Radio frequency assembly micro-strip reliability distribution analysis method based on failure physical model

Abstract

The invention relates to a radio frequency assembly micro-strip reliability distribution analysis method based on a failure physical model, belongs to the technical field of electronic component reliability analysis, and solves the problems of insufficient reliability evaluation precision and high cost in the prior art. According to the method, the failure physical model of the radio frequency assembly micro-strip is constructed, the temperature-stress distribution of the radio frequency assembly micro-strip under the temperature cycle condition is systematically analyzed, and accurate calculation of the reliability distribution of the micro-strip is achieved. The method not only can comprehensively consider the influence of the thermal fatigue failure mode of the typical radio frequency assembly micro-strip, but also can significantly improve the calculation efficiency, thereby providing a scientific basis for the design and manufacturing process optimization of electronic components, and effectively improving the long-term reliability of the radio frequency assembly micro-strip.

Description

Technical Field

[0001] The present invention belongs to the technical field of reliability analysis of electronic components, and particularly relates to a method for analyzing the reliability distribution of microstrip lines in radio frequency components based on a physics-of-failure model, which is used to analyze and estimate the reliability distribution of microstrip lines in radio frequency components under different working conditions. This method can be widely applied to the reliability analysis of semiconductor packaging, microelectronics assembly, and radio frequency and microwave equipment, especially for predicting the failure probability and estimating the life of microstrip lines, helping to optimize the manufacturing process and material selection, and improving the overall reliability of electronic products. Background Art

[0002] With the rapid development of electronic products towards high integration, miniaturization, and high performance, microstrip lines in radio frequency components have been widely used in the fields of semiconductor packaging and radio frequency electronics assembly. As a key connection structure in radio frequency components, the reliability of microstrip lines directly affects the stability and service life of the entire radio frequency and microwave electronic system. In practical applications, since microstrip lines usually serve in complex environmental conditions, including extreme temperature immersion and rapid temperature cycling, these factors will cause various failure problems in microstrip lines during long-term use, such as thermal fatigue, interface embrittlement, and stress failure. Therefore, accurately evaluating the reliability distribution of microstrip lines is crucial for the design, material selection, and manufacturing process optimization of electronic components.

[0003] Currently, traditional methods for microstrip line reliability analysis usually rely on accelerated life tests and empirical statistical models. By conducting accelerated tests under extreme conditions such as high temperature, temperature cycling, or mechanical vibration, the life of microstrip lines under actual working conditions is inferred. However, this empirical statistical method has certain limitations. First, the accelerated life test cycle is long and the cost is high, making it difficult to quickly meet the needs of product updates; second, the empirical statistical model fails to fully consider the fluctuating changes of microstrip lines under temperature cycling conditions, resulting in insufficient accuracy of reliability assessment. In the application of high-precision electronic devices, traditional methods are difficult to meet the high-precision requirements for microstrip line reliability prediction. Therefore, the method for analyzing the reliability distribution of microstrip lines in radio frequency components based on the physics-of-failure model has gradually become a research hotspot and development trend.

[0004] In recent years, some research institutions have begun to explore establishing a physics-of-failure model to simulate the failure behavior of microstrip lines in radio frequency components under multi-physical fields, and combining numerical simulation and statistical methods to deduce the reliability distribution of microstrip lines. However, existing technologies mostly only analyze the stress and strain of microstrip lines in radio frequency components, lacking comprehensive consideration of long-term reliability. Therefore, existing technologies have deficiencies in terms of the accuracy, comprehensiveness, and computational efficiency of the reliability distribution of microstrip lines in radio frequency components, and there is an urgent need for a new reliability assessment method to achieve comprehensive reliability distribution analysis of microstrip lines in radio frequency components and improve the accuracy and practicality of reliability assessment. Summary of the Invention

[0005] In view of the above problems, the present invention provides a method for analyzing the reliability distribution of microstrip lines in RF components based on a physics-of-failure model, aiming to overcome the problems of insufficient accuracy and high cost in reliability assessment in the prior art. The method of the present invention constructs a physics-of-failure model of the microstrip lines in RF components, systematically analyzes the temperature-stress distribution of the microstrip lines in RF components under temperature cycling conditions, and realizes the accurate calculation of the reliability distribution of the microstrip lines. The method of the present invention can not only comprehensively consider the influence of the thermal fatigue failure mode of typical microstrip lines in RF components, but also significantly improve the calculation efficiency, thereby providing a scientific basis for the design and manufacturing process optimization of electronic components and effectively improving the long-term reliability of the microstrip lines in RF components.

[0006] The present invention provides a method for analyzing the reliability distribution of microstrip lines in RF components based on a physics-of-failure model, and the specific steps are as follows:

[0007] S1. Construct a parametric finite element model of the microstrip line structure in the RF component;

[0008] S2. Based on the parametric finite element model of the microstrip line structure in the RF component, perform thermo-mechanical coupling simulation to obtain the strain energy density distribution of the microstrip line under temperature cycling;

[0009] S3. Based on the physics-of-failure model and the strain energy density distribution of the microstrip line, predict the life of the microstrip line;

[0010] S4. Based on the microstrip line life prediction result, analyze the reliability distribution of the microstrip line in the RF component.

[0011] Optionally, the specific steps of step S1 are as follows:

[0012] S11. Determine the parameters of the substrate;

[0013] S12. Determine the parameters of the microstrip line;

[0014] S13. Determine the parameters of the solder joints;

[0015] S14. Determine the material property parameters;

[0016] S15. Determine the temperature boundary conditions;

[0017] S16. Based on the above geometric parameters, material properties and boundary conditions, construct a parametric finite element model of the typical structure of the microstrip line, providing basic data for subsequent strain energy density analysis and life prediction.

[0018] Optionally, the parameters of the substrate include geometric structure parameters and boundary conditions;

[0019] The geometric structure parameters of the substrate include the substrate length L, the substrate width H, and the substrate thickness T;

[0020] The boundary condition of the substrate is fixed at the bottom to simulate the fixed constraint of the substrate in actual electronic packaging.

[0021] Optionally, the microstrip includes a rectangular portion and a connecting strip portion; the microstrip is disposed on the substrate; one end of the connecting strip portion is connected to the middle of one side of the rectangular portion, and the other end is connected to the solder joint; the microstrip bifurcation opening angle is provided on the inner side of the rectangular portion at the position where it is connected to the connecting strip portion;

[0022] The bandwidth of the connecting strip portion is H1 and the length is L1.

[0023] Optionally, the solder joint length of the solder joint is L4 and the solder joint width is H1, and the solder joint height is half of the width.

[0024] Optionally, the microstrip material parameters are elastic modulus E1, Poisson's ratio v1, specific heat capacity sh1, density ρ1, thermal conductivity hc1, and thermal expansion coefficient α1;

[0025] The solder joint material parameters are elastic modulus E2, Poisson's ratio v2, specific heat capacity sh2, density ρ2, thermal conductivity hc2, and thermal expansion coefficient α2;

[0026] The substrate material parameters are elastic modulus E3, Poisson's ratio v3, specific heat capacity sh3, density ρ3, thermal conductivity hc3, and thermal expansion coefficient α3.

[0027] Optionally, the temperature environment boundary conditions include the maximum temperature of t1, the high-temperature immersion time of s1, the minimum temperature of t2, the low-temperature immersion time of s2, and the high-low temperature change time of sc.

[0028] Optionally, the specific steps of step S2 are as follows:

[0029] S21. Under the set temperature cycle conditions, perform thermal stress simulation on the parametric finite element model of the microstrip structure of the RF component by the finite element analysis method to obtain the stress and strain distributions of the microstrip.

[0030] S22. According to the thermal stress simulation results and the stress and strain distributions of the microstrip, obtain the strain energy density distribution of the microstrip during a single-cycle temperature cycle.

[0031] Optionally, the specific steps of step S3 are as follows:

[0032] S31. Analyze the strain energy density distribution of the microstrip, and select the mean value of the regions with larger unit microstrip strain energy density in a single cycle as the input parameters of the failure physics model;

[0033] S32. For thermal fatigue failure, the failure physics model predicts the life of the microstrip.

[0034] Optionally, the expression for the strain energy density distribution of the microstrip during a single-cycle temperature cycle is as follows:

[0035] W 单元 = 1 / 2 × σ 单元 ε 单元

[0036] where W 单元 is the strain energy density of the finite element cell of the microstrip, and σ 单元 and ε 单元 are the stress and strain within the finite element cell of the microstrip.

[0037] Compared with the prior art, the present invention has at least the following beneficial effects:

[0038] 1. Precise reliability assessment: The present invention adopts a failure physics model, combines finite element simulation with thermo-mechanical coupling analysis, can accurately calculate the strain energy density distribution of the microstrip during temperature cycling, and predict the life of the microstrip based on a fatigue model. Compared with traditional empirical life estimation methods, the evaluation method of the present invention has higher accuracy and can more accurately reflect the stress and strain characteristics of the microstrip in the actual working environment, providing reliable theoretical support for the reliability of RF components.

[0039] 2. Quantitative reliability distribution analysis: The present invention can generate the life data distribution of the microstrip under different temperature boundary conditions and obtain the reliability distribution function through Monte Carlo sampling and reliability distribution fitting (such as Weibull distribution, lognormal distribution). This method can intuitively display the change trend of the failure probability of the microstrip over time, provide support for identifying weak links in the reliability of the microstrip, and thus help optimize the structural parameters during the product design stage and improve the overall reliability.

[0040] 3. Reference basis for optimized design: Through the reliability distribution analysis method of the present invention, the failure risks of the microstrip under the influence of various temperature profile parameters can be identified, and then the geometric structure and material parameters of the microstrip can be optimized. The present invention can not only improve the working stability of electronic products, but also reduce the maintenance cost of products, improve the use safety and life of equipment, and provide an important basis for the reliability design of electronic products. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 is a flowchart of the method for analyzing the reliability distribution of the microstrip of an RF component based on a failure physics model according to the present invention;

[0042] Figure 2 is a schematic diagram of the microstrip structure according to the present invention;

[0043] Figure 3 is a schematic diagram of the substrate parameters according to the present invention;

[0044] Figure 4 Schematic diagram of the microstrip parameters of the present invention;

[0045] Figure 5 Schematic diagram of the pin solder joint parameters of the present invention;

[0046] Figure 6 Structural stress distribution of the microstrip of the present invention;

[0047] Figure 7 Structural strain distribution of the microstrip of the present invention;

[0048] Figure 8 Structural strain energy density distribution of the microstrip of the present invention;

[0049] Figure 9 Frequency statistics chart of the microstrip TTF of the present invention;

[0050] Figure 10 Reliability distribution of the microstrip of the present invention.

[0051] Reference signs:

[0052] 1. Substrate; 2. Rectangular part; 3. Connection strip part; 4. Pin solder joint. Detailed implementation manners

[0053] In order to more clearly understand the above objects, features and advantages of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific implementation manners. It should be noted that, without conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other. In addition, the present invention can also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited by the specific embodiments disclosed below.

[0054] A specific embodiment of the present invention, as Figures 1 - 10 , discloses a method for analyzing the reliability distribution of the microstrip of a radio frequency component based on a physics-of-failure model. By constructing a parametric finite element model through finite element simulation and combining it with the physics-of-failure model, the reliability of the microstrip of the radio frequency component in a typical application scenario is comprehensively evaluated. The specific steps are as follows:

[0055] S1. Construct a parametric finite element model of the microstrip structure of the radio frequency component;

[0056] As Figure 2 shown, construct a parametric finite element model of the microstrip structure of the radio frequency component, and the parametric finite element model includes a microstrip, a pin solder joint 4 and the connected substrate 1.

[0057] The specific steps include:

[0058] S11. Determine the parameters of the substrate;

[0059] The geometric structure parameters of the substrate 1 include the substrate length L, the substrate width H, and the substrate thickness T, as shown in the appendix Figure 3 shown.

[0060] The boundary condition of the substrate 1 is fixed at the bottom to simulate the fixed constraint of the substrate in the actual electronic packaging.

[0061] S12. Determine the parameters of the microstrip;

[0062] The microstrip includes a rectangular part 2 and a connecting strip part 3; the microstrip is arranged on the substrate 1; one end of the connecting strip part 1 is connected to the middle of one side of the rectangular part 2, and the other end is connected to the pin solder joint 4;

[0063] As shown in the appendix Figure 4 shown, the thickness of the microstrip is T1; the bandwidth of the rectangular part 2 is H1, the outer length of the short side is L2; the outer length of the long side is H3, the inner length of the short side is L3, and the outer length of the short side is H2;

[0064] Furthermore, a microstrip bifurcation opening angle is set on the inner side of the rectangular part 2 at the position where it is connected to the connecting strip part 3, and the bifurcation angle is θ.

[0065] The bandwidth of the connecting strip part 3 is H1 and the length is L1.

[0066] S13. Determine the parameters of the pin solder joint;

[0067] As shown in the appendix Figure 5 shown, the pin solder joint length of the pin solder joint 4 is L4 and the pin solder joint width is H1, and the pin solder joint height is half of the width, that is, H1 / 2.

[0068] S14. Determine the material property parameters;

[0069] Specifically, the microstrip material parameters are elastic modulus E1, Poisson's ratio v1, specific heat capacity sh1, density ρ1, thermal conductivity hc1, and thermal expansion coefficient α1.

[0070] The pin solder joint material parameters are elastic modulus E2, Poisson's ratio v2, specific heat capacity sh2, density ρ2, thermal conductivity hc2, and thermal expansion coefficient α2.

[0071] The substrate material parameters are elastic modulus E3, Poisson's ratio v3, specific heat capacity sh3, density ρ3, thermal conductivity hc3, and thermal expansion coefficient α3.

[0072] S15. Determine the temperature boundary conditions;

[0073] The temperature environment boundary conditions are the maximum temperature is t1, the high-temperature immersion time is s1, the minimum temperature is t2, the low-temperature immersion time is s2, and the high-low temperature change time is sc.

[0074] S16. Based on the above geometric parameters, material properties, and boundary conditions, a parametric finite element model of the typical structure of the microstrip is constructed to provide basic data for subsequent strain energy density analysis and life prediction.

[0075] S2. Based on the parametric finite element model of the microstrip structure of the RF component, a thermo-mechanical coupling simulation is carried out to obtain the strain energy density distribution of the microstrip under temperature cycling. The specific steps are as follows:

[0076] S21. Under the set temperature cycling conditions, a thermal stress simulation is carried out on the parametric finite element model of the microstrip structure of the RF component by the finite element analysis method to obtain the stress and strain distributions of the microstrip.

[0077] S22. According to the thermal stress simulation results and the stress and strain distributions of the microstrip, the strain energy density distribution of the microstrip during a single-cycle temperature cycle is obtained. The expression is:

[0078] W 单元 =1 / 2×σ 单元 ε 单元

[0079] Where W 单元 is the strain energy density of the finite element of the microstrip, and σ 单元 and ε 单元 are the stress and strain in the finite element of the microstrip.

[0080] The present invention identifies the potential failure regions of the microstrip according to the strain energy density of the microstrip element, providing a basis for subsequent life prediction. Exemplarily, the regions with larger strain energy density are potential failure regions.

[0081] S3. Based on the physics-of-failure model and the strain energy density distribution of the microstrip, predict the life of the microstrip;

[0082] Based on the strain energy density distribution obtained from the thermo-mechanical coupling simulation, the physics-of-failure model is used to predict the life of the microstrip. The specific steps are as follows:

[0083] S31. Analyze the strain energy density distribution of the microstrip, and select the mean value W ave of the top 10% of the unit microstrip with larger strain energy density in a single cycle as the input parameter of the physics-of-failure model;

[0084] S32. For thermal fatigue failure, the physics-of-failure model predicts the life TTF of the microstrip. The expression is:

[0085] TTF=N f ×(s1 + s2 + sc×2) = C(s1 + s2 + sc×2)(1 / W ave ) m

[0086] wherein, N f is the fatigue life number of the micro wire strip, which is the predicted number of failures under given temperature cycle conditions; s1 represents the high temperature immersion time; s2 represents the low temperature immersion time; sc represents the temperature change time between high and low temperatures; C is the fatigue coefficient of strain energy density, which is related to the material properties; m is the fatigue index of strain energy density.

[0087] According to the calculation results of the life prediction model, the predicted life value of the micro wire strip under specific environmental conditions with specified parameter conditions is obtained. This life value can be used to evaluate the long-term stability of the micro wire strip under different temperature cycles and provide a reference for reliability analysis.

[0088] S4. Analyze the reliability distribution of the micro wire strip of the RF component based on the life prediction result of the micro wire strip.

[0089] Based on the life prediction result of the micro wire strip, by assuming the probability distribution parameters of the micro wire strip structure parameters and temperature boundary condition parameters, using Monte Carlo sampling, n groups of micro wire strip structure parameters and temperature boundary condition parameters are sampled, and according to the TTF calculation method of the micro wire strip in steps 1-3, n TTF values are obtained;

[0090] Use the Weibull distribution or lognormal distribution to fit the n TTF values to obtain the reliability distribution function, and thus the change trend of the failure probability of the micro wire strip of the RF component over time can be predicted.

[0091] Preferably, the probability distribution is a normal distribution or a uniform distribution.

[0092] According to the reliability distribution result, the reliability weak links of the micro wire strip are identified. By adjusting the structure parameters and optimizing the material parameters, the overall reliability of the micro wire strip can be improved. In addition, the reliability distribution result can also be used to optimize the design and maintenance cycle arrangement of electronic products and improve the use safety and reliability of equipment.

[0093] The above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by those skilled in the art within the technical scope disclosed by the present invention should be covered by the protection scope of the present invention.

Claims

1. A method for analyzing the reliability distribution of radio frequency components microstrip based on a failure physics model, characterized in that: The specific steps are as follows: S1. Construct a parametric finite element model of the micro-strip structure of the RF component; S2. Based on the parametric finite element model of the micro-strip structure of the RF component, a thermal-mechanical coupling simulation is performed to obtain the strain energy density distribution of the micro-strip under the action of temperature cycling; S3. Predict the life of micro-belt based on the failure physics model and strain energy density distribution of micro-belt; S4. Based on the micro-strip life prediction results, analyze the reliability distribution of the micro-strip of the RF component.

2. The method for analyzing the reliability distribution of a radio frequency component microstrip according to claim 1, characterized in that: The specific steps of step S1 are as follows: S11, determining parameters of the substrate; S12, determining the parameters of the micro strip; S13, determining the parameters of the pin soldering point; S14, determining material property parameters; S15, determining temperature boundary conditions; S16. Based on the above geometric parameters, material properties and boundary conditions, a parametric finite element model of the typical structure of the micro-belt is constructed to provide basic data for subsequent strain energy density analysis and life prediction.

3. The method for analyzing the reliability distribution of a radio frequency component microstrip according to claim 2, characterized in that: The parameters of the substrate include geometric structure parameters and boundary conditions; The geometric structure parameters of the substrate include substrate length L, substrate width H and substrate thickness T; The boundary condition of the substrate is bottom fixed to simulate the fixed constraint of the substrate in actual electronic packaging.

4. The method for analyzing the reliability distribution of a radio frequency component microstrip according to claim 2, characterized in that: The micro-strip includes a rectangular portion and a connecting strip portion; the micro-strip is arranged on a substrate; one end of the connecting strip portion is connected to the middle of one side of the rectangular portion, and the other end is connected to a pin soldering point; a micro-strip bifurcation angle is arranged on the inner side of the rectangular portion at a position where the connecting strip portion is connected; The width of the connecting belt is H1 and the length is L1.

5. The method for analyzing the reliability distribution of a radio frequency component microstrip according to claim 2, characterized in that: The pin solder joint has a pin solder joint length of L4 and a pin solder joint width of H1, and a pin solder joint height is half of the width.

6. The method for analyzing the reliability distribution of a radio frequency component microstrip according to claim 2, characterized in that: The material parameters of the micro-strip are elastic modulus E1, Poisson’s ratio v1, specific heat capacity sh1, density ρ1, thermal conductivity hc1, and thermal expansion coefficient α1; The material parameters of the pin solder joint are elastic modulus E2, Poisson's ratio v2, specific heat capacity sh2, density ρ2, thermal conductivity hc2, and thermal expansion coefficient α2; The parameters of the substrate material are elastic modulus E3, Poisson's ratio v3, specific heat capacity sh3, density ρ3, thermal conductivity hc3, and thermal expansion coefficient α3.

7. The method for analyzing the reliability distribution of a radio frequency component microstrip according to claim 2, characterized in that: The temperature environment boundary conditions include the highest temperature t1, the high temperature immersion time s1, the lowest temperature t2, the low temperature immersion time s2, and the high and low temperature temperature change time sc.

8. The method for analyzing the reliability distribution of a radio frequency component microstrip according to claim 1, characterized in that: The specific steps of step S2 are: S21. Under the set temperature cycle conditions, the thermal stress simulation is performed on the parameterized finite element model of the micro-strip structure of the RF component by the finite element analysis method to obtain the stress and strain distribution of the micro-strip. S22. Based on the thermal stress simulation results, the stress and strain distribution of the micro-wire strip, the strain energy density distribution of the micro-wire strip during a single-cycle temperature cycle is obtained.

9. The method for analyzing the reliability distribution of a radio frequency component microstrip according to claim 1, characterized in that: The specific steps of step S3 are: S31, analyzing the strain energy density distribution of the micro-wire strip, and selecting the mean value of the area with larger strain energy density of the unit micro-wire strip under a single cycle as the input parameter of the failure physical model; S32. For thermal fatigue failure, the failure physics model is used to predict the life of the micro-strip.

10. The method for analyzing the reliability distribution of a radio frequency component microstrip according to claim 8, characterized in that: The expression of strain energy density distribution of micro-wire strip during single-cycle temperature cycling is: W 单元 =1 / 2×σ 单元 e 单元 Among them, W 单元 is the strain energy density of the finite element of the microstrip, σ 单元 and ε 单元 are the stress and strain in the finite element unit of the microstrip.

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