A method for predicting the life of electronic components

Abstract

The present invention relates to the technical field of electronic digital data processing, and specifically discloses a life prediction method for electronic components, the method comprising: obtaining actual use environment parameters of electronic components; generating deviation rates of the use environment parameters of electronic components, and obtaining actual use environment ratings of electronic components by comparison; obtaining historical use progress evaluation values ​​and wear conditions of electronic components, analyzing to obtain quality parameters of electronic components and performing quality ratings of electronic components; forming an electronic component data set based on the use environment ratings and quality ratings of electronic components, extracting data information to obtain qualified electronic component information combinations; based on electronic component level life prediction correction factors in a database, comprehensively analyzing qualified electronic component information combinations to obtain predicted life of electronic components, which is helpful for accurately expressing relevant influencing factors of electronic component life prediction, saving and avoiding meaningless life predictions with large errors, and improving the accuracy of life prediction.

Description

Technical Field

[0001] The invention relates to the technical field of electrical digital data processing, in particular to a life prediction method for electronic components. Background Art

[0002] The life prediction of electronic components is very important for product design and maintenance. Using electronic component-related electrical digital data technology to accurately predict the life of electronic components can ensure that the product can achieve the expected life under normal use conditions, improve product reliability and stability, and reduce maintenance and replacement costs. In view of the influence of the use environment, load and manufacturing quality of electronic components under different working conditions, the existing life prediction methods of electronic components can monitor various parameters of electronic components in real time through sensors and monitoring equipment, and directly analyze and calculate various parameters of electronic components through electrical digital data technology. It can evaluate the working conditions and service life of electronic components in real time. At the same time, advanced information collection technologies such as cloud computing and wireless communication can be used to achieve efficient information transmission between electronic components, ensure the real-time and coordination of the electronic component system, and ensure the long-term stable operation of electronic components within the expected service life.

[0003] For example, the invention patent with announcement number: CN113566376B provides an electrical appliance life prediction method, air conditioner and computer-readable storage medium, the method comprising: obtaining the component temperature value of at least one component to be detected in the main electrical appliance in the current working state; predicting the life of the component to be detected according to the component temperature value, obtaining the predicted service life of the component to be detected; estimating the service life of the electrical appliance according to the predicted service life of the component to be detected. The electrical appliance life prediction method of the present invention can use the working temperature of electronic components to achieve accurate evaluation of the service life of the equipment.

[0004] For example, the invention patent with announcement number: CN113901675B, relates to a method, device, computer equipment and storage medium for predicting the life of electronic components. It includes: determining the characteristic parameters and the first working condition of the standard electronic components; obtaining the first test life of the standard electronic components at a preset temperature; determining the acceleration multiple of the standard electronic components; obtaining the second working condition of the electronic components to be predicted, and determining the test temperature when the acceleration multiple of the electronic components to be predicted is equal to the acceleration multiple of the standard electronic components according to the acceleration multiple of the standard electronic components, the second working condition, and the characteristic parameters of the electronic components to be predicted; determining the working condition difference multiple according to the first working condition and the second working condition; determining the second test life of the electronic components to be predicted at the test temperature according to the first test life and the working condition difference multiple. In this way, the life of electronic components under other working conditions can be predicted, which shortens the test time and saves the test cost.

[0005] At present, there are still some deficiencies in the prediction methods of electronic component life, which are specifically reflected in the following aspects: (1) The life of existing electronic components is mostly predicted based on historical statistical data of the ambient temperature of the electronic components. The volatility of the ambient temperature means that the prediction of the life of electronic components can only give a range of values, which lacks targeted and refined prediction. In actual production, such rough prediction results are difficult to meet the requirements of product design and maintenance, and may lead to underestimation or overestimation of product life, and even unexpected failures during use. The accuracy and targeting of electronic component life prediction are obviously insufficient only when the ambient temperature is considered;

[0006] (2) Given that the actual use environment has a significant impact on the life prediction of electronic components, under certain existing quality conditions, it is impossible to make an accurate prediction and expression of the life of electronic components in an environment that is too harsh or too favorable. At this time, the use of technical methods to predict the life of electronic components not only leads to large errors in the predicted life, but also the prediction results are difficult to have practical working significance in the actual use environment. The life prediction effect for specific environmental conditions or changing use environments is not good. The information correspondence between electronic components and their use environment is poor, resulting in low data processing efficiency.

[0007] In summary, the existing life prediction methods for electronic components have limited processing capabilities for electronic component parameters and low information integration, which in turn affects the accuracy and pertinence of electronic component life prediction. Summary of the invention

[0008] In view of the deficiencies in the prior art, the present invention provides a method for predicting the life of electronic components, which can effectively solve the problems involved in the above-mentioned background technology.

[0009] To achieve the above objectives, the present invention is implemented through the following technical solutions: a method for predicting the life of electronic components, comprising the following steps: obtaining actual use environment parameters of electronic components, the actual use environment parameters including ambient temperature, ambient humidity, mechanical stress consequences and vibration frequency of electronic components; generating electronic component use environment parameter deviation rates based on standard values ​​of electronic component use environment parameters in a database, and obtaining actual use environment ratings of electronic components by comparison; obtaining historical use progress assessment values ​​and wear conditions of electronic components, comprehensively analyzing to obtain electronic component quality parameters, and performing electronic component quality ratings based on the electronic component quality parameters; forming an electronic component data set based on the electronic component use environment rating and the electronic component quality rating, extracting corresponding rating levels, and comparing to obtain qualified electronic component information combinations; based on the electronic component level life prediction correction factors in the database, comprehensively analyzing the qualified electronic component information combinations to obtain the predicted life of the electronic components.

[0010] As a further method, the mechanical stress consequences in the actual use environment parameters are specifically determined by: obtaining the calculation parameters of the mechanical stress consequences in the actual use environment parameters, the mechanical stress consequences calculation parameters include the loosening ratio of electronic component solder joints, the rupture area of ​​electronic components, the surface deformation curvature, the damaged wire ratio, and the connection failure point ratio; the five parameters are fused and analyzed to obtain the mechanical stress consequences in the actual use environment parameters.

[0011] As a further approach, the calculation formula for the mechanical stress consequences in the actual use environment parameters is as follows:

[0012] ;

[0013] In the formula, are the mechanical stress consequences in the actual use environment parameters, a represents the loosening ratio of the solder joints of electronic components, b represents the rupture area of ​​electronic components, represents the surface deformation curvature, c represents the proportion of wire damage, d represents the proportion of connection point failure, and e is a natural constant.

[0014] As a further method, the deviation rate of the environmental parameters for the use of electronic components is generated. The specific analysis process is: obtaining the standard values ​​of the environmental parameters for the use of electronic components in the database; determining the difference between the actual environmental parameters for the use of electronic components and the standard values ​​of the environmental parameters for the use of electronic components in the database; and obtaining the deviation rate of the environmental parameters for the use of electronic components based on a comprehensive analysis of the standard values ​​and differences of the environmental parameters for the use of electronic components in the database.

[0015] As a further method, based on the deviation rate of the environmental parameters of electronic components, the environmental rating of electronic components is obtained by comparison. The specific analysis process is: obtaining the deviation rate of the environmental parameters of electronic components obtained by analysis, and using the deviation rate of the environmental parameters of electronic components as the basis for the environmental rating of electronic components; matching the environmental rating of electronic components corresponding to the environmental parameter deviation rate of each electronic component stored in the database to obtain the environmental rating of electronic components.

[0016] As a further method, the historical usage progress life assessment value of the electronic components is obtained, and the specific analysis process is: obtain the average service life and the longest service life of the electronic components in the database; obtain the cumulative usage time of the electronic components since they were put into use; obtain the average proportion of historical usage progress and the longest proportion of historical usage progress, and take the average of the average proportion of historical usage progress and the longest proportion of historical usage progress as the historical usage progress life assessment value, the average proportion of historical usage progress is the proportion of the cumulative usage time of the electronic components since they were put into use to the average service life of the electronic components in the database, and the longest proportion of historical usage progress is the proportion of the cumulative usage time of the electronic components since they were put into use to the longest service life of the electronic components in the database.

[0017] As a further method, electronic component quality rating is performed based on electronic component quality parameters. The specific analysis process is: using the quality assessment model to process the historical usage progress assessment values ​​and wear conditions of the electronic components to obtain the electronic component quality parameters, and the electronic component quality parameters are used as the basis for the electronic component quality rating; matching the electronic component quality parameters with the electronic component quality ratings corresponding to the deviation rates of the quality parameters of each electronic component stored in the database to obtain the electronic component quality ratings.

[0018] As a further method, based on the actual use environment ratings and quality ratings of electronic components, an electronic component data set is formed, the corresponding rating levels are extracted, and the qualified electronic component information combination is obtained by comparison. The specific analysis process is: collect the actual use environment parameter ratings and quality ratings of electronic components, and upload them to the database to form an electronic component data set; for any electronic component quality rating, extract the corresponding actual use environment rating in the electronic component data set; verify whether the quality rating of the electronic component and its actual use environment rating match, as the basis for judging whether it is a qualified electronic component, and unqualified electronic components are considered meaningless in life prediction; the quality rating of the electronic component and its matching actual use environment rating are used as the qualified electronic component information combination.

[0019] As a further method, based on the electronic component level life prediction correction factor in the database, a comprehensive analysis of qualified electronic component information combinations is performed to obtain the predicted life of the electronic components. The specific analysis process is: for any electronic component, a qualified electronic component information combination in the electronic component data set is extracted; based on the electronic component quality rating in the qualified electronic component information combination, the electronic component level life prediction correction factor set in the database is extracted; the actual use environment rating in the qualified electronic component information combination is extracted, and the predicted life of the electronic component is obtained through comprehensive analysis.

[0020] As a further approach, the predicted lifespan of electronic components is calculated as follows:

[0021] ;

[0022] In the formula, is the electronic component number, , is the total number of electronic components, Predicting the life of electronic components, For the Electronic component quality rating, For the The actual use environment rating of electronic components, For the The life prediction correction factor of an electronic component is e, which is a natural constant.

[0023] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects:

[0024] (1) The present invention provides a method for predicting the life of electronic components. The method can integrate the quality parameters of electronic components and the parameters of the actual use environment, and provide parameter acquisition of electronic components from multiple perspectives and dimensions. This makes up for the problem of inaccurate prediction of the life of electronic components caused by insufficient consideration of factors in existing prediction methods. The method comprehensively considers various factors that affect the prediction of the life of electronic components, including ambient temperature, ambient humidity, consequences of mechanical stress, and vibration frequency of electronic components, thereby improving the accuracy of life prediction of electronic components.

[0025] (2) The present invention objectively evaluates the life evaluation value of the historical use progress of electronic components, increases the accuracy of the expression of the quality parameters of electronic components, and further increases the accuracy of the quality rating of electronic components. The calculation of the historical use progress of electronic components breaks the objectivity of the previous consideration of only the historical average life, and newly considers the maximum service life of electronic components. At the same time, considering that electronic components often have individual extreme problems and damage, resulting in an extremely short life and no reference value, the shortest service life of electronic components is avoided from participating in the calculation of the life evaluation value of the historical use progress of electronic components, thereby achieving an accurate expression of the historical use progress of electronic components as a whole.

[0026] (3) The present invention realizes the practical significance of electronic component life prediction by extracting qualified electronic component information combinations through concentrated comparison of electronic component data. The actual use environment that electronic components can meet under certain self-quality conditions has certain requirements. To a certain extent, pre-screening qualified electronic component information combinations is not only a high-efficiency saving of prediction behavior to avoid meaningless life prediction with large errors, but also an effective method to improve the accuracy of life prediction. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The present invention is further described using the accompanying drawings, but the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative work.

[0028] Figure 1 It is a schematic diagram of the method flow of the present invention.

[0029] Figure 2 A flow chart of the steps for obtaining the deviation rate of the environmental parameters of electronic components. DETAILED DESCRIPTION

[0030] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0031] Reference Figure 1 As shown, the present invention provides a method, including: obtaining actual use environment parameters of electronic components, wherein the actual use environment parameters include ambient temperature, ambient humidity, mechanical stress consequences, and vibration frequency of the electronic components;

[0032] Specifically, the mechanical stress consequences in the actual use environment parameters are specifically determined in the following process: obtaining the calculation parameters of the mechanical stress consequences in the actual use environment parameters, the mechanical stress consequence calculation parameters including the loosening ratio of solder joints of electronic components, the rupture area of ​​electronic components, the surface deformation curvature, the damaged wire ratio, and the connection failure point ratio; performing a fusion analysis on the five parameters to obtain the mechanical stress consequences in the actual use environment parameters.

[0033] It needs to be explained that ultrasonic detection equipment is used to perform ultrasonic detection on welding points, and the reflection of the sound wave is used as the basis for judging whether the connection state of the broken solder point is loose. The loose solder point ratio of electronic components is the number of loose solder points of electronic components to the total number of solder points of electronic components. The broken area of ​​electronic components needs to consider the area where the cracks extend to different material layers and the broken area between different parts of the electronic components. Determining the curvature of the surface deformation of electronic components usually requires the use of special surface morphology testing instruments, such as three-dimensional optical microscopes, laser interferometers, electron microscopes, etc. The damaged wire ratio is the ratio of the length of the damaged part of the wire to the overall wire length.

[0034] Furthermore, the mechanical stress consequences in the actual use environment parameters can not only be further analyzed by the machine learning integrated model, using integrated methods such as random forest or gradient boosting tree to combine the prediction results of multiple basic models to obtain more accurate mechanical stress consequences in the actual use environment parameters, but also can be calculated by the following method. The specific calculation process is:

[0035] ;

[0036] In the formula, are the mechanical stress consequences in the actual use environment parameters, a represents the loosening ratio of the solder joints of electronic components, b represents the rupture area of ​​electronic components, represents the surface deformation curvature, c represents the proportion of wire damage, d represents the proportion of connection point failure, and e is a natural constant.

[0037] It should be noted that the proportion of loose solder joints of electronic components, the proportion of damaged wires of electronic components and the proportion of connection point failure are important parameters for evaluating the reliability of electronic component connections. The fracture area and surface deformation curvature of electronic components can be used to evaluate the basic structural conditions of components. The fracture area of ​​the electronic component indicates the stress condition of the component, and the surface deformation curvature reflects whether the component has been subjected to excessive deformation stress, thereby comprehensively evaluating the impact of mechanical stress on electronic components in terms of reliability and basic structural conditions. Among them, loose solder joints of electronic components may cause unstable wire connections and increase the risk of wire damage. Large surface deformation curvature may cause uneven force on components and increase the risk of fracture. At the same time, the size of the fracture area of ​​electronic components or the length of damaged wires directly affects the possibility of connection point failure.

[0038] In a specific embodiment, a high temperature environment in an actual use environment will increase the internal temperature of electronic components, causing the internal structure of the components to expand, physical properties to change, and may even cause problems such as thermal failure and leakage of components, thereby affecting the normal operation and life of electronic components. A high humidity environment may cause chemical reactions such as corrosion and oxidation inside electronic components, affecting the conductive properties of components, leading to circuit short circuits, open circuits, etc., and easily causing aging and breakdown of insulating materials, affecting the reliability and life of components. Mechanical stress is the interaction force between molecules or atoms inside an object generated by an external force acting on an object. It is an internal force per unit area inside an electronic component. The consequences of mechanical stress in the actual use environment parameters include the proportion of loose solder joints of electronic components, the damage of electronic components, and the probability of electronic component failure. Crack area, surface deformation curvature, proportion of damaged wires, proportion of connection point failure, vibration frequency refers to the vibration frequency to which electronic components are subjected during use. If the frequency is close to the natural vibration frequency of the component, it may cause resonance, thereby aggravating local mechanical structure fatigue and solder joint fatigue, embrittlement and other problems, affecting the life of the component. The actual use environment parameters can integrate the quality parameters of the electronic components and the actual use environment parameters, and provide parameter acquisition of the electronic components from multiple perspectives and dimensions, which makes up for the problem of inaccurate life prediction of electronic components caused by insufficient consideration of factors in existing prediction methods, and comprehensively considers various factors affecting the life prediction of electronic components, including ambient temperature, ambient humidity, consequences of mechanical stress and vibration frequency of electronic components, so as to improve the accuracy of life prediction of electronic components.

[0039] Generate the electronic component use environment parameter deviation rate based on the electronic component use environment parameter standard value in the database, and compare it to obtain the actual use environment rating of the electronic components;

[0040] Specifically, the deviation rate of the environmental parameters for the use of electronic components is generated, and the specific analysis process is: obtaining the standard values ​​of the actual environmental parameters for the electronic components in the database; determining the difference between the actual environmental parameters for the electronic components and the standard values ​​of the environmental parameters for the use of electronic components in the database; and obtaining the deviation rate of the environmental parameters for the use of electronic components based on a comprehensive analysis of the standard values ​​and differences of the environmental parameters for the use of electronic components in the database.

[0041] It should be noted that the standard value of the environmental parameters for the use of electronic components in the database refers to the optimal value of the environmental parameters to which any electronic component can adapt while keeping its material and workmanship quality relatively unchanged. Under the optimal value of the environmental parameters, the working efficiency and quality status of the electronic components remain stable. By comparing the actual environmental parameters for the use of electronic components with the standard values ​​of the environmental parameters for the use of electronic components in the database, the parameter deviation rate of the electronic components in the actual use environment can be quantitatively evaluated, which helps to more accurately understand the performance of components under different environmental conditions, provide basic data support for actual life prediction, and help to formulate corresponding preventive maintenance plans and improvement measures, improve the quality reliability, performance stability and durability of electronic components, reduce the potential risk of life changes due to environmental changes, and improve the accuracy of life prediction.

[0042] Specifically, based on the deviation rate of the environmental parameters of electronic components, the environmental rating of the electronic components is obtained by comparison. The specific analysis process is: obtaining the deviation rate of the environmental parameters of the electronic components obtained by analysis, and using the deviation rate of the environmental parameters of the electronic components as the basis for the environmental rating of the electronic components; matching the environmental parameters deviation rate of the electronic components with the environmental ratings of the electronic components corresponding to the environmental parameters deviation rates of each electronic component stored in the database to obtain the environmental rating of the electronic components.

[0043] It needs to be explained that by comparing the deviation rate of the actual use environment parameters with the deviation rate of the standard environment parameters in the database, the adaptability of electronic components in the actual use environment can be objectively evaluated. According to the rating results, the adaptation effect of the actual use environment parameters of the electronic components can be quantified, so as to more accurately understand the stability and reliability of the electronic components under specific conditions, and provide a basis for life prediction. At the same time, it can provide quantitative information for subsequent matching information combination, which is convenient for subsequent data processing. Life prediction based on the use environment rating of electronic components can help to discover potential use environment problems early, reduce the failure rate of electronic components due to mismatched environment, effectively reduce the risk of failure, and is conducive to the targeted life prediction of electronic components in specific environments, and improve prediction efficiency and prediction quality.

[0044] Specifically, the life assessment value of the historical usage progress of electronic components is obtained. The specific analysis process is: obtain the average service life and the longest service life of the electronic components in the database; obtain the cumulative usage time of the electronic components since they were put into use; obtain the average proportion of historical usage progress and the longest proportion of historical usage progress, and take the average of the average proportion of historical usage progress and the longest proportion of historical usage progress as the life assessment value of the historical usage progress, the average proportion of historical usage progress is the proportion of the cumulative usage time of the electronic components since they were put into use to the average service life of the electronic components in the database, and the longest proportion of historical usage progress is the proportion of the cumulative usage time of the electronic components since they were put into use to the longest service life of the electronic components in the database.

[0045] It needs to be explained that due to the characteristics of the working environment and the working mechanism of electronic components, when individual unexpected extreme working conditions occur or the influencing factors affect the path, the shortest service life of the electronic components will produce extreme values. The extreme values ​​of the shortest service life often deviate from the actual working significance of the electronic component life prediction, but will affect the average service life of the electronic components. Therefore, based on the average service life and the longest service life of the electronic components in the database, the life assessment value of the historical use progress of the electronic components is obtained, and the life assessment value of the historical use progress of the electronic components is objectively evaluated, which increases the accuracy of the expression of the quality parameters of the electronic components, and thus increases the accuracy of the quality rating of the electronic components. The calculation of the historical use progress of the electronic components breaks the objectivity of only considering the historical average life in the past, and newly considers the longest service life of the electronic components. At the same time, considering that electronic components often have individual extreme problems and damage, resulting in an extremely short life and no reference value, the shortest service life of the electronic components is avoided from participating in the calculation of the life assessment value of the historical use progress of the electronic components, and the overall accurate expression of the historical use progress of the electronic components is achieved.

[0046] Obtain the historical usage progress evaluation value and wear status of electronic components, conduct comprehensive analysis to obtain the quality parameters of electronic components, and perform electronic component quality rating based on the quality parameters of electronic components;

[0047] Specifically, the quality rating of electronic components is performed based on the quality parameters of electronic components. The specific analysis process is: using the quality assessment model to process the historical usage progress assessment values ​​and wear conditions of the electronic components to obtain the quality parameters of the electronic components, and the quality parameters of the electronic components are used as the basis for the quality rating of the electronic components; matching the quality parameters of the electronic components with the quality ratings corresponding to the deviation rates of the quality parameters of each electronic component stored in the database to obtain the quality ratings of the electronic components.

[0048] It should be explained that the electronic component quality parameters can not only be solved by mathematical optimization algorithms, combined with the electronic component working data and constraints, using linear programming, integer programming, planning algorithms, etc. to obtain appropriate quality parameters, but can also be calculated by the following quality assessment model. The calculation formula of the quality assessment model is:

[0049] ;

[0050] In the formula, is the electronic component number, , is the total number of electronic components, is the quality parameter of the i-th electronic component, is the cumulative usage time of the i-th electronic component since it was put into use, is the average service life of the i-th electronic component in the database, is the longest service life of the ith electronic component in the database, e is a natural constant, is the wear degree of the i-th electronic component.

[0051] It needs to be explained that the historical usage progress evaluation value of the electronic components in the quality assessment model can reflect the workload, operating status and other information of the electronic components. The degree of wear of the electronic components directly affects their working performance and quality reliability, thereby affecting the life of the components. During the working process, the historical usage progress of the electronic components corresponds to different structural performance, heat dissipation and other factors, which leads to the degree of wear of the components. By using the quality assessment model to process the historical usage progress and wear status of the electronic components, specific quality parameters are obtained as the basis for rating. This quantitative assessment method can more objectively reflect the quality status of the components and help to accurately assess the quality level of electronic components.

[0052] Based on the electronic component use environment rating and electronic component quality rating, an electronic component data set is formed, and the corresponding rating levels are extracted and compared to obtain a qualified electronic component information combination;

[0053] Specifically, based on the actual use environment ratings and quality ratings of electronic components, an electronic component data set is formed, the corresponding rating levels are extracted, and the qualified electronic component information combination is obtained by comparison. The specific analysis process is: collect the actual use environment parameter ratings and quality ratings of electronic components, and upload them to the database to form an electronic component data set; for any electronic component quality rating, extract the corresponding actual use environment rating in the electronic component data set; verify whether the quality rating of the electronic component and its actual use environment rating match, as the basis for judging whether it is a qualified electronic component, and unqualified electronic components are deemed to have meaningless life prediction; the quality rating of the electronic component and its matching actual use environment rating are used as the qualified electronic component information combination.

[0054] It needs to be explained that by extracting the corresponding rating levels from the data set of electronic components and conducting a comprehensive analysis, complete information data can be formed and the data processing process can be retained. At the same time, a more comprehensive understanding of the quality and usage environment of components can be obtained, and the performance and life status of components can be more accurately predicted, thereby enhancing the accuracy of prediction of the life of electronic components. By comparing and extracting qualified electronic component information combinations from the electronic component data set, the practical significance of electronic component life prediction can be realized. The actual usage environment that electronic components can meet under certain conditions of their own quality has certain requirements. To a certain extent, pre-screening qualified electronic component information combinations is not only a high-efficiency saving of prediction behavior to avoid meaningless life predictions with large errors, but also an effective method to improve the accuracy of life predictions.

[0055] Based on the electronic component level life prediction correction factor in the database, the qualified electronic component information combination is comprehensively analyzed to obtain the predicted life of the electronic components.

[0056] Specifically, based on the electronic component level life prediction correction factor in the database, a comprehensive analysis is performed on the qualified electronic component information combination to obtain the predicted life of the electronic component. The specific analysis process is: for any electronic component, the qualified electronic component information combination in the electronic component data set is extracted; based on the electronic component quality rating in the qualified electronic component information combination, the electronic component level life prediction correction factor set in the database is extracted; the actual use environment rating in the qualified electronic component information combination is extracted, and the predicted life of the electronic component is obtained through comprehensive analysis.

[0057] In a specific embodiment, the electronic component-level life prediction correction factor in the database extracted based on the electronic component quality rating in the qualified electronic component information combination is data verified by a large number of electronic component usage data processing experiments, combined with the quality rating and actual use environment rating in the qualified electronic component information combination. The quality rating and actual use environment rating are data obtained through actual testing and monitoring and are compared to form a corresponding matching relationship, which ensures the feasibility and practical significance of electronic component life prediction, and directly participates in the calculation formula of electronic component life prediction as a relevant parameter, which can improve the accuracy of electronic component life prediction while retaining data characteristics.

[0058] It should be explained that the predicted life of electronic components can not only be obtained by further analysis through machine learning integrated models, using integrated methods such as K-means clustering model or support vector machine model to average the prediction results of multiple basic models to obtain more accurate predicted life of electronic components, but also can be calculated in the following way. The calculation formula for the predicted life of electronic components is:

[0059] ;

[0060] In the formula, is the electronic component number, , is the total number of electronic components, Predicting the life of electronic components, For the Electronic component quality ratings, For the The actual use environment rating of electronic components, For the The life prediction correction factor of an electronic component is e, which is a natural constant.

[0061] It should be noted that different actual use environments will affect the aging speed and loss degree of electronic components, which in turn directly affect the predicted life of electronic components. The quality rating of electronic components usually reflects the manufacturing quality, material quality, process stability and other factors of the components themselves. Electronic components with high quality ratings usually have better stability and reliability, and the level life prediction correction factor will be affected accordingly. The life predicted by the interaction between the two is closer to the actual value. At the same time, the quality rating of electronic components and the actual use environment rating influence each other. For example, low-quality electronic components have poor heat dissipation capabilities, resulting in higher actual use environment temperatures, which in turn affects the actual use environment rating. The two jointly determine the life prediction results of electronic components, and their life prediction will be more accurate.

[0062] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. A method for predicting the life of an electronic component, characterized in that: The following steps are involved: Acquire actual use environment parameters of electronic components, wherein the actual use environment parameters include ambient temperature, ambient humidity, mechanical stress consequences, and vibration frequency of electronic components; Generate the electronic component use environment parameter deviation rate based on the electronic component use environment parameter standard value in the database, and compare it to obtain the actual use environment rating of the electronic components; Obtain the historical usage progress evaluation value and wear status of electronic components, conduct comprehensive analysis to obtain the quality parameters of electronic components, and perform electronic component quality rating based on the quality parameters of electronic components; Based on the electronic component use environment rating and electronic component quality rating, an electronic component data set is formed, and the corresponding rating levels are extracted and compared to obtain a qualified electronic component information combination; Based on the electronic component level life prediction correction factor in the database, the qualified electronic component information combination is comprehensively analyzed to obtain the predicted life of the electronic components; Based on the electronic component level life prediction correction factor in the database, the qualified electronic component information combination is comprehensively analyzed to obtain the predicted life of the electronic component. The specific analysis process is: For any electronic component, extract a qualified electronic component information combination in the electronic component data set; Based on the electronic component quality rating in the qualified electronic component information combination, extract the electronic component level life prediction correction factor set in the database; Extract the actual use environment rating from the qualified electronic components information combination, and conduct comprehensive analysis to obtain the predicted life of the electronic components; The electronic component predicted life calculation formula is: In the formula, is the electronic component number, , is the total number of electronic components, Predicting the life of electronic components, For the Electronic component quality rating, For the The actual use environment rating of electronic components, For the The life prediction correction factor of an electronic component is e, which is a natural constant.

2. The method for predicting the life of an electronic component according to claim 1, characterized in that: The specific determination process of the mechanical stress consequences in the actual use environment parameters is as follows: Obtaining mechanical stress consequence calculation parameters from actual use environment parameters, wherein the mechanical stress consequence calculation parameters include loose solder joint ratio of electronic components, rupture area of ​​electronic components, surface deformation curvature, wire damage ratio, and connection failure point ratio; The five parameters are fused and analyzed to obtain the mechanical stress consequences in the actual use environment parameters.

3. The method for predicting the life of an electronic component according to claim 1, characterized in that: The calculation formula for the mechanical stress consequences in the actual use environment parameters is as follows: In the formula, are the mechanical stress consequences in the actual use environment parameters, a represents the loosening ratio of the solder joints of electronic components, b represents the rupture area of ​​electronic components, represents the surface deformation curvature, c represents the proportion of wire damage, d represents the proportion of connection point failure, and e is a natural constant.

4. The method for predicting the life of an electronic component according to claim 1, characterized in that: The specific analysis process of generating the electronic component use environment parameter deviation rate is as follows: Obtain standard values ​​of environmental parameters for electronic components in the database; Determine the difference between the actual use environment parameters of the electronic components and the standard values ​​of the use environment parameters of the electronic components in the database; Based on the comprehensive analysis of the standard values ​​and differences of the environmental parameters of electronic components in the database, the deviation rate of the environmental parameters of electronic components is obtained.

5. The method for predicting the life of an electronic component according to claim 1, characterized in that: Based on the deviation rate of the environmental parameters of the electronic components, the environmental rating of the electronic components is obtained by comparison. The specific analysis process is as follows: Obtaining the deviation rate of the environmental parameters of the electronic components obtained through analysis, wherein the deviation rate of the environmental parameters of the electronic components is used as a basis for rating the environmental conditions of the electronic components; The electronic component use environment parameter deviation rate is matched with the electronic component use environment rating corresponding to each electronic component use environment parameter deviation rate stored in the database to obtain the actual use environment rating of the electronic component.

6. The method for predicting the life of an electronic component according to claim 1, characterized in that: The specific analysis process of obtaining the historical usage progress life evaluation value of the electronic components is as follows: Get the average service life and maximum service life of electronic components in the database; Obtain the cumulative usage time of electronic components since they were put into use; The average proportion of historical use progress and the longest proportion of historical use progress are obtained, and the average of the average proportion of historical use progress and the longest proportion of historical use progress is used as the historical use progress life assessment value. The average proportion of historical use progress is the proportion of the cumulative use time of electronic components since they were put into use to the average service life of electronic components in the database, and the longest proportion of historical use progress is the proportion of the cumulative use time of electronic components since they were put into use to the longest service life of electronic components in the database.

7. The method for predicting the life of an electronic component according to claim 1, characterized in that: The specific analysis process of the electronic component quality rating based on the electronic component quality parameters is as follows: Using the quality assessment model to process the historical usage progress assessment value and wear condition of the electronic components to obtain the quality parameters of the electronic components, and the quality parameters of the electronic components are used as the basis for the quality rating of the electronic components; The electronic component quality parameters are matched with the electronic component quality ratings corresponding to the deviation rates of the quality parameters of each electronic component stored in the database to obtain the electronic component quality ratings.

8. The method for predicting the life of an electronic component according to claim 1, characterized in that: The specific analysis process of forming an electronic component data set based on the actual use environment rating and the electronic component quality rating, extracting the corresponding rating level, and comparing to obtain the qualified electronic component information combination is as follows: Collect the actual use environment parameter ratings and quality ratings of electronic components, and upload them to the database to form an electronic component data set; For any electronic component quality rating, extract the corresponding actual use environment rating from the electronic component data set; Verify whether the quality rating of the electronic component matches the rating of its actual use environment, which serves as the basis for judging whether it is a qualified electronic component. Unqualified electronic components are considered meaningless in life prediction; The quality rating of the electronic component and its matching actual use environment rating are used as a qualified electronic component information combination.

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