion: ;

[0076] The thermal stress σt satisfies Hooke's Law: σt = E(T) × (Gt - G0); G0 is the constraint strain, generated by the structural boundary; E(T) represents the elastic modulus of the material as a function of temperature T.

[0077] Thermal strain energy density W t The integral of the stress-strain curve:

[0078] ;

[0079] The life test platform generates micro-deformation analysis signals and sends them to the micro-deformation analysis unit;

[0080] After receiving the micro-deformation analysis signal, the micro-deformation analysis unit performs micro-deformation analysis on the electronic product, infers the deformation effect of the electronic product through cyclic temperature testing, and infers whether the overall material properties of the electronic product are suitable for the current set usage scenario through the deformation effect, thereby improving the operating efficiency and stability of the electronic product.

[0081] Temperature cycling tests are performed on the current batch of electronic products to obtain the lattice spacing of the soldering material on the surface of the electronic products, and the lattice distortion rate is obtained by comparing the lattice spacing in the initial state (before cycling).

[0082] The numerical expansion range of the lattice distortion rate of the electronic product during the temperature cycling test phase and the area percentage of the region where the lattice distortion rate increases in adjacent temperature cycles are obtained and analyzed:

[0083] If the expansion range of the lattice distortion rate of the electronic product exceeds the threshold during the temperature cycling test, or if the area ratio of the region where the lattice distortion rate increases in adjacent temperature cycles exceeds the area ratio threshold, it is inferred that the micro-deformation analysis is abnormal, a deformation risk signal is generated and sent to the life test platform. After receiving the deformation risk signal, the life test platform optimizes or replaces the overall material of the current electronic product, that is, it controls the type of the overall material within the welding boundary.

[0084] If the range of increase in the lattice distortion rate of the electronic product during the temperature cycling test does not exceed the threshold for range increase, and the area ratio of the region where the lattice distortion rate increases in adjacent temperature cycles does not exceed the area ratio threshold, then it is inferred that the microscopic deformation analysis is normal, a deformation stabilization signal is generated and sent to the life test platform.

[0085] In use, this invention includes a usage scenario joint analysis unit that analyzes the lifespan of electronic products based on their usage scenarios, extracts harsh scenarios and integrates them into a temperature cycling scheme, and conducts temperature cycling tests to test electronic products under simulated usage scenarios; a material failure analysis unit that performs material failure analysis on electronic products, determines the risk of material welding failure, and promptly controls the material connections of electronic products; and a micro-deformation analysis unit that performs micro-deformation analysis on electronic products to ensure the usability of the overall connection materials.

[0086] Thresholds, preset values, preset ranges, etc. are set for result comparison and analysis to determine whether they are good or bad. The value of these thresholds is determined by a combination of large-scale model analysis of sample data and human experience. They can also be adjusted appropriately based on seasonal or common-sense influences.

[0087] Furthermore, the settings for weighting ratios, influence factors, etc., are based on the magnitude of each parameter's influence on the results. The specific values ​​are allocated to ultimately reflect the impact on the results. The settings for input and storage are also determined by a combination of large-scale model analysis of sample data and human experience. Appropriate adjustments can also be made based on seasonal or rational influence conditions.

[0088] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A data analysis-based temperature cycling life testing system for electronic products, characterized in that, This includes a life testing platform, which is connected to a usage scenario joint analysis unit, a material failure analysis unit, and a micro-deformation analysis unit. The usage scenario joint analysis unit analyzes the life test of electronic products by combining the usage scenarios of electronic products, extracts harsh scenarios and integrates them into temperature cycling schemes, conducts temperature cycling tests, and tests electronic products under simulated usage scenarios. The material failure analysis unit performs material failure analysis on electronic products. Identify the risk of material welding failure and promptly control the material connections in electronic products; The micro-deformation analysis unit performs micro-deformation analysis on electronic products to ensure the usability of the overall connecting materials.

2. The electronic product temperature cycle life testing system based on data analysis according to claim 1, characterized in that, The process of using the scenario-based joint analysis unit is as follows: The system collects usage scenarios set at the factory default of electronic devices and usage scenarios at the location of users of the current type of electronic devices. Temperature data is collected according to the corresponding usage scenarios, and the temperature data is represented as temperature fluctuation frequency and temperature fluctuation amplitude. Any operating parameter of the electronic device is used as a state division parameter. That is, when the value of the state division parameter exceeds the set interval threshold, the device enters the next state. The temperature values ​​within the usage scenario are divided into intervals according to the operating status of the electronic device, and the temperature interval corresponds to each state of the electronic product.

3. The electronic product temperature cycle life testing system based on data analysis according to claim 2, characterized in that, Based on the temperature range of historical usage scenarios, record the probability, P, of the electronic product transitioning from state i to state j. ij ; Form a transition matrix P with a row sum of 1; i and j are letter substitutions for different states, used to represent the transitions between different states; An initial temperature state is set, and the next temperature state is randomly selected based on the probability distribution of the transition matrix. This process is iterated to generate a continuous, non-uniform temperature change sequence, which is then fitted as a curve. The threshold of the thermal expansion coefficient of key materials in electronic products is tested in advance. The temperature change rate is calculated for each moment of the generated dynamic temperature curve. If the temperature change rate corresponding to the thermal expansion coefficient exceeds the set temperature change rate threshold, the corresponding temperature moment is set as a risk point; otherwise, it is marked as a safe point.

4. The electronic product temperature cycle life testing system based on data analysis according to claim 3, characterized in that, The simulation process of traversing the dynamic temperature curve is carried out, all risk points that trigger the material threshold are marked, risk temperature ranges are constructed, and harsh scenarios are extracted. Integrate temperature cycling solutions; The current batch of electronic products is tested based on a temperature cycling scheme and harsh scenarios. The operating status of the electronic products is inferred based on the current test conditions, and the test results are sent to the life test platform. The life test platform optimizes the material selection and adds temperature control modules to the electronic products based on the test results.

5. The electronic product temperature cycle life testing system based on data analysis according to claim 4, characterized in that, The process of the material failure analysis unit is as follows: Temperature and vibration data of electronic products are collected by sensors. The temperature data is represented as the temperature value changing over time. The vibration data is represented as a triaxial acceleration time history curve. Finite element modeling is performed. Electronic products are modeled using CAD, and material data in the model are assigned values, such as temperature-related data: input thermal expansion coefficient and thermal conductivity; vibration-related data: input elastic modulus, Poisson's ratio, density, and fatigue strength of the material; boundary adjustment and division of the model are performed, that is, the temperature field loading data is used as temperature load, and the vibration field loading data is used as acceleration load. Enable thermal-structural indirect coupling analysis in finite element software to output thermal strain energy density and vibration fatigue damage; Thermal strain energy density represents the material strain energy caused by temperature changes; vibration fatigue damage represents the cumulative damage caused by vibration cycles.

6. The electronic product temperature cycle life testing system based on data analysis according to claim 5, characterized in that, Failure simulation of electronic products was carried out through temperature cycling tests, and the critical values ​​for cracking of corresponding solder points of electronic products were recorded: thermal strain energy density threshold and vibration fatigue damage threshold. The thermal strain energy density and vibration fatigue damage generated by the finite element method were compared with the thermal strain energy density threshold and the vibration fatigue damage threshold, respectively. If the product of thermal strain energy density and vibration fatigue damage exceeds the product of thermal strain energy density threshold, vibration fatigue damage threshold, and safety factor, a failure warning signal will be generated and sent to the life test platform. The life test platform will implement failure protection for the corresponding solder joints of the current batch of electronic products and adjust the soldering process. The safety factor is a manually set coefficient to balance false alarms and missed alarms.

7. The electronic product temperature cycle life testing system based on data analysis according to claim 6, characterized in that, The process of the micro-deformation analysis unit is as follows: Temperature cycling tests are conducted on the current batch of electronic products to obtain the lattice spacing of the soldering material on the surface of the electronic products, and the lattice distortion rate is obtained by comparing the lattice spacing in the initial state. The range of the expansion of the lattice distortion rate of the electronic products during the temperature cycling test and the area ratio of the region where the lattice distortion rate increases in adjacent temperature cycles are obtained and analyzed.

8. The electronic product temperature cycle life testing system based on data analysis according to claim 7, characterized in that, If the range of increase in the lattice distortion rate of an electronic product exceeds the threshold for the range of increase in the lattice distortion rate during the temperature cycling test, or if the area of ​​the region where the lattice distortion rate increases in adjacent temperature cycles exceeds the area percentage threshold, a deformation risk signal will be generated and sent to the life test platform. If the expansion range of the lattice distortion rate of the electronic product during the temperature cycling test does not exceed the threshold for expansion range, and the area ratio of the region where the lattice distortion rate increases in adjacent temperature cycles does not exceed the area ratio threshold, then a deformation stabilization signal is generated and sent to the life test platform.

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