Steel cable whole-process life prediction method considering corrosion-fatigue coupling

Abstract

The embodiment of the invention discloses a steel cable whole-process life prediction method considering corrosion-fatigue coupling. The method comprises the steps that the initial stress of a to-be-predicted steel cable is acquired; randomly generating an initial crack depth x0 and a critical crack depth xc of each segment; according to the diffusion coefficient of steel wire metal ions to the corrosion solution, the saturated ion concentration of the metal solution in the pit, and the delta Kth and stress distribution of each section, calculating the time tc for the corrosion pit of each section to reach the critical corrosion pit depth; starting from the subsection with the shortest tc, sequentially executing the following operations according to time steps: determining a target subsection in a crack propagation stage in the current time step; loading a stress cycle with a set step length on the basis of x0 of each target segment, and calculating a crack propagation depth x after loading of each target segment; and judging whether x of each target segment reaches xc of each target segment or not, judging whether the steel wire is invalid or not, and finally obtaining the service life of the steel cable. The embodiment of the invention can improve the accuracy of steel cable life prediction.

Description

TECHNICAL FIELD

[0001] The embodiment of the present application relates to the technical field of steel cable life prediction, and particularly relates to a steel cable whole-process life prediction method considering corrosion-fatigue coupling. BACKGROUND

[0002] Large-span bridges are important infrastructures in modern transportation networks. Long-span structures such as cable-stayed bridges and suspension bridges achieve kilometer-level span through high-strength steel cable systems, breaking the bottleneck of traditional bridges limited by span and geological conditions. However, the steel cable system faces performance degradation challenges during the whole life cycle. As the key load transmission component connecting the bridge deck and the supporting structure, the steel cable continuously bears the dual effects of dynamic traffic load and environmental erosion during service.

[0003] The corrosion-fatigue damage caused by this environmental-mechanical coupling has significant characteristics of complex damage mechanism and concealed damage evolution. The damage process usually goes through three stages: local electrochemical corrosion caused by the failure of the initial protection system, micron-scale corrosion pits developing into crack sources under alternating stress (referred to as the corrosion stage); the wedge effect of corrosion products further accelerates the fracture process during crack propagation, eventually leading to sudden failure (referred to as the crack propagation stage); and the steel cable system failure stage, with the increase in the number of broken steel wires, stress redistribution increases the load of the remaining steel wires, and when the number of broken wires reaches a critical value, the whole steel cable fails.

[0004] For the above three stages, there are some life prediction methods in the prior art, but all have some limitations. Among them,

[0005] In the corrosion stage, Kondo et al. consider that the pit depth is proportional to the cube root of time t:

[0006] a = Bt 1 / 3 (1)

[0007] In the formula, a is the pit depth, and B is a coefficient related to the environment and the material. Formula (1) is a fitting result based on experimental data, reflecting the macroscopic pitting propagation behavior, but it does not reflect the micro-mechanism of corrosion. Harlow et al. simplified the shape of the pit as a hemisphere and derived a pit propagation model based on Faraday's law:

[0008]

[0009] In the formula, m c is the mass of the corroded metal in the steel wire, I is the corrosion current, Q is the charge quantity, M r is the molar mass of the metal, z is the valence, F is the Faraday constant, t is the time, and V is the pit volume (hemisphere), i.e. the volume of the corroded metal.

[0010] Thus, we can get:

[0011]

[0012] The specific expression of the coefficient B is obtained by combining formula (4) with Faraday's law, which reflects the micro-corrosion mechanism, but the assumption that the current I is a constant in the corrosion process does not conform to the actual situation.

[0013] In the crack propagation stage, the calculation is mainly based on the Paris formula, and the related research method is relatively mature. The material parameters C and m in the Paris formula have a great influence on the fatigue life and are related to the actual material. Many fatigue studies use empirical values, which are not accurate enough. For example, Ye et al. derived a fatigue strength prediction formula considering the influence of pit depth and stress ratio based on the Paris law. The method shows that the pit depth is the most critical parameter for representing the degree of corrosion and dominates the decrease of fatigue strength, and its influence is significantly greater than that of the pit shape. However, in the calculation process, the parameters C and m use the values from the European standard.

[0014] For steel cords, most of the current research methods for steel cords are based on the fiber bundle theory, which discretizes the steel cord into a series-parallel model for research. Stallings et al. based on the fiber bundle theory, discretized the steel cord into a parallel system of multiple steel wires, and each steel wire was further divided into a series of sub-unit chains; based on the Miner damage criterion, the life distribution of a single steel wire was established, and a steel cord life model was established by combining the stress redistribution mechanism of broken wires, and was verified by the Monte Carlo model. However, this model needs to know the life distribution of the steel wire, and does not consider the influence of corrosion.

[0015] In summary, the current steel cord fatigue life prediction methods have the following limitations:

[0016] The pitting model machine assumes too ideal: Kondo model is only a macroscopic empirical formula, which does not reveal the micro-electrochemical mechanism of corrosion; Harlow model is based on Faraday's law, but assumes that the corrosion current is constant, which does not conform to the actual dynamic diffusion process; fatigue parameters are empirical: the crack propagation stage relies on the Paris formula, but the key parameters C and m are mostly empirical values (such as European standards), which are not calibrated for actual material properties, resulting in life prediction deviation; corrosion-fatigue decoupling: existing fiber bundle models only consider mechanical fatigue wire breaking, ignoring the influence of corrosion on the performance degradation of steel wires, and need to preset the life distribution of steel wires, which limits the applicability. SUMMARY

[0017] The embodiments of the present application provide a steel cord whole process life prediction method considering corrosion-fatigue coupling to solve at least one of the above problems.

[0018] In a first aspect, the embodiments of the present application provide a steel cord whole process life prediction method considering corrosion-fatigue coupling, comprising:

[0019] Obtain the initial stress of the cable to be predicted and distribute it to each segment of each wire in the cable;

[0020] Randomly generate the stress intensity factor threshold ΔK for each segment. th and the fracture toughness K of steel wire C This allows for the calculation of the initial crack depth x0 and critical crack depth x0 for each segment. c ;

[0021] Based on the diffusion coefficient D of steel wire metal ions into the corrosive solution during the corrosion stage, the saturated ion concentration C of the metal solution in the pit... s and ΔK for each segment th And stress distribution, calculate the time t for each segment of the erosion pit to reach the critical erosion pit depth. c ;

[0022] From t c Starting with the shortest segment, the following operations are executed sequentially at each time step:

[0023] S1-1. Determine the target segment in the crack propagation stage within the current time step; apply stress cycles with a set step size based on x0 of each target segment, and calculate the crack propagation depth x of each target segment after loading;

[0024] S1-2, Determine whether x of each target segment has reached x of each target segment. c If the target is reached, determine the breakage of the steel wire in each target segment and record the cumulative lifespan N of the steel cable. sum,t If N sum,t The increase in cumulative cable life compared to the last recorded value and N sum,t If the ratio is less than the threshold E, the steel cable is considered to have failed, and N is set to... sum,t As the lifespan of the steel cable; if the ratio ≥ E, the stress of the broken wire is distributed to each segment of the unbroken wire, and each segment of the unbroken wire is placed at N. sum,t The crack depth is taken as the new x0, and the cycle continues into the next time step until the cable fails.

[0025] In a second aspect, embodiments of the present invention provide an electronic device, the electronic device comprising:

[0026] One or more processors;

[0027] Memory, used to store one or more programs.

[0028] When the one or more programs are executed by the one or more processors, the one or more processors implement the steel cable full-process life prediction method considering corrosion-fatigue coupling as described in any embodiment.

[0029] Thirdly, embodiments of the present invention also provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for predicting the life of steel cables throughout the entire process, taking into account corrosion-fatigue coupling, as described in any embodiment.

[0030] In summary, this embodiment provides a method for predicting the entire lifespan of steel cables considering corrosion-fatigue coupling. This method can:

[0031] 1. Based on Fick's diffusion law, an explicit relationship between pit depth a(t) and diffusion gradient is established; the diffusion effect of ions is considered. As the pit deepens, the path of metal ions diffusing into the solution becomes longer, which leads to the decay of corrosion current density j with increasing depth, breaking the constant current assumption.

[0032] 2. The SN curve is obtained based on the fatigue data of actual specimens. The Paris parameter C,m is inverted through the logarithmic linear mapping relationship, which can truly reflect the material properties and break through the limitations of empirical values ​​in the failure criteria of the cable system.

[0033] 3. Combining the series-parallel fiber bundle model, a full-process simulation of steel cables that can consider the effects of corrosion is proposed, which is more in line with the service scenarios of steel cables. In the simulation prediction, the influence of steel wire corrosion is considered and the corrosion stage life is calculated. Stress distribution and cumulative damage phenomena are considered. When the life added by a single wire break is less than a certain threshold of the cumulative life (such as 5%), the steel cable is judged to be in failure. The dynamic determination of whether the steel cable is in failure overcomes the empirical defects of the traditional critical wire breakage number. Attached Figure Description

[0034] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0035] Figure 1 This is a flowchart of a method for predicting the life of a steel cable throughout the entire process, considering corrosion-fatigue coupling, provided by an embodiment of the present invention.

[0036] Figure 2 This is a schematic diagram of a series-parallel connection model of steel cables provided in an embodiment of the present invention;

[0037] Figure 3 This is a flowchart of another method for predicting the life of steel cables throughout the entire process, which considers corrosion-fatigue coupling, provided by an embodiment of the present invention.

[0038] Figure 4This is a flowchart of another method for predicting the life of steel cables throughout the entire process, which considers corrosion-fatigue coupling, provided by an embodiment of the present invention.

[0039] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0040] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below. Obviously, the described embodiments are only a part of the embodiments of this invention, and not all of them. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0041] In the description of this invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0042] In the description of this invention, it should also be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0043] Figure 1 This is a flowchart illustrating a method for predicting the entire lifespan of a steel cable considering corrosion-fatigue coupling, provided by an embodiment of the present invention. This method is executed by electronic equipment. Figure 1 As shown, the method specifically includes:

[0044] S110. Construct a pitting rate model for steel wire.

[0045] Based on Faraday's law, we can obtain:

[0046] Q = nzF (5)

[0047] Where n is the amount of reactant, and in this embodiment, the reactant is steel wire metal.

[0048] Differentiating both sides of the transformed equation (5):

[0049]

[0050] The differential of the amount of reactant with respect to time is the chemical reaction rate, v, with units of mol / s. The differential of charge with respect to time is the current, I, with units of C·s. -1 Therefore, equation (6) can be rewritten as:

[0051]

[0052] Normalizing the electrode area yields:

[0053]

[0054] Where j is the current density, with units of C·s. -1 ·m -2 The unit of chemical reaction rate at this point is mol·m⁻². -2 ·s -1 This is the reaction rate corresponding to the current density, expressed in v. j express.

[0055] As the pit deepens, the path for metal ions to diffuse into the solution becomes longer, causing the corrosion current density j to decrease with increasing depth, obeying Fick's diffusion law. The expression for Fick's first law is:

[0056]

[0057] Where J is the ion flux, with units of mol·m -2 ·s -1 D is the diffusion coefficient, with units of m³. 2 ·s -1 C is the ion concentration, with units of mol·m⁻¹. -3 h is the distance perpendicular to the diffusion direction. The negative sign in equation (9) indicates the direction. In this embodiment, only scalars are calculated, so the negative sign is ignored in the subsequent derivation.

[0058] Let the ion concentration in the erosion pit be C. s The concentration of the bulk solution (i.e., the corrosion solution) is C. b And make the following assumptions:

[0059] (1) Metal dissolution within the corrosion pit generates high concentrations of ions (such as Fe). 2+ Al 3+ ), concentration C s When it is close to saturation, it is considered as saturation concentration.

[0060] (2) The bulk solution is located in a region far from the corrosion pit and can be considered an open system. The volume of the bulk solution is much larger than the volume of the corrosion pit, and the ions combine to form corrosion products, thus maintaining a low concentration relative to C. s As far as C is concerned, b ≈0.

[0061] Therefore, we get:

[0062]

[0063] Where a(t) represents the function of the pit depth a during the corrosion stage as a function of time t. Note that v j J and J have the same dimensions and are mathematically equivalent, therefore:

[0064]

[0065] During service, steel wire is not only affected by corrosion but also subjected to cyclic stress, which further exacerbates the corrosion process. Therefore, in this embodiment, the effect of stress on corrosion is equated to the effect of stress on current:

[0066] j σ =jc Δσ (12)

[0067] Where, j σ Δσ represents the current density as a function of stress, Δσ represents the stress range of the steel wire, and c represents an empirical coefficient related to the stress range, calculated based on experimental data, which can be taken as 1.0002.

[0068] The surface area A(t) of the hemispherical pit is:

[0069] A(t) = 2πa(t) 2 (13)

[0070] The total current I(t) is:

[0071]

[0072] The mass of dissolved metal m can be obtained from equation (3). c (t) is:

[0073]

[0074] From equation (2), we can obtain:

[0075]

[0076] In equation (16), I(t) is temporarily written as I(τ) to distinguish it from the upper and lower limits of integration.

[0077] Combined equations (15) and (16):

[0078]

[0079] Simplify equation (17) and differentiate both sides of the equation:

[0080]

[0081] Simplifying equation (18) yields:

[0082]

[0083] The deep time-varying laws were finally obtained:

[0084]

[0085] As the pit depth increases, the stress intensity factor at the bottom of the pit approaches the critical value for the pit-crack transition, and microcracks appear at the bottom of the pit. The stress intensity factor ΔK at the bottom of the pit... pit Calculate according to formula (21):

[0086]

[0087] Among them, K t This is the stress concentration factor generated by the circular rivet hole.

[0088] ΔK pit The stress intensity factor increases with increasing pit depth, and gradually increases to the stress intensity factor threshold ΔK. th At this point, cracks appear in the pit, and the depth is the critical pit depth a. c (Further steps will lead to cracks). Therefore, let ΔK pit =ΔK th The critical pit depth 'a' can be calculated by back-calculation. c :

[0089]

[0090] Combining equations (20) and (22), the service life of the corrosion stage can be obtained as follows:

[0091]

[0092] Among them, t c This indicates the time it takes for the pit to reach the critical pit depth, which is the lifespan of the corrosion stage.

[0093] Furthermore, in one specific embodiment, D and C s It can be measured in the following ways:

[0094] The Stokes-Einstein equations indicate that:

[0095]

[0096] Where, k B η is the Boltzmann constant, with a value of 1.38 × 10⁻²³ J / K, T is the temperature (K), η is the solution viscosity (Pa·s), and r is the radius of the hydrated ion (determined by referring to a table).

[0097] The viscosity of the solution is measured using a capillary viscometer. The time t it takes for the solution to flow through the capillary is compared with that of a reference liquid with a known viscosity (such as water, determined by referring to a table).

[0098]

[0099] That is, the test solution and water are passed through capillary tubes of the same length, and the time taken for each is t and t', respectively. 水 The density ρ of the solution to be tested and the density ρ of water are... 水 , and η 水 Since it is known, η can be measured.

[0100] In a saturated solution, due to the dissolution-precipitation equilibrium, the ion concentration at the electrode surface no longer changes netly with time. Therefore, the open circuit potential (OCP) of the electrode reaches a stable value that does not drift over time. This stable OCP value directly corresponds to the saturation concentration C. s .

[0101] Prepare a series of metal ion solutions with known concentrations (below the saturation concentration). For each concentration solution, measure the OCP value of the working electrode after it reaches stability, and obtain the relationship between the OCP value and the corresponding log(ion concentration).

[0102] Measuring the stable OCP in this saturated solution sat (It contains an excess of solid phase, ensuring a saturated state), substituting this into the previously established relationship, yields the corresponding C. s .

[0103] S120. Construct a model for the crack propagation rate of steel wire.

[0104] When the pitting reaches a critical size, cracks will initiate. Crack propagation follows the Paris equation.

[0105]

[0106] Where ΔK cra Y represents the stress intensity factor of the crack, Y represents the shape factor, and N represents the number of stress cycles.

[0107] Integrating equation (26) yields the fatigue life:

[0108]

[0109] To calculate fatigue life, determine the initial crack depth x0 and the critical crack depth x during the crack propagation stage. c , C, m.

[0110] Since cracks initiate at the critical pitting point, the critical pitting depth a c It can be considered as the initial crack x0.

[0111] And ΔK th Since x0 follows a normal distribution, the probability distribution F(X0) can be derived. However, its analytical expression is too complex; therefore, in this embodiment, the Monte Carlo method will be used to determine ΔK. th and x0.

[0112] steel wire fracture toughness K c Also following a normal distribution, the critical crack depth x c According to K c Iterative calculations yielded the following results:

[0113]

[0114] Where, σ max This represents the maximum stress during the loading process. The parameters C and m can be calculated by testing the SN curve. First, the Paris formula is simplified to:

[0115]

[0116] Separate variables and integrate:

[0117]

[0118] Simplifying, we get:

[0119]

[0120] set up:

[0121]

[0122] but:

[0123]

[0124] Take the logarithmic form:

[0125] logN=logH-mlogΔσ (36) The general form of the SN curve is:

[0126] Δσ m' ·N=C SN (37)

[0127] Or in logarithmic form:

[0128] logN = logC SN -m'logΔσ (38)

[0129] Among them, C SN denoted as fatigue strength coefficient, and m′ is the slope parameter in the SN curve.

[0130] Comparing the two equations, we can obtain:

[0131] m=m' (39)

[0132]

[0133] By subjecting steel wire to fatigue loading at different stress levels and plotting the data on a double logarithmic coordinate system, a linear relationship can be fitted. The parameters C and m can then be obtained from the slope and intercept of the relationship.

[0134] S130, Predict the life of steel cables.

[0135] After obtaining the wire failure model, the failure of the steel cable can be simulated and calculated based on fiber bundle theory. This embodiment uses a series-parallel model of the steel cable to progressively simulate and predict the failure of the wires in the cable until the cable's failure criteria are met. Specifically, the steel cable to be predicted is modeled as follows: Figure 2 The series-parallel model shown consists of n units of length l0 connected in series to form a single steel wire, and K steel wires of length L connected in parallel to form the entire steel cable.

[0136] Crack propagation is a high-cyclic fatigue problem, and stepwise cyclic analysis of high-cyclic fatigue requires significant computation time. Therefore, the skip-cycle method is used to simulate crack propagation.

[0137] First, determine the number of steel wires K, the number of elements n, and the initial load S. Then, based on the known parameter distribution, use the Monte Carlo method to randomly generate a set of data (including K×n ΔK values). th and K c The values ​​are combined and assigned to each wire unit (or segment). Finally, the pitting and crack propagation formulas in S110 and S120 are used to calculate and determine whether the wire has broken, and the corresponding fatigue life is recorded. When the additional fatigue life after the wire breaks is less than the set threshold E of the cumulative life (e.g., 5%, which can be adjusted according to actual conditions), it is considered that the remaining wires in the cable are breaking rapidly, and the cable is considered to have failed (continued use may cause the entire cable to break instantly).

[0138] Specifically, in combination Figure 3 ΔK for each segment th and K cOnce determined, ΔK is used for each segment. th and K C Calculate the initial crack depth x0 and critical crack depth x for each segment. c The specific method is shown in equations (22) and (30). In this case, Δσ in equation (22) is the stress distributed by the initial load S to each segment.

[0139] Then, based on the diffusion coefficient D of steel wire metal ions into the corrosive solution during the corrosion stage, the saturated ion concentration C of the metal solution in the pit... s and ΔK for each segment th And stress distribution (i.e. stress range), calculate the time t for each segment of the pit to reach the critical pit depth. c The specific calculation method is shown in equation (23).

[0140] Next, from t c Starting with the shortest segment, the following operations are executed sequentially at each time step:

[0141] S1-1. Determine the target segment in the crack propagation stage within the current time step; apply stress cycles with a set step size based on x0 of each target segment, and calculate the crack propagation depth x of each target segment after loading. Specifically, for each segment, t... c The timing of each segment entering the crack propagation stage is not necessarily the same, therefore the timing also differs. c The smallest segment enters the crack propagation stage first. Stress cycles are applied based on the x0 value of this segment, and x is calculated. Segments that have not yet entered the crack propagation stage remain in the corrosion stage, and crack propagation does not need to be calculated. Therefore, this embodiment first determines which segments have entered the crack propagation stage within the current time step.

[0142] Optionally, select the shortest t among the segments. c The simulation begins at time t0, which is the first time step. The duration of the stress cycle with a set step length applied in each time step is taken as the simulation duration Δt for each time step. Based on the simulated start time and simulation duration, the simulation start time t0 + uΔt for the current time step can be calculated, where u represents the number of time steps calculated before the current time step. If the current time step is the first time step, then u = 1. Then, for each segment that has not yet entered the crack propagation stage, the following judgment is made: if the t0 of this segment... c If the time interval is less than or equal to the start time of the simulation at the current time step, then the segment has entered the crack propagation stage at the current time step. For ease of distinction and description, each segment that enters the crack propagation stage within each time step is referred to as the target segment.

[0143] Then, for each target segment, the crack propagation depth of each segment at the end of the simulated duration in the current time step is calculated. The calculation method is as follows:

[0144] x = x0 + ∑C(ΔK) cra ) m ΔN (41)

[0145] Where ΔN represents the stress cyclic loading step size for each time step, that is, ΔN stress cycles are applied for each time step.

[0146] S1-2, Determine whether x of each target segment reaches x of each target segment. c Specifically, for each target segment:

[0147] If x <x c This indicates that the current target segment is not broken.

[0148] If x≥x c This indicates that the current target segment and the steel wire it belongs to have broken. At this point, the minimum fatigue life of all segments within that steel wire is taken as the fatigue life of the steel wire. Simultaneously, the cumulative fatigue life N of the cable at the time of wire breakage is recorded. sum,t And calculate the cumulative life N of the steel cable recorded in this instance. sum,t Compared to the previous record, the cumulative lifespan of the steel cable N sum,t-1 The percentage R of the increase in the cumulative lifespan of the steel cable recorded in this study is:

[0149]

[0150] If R is less than the set threshold E (e.g., 5%), it is determined that the steel wire will break rapidly in a short time, and the steel cable will fail. In this case, N... sum,t That is, the final lifespan of the steel cable.

[0151] If R is greater than or equal to the set threshold E, the cable is determined not to have failed. The stress originally borne by the broken wire is then distributed to the segments of the unbroken wire; and the stress is then determined based on the stress on each segment of the unbroken wire at N. sum,t The crack depth at time step (i.e., x at that time) is used as the new x0, and the cycle continues into the next time step. This cycle repeats until the cable fails, yielding the final wire life.

[0152] The entire process described above is also a simulation of cable failure, and it can be combined with... Figure 4 This is understandable, among which, Figure 4 N in wire N refers to the cumulative lifespan of the steel wire after each breakage. wire / N sum This is equivalent to the R mentioned above.

[0153] In summary, this embodiment provides a method for predicting the entire lifespan of steel cables considering corrosion-fatigue coupling. This method can:

[0154] 1. Based on Fick's diffusion law, an explicit relationship between pit depth a(t) and diffusion gradient is established; the diffusion effect of ions is considered. As the pit deepens, the path of metal ions diffusing into the solution becomes longer, which leads to the decay of corrosion current density j with increasing depth, breaking the constant current assumption.

[0155] 2. The SN curve is obtained based on the fatigue data of actual specimens. The Paris parameter C,m is inverted through the log-linear mapping relationship (Equation 38-40), which can truly reflect the material properties and break through the limitations of empirical values ​​in the failure criteria of the cable system.

[0156] 3. Combining the series-parallel fiber bundle model, a full-process simulation of steel cables that can consider the effects of corrosion is proposed, which is more in line with the service scenarios of steel cables. In the simulation prediction, the influence of steel wire corrosion is considered and the corrosion stage life is calculated. Stress distribution and cumulative damage phenomena are considered. When the life added by a single wire break is less than a certain threshold of the cumulative life (such as 5%), the steel cable is judged to be in failure. The dynamic determination of whether the steel cable is in failure overcomes the empirical defects of the traditional critical wire breakage number.

[0157] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention, such as... Figure 5 As shown, the device includes a processor 60, a memory 61, an input device 62, and an output device 63; the number of processors 60 in the device can be one or more. Figure 5 Taking a processor 60 as an example; the processor 60, memory 61, input device 62, and output device 63 in the device can be connected via a bus or other means. Figure 5 Taking the example of a connection between China and Israel via a bus.

[0158] The memory 61, as a computer-readable storage medium, can be used to store software programs, computer-executable programs, and modules, such as the program instructions / modules corresponding to the corrosion-fatigue coupling-considered steel cable life prediction method in this embodiment of the invention. The processor 60 executes various functional applications and data processing of the device by running the software programs, instructions, and modules stored in the memory 61, thereby realizing the aforementioned corrosion-fatigue coupling-considered steel cable life prediction method.

[0159] The memory 61 may primarily include a program storage area and a data storage area. The program storage area may store the operating system and at least one application program required for a given function; the data storage area may store data created based on terminal usage. Furthermore, the memory 61 may include high-speed random access memory and non-volatile memory, such as at least one disk storage device, flash memory, or other non-volatile solid-state storage device. In some instances, the memory 61 may further include memory remotely located relative to the processor 60, which can be connected to the device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0160] Input device 62 can be used to receive input digital or character information, and to generate key signal inputs related to user settings and function control of the device. Output device 63 may include display devices such as a display screen.

[0161] This invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steel cable full-process life prediction method considering corrosion-fatigue coupling of any embodiment.

[0162] The computer storage medium of this invention can be any combination of one or more computer-readable media. A computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0163] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, capable of sending, propagating, or transmitting programs for use by or in connection with an instruction execution system, apparatus, or device.

[0164] Program code contained on a computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0165] Computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof. Programming languages ​​include object-oriented programming languages—such as Java, Smalltalk, and C++—as well as conventional procedural programming languages—such as C or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0166] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the technical solutions of the embodiments of the present invention.

Claims

1. A method for predicting the lifespan of steel cables throughout the entire process, considering corrosion-fatigue coupling, characterized in that, include: Obtain the initial stress of the cable to be predicted and distribute it to each segment of each wire in the cable; Randomly generate the stress intensity factor threshold ΔK for each segment. th and the fracture toughness K of steel wire C This allows for the calculation of the initial crack depth x0 and critical crack depth x0 for each segment. c ; Based on the diffusion coefficient D of steel wire metal ions into the corrosive solution during the corrosion stage, the saturated ion concentration C of the metal solution in the pit... s and ΔK for each segment th And stress distribution, calculate the time t for each segment of the erosion pit to reach the critical erosion pit depth. c ; From t c Starting with the shortest segment, the following operations are executed sequentially at each time step: S1-1. Determine the target segment in the crack propagation stage within the current time step; apply stress cycles with a set step size based on x0 of each target segment, and calculate the crack propagation depth x of each target segment after loading; S1-2, Determine whether x of each target segment has reached x of each target segment. c If the target is reached, determine the breakage of the steel wire in each target segment and record the cumulative lifespan N of the steel cable. sum,t If N sum,t The increase in cumulative cable life compared to the last recorded value and N sum,t If the ratio is less than the threshold E, the steel cable is considered to have failed, and N is set to... sum,t As the lifespan of the steel cable; if the ratio ≥ E, the stress of the broken wire is distributed to each segment of the unbroken wire, and each segment of the unbroken wire is placed at N. sum,t The crack depth is taken as the new x0, and the cycle continues into the next time step until the cable fails.

2. The method according to claim 1, characterized in that, S1-1 includes: The time t for the current segment to reach the critical pit depth is calculated using the following formula. c : Where ρ represents the density of the steel wire, M r Let K represent the molar mass of the steel wire metal, Δσ represent the stress range of the steel wire, c represent an empirical coefficient related to the stress range, and K represent the stress range. t This represents the stress concentration factor generated by the circular rivet hole.

3. The method according to claim 1, characterized in that, Before S1-1, it also includes: Based on Faraday's law and Fick's first law, the expansion law of the pit depth *a* during the corrosion stage of steel wire with time *t* is derived as follows: Calculate the critical pit depth 'a' using the following formula. c : In equation (22), a c Substituting a(t) into equation (20), we obtain equation (23).

4. The method according to claim 3, characterized in that, Based on Faraday's law and Fick's first law, the expansion law of the pit depth 'a' during the corrosion stage of steel wire with time 't' is derived, including: According to Faraday's law and Fick's first law, the expansion law of the pit depth 'a' during the corrosion stage of steel wire with time 't' is obtained, and a(t) satisfies the following formula: Where j represents the current density during the corrosion process, z represents the valence, and F represents the Faraday constant; By equating the promotion of corrosion by stress with the promotion of current by stress, the current density j as a function of stress is obtained. σ : j σ =jc Δσ (12) Based on equations (11) and (12), and the pit expansion model based on Faraday's theorem, equation (20) is obtained.

5. The method according to claim 4, characterized in that, Based on equations (11) and (12), and the pit expansion model based on Faraday's theorem, equation (20) is obtained, which includes: According to equations (11) and (12), the total current I(t) during the corrosion process is obtained: Where A(t) represents the surface area of ​​the hemispherical pit; According to the pit propagation model based on Faraday's theorem, we have: Where, m c (t) represents the mass of soluble metal; Will Substituting into equation (16), we have: Differentiating and simplifying equation (17), we obtain equation (20).

6. The method according to claim 1, characterized in that, The determination of the target segment in the crack propagation stage within the current time step includes: Find the shortest t in each segment c As the starting moment simulated in the first time step; The duration of the stress cycle with a set step length applied at each time step is taken as the duration of the simulation at each time step. Calculate the start time of the simulation at the current time step based on the simulated start time and the simulated duration. If any segment t c Any segment that is less than or equal to the start time simulated at the current time step is a target segment in the crack propagation stage.

7. The method according to claim 1, characterized in that, S1-2 includes: Calculate the crack propagation depth x of the current segment using the following formula: x=x0+∑C(ΔK cra ) m ΔN Where C and m represent the material parameters of the steel wire, Δk cra ΔN represents the stress intensity factor of the crack, and ΔN represents the loading step size of the stress cycle.

8. The method according to claim 7, characterized in that, Before calculating the crack propagation depth x of the current segment according to the following formula, the method further includes: Pre-determine the SN curve of the steel wire: logN=logC SN -m'logΔσ Where N represents the number of stress cycles, Δσ represents the stress range of the steel wire, and C SN This represents the fatigue strength coefficient, and m′ is the slope parameter in the SN curve; Based on the slope and intercept of the SN curve, m′ and C are obtained. SN ; C and m are obtained using the following formula: m = m' Where, x c Y represents the critical crack of the steel wire, and Y represents the shape factor.

9. An electronic device, characterized in that, The electronic device includes: One or more processors; Memory, used to store one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the steel cable full-process life prediction method considering corrosion-fatigue coupling as described in any one of claims 1-8.

10. A computer-readable storage medium, characterized in that, It stores a computer program that, when executed by a processor, implements the method for predicting the life of steel cables throughout the entire process, taking into account corrosion-fatigue coupling, as described in any one of claims 1-8.

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