Construction method and system of silica gel insulation performance degradation model

Abstract

The invention provides a construction method and system of a silica gel insulation performance degradation model, and relates to the technical field of reliability evaluation of an electric connector insulation material, and the method comprises the steps: obtaining a failure mechanism and a failure condition of a silica gel insulation part in a storage environment; key indexes influencing the insulation performance are screened through failure mechanism analysis, and the key indexes comprise carrier concentration, conductivity and insulation resistance; establishing a first mathematical relational expression of the relationship between the carrier concentration and the environmental condition through a chemical reaction kinetics theory; establishing a second mathematical relationship among the carrier concentration, the conductivity and the insulation resistance through an ionic conductance mechanism; based on the first mathematical relationship and the second mathematical relationship, constructing a silica gel insulation performance accelerated degradation model; and based on the silica gel insulation performance accelerated degradation model and the failure condition, constructing a silica gel insulation part reliability statistical model.

Description

Technical Field

[0001] The present invention relates to the technical field of reliability evaluation of insulating materials for electrical connectors, and particularly to a method and system for constructing a degradation model of the insulating performance of silicone rubber. Background Art

[0002] An electrical connector is a core component for signal transmission in an equipment system, and its insulating performance directly determines the reliability of the system. As room temperature vulcanized silicone rubber, silicone rubber is widely used in insulating parts of electrical connectors due to its excellent insulation and weather resistance. However, during long-term storage, temperature and humidity can cause its thermal-oxidative aging, condensation cross-linking and hydrolysis reactions, resulting in an increase in the concentration of free ions and a decrease in insulation resistance, ultimately leading to insulation failure.

[0003] In existing research, statistical or data-driven modeling methods based on a large amount of experimental data are mostly used to analyze and predict the degradation of material properties. For example, machine learning algorithms such as regression analysis, artificial neural networks, and support vector machines are used to estimate the material life.

[0004] However, existing technologies are mostly trained based on specific data sets and have a strong dependence on data distribution. Therefore, when facing new environmental conditions, the reliability and stability of the prediction results of the model are significantly reduced, and there is a lack of sufficient generalization ability. Although existing statistical methods and machine learning models can meet the requirements of life prediction in engineering practice to a certain extent, they essentially fail to reveal the internal physical and chemical mechanisms during the degradation process of material properties, resulting in relatively low accuracy of the model prediction results. Summary of the Invention

[0005] In order to solve the technical problems that existing technologies are mostly trained based on specific data sets and have a strong dependence on data distribution. Therefore, when facing new environmental conditions, the reliability and stability of the prediction results of the model are significantly reduced, and there is a lack of sufficient generalization ability. Although existing statistical methods and machine learning models can meet the requirements of life prediction in engineering practice to a certain extent, they essentially fail to reveal the internal physical and chemical mechanisms during the degradation process of material properties, resulting in relatively low accuracy of the model prediction results, the present invention provides a method and system for constructing a degradation model of the insulating performance of silicone rubber.

[0006] The technical solutions provided by the embodiments of the present invention are as follows:

[0007] First aspect:

[0008] A method for constructing a degradation model of the insulating performance of silicone rubber provided by an embodiment of the present invention includes:

[0009] S1: Obtain the failure mechanism and failure conditions of the silicone rubber insulating part in the storage environment;

[0010] S2: By analyzing the failure mechanism, screen the key indicators affecting the insulation performance, where the key indicators include carrier concentration, conductivity, and insulation resistance;

[0011] S3: Based on the theory of chemical reaction kinetics, establish a first mathematical relationship between the carrier concentration and environmental conditions;

[0012] S4: Based on the ion conduction mechanism, establish a second mathematical relationship between the carrier concentration, the conductivity, and the insulation resistance;

[0013] S5: Based on the first mathematical relationship and the second mathematical relationship, construct an accelerated degradation model for the silicone insulation performance;

[0014] S6: Based on the accelerated degradation model of the silicone insulation performance and the failure conditions, construct a reliability statistical model for the silicone insulation parts.

[0015] Second aspect:

[0016] A system for constructing a degradation model of silicone insulation performance provided by an embodiment of the present invention includes:

[0017] A processor;

[0018] A memory, on which computer-readable instructions are stored, and when the computer-readable instructions are executed by the processor, the method for constructing a degradation model of silicone insulation performance as described in the first aspect is implemented.

[0019] Third aspect:

[0020] A computer-readable storage medium provided by an embodiment of the present invention, on which a computer program is stored, and when the program is executed by a processor, the method for constructing a degradation model of silicone insulation performance as described in the first aspect is implemented.

[0021] The beneficial effects brought by the technical solution provided by the embodiment of the present invention at least include:

[0022] (1) In the embodiment of the present invention, by deeply analyzing the failure mechanism of the silicone insulation parts in the storage environment, combining the chemical reaction kinetics and the ion conduction mechanism, a mathematical relationship between the carrier concentration and environmental stress, conductivity, and insulation resistance is systematically established, and an accelerated degradation model of insulation performance supported by a physical mechanism is constructed. The model abandons the high dependence on specific data sets, significantly improves the prediction stability and generalization ability under different environmental conditions. At the same time, by revealing the microscopic physical and chemical mechanisms in the material degradation process, the accuracy of model prediction is effectively improved. Description of the Drawings

[0023] To more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the accompanying drawings required for the description of the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can be obtained based on these drawings.

[0024] Figure 1 It is a schematic flowchart of a method for constructing a silicone insulation performance degradation model provided by an embodiment of the present invention;

[0025] Figure 2 It is a schematic flowchart of a technical route provided by an embodiment of the present invention;

[0026] Figure 3 It is a schematic structural diagram of a system for constructing a silicone insulation performance degradation model provided by an embodiment of the present invention. Detailed implementation manners

[0027] The following will describe the technical solutions in the present invention with reference to the accompanying drawings.

[0028] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to represent examples, illustrations or explanations. Any embodiment or design solution described as an "example" in the present invention should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Exactly, the use of the word "example" is intended to present concepts in a specific way. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one of the two.

[0029] In the embodiments of the present invention, "image" and "picture" can sometimes be used interchangeably. It should be noted that when the difference is not emphasized, the meanings they express are the same. "(of)", "corresponding", and "corresponding" can sometimes be used interchangeably. It should be noted that when the difference is not emphasized, the meanings they express are the same.

[0030] In the embodiments of the present invention, sometimes subscripts such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meanings they express are the same.

[0031] To make the technical problems, technical solutions and advantages to be solved by the present invention clearer, the following will be described in detail with reference to the accompanying drawings and specific embodiments.

[0032] Refer to the attached specification Figure 1 , which shows a schematic flowchart of a method for constructing a silicone insulation performance degradation model provided by an embodiment of the present invention.

[0033] Refer to the attached specification Figure 2 , which shows a schematic flowchart of a technical route provided by an embodiment of the present invention.

[0034] An embodiment of the present invention provides a method for constructing a silicone insulation performance degradation model. This method can be implemented by a device for constructing a silicone insulation performance degradation model, and the device for constructing a silicone insulation performance degradation model can be a terminal or a server. The processing flow of the method for constructing a silicone insulation performance degradation model may include the following steps:

[0035] S1: Obtain the failure mechanism and failure conditions of the silicone insulation component in the storage environment.

[0036] Among them, the failure mechanism is that when the silicone insulation component is exposed to temperature and humidity stresses in the storage environment for a long time, a series of irreversible physical and chemical reactions will occur inside its material, ultimately leading to the degradation of insulation performance and the formation of failure.

[0037] In a possible implementation manner, the failure mechanism specifically includes:

[0038] High temperature accelerates the thermal oxygen aging and condensation cross-linking reaction of silicone, resulting in an increase in free ions.

[0039] A high-humidity environment triggers a hydrolysis reaction, forming a conductive path, thereby reducing the insulation resistance.

[0040] In a possible implementation manner, the failure condition is specifically:

[0041] In the storage environment, the insulation resistance value between adjacent contact pairs of the electrical connector decreases monotonically with time. When the insulation resistance value drops to the failure threshold, it is determined that the silicone insulation component has insulation failure.

[0042] In the embodiment of the present invention, by clarifying the failure mechanism and failure conditions of the silicone insulation component in the storage environment, a direct correlation can be established between the microscopic physical and chemical changes and the macroscopic performance degradation, which helps to construct a degradation model with physical significance and prediction ability.

[0043] S2: Through failure mechanism analysis, screen the key indicators affecting insulation performance. Among them, the key indicators include carrier concentration, conductivity, and insulation resistance.

[0044] Among them, failure mechanism analysis is a systematic study of the root causes of performance degradation of silicone insulation components in the storage environment, aiming to reveal the whole process of material evolution from microscopic reaction paths to macroscopic performance under the combined action of temperature and humidity.

[0045] Among them, carrier concentration is a physical quantity that describes the number of free charge carriers (such as electrons, ions, or holes) in a material and is usually used to characterize the electrical conductivity of the material. It is very important in the analysis of the electrical properties of semiconductors, conductors, and insulating materials.

[0046] Among them, conductivity is a physical quantity that measures the electrical conductivity of a material. It reflects the ability of the material to allow the movement of charge carriers (such as electrons, ions) inside the material and is a concept that is the reciprocal of resistivity.

[0047] Among them, insulation resistance is an important parameter that measures the ability of a material or component to block current. It represents the ability of the material to suppress leakage current under a certain voltage, and the unit is ohm (Ω). The higher the insulation resistance, the better the insulation performance of the material and the less likely the current is to pass through.

[0048] In the embodiments of the present invention, by screening key indicators such as carrier concentration, conductivity, and insulation resistance through an analysis method based on failure mechanisms, it is possible to ensure that the established performance model has physical interpretability and a causal logic basis. Compared with the selection of empirical parameters, this indicator screening method can more accurately reflect the dynamic relationship between the microscopic reactions (such as ion generation and migration) of the material and the macroscopic performance degradation (such as resistance decrease), which helps to construct a more adaptable and predictive insulation degradation model.

[0049] S3: Establish a first mathematical relationship between the carrier concentration and environmental conditions through the theory of chemical reaction kinetics.

[0050] Among them, the theory of chemical reaction kinetics is a scientific theory that studies the reaction rate, reaction process, and the relationship between the reaction rate and various influencing factors. It not only describes "the reaction will occur", but more importantly studies "how fast the reaction occurs", "what controls it", and "how it changes with conditions".

[0051] In a possible implementation manner, the environmental conditions include time, temperature, and humidity. S3 specifically includes:

[0052] S301: Determine the carrier concentration under temperature stress.

[0053] Specifically, according to the principle of chemical reaction kinetics, the reaction rate dN / dt and the concentration N of the reactant have the following relationship:

[0054]

[0055] Among them, d represents the differential operation, N represents the concentration of the 771 silica gel macromolecular group of the reactant, t represents time, and K represents the reaction rate constant.

[0056] Integrating Equation (1), the concentration N at time t can be obtained. t The relationship between N and the initial concentration N0 is as follows:

[0057]

[0058] Where N t represents the concentration of the reactant 771 silica gel macromolecular groups at time t, N0 is the initial concentration of the 771 silica gel macromolecular groups, and e represents the exponential function.

[0059] Since the carriers mainly come from the small molecular groups generated by the cross-linking reaction of the 771 silica gel macromolecular groups, it can be considered that the carrier concentration is inversely proportional to the concentration of the 771 silica gel macromolecular groups. Let the proportionality coefficient be λ1, then the relationship between the carrier concentration n1(t) and time is:

[0060]

[0061] Where n1(t) represents the carrier concentration and λ1 represents the first proportionality coefficient.

[0062] The thermal-oxidative aging reaction of the 771 silica gel side groups can be expressed by the following formula:

[0063] RSiCH3 + O2 → RSiCH2OOH (4-4).

[0064] Specifically, at high temperatures, oxygen reacts with the methyl groups of the 771 silica gel side chains, the hydrogen in the methyl groups is taken away to generate free radicals, and the free radicals combine with oxygen to form hydroperoxides.

[0065] According to the law of mass action, the oxidation rate is:

[0066]

[0067] Where NO2 represents the oxygen concentration in the storage environment.

[0068] In the storage environment, it can be considered that the oxygen concentration in the air is constant and its change is not considered. Therefore, integrating Equation (5) gives:

[0069]

[0070] Where ln represents the natural logarithm function with base e.

[0071] Similarly, it can be obtained that the carrier concentration is inversely proportional to the reactant concentration. Let the proportionality coefficient be λ2, and the relationship between the carrier concentration n2(t) and time is:

[0072]

[0073] Among them, \(n_2(t)\) represents the carrier concentration at time \(t\), and \(\lambda_2\) represents the second proportionality coefficient.

[0074] Under the action of environmental stress temperature, the main chain scission cross-linking reaction and the side group oxidation reaction of the 771 silicone rubber insulator for electrical connectors occur simultaneously, and there is a certain mutual promotion effect.

[0075] Therefore, the carrier concentration under temperature stress is jointly generated by the main chain scission and side group oxidation, and can be expressed as:

[0076]

[0077] Among them, \(n\) T (t) represents the carrier concentration under temperature stress.

[0078] In the embodiment of the present invention, by decomposing the carrier generation process under temperature stress into two typical reaction mechanisms of main chain scission cross-linking reaction and side group oxidation reaction, and respectively establishing a mathematical model based on the principle of chemical reaction kinetics, not only can the contribution of different chemical paths to the carrier concentration be accurately characterized, but also the characteristics of the simultaneous occurrence and synergistic effect of these two reactions in the actual storage environment can be truly reflected.

[0079] S302: Determine the carrier concentration under humidity stress.

[0080] Specifically, under the action of environmental humidity, the silanol groups at the ends of the 771 silicone rubber matrix macromolecules react with water molecules, and the hydrolysis reaction process is as follows:

[0081] -Si-OH + H2O → -Si-O - +H3O + (4-9).

[0082] Specifically, the silanol group (-Si-OH) reacts with water molecules, loses a proton to form a negatively charged siloxyl group (-Si-O-), and at the same time the water molecule combines with the proton to form a hydronium ion (H3O + ).

[0083] According to the law of mass action, the hydrolysis reaction rate is:

[0084]

[0085] Among them, \(N\) is the concentration of 771 silicone rubber macromolecular groups, and \(N\) H2O is the humidity in the storage environment.

[0086] For the convenience of calculation, ignoring the difference in the distribution of humidity inside the 771 silicone rubber and assuming that the humidity is uniformly distributed inside the material, integrating Equation (10) gives:

[0087]

[0088] Among them, ln represents the natural logarithm function with base e, and RH represents the environmental relative humidity.

[0089] Similarly, it can be obtained that the carrier concentration is inversely proportional to the reactant concentration. Let the proportionality coefficient be λ3, and the carrier concentration n3(t) at time t is:

[0090]

[0091] Among them, λ3 represents the third proportionality coefficient.

[0092] Under the action of humidity, in addition to the silanol at the end group of the 771 silica gel macromolecular group reacting with water molecules, the siloxane group in the main chain is also prone to hydrolysis reaction. The hydrolysis reaction process is shown as follows:

[0093] ROSi(CH3)2OSi(CH3)2OSi(CH3)2OR + H2O → OSi(CH3)2OH + ROSi(CH3)2OSi(CH3)2OH(4 - 13)

[0094] Specifically, in a humidity environment, the Si - O bond in the siloxane main chain reacts with water and decomposes into two products: a short chain with a silanol group at one end (OSi(CH3)2OH) and a siloxane retaining part of the main chain at the other end (ROSi(CH3)2OSi(CH3)2OH).

[0095] Similarly, it can be obtained that the carrier concentration n4(t) at time t is:

[0096]

[0097] Among them, λ4 represents the fourth proportionality coefficient.

[0098] For the 771 silica gel insulator used in the electrical connector, under the action of humidity, the hydrolysis reaction of silanol and the hydrolysis reaction of siloxane occur simultaneously and there is a certain interaction. The carrier concentration under humidity stress can be expressed as:

[0099]

[0100] In the embodiment of the present invention, by separately analyzing the influence of humidity stress on the carrier concentration, the mechanism of the hydrolysis reaction in the high - humidity environment on the degradation of the silica gel insulation performance can be clearly revealed. The chemical reactions induced by humidity (such as the hydrolysis of silanol or siloxane) will generate polar small molecules with conductive ability, thereby increasing the number of free ions in the material.

[0101] S303: Combine the carrier concentration under humidity stress and the carrier concentration under temperature stress to obtain the first mathematical relationship.

[0102] It should be noted that during long-term storage, the effects of temperature and humidity occur simultaneously and interact with each other, promoting the aging rate of 771 silica gel. Therefore, the total carrier concentration is generated by the combined action of temperature and humidity.

[0103] In a possible implementation manner, the first mathematical relationship is specifically:

[0104]

[0105] where n(t) represents the first mathematical relationship, n T (t) represents the carrier concentration under temperature stress, n RH (t) represents the carrier concentration under humidity stress, λ1 represents the first proportionality coefficient, λ2 represents the second proportionality coefficient, λ3 represents the third proportionality coefficient, λ4 represents the fourth proportionality coefficient, e represents the exponential function, N0 represents the initial concentration of the 771 silica gel macromolecular group, K represents the reaction rate constant, and RH represents the environmental relative humidity.

[0106] In the embodiments of the present invention, the two environmental factors of temperature and humidity that act simultaneously and interact with each other are unified into a mathematical model to comprehensively reflect their superposition and synergistic effects on the carrier concentration. By multiplying the two concentration expressions, not only the formula structure is simplified, but also the actual situation that temperature and humidity jointly accelerate the aging of silica gel and cause the continuous increase of carriers during long-term storage can be accurately expressed, making the model closer to the real degradation process and easier to be used for prediction and analysis.

[0107] S4: Through the ion conduction mechanism, establish a second mathematical relationship between the carrier concentration, conductivity, and insulation resistance.

[0108] In a possible implementation manner, S4 specifically includes:

[0109] S401: Determine the relationship between the insulation resistance and the conductivity.

[0110] S402: Determine the relationship between the conductivity and the carrier concentration.

[0111] Specifically, the insulation resistance can be expressed as the parallel value of the surface resistance and the volume resistance, that is:

[0112]

[0113] where r represents the insulation resistance, r s represents the insulation resistance, r v represents the volume resistance.

[0114] Resistance reflects the ability of a substance to impede the movement of electrons, and is proportional to the length of the material and inversely proportional to the area of the material. Therefore, from the definition of resistance, the calculation formulas for volume resistance and surface resistance are as follows:

[0115]

[0116] Among them, σ v represents volume conductivity, σ3 represents surface conductivity, L represents the hole pitch, that is, the shortest distance between two pins, A represents the cross-sectional area of the pin, A = dh, d is the diameter of the pin, and h is the thickness of the insulating part of the electrical connector.

[0117] Therefore, the expression for the insulation resistance of the electrical connector can be obtained as:

[0118]

[0119] The number of excess migrating ions generated per second along the direction of the electric field is

[0120]

[0121] Among them, Δn represents the number of excess migrating ions generated along the direction of the electric field, n represents the ion concentration, v represents the number of vibrations of the ions per second, U0 represents the average potential barrier that must be overcome when the ions transition, ΔU represents the change in the potential barrier caused by the applied electric field, k represents the Boltzmann constant, and T represents the absolute temperature.

[0122] When ΔU << kT, Then Equation (2-4) is rewritten as:

[0123]

[0124] Among them, δ represents the mean free path of the ions, q is the ion charge, and E represents the electric field strength.

[0125] The distance of each ion transition is δ, and the number of transitions generated along the direction of the electric field per second is more than that in the opposite direction by Δn. Then, under the action of the electric field, the macroscopic average migration velocity ν of the ions in the direction of the electric field is:

[0126]

[0127] The mobility μ is:

[0128]

[0129] From this, the expression for the conductivity of the 771 silicone rubber insulating part can be obtained as:

[0130]

[0131] Among them, σ represents the conductivity of the 771 silicone rubber insulator, and γ represents the carrier concentration.

[0132] Combining Equation (2-3) and Equation (2-8), the insulation resistance expression of the electrical connector can be obtained:

[0133]

[0134] Among them, r(t) represents the insulation resistance of the electrical connector, q1 represents the charge carried by the carriers in the volume conductivity respectively, q2 represents the charge carried by the carriers in the surface conductivity, δ1 represents the transition distance of the carriers in the volume conductivity respectively, and δ2 represents the transition distance of the carriers in the surface conductivity.

[0135] S403: Combining the relational expression between the insulation resistance and the conductivity and the relational expression between the conductivity and the carrier concentration, a second mathematical relational expression is obtained.

[0136] In the embodiment of the present invention, the change at the microscopic level inside the material (carrier concentration) can be mathematically related to the macroscopic electrical performance index (insulation resistance), so as to realize the quantifiable modeling from the microscopic mechanism to the macroscopic performance. By deriving step by step the relationships between the conductivity and the carrier concentration, and between the resistance and the conductivity, and then combining the two into a unified mathematical expression, it helps to accurately describe how the insulation performance degrades with environmental factors such as time, temperature, and humidity. This not only makes the model have a physical basis and engineering computability, but also provides a solid foundation for subsequent degradation trend prediction and reliability assessment.

[0137] S5: Based on the first mathematical relational expression and the second mathematical relational expression, an accelerated degradation model of the silicone rubber insulation performance is constructed.

[0138] In a possible implementation manner, the accelerated degradation model of the silicone rubber insulation performance is specifically:

[0139]

[0140] Among them, r(t) represents the accelerated degradation model of the silicone rubber insulation performance, r0 represents the initial value of the insulation resistance, e represents the exponential function, α represents the degradation rate of the insulation resistance, A, B, and C represent random coefficients, RH represents, and T represents the absolute temperature.

[0141] Specifically, according to the Maxwell-Boltzmann law, the frequency of activated molecules that can cross the energy barrier to react follows the Boltzmann distribution. The relationship between the reaction rate and the temperature is as follows:

[0142]

[0143] In the formula, Λ represents the frequency factor, ΔE represents the activation energy, k represents the Boltzmann constant, and T represents the absolute temperature.

[0144] Substituting Equation (5-1) into the insulation resistance expression gives:

[0145]

[0146] To make the model convenient for application, the above equation is simplified. Under the storage environment, the temperature change is small, the influence of temperature on the carrier mobility can be ignored, and the initial carrier concentration n_0 is determined by the initial state of the product. Therefore, the initial volume conductivity and surface conductivity can be regarded as constant values. When the material and process are determined, L, d, and h are all constant values. Let

[0147]

[0148] where r0 represents the initial value of the insulation resistance in terms of physical meaning. It can be seen that the hole pitch L has an impact on r0. Under the condition that other parameters are constant values, the larger the hole pitch, the larger the initial value.

[0149] Thus, the insulation resistance can be written as:

[0150]

[0151] To further facilitate statistical processing, let

[0152]

[0153] Then Equation (5-4) can be written as

[0154] r = r0·e -αt (5-6)

[0155] Equation (5-6) is the insulation performance degradation trajectory model of 771 silicone rubber. α is the degradation rate of the insulation performance. By organizing Equation (5-5), the relationship between the degradation rate and temperature and humidity can be obtained:

[0156]

[0157] where B = 2Λ, C = -ΔE / k, and T is the absolute temperature.

[0158] In summary, the insulation performance accelerated degradation model of 771 silicone rubber is:

[0159]

[0160] where r(t) represents the insulation performance accelerated degradation model of silicone rubber, r0 represents the initial value of the insulation resistance, e represents the exponential function, α represents the degradation rate of the insulation resistance, A, B, and C represent random coefficients, RH represents the environmental relative humidity, and T represents the absolute temperature.

[0161] In the embodiments of the present invention, the advantages of doing so are as follows: environmental stresses such as temperature and humidity can be directly introduced into the insulation performance degradation model in a mathematical form, and an accelerated degradation expression that not only conforms to the actual physical process but also is convenient for engineering calculations and life prediction can be constructed. By introducing the degradation rate α and expressing it as a function of temperature and humidity, the change trend of the insulation resistance under different storage environments can be flexibly described, enabling the model to have good environmental adaptability, adjustability, and prediction ability, and providing a scientific basis for product design, life assessment, and reliability analysis.

[0162] S6: Based on the accelerated degradation model of silicone insulation performance and the failure conditions, construct a reliability statistical model for silicone insulation parts.

[0163] In a possible implementation manner, S6 specifically includes:

[0164] S601: Define the insulation life of silicone insulation.

[0165] Specifically, in the storage environment, the insulation resistance between adjacent contact pairs of the electrical connector decreases monotonically with time. Let the failure threshold of the insulation resistance be D. If the insulation resistance value between adjacent contact pairs at time t is r(t), the insulation life is the time when the insulation resistance reaches the failure threshold:

[0166] T e =inf{t:r(t)≤D;t≥0}(6-1)

[0167] Among them, T e represents the insulation life.

[0168] In the embodiments of the present invention, by defining the insulation life as the time point when the insulation resistance first drops to the failure threshold, the continuously changing degradation process can be transformed into a clear failure criterion, providing a clear time-scale basis for subsequent life modeling and reliability assessment.

[0169] S602: Based on the accelerated degradation model of silicone insulation performance and the insulation life, deduce the life distribution function under a single contact pair.

[0170] Specifically, according to the formula r=r0·e -αt , the insulation life between adjacent contact pairs can be derived:

[0171]

[0172] Among them, the insulation life between adjacent contact pairs represents the insulation life between adjacent contact pairs.

[0173] If the initial value R0 of the insulation resistance of the electrical connector is a constant, the insulation life distribution function can be written as:

[0174]

[0175] Among them, F s (t) represents the insulation life distribution function.

[0176] S603: Construct a system life distribution model under multiple contact pairs, and determine the overall life distribution function according to the minimum extreme value theory.

[0177] Specifically, assume that there are m insulation resistance measurement points on a certain type of electrical connector, and the insulation life between the i-th adjacent contact pairs is Then the insulation life of the electrical connector is equal to the life between the adjacent contact pairs that fail first, that is The insulation life distribution function of the electrical connector can be written as:

[0178] t(t) = P{T≤t} = 1 - P{T≥t} = 1 - [1 - F e (t)] m (6 - 4)

[0179] Among them, F(t) represents the insulation life distribution function, and F e (t) represents the insulation life distribution function of a single contact pair.

[0180] In the embodiment of the present invention, the performance degradation process of the silicone insulation part during storage is quantified into a clear life distribution, and further extended from a single contact pair to a system-level life model of multiple contact pairs. This modeling method not only reflects the reasoning process from local components to the overall system, but also conforms to the reliability principle of "the first failure determines the system failure" in actual electrical connectors. By introducing the statistical distribution of the degradation rate and incorporating uncertainty into the model, the degradation volatility of materials under long-term storage can be more realistically reflected, and the prediction ability and risk assessment value of the model can be improved.

[0181] S604: Determine the reliability statistical model of the silicone insulation part based on the overall life distribution function.

[0182] In a possible implementation manner, the reliability statistical model of the silicone insulation part is specifically:

[0183]

[0184] Among them, R(t) represents the reliability statistical model of the silicone insulation part, F(t) represents the insulation life distribution function, Φ{} represents the standard normal distribution function, t represents time, r0 represents the initial value of the insulation resistance, D represents the failure threshold of the insulation resistance, μ α represents the logarithmic mean of the degradation rate, and σ α represents the logarithmic standard deviation of the insulation resistance degradation rate, and m represents the total number of insulation resistance measurement points.

[0185] In the embodiments of the present invention, the material degradation process, failure criteria, and statistical uncertainty are effectively integrated to construct a reliability function model with a physical basis, statistical completeness, and engineering usability. By introducing the standard normal distribution function and the number of contact pairs, this model can not only describe the probability of single-point failure but also quantify the failure risk of the entire electrical connector system at any time. At the same time, it takes into account the uncertainty of the degradation rate, improving the prediction accuracy and robustness of the model, and providing quantitative support for product life assessment, reliability design, and storage life management.

[0186] The beneficial effects brought by the technical solutions provided in the embodiments of the present invention at least include:

[0187] (1) In the embodiments of the present invention, by deeply analyzing the failure mechanism of the silicone insulating part in the storage environment, combining chemical reaction kinetics and ion conduction mechanism, a mathematical relationship between carrier concentration, environmental stress, conductivity, and insulation resistance is systematically established, and an insulation performance accelerated degradation model with physical mechanism support is constructed. The model abandons the high dependence on specific data sets, significantly improving the prediction stability and generalization ability under different environmental conditions. At the same time, by revealing the microscopic physical and chemical mechanisms in the material degradation process, the prediction accuracy of the model is effectively improved.

[0188] Refer to the attached Figure 3 description, which shows the structural schematic diagram of a construction system of a silicone insulation performance degradation model provided by the present invention.

[0189] The present invention also provides a construction system 20 of a silicone insulation performance degradation model, which is applied to the above-mentioned construction method of the silicone insulation performance degradation model, and includes:

[0190] A processor 201.

[0191] A memory 202, on which computer-readable instructions are stored. When the computer-readable instructions are executed by the processor 201, the construction method of the silicone insulation performance degradation model as in the method embodiment is realized.

[0192] The construction system 20 of the silicone insulation performance degradation model provided by the present invention can execute the above-mentioned construction method of the silicone insulation performance degradation model and achieve the same or similar technical effects. To avoid repetition, the present invention will not elaborate further.

[0193] The beneficial effects brought by the technical solutions provided in the embodiments of the present invention at least include:

[0194] (1) In the embodiment of the present invention, by deeply analyzing the failure mechanism of the silicone insulating part in the storage environment, combining the chemical reaction kinetics and the ion conduction mechanism, a mathematical relationship between the carrier concentration, environmental stress, conductivity and insulation resistance is systematically established, and an insulation performance accelerated degradation model supported by physical mechanisms is constructed. The model abandons the high dependence on specific data sets, significantly improving the prediction stability and generalization ability under different environmental conditions. At the same time, by revealing the microscopic physical and chemical mechanisms in the material degradation process, the accuracy of model prediction is effectively improved.

[0195] It should be understood that the processor in the embodiment of the present invention may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0196] It should also be understood that the memory in the embodiments of the present invention may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example but not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchlink DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0197] The above embodiments can be implemented in whole or in part by software, hardware (such as circuits), firmware, or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the processes or functions described in the embodiments of the present invention are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (such as infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more collections of available media. The available media can be magnetic media (such as floppy disks, hard disks, magnetic tapes), optical media (such as DVDs), or semiconductor media. The semiconductor media can be a solid-state drive.

[0198] It should be understood that the term "and / or" in this document is merely a description of the association relationship between associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. Here, A and B can be singular or plural. In addition, the character " / " in this document generally represents an "or" relationship between the associated objects before and after, but it may also represent an "and / or" relationship, which can be specifically understood with reference to the context before and after.

[0199] In the present invention, "at least one" means one or more, and "a plurality" means two or more. "At least one of the following" or its similar expressions refer to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, or c can represent: a, b, c, a - b, a - c, b - c, or a - b - c, where a, b, and c can be single or multiple.

[0200] It should be understood that in various embodiments of the present invention, the magnitudes of the sequence numbers of the above processes do not mean the order of execution, and the order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

[0201] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in connection with the embodiments disclosed herein can be implemented in electronic hardware, or in a combination of computer software and electronic hardware. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0202] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the devices, apparatuses, and units described above can refer to the corresponding processes in the foregoing method embodiments, and will not be elaborated herein.

[0203] In several embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of the devices or units can be electrical, mechanical, or other forms.

[0204] The units described as separate components may or may not be physically separated. The components shown as units may or may not be physical units, that is, they can be located in one place, or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0205] In addition, the functional units in the various embodiments of the present invention can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit.

[0206] If the above-mentioned functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks, or optical discs that can store program codes.

[0207] An embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, it implements the method for constructing a silicone insulation performance degradation model as described in the method embodiment.

[0208] The computer-readable storage medium provided by the present invention can implement the steps and effects of the method for constructing a silicone insulation performance degradation model in the above method embodiment. To avoid repetition, the present invention will not elaborate further.

[0209] The beneficial effects brought by the technical solution provided by the embodiments of the present invention at least include:

[0210] (1) In the embodiments of the present invention, by deeply analyzing the failure mechanism of silicone insulation components in the storage environment, combining chemical reaction kinetics and ion conduction mechanism, a mathematical relationship between carrier concentration and environmental stress, conductivity, and insulation resistance is systematically established, and an insulation performance accelerated degradation model supported by physical mechanisms is constructed. The model abandons the high dependence on specific data sets, significantly improving the prediction stability and generalization ability under different environmental conditions. At the same time, by revealing the microscopic physical and chemical mechanisms during the material degradation process, the accuracy of model prediction is effectively improved.

[0211] The above is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of changes or substitutions, which should all be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

[0212] The following points need to be explained:

[0213] (1) The accompanying drawings of the embodiments of the present invention only relate to the structures involved in the embodiments of the present invention, and other structures can refer to the usual designs.

[0214] (2) For clarity, in the drawings used to describe the embodiments of the present invention, the thickness of layers or regions is enlarged or reduced, that is, these drawings are not drawn to actual scale. It will be understood that when an element such as a layer, film, region, or substrate is referred to as being "on" or "under" another element, the element can be "directly" on or under the other element or intervening elements may be present.

[0215] (3) Without conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other to obtain new embodiments.

[0216] The above are only the specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. The protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A method for constructing a degradation model of the insulation performance of silicone rubber, characterized in that, Including: S1: Obtain the failure mechanism and failure conditions of the silicone insulating part in the storage environment; S2: Through failure mechanism analysis, screen the key indicators affecting insulation performance, where the key indicators include carrier concentration, conductivity, and insulation resistance; S3: Establish a first mathematical relationship between the carrier concentration and environmental conditions through the theory of chemical reaction kinetics; S4: Establish a second mathematical relationship between the carrier concentration, the conductivity, and the insulation resistance through the ion conduction mechanism; S5: Based on the first mathematical relationship and the second mathematical relationship, construct an accelerated degradation model of the silicone insulation performance; S6: Based on the accelerated degradation model of the silicone insulation performance and the failure conditions, construct a reliability statistical model of the silicone insulating part.

2. The method for constructing a silicone insulation performance degradation model according to claim 1, characterized in that The failure mechanism specifically includes: High temperature accelerates the thermal oxygen aging and condensation cross-linking reaction of silicone, resulting in an increase in free ions; A high-humidity environment triggers a hydrolysis reaction, forming a conductive path, thereby reducing the insulation resistance.

3. The method for constructing a silicone insulation performance degradation model according to claim 1, wherein, The failure conditions are specifically: In the storage environment, the insulation resistance value between adjacent contact pairs of the electrical connector decreases monotonically with time. When the insulation resistance value drops to the failure threshold, it is determined that the silicone insulating part has insulation failure.

4. The method for constructing a silicone insulation performance degradation model according to claim 1, characterized in that The environmental conditions include time, temperature, and humidity; S3 specifically includes: S301: Determine the carrier concentration under temperature stress; S302: Determine the carrier concentration under humidity stress; S303: Combine the carrier concentration under humidity stress and the carrier concentration under temperature stress to obtain the first mathematical relationship.

5. The method for constructing the silicone insulation performance degradation model according to claim 4, wherein, The first mathematical relationship is specifically: Among them, n(t) represents the first mathematical relationship, and n T (t) represents the carrier concentration under temperature stress, and n RH (t) represents the carrier concentration under humidity stress. λ1 represents the first proportionality coefficient, λ2 represents the second proportionality coefficient, λ3 represents the third proportionality coefficient, λ4 represents the fourth proportionality coefficient, e represents the exponential function, N0 represents the initial concentration of the 771 silicone macromolecular group, K represents the reaction rate constant, and RH represents the environmental relative humidity.

6. The method for constructing the silicone insulation performance degradation model according to claim 1, characterized in that, S4 specifically includes: S401: Determine the relationship between the insulation resistance and the conductivity; S402: Determine the relationship between the conductivity and the carrier concentration; S403: Combine the relationship between the insulation resistance and the conductivity and the relationship between the conductivity and the carrier concentration to obtain the second mathematical relationship.

7. The method for constructing the silicone insulation performance degradation model according to claim 1, characterized in that The accelerated degradation model of the silicone insulation performance is specifically: Where r(t) represents the accelerated degradation model of the silicone insulation performance, r0 represents the initial value of the insulation resistance, e represents the exponential function, α represents the degradation rate of the insulation resistance, A, B, and C represent random coefficients, RH represents the environmental relative humidity, and T represents the absolute temperature.

8. The method for constructing the silicone insulation performance degradation model according to claim 1, characterized in that S6 specifically includes: S601: Define the insulation life of the silicone insulation; S602: Based on the accelerated degradation model of the silicone insulation performance and the insulation life, deduce the life distribution function under a single contact pair; S603: Construct a system life distribution model under multiple contact pairs, and determine the overall life distribution function according to the minimum extreme value theory; S604: Based on the overall life distribution function, determine the reliability statistical model of the silicone insulating part.

9. The method for constructing a silicone insulation performance degradation model according to claim 8, wherein The reliability statistical model of the silicone insulating part is specifically: Among them, R(t) represents the reliability statistical model of the silicone rubber insulating part, F(t) represents the insulation life distribution function, Φ{} represents the standard normal distribution function, t represents time, r0 represents the initial value of the insulation resistance, D represents the failure threshold of the insulation resistance, μ α represents the logarithmic mean of the degradation rate, σ α represents the logarithmic standard deviation of the insulation resistance degradation rate, and m represents the total number of insulation resistance measurement points.

10. A construction system for a silicone insulation performance degradation model, characterized in that, Including: A processor; A memory, on which computer-readable instructions are stored. When the computer-readable instructions are executed by the processor, the method for constructing the degradation model of the silicone insulation performance as described in any one of claims 1 to 9 is implemented.

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