String vibration multi-modal fatigue life prediction method and system

Abstract

The application discloses a string vibration multi-modal fatigue life prediction method and system, belongs to the technical field of structure fatigue life prediction, and comprises the following steps: acquiring characteristic data of a string structure, curvature in multi-modal vibration time and environmental data of an environment where the string structure is located; generating dynamic stress of a structure point of the string structure according to the characteristic data of the string structure and the curvature in multi-modal vibration time; performing rain flow counting method processing on the dynamic stress to analyze complete stress cycles, wherein the stress cycles comprise stress amplitudes and average stresses; generating equivalent zero average stress amplitudes according to the stress amplitudes and the average stresses; generating an initial fatigue damage value of the structure point of the string structure according to the equivalent zero average stress amplitudes; generating an environmental influence factor according to environmental parameters of the environment where the string structure is located; and generating a fatigue life prediction value of the string structure according to the initial fatigue damage value of the structure point of the string structure and the environmental influence factor. The application has the advantages of improving the accuracy of fatigue life prediction under multi-modal vibration and complex environmental conditions.

Description

Technical Field

[0001] This invention belongs to the field of structural fatigue life prediction technology, and particularly relates to a method and system for predicting the fatigue life of string vibration multimodal. Background Technology

[0002] String structures, as key load-bearing components, play a core role in aerospace, bridge engineering, and precision instrument manufacturing. In actual operation, these structures are often exposed to multi-frequency excitation sources, leading to multimodal vibration coupling and resulting in a highly nonlinear alternating stress field within the material. Multimodal vibration not only causes spatial heterogeneity in stress distribution but also generates complex transient stress waves due to intermodal interference effects, significantly accelerating the initiation and propagation of microcracks.

[0003] Traditional fatigue life assessment systems primarily rely on simplified single-mode models, extracting peak stress amplitudes from a single vibration mode and performing linear extrapolation using static SN curves. This approach suffers from fundamental flaws when dealing with multimodal superposition problems: First, the single-mode assumption completely ignores the superposition characteristics of curvature distributions across modes, failing to reconstruct the dynamic stress evolution trajectory of structural points during vibration. Second, existing stress cycle statistical techniques using the rainflow counting method rely solely on empirical coefficients for correcting non-zero mean stress, failing to establish an accurate mapping between mean stress and equivalent zero-mean stress amplitude. Third, the environmental factor handling mechanism is severely lagging; the dynamic interaction between the temperature field and corrosive media is simplified to a fixed safety factor, failing to quantify the time-varying impact of temperature gradients on material activation energy or analyze the nonlinear correlation between corrosion progress and cumulative exposure time. Especially under extreme conditions, transient fluctuations in environmental parameters significantly alter the material's microstructure, and traditional models lack the ability to model the temperature-corrosion coupling effect in real time, leading to systematic deviations between predicted results and actual damage states. This theoretical limitation is particularly pronounced in long-term service string structures, potentially leading to unexpected and sudden failures. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a method and system for predicting the multimodal fatigue life of string vibrations, thus solving the aforementioned problems.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a method for predicting the multimodal fatigue life of string vibration, specifically comprising the following steps:

[0006] Acquire characteristic data of the string structure, curvature during multimodal vibration, and environmental data of the environment in which the string structure is located; among which, the characteristic data includes the Young's modulus and characteristic thickness of the string structure material; the curvature during multimodal vibration refers to the curvature change relative to the static shape of the string structure when it is not vibrating;

[0007] Based on the characteristic data of the string structure and the curvature during multimodal vibration, the dynamic stress at the structural points of the string structure is generated.

[0008] The dynamic stress at the structural points of the string structure is processed by the rainflow counting method to analyze the complete stress cycle, which includes stress amplitude and average stress.

[0009] Based on the stress amplitude and the average stress, an equivalent zero average stress amplitude is generated;

[0010] Based on the material reference SN curve of the string structure, the initial fatigue damage value of the structural point of the string structure is generated according to the equivalent zero mean stress amplitude.

[0011] Based on the environmental parameters of the environment in which the string structure is located, an environmental impact analysis model is established to generate environmental impact factors; among them, environmental data include environmental temperature and environmental corrosivity parameters; environmental corrosion intensity refers to environmental parameters that can cause corrosion to the string structure;

[0012] A fatigue life analysis model is established based on the initial fatigue damage values ​​of the structural points of the string structure and environmental impact factors, and the predicted fatigue life value of the string structure is generated.

[0013] Based on the above technical solutions, the present invention also provides the following optional technical solutions:

[0014] Further technical solution: The specific methods for generating dynamic stress at the structural points of the string structure include:

[0015] Through the formula:

[0016]

[0017] Dynamic stress at structural points of the generated string structure ;

[0018] In the formula, E represents the Young's modulus of the string structure material, d represents the characteristic thickness of the string structure material, and n is a constant term. This represents the curvature of the i-th mode of the string structure at position x. This represents the generalized coordinates of the i-th mode of the string structure; where the generalized coordinates are dimensionless parameters characterizing the temporal evolution of the mode amplitude, used to dynamically quantify the contribution ratio of the i-th mode in the vibration response.

[0019] Further technical solution: The method for generating the equivalent zero average stress amplitude specifically includes:

[0020] Through the formula:

[0021]

[0022] Generating equivalent zero mean stress amplitude ;

[0023] In the formula, This represents the stress amplitude. This represents the average stress. This represents the ultimate tensile strength of a string structure material at room temperature.

[0024] Further technical solution: The method for generating the initial fatigue damage value of the structural point of the string structure specifically includes:

[0025] Through the formula:

[0026]

[0027] Initial fatigue damage values ​​of structural points in the generated string structure ;

[0028] In the formula, This represents the equivalent zero mean stress amplitude. The number of stress cycles that occur. This indicates the equivalent zero mean stress amplitude. The number of cycles required to cause material failure, k represents the total number of different equivalent zero mean stress amplitudes identified within the time period t, and j is the index of the different equivalent zero mean stress amplitudes; where, in the equivalent zero mean stress amplitude The number of cycles required to cause material failure It is obtained based on the material reference SN curve of the string structure.

[0029] Further technical solutions: The specific methods for generating the environmental impact factors include:

[0030] Based on the ambient temperature, generate temperature influence factors;

[0031] Based on environmental corrosivity parameters, generate corrosion influencing factors;

[0032] An environmental impact analysis model is established based on temperature and corrosion factors to generate environmental impact factors.

[0033] The specific expression of the environmental impact analysis model is as follows:

[0034]

[0035] In the expression, This represents environmental impact factors. This represents the temperature influence factor. This represents the corrosiveness factor.

[0036] Further technical solution: The specific method for generating the temperature influence factor includes:

[0037] Through the formula:

[0038]

[0039] Generation temperature influence factor ;

[0040] In the formula, Q represents the activation energy of the string structure material, and R represents the ideal gas constant. The value represents the reference temperature, while T represents the current ambient temperature.

[0041] Further technical solution: The specific method for generating the corrosive influencing factor includes:

[0042] Through the formula:

[0043]

[0044] Corrosive Influencing Factors ;

[0045] In the formula, This represents the corrosive influence factor caused by the corrosive environment P within time t. This represents a function of the short-term corrosion time constant. This represents a function of the long-term corrosion time constant. This represents the cumulative exposure time of the string structure. A is the short-term amplitude coefficient, and B is the long-term amplitude coefficient. The amplitude coefficient refers to the maximum damage ratio that the corrosion effect can achieve.

[0046] Further technical solution: The method for generating the fatigue life prediction value of the string structure specifically includes:

[0047] Based on the initial fatigue damage values ​​of the structural points of the string structure and the environmental impact factors, a comprehensive fatigue damage value is generated;

[0048] A fatigue life analysis model is established based on the comprehensive fatigue damage value to generate the predicted fatigue life value of the string structure.

[0049] Further technical solutions: The method for generating the comprehensive fatigue damage value specifically includes:

[0050] Through the formula:

[0051]

[0052] Generate comprehensive fatigue damage value ;

[0053] In the formula, This represents the initial fatigue damage value at a structural point in the string structure. This represents environmental impact factors;

[0054] The specific expression of the fatigue life analysis model is as follows:

[0055]

[0056] In the expression, This represents the predicted fatigue life value for a string structure. This represents the critical damage value for fatigue failure of the string structure. This represents the overall fatigue damage value within a time period t. This represents the cumulative total fatigue damage value over time. dt represents the increment of the overall fatigue damage value, and dt represents the increment of the overall fatigue damage value at the current moment. The length of the time window, This represents the current rate of damage accumulation in the string structure.

[0057] A multimodal fatigue life prediction system for string vibration, which is used to execute the aforementioned multimodal fatigue life prediction method for string vibration, specifically includes:

[0058] The data acquisition unit is used to acquire characteristic data of the string structure, curvature during multimodal vibration, and environmental data of the environment in which the string structure is located. Among them, the characteristic data includes the Young's modulus and characteristic thickness of the string structure material; the curvature during multimodal vibration refers to the curvature change relative to the static shape of the string structure when it is not vibrating.

[0059] The dynamic stress analysis unit is used to generate dynamic stress at structural points of the string structure based on the characteristic data of the string structure and the curvature during multimodal vibration.

[0060] The stress cycle analysis unit is used to process the dynamic stress of the structural points of the string structure using the rainflow counting method, and to analyze the complete stress cycle, which includes stress amplitude and average stress.

[0061] The equivalent zero mean stress amplitude generation unit is used to generate the equivalent zero mean stress amplitude based on the stress amplitude and the mean stress.

[0062] The preliminary fatigue damage analysis unit is used to generate the initial fatigue damage values ​​of the structural points of the string structure based on the material reference SN curve of the string structure and the equivalent zero mean stress amplitude.

[0063] The environmental impact analysis unit is used to establish an environmental impact analysis model and generate environmental impact factors based on the environmental parameters of the environment in which the string structure is located. Among them, the environmental data includes environmental temperature and environmental corrosivity parameters; environmental corrosion intensity refers to environmental parameters that can cause corrosion to the string structure.

[0064] The fatigue life prediction unit is used to establish a fatigue life analysis model based on the initial fatigue damage values ​​of the structural points of the string structure and environmental impact factors, and to generate the fatigue life prediction value of the string structure.

[0065] This invention provides a method and system for predicting the multimodal fatigue life of string vibration, which has the following advantages compared with the prior art:

[0066] This invention integrates multimodal vibration curvature analysis, accurate equivalent zero mean stress amplitude generation, and dynamic quantification of environmental influence factors to achieve high-precision prediction of fatigue life of string structures. It has the advantage of improving the accuracy of fatigue life prediction under multimodal vibration and complex environmental conditions. Attached Figure Description

[0067] Figure 1 This is a flowchart illustrating the multimodal fatigue life prediction method for string vibration provided by the present invention.

[0068] Figure 2 This is a schematic diagram of the structure of the string vibration multimodal fatigue life prediction system provided by the present invention. Detailed Implementation

[0069] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0070] The specific implementation of the present invention will be described in detail below with reference to specific embodiments.

[0071] Please see Figure 1 The method for predicting the multimodal fatigue life of string vibration provided in one embodiment of the present invention specifically includes the following steps:

[0072] Step S10: Obtain the characteristic data of the string structure, the curvature during multimodal vibration, and the environmental data of the environment in which the string structure is located; wherein, the characteristic data includes the Young's modulus and characteristic thickness of the string structure material; the curvature during multimodal vibration refers to the curvature change relative to the static shape of the string structure when it is not vibrating;

[0073] Step S20: Based on the characteristic data of the string structure and the curvature during multimodal vibration, generate the dynamic stress at the structural points of the string structure;

[0074] Step S30: The dynamic stress at the structural points of the string structure is processed by the rainflow counting method to analyze the complete stress cycle, which includes stress amplitude and average stress.

[0075] Step S40: Generate an equivalent zero mean stress amplitude based on the stress amplitude and mean stress;

[0076] Step S50: Based on the material reference SN curve of the string structure, generate the initial fatigue damage value of the structural point of the string structure according to the equivalent zero mean stress amplitude;

[0077] Step S60: Based on the environmental parameters of the environment in which the string structure is located, establish an environmental impact analysis model and generate environmental impact factors; among which, environmental data include environmental temperature and environmental corrosivity parameters; environmental corrosion intensity refers to environmental parameters that can cause corrosion to the string structure, such as the pH value of the solution, chloride ion concentration, relative humidity, etc., which can be determined according to the corrosion resistance characteristics of the string structure, such as the string structure material being easily corroded in an acidic environment;

[0078] Step S70: Establish a fatigue life analysis model based on the initial fatigue damage values ​​of the structural points of the string structure and environmental influence factors, and generate the predicted fatigue life value of the string structure;

[0079] In this embodiment, the curvature during multimodal vibration refers to the change in curvature of the string structure relative to its static shape during vibration. This can be achieved using non-contact optical measurement techniques, such as capturing the surface deformation of the string structure and calculating the curvature distribution using a high-speed camera system combined with digital image correlation, or using a fiber optic grating sensor array to monitor the curvature changes at each location in real time. The main purpose is to achieve accurate characterization of the complex stress state generated by the superposition of multimodal vibrations.

[0080] Furthermore, rainflow counting refers to the process of cyclically counting dynamic stress data to extract complete stress cycles. This can be implemented using software algorithms, such as using the four-point rainflow counting program defined in the international standard ISO12110-2 to cyclically identify discrete stress data, or using a custom numerical script to cyclically decompose the dynamic stress time history. The main purpose is to achieve reliable extraction of stress amplitude and average stress.

[0081] The generation of equivalent zero mean stress amplitude refers to converting non-zero mean stress cycles into stress amplitudes under equivalent zero mean stress conditions. Its main purpose is to achieve accurate correction of the non-zero mean stress effect.

[0082] The generation of environmental impact factors refers to the coefficients that quantify the influence of environmental parameters on fatigue performance, mainly to achieve dynamic modeling of environmental temperature changes and corrosion factors.

[0083] This invention systematically solves the shortcomings of traditional methods in terms of multimodal stress superposition, non-zero average stress effect, and environmental impact by integrating multimodal vibration characteristics, mean stress correction mechanism, and dynamic modeling of environmental factors.

[0084] As a preferred implementation, this embodiment uses Young's modulus and characteristic thickness as the basis for material and geometric parameters when acquiring characteristic data. It correlates multimodal curvature changes when generating dynamic stress and incorporates environmental temperature and corrosivity parameters when establishing the environmental impact analysis model. This enables a comprehensive prediction of the fatigue damage accumulation process of the string structure. Therefore, this embodiment avoids the limitations of single-mode vibration analysis, ensures accurate quantification of stress state under multimodal vibration, and achieves dynamic impact assessment of environmental factors.

[0085] In practical applications, the multimodal fatigue life prediction method for string vibration achieves accurate assessment of the fatigue behavior of string structures through a systematic process. First, characteristic data, curvature during multimodal vibration, and environmental data are acquired. The characteristic data includes the Young's modulus and characteristic thickness of the string structure material, parameters that directly characterize the material's stiffness and geometric properties. The curvature during multimodal vibration is defined as the change in curvature relative to the unvibrated static shape of the string structure, thus accurately capturing the complex deformation state generated by the superposition of multimodal vibrations. Environmental data includes environmental temperature and environmental corrosivity parameters for subsequent quantitative analysis of environmental impacts.

[0086] Furthermore, based on the aforementioned characteristic data and curvature, dynamic stress at structural points of the string structure is generated. This process directly correlates material properties with the degree of vibration deformation, ensuring that the dynamic stress calculation accurately reflects the stress distribution at each structural point under multimodal vibration, avoiding the deficiency of traditional single-mode analysis that ignores the interaction between vibration modes. Subsequently, the dynamic stress is processed using the rainflow counting method, and the complete stress cycle is analyzed, in which the stress amplitude and mean stress are effectively extracted. This method is suitable for processing random vibration data, providing a reliable basis for subsequent correction of the mean stress effect. On this basis, an equivalent zero mean stress amplitude is generated. By incorporating non-zero mean stress into the correction mechanism, the stress amplitude is standardized to the zero mean stress condition, thereby solving the problem of simplified processing of the mean stress effect in existing technologies and ensuring the applicability of the material reference SN curve under asymmetric stress cycles.

[0087] Furthermore, based on the material reference SN curve and the equivalent zero mean stress amplitude, the initial fatigue damage value of the structural point of the string structure is generated. This step uses the SN curve as the reference for the material fatigue characteristics and combines it with the corrected stress amplitude to accurately quantify the damage accumulation caused by mechanical load.

[0088] Concurrently, an environmental impact analysis model was established, and environmental impact factors were generated. Environmental temperature and corrosivity parameters were used for dynamic modeling, reflecting the real-time impact of environmental factors on material fatigue performance and compensating for the shortcomings of the fixed safety factor method. Finally, initial fatigue damage values ​​and environmental impact factors were integrated, a fatigue life analysis model was established, and predicted fatigue life values ​​for the string structure were generated, achieving life assessment under multi-factor coupling.

[0089] Therefore, this method effectively solves the problem of complex stress states caused by the superposition of multimodal vibrations by accurately obtaining the curvature of multimodal vibrations and generating dynamic stress, avoiding the limitations of traditional methods in reflecting the actual stress field. Through the correction mechanism of equivalent zero mean stress amplitude, the non-zero mean stress effect is accurately handled, ensuring the reliability of damage calculation. At the same time, the dynamic modeling of the environmental impact analysis model allows environmental temperature changes and corrosion factors to be incorporated into the prediction process in real time, significantly improving the accuracy of fatigue life prediction under complex working conditions. Specifically, this scheme realizes the comprehensive quantification of mechanical damage and environmental impact, making the prediction results closer to actual working conditions and providing technical support for the safety assessment of string structures.

[0090] In practical applications, this invention proposes a method for generating dynamic stress at structural points of a string structure to calculate dynamic stress. However, in its implementation, traditional methods fail to fully consider the complex stress state generated by the superposition of multimodal vibrations, resulting in inaccurate calculation of dynamic stress distribution. This fails to truly reflect the alternating stress characteristics of the string structure caused by multimodal vibrations in the actual working environment, thus affecting the reliability of subsequent fatigue damage analysis.

[0091] In response, this invention further proposes a method for generating dynamic stress at structural points of the string structure, specifically including:

[0092] Through the formula:

[0093]

[0094] Dynamic stress at structural points of the generated string structure ;

[0095] In the formula, E represents the Young's modulus of the string structure material (its unit is Pa = N / m² = kg * m⁻¹ * s⁻²), d represents the characteristic thickness of the string structure material (its unit is m), and n is a constant term, typically taken as 2. It represents the curvature of the i-th mode of the string structure at position x (its unit is m-1). This represents the generalized coordinates of the i-th mode of the string structure;

[0096] Among them, Young's modulus refers to the basic mechanical property of a material resisting elastic deformation. It can be obtained through standard tensile tests or by querying material databases. It is used to ensure that dynamic stress calculation strictly follows the constitutive relationship of the material and avoids errors caused by ignoring material properties.

[0097] Characteristic thickness refers to the geometric characteristic dimension of a chord structure. It can be implemented by using the diameter of a circular cross section or the equivalent thickness of a rectangular cross section to adapt to the geometric dimensions of chord structures of different sizes and enhance the universality of the model.

[0098] The constant term refers to the dimensionless parameter used to calibrate the model scale. It can be determined through physical experiment calibration or theoretical derivation. Its purpose is to adjust the formula to match the physical scale of the actual vibration system.

[0099] Curvature refers to the spatial distribution characteristics of bending deformation of a string structure during vibration. It can be obtained by non-contact optical measurement equipment or strain sensor arrays and is used to accurately describe the deformation state of each mode in space.

[0100] Generalized coordinates refer to dimensionless parameters that characterize the temporal evolution of modal amplitude. They can be extracted by modal decomposition algorithms of vibration response signals, with the aim of dynamically quantifying the contribution ratio of each mode in the vibration response.

[0101] Specifically, the present invention constructs a complete mathematical expression of dynamic stress by multiplying the curvature distribution of each vibration mode with generalized coordinates, multiplying by the ratio of the material's Young's modulus to its characteristic thickness, and finally summing over all modes. This process strictly adheres to the physical nature of multimodal vibration, organically coupling material properties, geometric characteristics, and vibration parameters. The curvature distribution accurately characterizes the spatial deformation characteristics of the modes, while the generalized coordinates dynamically reflect the temporal evolution of the modes. The summation of these two parameters achieves a complete capture of the multimodal superposition effect, effectively overcoming the shortcomings of traditional single-mode analysis methods that cannot reflect the interaction of vibration modes. This ensures that the dynamic stress calculation can accurately reproduce the alternating stress distribution of the string structure in a complex vibration environment.

[0102] The above technical solutions can accurately characterize the dynamic stress distribution characteristics of string structures under multimodal vibration, truly reflect the complex alternating stress state caused by the superposition of vibration modes in the actual working environment, provide a reliable basis for the quantitative analysis of fatigue damage accumulation process, and thus improve the accuracy and engineering applicability of fatigue life prediction of string structures.

[0103] Specifically, this invention proposes an equivalent zero mean stress amplitude to correct the mean stress effect. However, in its implementation, the existing methods handle the influence of non-zero mean stress in a relatively simplified manner and lack a dynamic quantification mechanism for the relationship between mean stress and material strength. This results in the inability to accurately reflect the accelerating effect of mean stress on fatigue damage under the complex stress state generated by multimodal vibration, which in turn causes a significant deviation between the fatigue life prediction results and the actual working conditions.

[0104] In response, this invention further proposes a method for generating the equivalent zero average stress amplitude, specifically including:

[0105] Through the formula:

[0106]

[0107] Generating equivalent zero mean stress amplitude ;

[0108] In the formula, This represents the stress amplitude. This represents the average stress. This represents the ultimate tensile strength of a string structure material at room temperature; the unit of ultimate tensile strength is stress unit.

[0109] Among them, the equivalent zero mean stress amplitude refers to the correction value that converts the non-zero mean stress state into the standard zero mean stress state. It can be achieved by using a dynamic correction mechanism based on stress amplitude, mean stress and material ultimate tensile strength. The purpose is to accurately quantify the accelerating effect of mean stress on fatigue damage.

[0110] Specifically, stress amplitude refers to half of the difference between the maximum and minimum stress in a stress cycle, and its purpose is to characterize the magnitude of the dynamic stress cycle.

[0111] Mean stress is the arithmetic mean of the maximum and minimum stresses in a stress cycle, and its purpose is to reflect the bias level of the stress cycle.

[0112] Ultimate tensile strength refers to the maximum stress value that a chordal material can withstand in a tensile test at room temperature. It can be obtained through material mechanical property testing or by querying a standard material database, with the aim of providing an objective benchmark for material strength.

[0113] Specifically, the present invention calculates the stress amplitude and average stress as input parameters by combining the inherent ultimate tensile strength of the material. The term dynamically characterizes the degree to which average stress weakens the fatigue properties of materials, and then divides the stress amplitude by... The process generates an equivalent zero mean stress amplitude; this process realizes the equivalent transformation from a non-zero mean stress state to a standard zero mean stress state, making the correction mechanism closely fit the mechanical behavior of the material, avoiding the rough estimation of the fixed safety factor, and thus providing accurate input for subsequent fatigue damage calculation based on the material reference SN curve.

[0114] Through the above scheme, the present invention can accurately reflect the accelerating effect of mean stress on fatigue damage in multimodal vibration, significantly improve the accuracy of fatigue life prediction of string structures, and avoid the prediction deviation caused by the simplification of traditional methods.

[0115] This invention proposes the generation of initial fatigue damage values ​​to quantify the fatigue damage accumulation of string structures under multimodal vibration. However, in its implementation, traditional damage accumulation methods fail to fully consider the complex stress state generated by the superposition of multimodal vibrations, especially ignoring the stress cycle distribution characteristics of different equivalent zero mean stress amplitudes. This leads to an oversimplification of fatigue damage assessment, which cannot accurately reflect the contribution differences of each stress amplitude level in actual vibration, thus causing life prediction deviations.

[0116] In response, this invention further proposes a method for generating the initial fatigue damage value of the structural points of the string structure, specifically including:

[0117] Through the formula:

[0118]

[0119] Initial fatigue damage values ​​of structural points in the generated string structure ;

[0120] In the formula, This represents the equivalent zero mean stress amplitude. The number of stress cycles that occur. This indicates the equivalent zero mean stress amplitude. The number of cycles required to cause material failure, k represents the total number of different equivalent zero mean stress amplitudes identified within the time period t, and j is the index of the different equivalent zero mean stress amplitudes; where, in the equivalent zero mean stress amplitude The number of cycles required to cause material failure was obtained from the material reference SN curve of the string structure.

[0121] Among them, the stress cycle number refers to the actual number of stress cycles that occur under a specific equivalent zero average stress amplitude level. It can be determined by statistical analysis of dynamic stress signals using the rainflow counting method. Its purpose is to accurately capture the frequency of occurrence of different stress amplitude levels in multimodal vibration.

[0122] The number of cycles required to cause material failure refers to the theoretical number of cycles required for a material to undergo fatigue failure under a specific equivalent zero mean stress amplitude. It can be obtained by looking up the SN curve of the material reference of a string structure. Its purpose is to establish a quantitative relationship between stress amplitude and material fatigue life.

[0123] The total number of different equivalent zero mean stress amplitudes, k, refers to the number of discrete stress amplitude levels identified during the analysis period. Its purpose is to ensure that the damage accumulation model can reflect the complex stress state of multimodal vibration.

[0124] Specifically, the present invention categorizes and statistically analyzes the stress cycles generated by multimodal vibration using the rainflow counting method, classifying them according to the equivalent zero-mean stress amplitude. For each discrete stress amplitude level, the ratio of the actual number of cycles to the theoretical failure cycle number (i.e., the number of cycles required to cause material failure) is calculated. Then, the ratios of all stress amplitude levels are summed to obtain the initial fatigue damage value. This layered accumulation mechanism ensures that the contribution of different stress amplitude levels to fatigue damage is accurately quantified, avoiding the distortion caused by the simple averaging of all stress cycles in traditional methods. It effectively reflects the influence of the complex stress state generated by the superposition of multimodal vibrations on the accumulation of fatigue damage.

[0125] Through the above scheme, the present invention can accurately quantify the fatigue damage accumulation process of a chord structure under multimodal vibration, effectively solve the problem of life prediction deviation caused by neglecting the stress amplitude distribution characteristics of traditional methods, and significantly improve the accuracy of fatigue life prediction.

[0126] Specifically, this invention proposes a method for generating environmental impact factors to consider the influence of environmental parameters on fatigue life. However, in its implementation, the generation method lacks accurate modeling of temperature and corrosion factors, and cannot dynamically reflect the influence of environmental changes on material fatigue performance, resulting in a large deviation between the predicted fatigue life under complex environments and the actual results.

[0127] In response, this invention further proposes a specific method for generating the aforementioned environmental impact factors, including:

[0128] Step S61: Generate temperature influence factors based on ambient temperature;

[0129] Step S62: Generate corrosion influencing factors based on environmental corrosion parameters;

[0130] Step S63: Establish an environmental impact analysis model based on temperature and corrosivity factors, and generate environmental impact factors;

[0131] The specific expression of the environmental impact analysis model is as follows:

[0132]

[0133] In the expression, This represents environmental impact factors. This represents the temperature influence factor. This indicates the corrosiveness factor;

[0134] Among them, ambient temperature refers to the real-time temperature value of the environment in which the string structure is located. It can be obtained by an infrared thermometer or a thermistor and is used to quantify the dynamic impact of temperature fluctuations on the microstructure of the material.

[0135] Environmental corrosion parameters are parameters that characterize the intensity of environmental corrosion. They can be measured by electrochemical impedance spectroscopy, such as salt spray concentration or pH value, to assess the degree of erosion of material surfaces by environmental media.

[0136] The temperature influence factor is a coefficient that reflects the effect of temperature changes on the fatigue performance of materials. It can be determined based on the thermal expansion characteristics of materials by looking up tables or polynomial fitting. The purpose is to directly incorporate the temperature effect into the fatigue damage calculation process.

[0137] The corrosion impact factor refers to the coefficient that quantifies the accelerating effect of the corrosive environment on fatigue damage. It can be calculated by numerical integration or piecewise linear approximation in combination with the corrosion kinetic model. The purpose is to dynamically simulate the short-term transient effect and long-term cumulative effect of the corrosion process.

[0138] An environmental impact analysis model is a mathematical expression that couples the effects of temperature and corrosion. It can use a multiplicative coupling form to take the temperature effect factor as the basic term and the corrosion effect factor as the correction term, with the aim of ensuring that the interaction of environmental factors is systematically captured.

[0139] Specifically, the present invention first generates a temperature influence factor based on ambient temperature to directly quantify the dynamic impact of temperature on material fatigue performance; secondly, it generates a corrosion influence factor based on environmental corrosion parameters to consider the erosive effect of corrosion environment parameters and time accumulation on materials; finally, it couples the temperature influence factor and the corrosion influence factor through an environmental impact analysis model, where the temperature influence factor serves as a basic term to ensure the dominant role of the temperature effect, and the superposition term of the corrosion influence factor dynamically corrects the accelerating effect of corrosion on fatigue damage, thereby achieving accurate dynamic modeling of environmental factors in fatigue life prediction.

[0140] Through the above scheme, the present invention achieves accurate modeling of temperature and corrosion factors, which can dynamically reflect the impact of environmental changes on the fatigue performance of materials, thereby improving the accuracy of fatigue life prediction in complex environments and reducing the deviation between prediction results and reality.

[0141] This invention proposes a temperature influence factor to consider the impact of ambient temperature on fatigue life. However, in this process, the generation of the temperature influence factor lacks an accurate mathematical model, which makes it impossible to accurately quantify the dynamic impact of temperature changes on the fatigue performance of materials. This makes it difficult for traditional methods to reflect the nonlinear accelerating effect of temperature on fatigue damage accumulation by relying solely on a fixed safety factor for simplification.

[0142] In response, this invention further proposes a method for generating the temperature influence factor, specifically including:

[0143] Through the formula:

[0144]

[0145] Generation temperature influence factor ;

[0146] In the formula, Q represents the activation energy of the string structure material (in J / mol), and R represents the ideal gas constant (in J / (mol·K), typically taken as 8.314). The value indicated is the reference temperature, while T represents the current ambient temperature.

[0147] Among them, the temperature influence factor refers to the correction coefficient used to quantify the influence of ambient temperature on the fatigue performance of string structures. Its purpose is to establish the physical relationship between temperature and fatigue damage accumulation rate.

[0148] The activation energy Q can be understood as the minimum energy threshold required for fatigue damage to occur in string-structured materials. It can be determined through material thermodynamic experiments or obtained from material databases. Its purpose is to characterize the differences in the sensitivity of different materials to temperature changes.

[0149] The ideal gas constant R, as a fundamental thermodynamic constant, has a fixed value of 8.314 J / (mol·K), the purpose of which is to provide a standardized scale that conforms to the laws of physics.

[0150] The reference temperature specifically refers to a specific temperature point that serves as a normalization benchmark for temperature effects. It can be set to the temperature under standard material testing conditions, with the aim of establishing a consistent comparison benchmark.

[0151] The current ambient temperature specifically refers to the real-time temperature value in the actual working environment of the string structure, which can be obtained through dynamic monitoring by a temperature sensor. Its purpose is to enable the model to respond to changes in actual working conditions.

[0152] Specifically, the present invention constructs a temperature influence factor generation mechanism by incorporating the activation energy, ideal gas constant, reference temperature, and current ambient temperature T of the string-structured material into the Arrhenius equation framework. In this mechanism, the activation energy Q, as an inherent material property parameter, determines the sensitivity of temperature changes to fatigue damage accumulation; the ideal gas constant R, as a fundamental physical constant, ensures the equation conforms to thermodynamic principles; the reference temperature serves as a benchmark, allowing for normalized comparison of temperature effects under different environmental conditions; and the current ambient temperature T, as a dynamic input variable, drives the model to respond in real-time to changes in the working environment. These parameters are nonlinearly combined through exponential function relationships to form a mathematical model that accurately reflects the accelerating effect of temperature on fatigue damage. This model replaces the simplified treatment of fixing a safety factor in traditional methods, enabling the temperature influence factor to be dynamically adjusted according to the actual ambient temperature. Therefore, it works synergistically with the corrosive influence factor in the environmental impact analysis model, providing an accurate basis for environmental factor correction for fatigue life prediction.

[0153] Through the above-described scheme, this invention achieves precise quantification of the influence of ambient temperature, solving the problem of inaccurate temperature effect modeling. This technical solution can accurately reflect the dynamic impact of temperature changes on material fatigue performance, particularly effectively capturing the nonlinear accelerating effect of temperature on fatigue damage accumulation. This makes fatigue life prediction results more realistically reflect material performance changes under actual working conditions, avoiding prediction bias caused by temperature factors, thereby improving the accuracy of fatigue life prediction for string structures.

[0154] This invention proposes a corrosion impact factor to quantify the dynamic impact of environmental corrosion on fatigue damage. However, in its implementation, the generation of the corrosion impact factor lacks accurate modeling of the time-dependent characteristics of the corrosion process. In particular, it fails to distinguish between the short-term effects that develop rapidly in the early stages of corrosion and the corrosion behavior that may be accelerated in the long term. As a result, the static processing method that relies solely on environmental corrosion parameters cannot accurately reflect the nonlinear contribution of cumulative exposure time to corrosion damage, thus causing distortion in the calculation of the environmental impact factor and ultimately affecting the reliability of fatigue life prediction in complex corrosive environments.

[0155] In response, this invention further proposes a specific method for generating the aforementioned corrosiveness influencing factor, including:

[0156] Through the formula:

[0157]

[0158] Corrosion-influencing factors ;

[0159] In the formula, This represents the corrosive influence factor caused by the corrosive environment P within time t. This represents the short-term corrosion time constant function, which is used to dynamically adjust the short-term corrosion time constant based on corrosion environment parameters. The short-term corrosion time constant refers to the time it takes for a string-structured material to complete short-term corrosion characteristics under standard conditions. This represents the long-term corrosion time constant function, which is analogous to the short-term corrosion time constant function. This represents the cumulative exposure time of the string structure. A is the short-term amplitude coefficient, and B is the long-term amplitude coefficient. The amplitude coefficient refers to the maximum damage ratio that the corrosion effect can achieve.

[0160] Among them, the corrosion impact factor refers to the comprehensive parameter that quantifies the dynamic impact of environmental corrosion on fatigue damage, with the aim of accurately characterizing the nonlinear characteristics of corrosion damage evolution over time.

[0161] Short-term corrosion time constant function It can be understood as a short-term corrosion timescale that is dynamically adjusted according to environmental corrosivity parameters. It can be achieved by polynomial fitting or table lookup method. Its purpose is to reflect the transient behavior of rapid saturation in the early stage of corrosion under different corrosive environments (such as acid or salt spray conditions).

[0162] Long-term corrosion time constant function It refers to the time constant function for environmental adaptive calibration of long-term corrosion kinetics. It can be implemented by exponential decay model or neural network prediction, with the aim of capturing long-term accelerated corrosion phenomena such as pitting corrosion propagation or stress corrosion cracking.

[0163] Specifically, it refers to the total time that the string structure is continuously exposed to a corrosive environment, which can be achieved through time recording modules or sensor data accumulation. The purpose is to quantify the contribution of the time accumulation effect to corrosion damage.

[0164] A and B serve as amplitude coefficients for controlling the weights of short-term and long-term effects, respectively. These coefficients can be determined through experimental calibration or historical data fitting based on material type and environmental conditions. The aim is to flexibly allocate the relative influence of corrosion behavior at different stages.

[0165] Specifically, the present invention dynamically generates time-scale parameters that match the current corrosive environment by inputting the environmental corrosivity parameter P into short-term and long-term corrosion time constant functions; subsequently, the short-term effect term is calculated using the cumulative exposure time. and long-term effects The short-term effect term simulates the rapid accumulation and stabilization process in the early stage of corrosion through an exponential decay mechanism, while the long-term effect term characterizes the potential acceleration of corrosion in the long term through an exponential growth mechanism. Finally, the two terms are superimposed to generate a comprehensive corrosion influence factor, thereby establishing a dynamic mapping relationship between environmental corrosion parameters, time variables, and corrosion damage. This design achieves a refined description of the entire corrosion process by distinguishing between the short-term transient response and the long-term gradual behavior of corrosion.

[0166] As a specific implementation method, the present invention is implemented as follows: For steel string structures exposed to marine salt spray environment, the environmental corrosion parameter P can be expressed as a combined characteristic quantity of salt spray concentration and relative humidity; the short-term corrosion time constant function is determined based on salt spray concentration by a lookup table method, and a smaller value is taken when the salt spray concentration is high to reflect the rapid corrosion characteristics; the long-term corrosion time constant function is calculated using an exponential model based on historical corrosion data; the cumulative exposure time is provided by a time recorder installed on the string structure; the short-term amplitude coefficient A and the long-term amplitude coefficient B are calibrated according to the experimental data of the steel material, A is used to control the initial corrosion rate, and B is used to reflect the long-term pitting corrosion expansion trend; in the calculation, the short-term effect term and the long-term effect term are calculated first according to the current environmental parameter P and the cumulative exposure time, and then added together to obtain the corrosion influence factor.

[0167] Through the above scheme, the present invention can accurately quantify the time-dependent characteristics of the corrosion process, effectively distinguish between the short-term effects that develop rapidly in the early stage of corrosion and the corrosion behavior that may be accelerated in the long term, and avoid the defects of traditional static treatment methods that cannot reflect the nonlinear contribution of cumulative exposure time to corrosion damage, thereby improving the accuracy of environmental impact factor calculation and ultimately enhancing the reliability of fatigue life prediction of string structures in complex corrosion environments.

[0168] In some embodiments of the present invention, a method for generating fatigue life prediction values ​​of string structures is proposed to integrate initial fatigue damage values ​​and environmental influence factors. However, in its implementation, the lack of a specific generation mechanism for comprehensive fatigue damage values ​​and the precise construction of a fatigue life analysis model leads to the failure to effectively quantify the dynamic impact of environmental factors on fatigue damage accumulation. This makes it impossible for traditional methods to accurately reflect the real-time evolution of fatigue damage under complex environments (such as temperature fluctuations and corrosion), resulting in a significant deviation between the life prediction results and the actual working conditions.

[0169] In response, this invention further proposes a method for generating the fatigue life prediction value of the string structure, specifically including:

[0170] Step S71: Generate a comprehensive fatigue damage value based on the initial fatigue damage value of the structural points of the string structure and the environmental influence factor;

[0171] Step S72: Establish a fatigue life analysis model based on the comprehensive fatigue damage value and generate the predicted fatigue life value of the string structure;

[0172] Among them, the comprehensive fatigue damage value refers to a physical quantity that couples the damage caused by mechanical vibration with the dynamic effects of the environment, with the aim of dynamically quantifying the real-time impact of environmental parameters on the accumulation of fatigue damage.

[0173] The fatigue life analysis model can be understood as a mathematical framework for predicting remaining life based on comprehensive damage state. Its purpose is to transform instantaneous damage state into an operable life prediction result, thereby avoiding the static processing defects of traditional methods that only correct environmental factors with fixed coefficients.

[0174] Specifically, the present invention couples the initial fatigue damage value with environmental influence factors in step S71 to generate a comprehensive fatigue damage value characterizing the interaction between vibration and the environment. This value fully reflects the dynamic correlation between multimodal vibration stress and environmental parameters such as temperature and corrosion. Subsequently, in step S72, a real-time updated fatigue life analysis model is established based on this comprehensive value. By monitoring the changing trend of the damage accumulation rate and combining it with the critical damage threshold, the remaining service life is dynamically calculated. This step-by-step processing mechanism ensures that the dynamic influence of environmental factors is accurately incorporated into the damage assessment process, avoiding the static processing defects of environmental correction in traditional methods, thereby achieving adaptive updating of fatigue life prediction under complex working conditions.

[0175] Through the above technical solutions, the dynamic impact of environmental factors on fatigue damage accumulation can be effectively quantified, enabling the real-time evolution of fatigue damage to be accurately reflected under complex environments such as temperature fluctuations and corrosion, and significantly improving the consistency between the fatigue life prediction results of string structures and actual working conditions.

[0176] Specifically, in some embodiments of the present invention described above, a comprehensive fatigue damage value is proposed to integrate the effects of initial fatigue damage caused by mechanical vibration and environmental factors. However, in its implementation process, only the steps for generating the comprehensive fatigue damage value and fatigue life prediction value are outlined, but no specific mathematical expression is provided. It is impossible to accurately quantify the dynamic correction effect of environmental temperature changes and corrosion factors on fatigue damage. At the same time, the coupling effect of historical accumulated damage and current damage rate on the remaining life prediction is not considered, resulting in significant deviations in the fatigue life prediction results under the interaction of multimodal vibration and complex environment.

[0177] In response, this invention further proposes a method for generating the comprehensive fatigue damage value, specifically including:

[0178] Through the formula:

[0179]

[0180] Generate comprehensive fatigue damage value ;

[0181] In the formula, This represents the initial fatigue damage value at a structural point in the string structure. This represents environmental impact factors;

[0182] The specific expression of the fatigue life analysis model is as follows:

[0183]

[0184] In the expression, This represents the predicted fatigue life value for a string structure. This represents the critical damage value for fatigue failure of the string structure. This represents the overall fatigue damage value within a time period t. This represents the cumulative total fatigue damage value over time. dt represents the increment of the overall fatigue damage value, and dt represents the increment of the overall fatigue damage value at the current moment. The length of the time window, This represents the current rate of damage accumulation in the string structure;

[0185] Among them, the comprehensive fatigue damage value refers to the comprehensive damage index that integrates mechanical vibration damage and environmental influence. It can be realized by multiplying the initial fatigue damage value with the environmental influence factor. The purpose is to dynamically quantify the real-time damage state under the coupling effect of multimodal vibration and environmental factors.

[0186] Fatigue life prediction refers to the remaining working life of a string structure. It can be calculated based on critical damage value, current comprehensive damage value, historical cumulative damage value and damage accumulation rate. Its purpose is to provide a remaining life prediction that takes into account the entire damage evolution process.

[0187] The critical damage value refers to the damage threshold at which a string structure fails due to fatigue. It can be determined based on material fatigue characteristics experiments, with the aim of setting a limit reference point for damage accumulation.

[0188] The historical cumulative comprehensive fatigue damage value refers to the comprehensive damage value accumulated by the string structure before the current analysis period. It can be obtained through historical monitoring data, and its purpose is to incorporate the damage accumulation effect during long-term use.

[0189] The increment of the comprehensive fatigue damage value refers to the change in the comprehensive fatigue damage value within a specific time window. It can be obtained by differential calculation of continuous monitoring data, with the aim of capturing the instantaneous changes in damage development.

[0190] The time window length refers to the time interval used to calculate the damage increment. It can be set according to the sampling frequency of the monitoring system, and its purpose is to define the time reference for damage rate calculation.

[0191] The current damage accumulation rate refers to the rate of increase of the comprehensive fatigue damage value per unit time. It can be calculated by the ratio of the increment to the length of the time window, and its purpose is to reflect the dynamic trend of damage development.

[0192] Specifically, the present invention generates a comprehensive fatigue damage value by multiplying the initial fatigue damage value by an environmental impact factor, thereby achieving a nonlinear superposition of mechanical vibration damage and environmental effects. This avoids the simplistic limitation of traditional methods that only correct environmental factors with fixed coefficients. Furthermore, it calculates the remaining tolerable damage capacity. Compared with the current rate of damage accumulation The ratio of the two values ​​generates fatigue life prediction values, enabling continuous tracking of the entire damage evolution process. It not only depends on the current damage state, but also incorporates the cumulative effect of historical damage and the damage acceleration trend.

[0193] Through the above scheme, the present invention realizes the dynamic correction of fatigue damage caused by changes in ambient temperature and corrosion factors, and at the same time considers the coupling effect of historical cumulative damage and current damage rate, which significantly improves the accuracy of fatigue life prediction under the interaction of multimodal vibration and complex environment.

[0194] Please see Figure 2 The present invention also proposes a multimodal fatigue life prediction system for string vibration, which is used to execute the above-mentioned multimodal fatigue life prediction method for string vibration, specifically including:

[0195] The data acquisition unit 10 is used to acquire characteristic data of the string structure, curvature during multimodal vibration, and environmental data of the environment in which the string structure is located; wherein, the characteristic data includes the Young's modulus and characteristic thickness of the string structure material; the curvature during multimodal vibration refers to the curvature change relative to the static shape of the string structure when it is not vibrating;

[0196] The dynamic stress analysis unit 20 is used to generate the dynamic stress at the structural points of the string structure based on the characteristic data of the string structure and the curvature during multimodal vibration.

[0197] The stress cycle analysis unit 30 is used to process the dynamic stress of the structural points of the string structure using the rainflow counting method, and to analyze the complete stress cycle, which includes stress amplitude and average stress.

[0198] The equivalent zero average stress amplitude generation unit 40 is used to generate an equivalent zero average stress amplitude based on the stress amplitude and the average stress.

[0199] The fatigue damage preliminary analysis unit 50 is used to generate the initial fatigue damage value of the structural point of the string structure based on the material reference SN curve of the string structure and the equivalent zero mean stress amplitude.

[0200] The environmental impact analysis unit 60 is used to establish an environmental impact analysis model and generate environmental impact factors based on the environmental parameters of the environment in which the string structure is located. Among them, the environmental data includes environmental temperature and environmental corrosivity parameters; environmental corrosion intensity refers to environmental parameters that can cause corrosion to the string structure.

[0201] The fatigue life prediction unit 70 is used to establish a fatigue life analysis model based on the initial fatigue damage values ​​of the structural points of the string structure and environmental impact factors, and generate the fatigue life prediction value of the string structure.

[0202] The present invention further proposes that the environmental impact analysis unit 60 specifically includes:

[0203] The temperature analysis module is used to generate temperature influence factors based on the ambient temperature.

[0204] The corrosion analysis module is used to generate corrosion influencing factors based on environmental corrosion parameters.

[0205] The comprehensive analysis module is used to establish an environmental impact analysis model based on temperature and corrosion factors, and to generate environmental impact factors.

[0206] The present invention further proposes that the fatigue life prediction unit 70 specifically includes:

[0207] The comprehensive fatigue damage value generation module is used to generate comprehensive fatigue damage values ​​based on the initial fatigue damage values ​​of the structural points of the string structure and environmental influence factors.

[0208] The fatigue life prediction value generation module is used to establish a fatigue life analysis model based on the comprehensive fatigue damage value and generate fatigue life prediction values ​​for the string structure.

[0209] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for predicting the multimodal fatigue life of string vibration, characterized in that, The method specifically includes the following steps: Acquire characteristic data of the string structure, curvature during multimodal vibration, and environmental data of the environment in which the string structure is located; among which, the characteristic data includes the Young's modulus and characteristic thickness of the string structure material; the curvature during multimodal vibration refers to the curvature change relative to the static shape of the string structure when it is not vibrating; Based on the characteristic data of the string structure and the curvature during multimodal vibration, the dynamic stress at the structural points of the string structure is generated. The dynamic stress at the structural points of the string structure is processed by the rainflow counting method to analyze the complete stress cycle, which includes stress amplitude and average stress. Based on the stress amplitude and the average stress, an equivalent zero average stress amplitude is generated; Based on the material reference SN curve of the string structure, the initial fatigue damage value of the structural point of the string structure is generated according to the equivalent zero mean stress amplitude. Based on the environmental parameters of the environment in which the string structure is located, an environmental impact analysis model is established to generate environmental impact factors; among them, environmental data include environmental temperature and environmental corrosivity parameters; environmental corrosion intensity refers to environmental parameters that can cause corrosion to the string structure; A fatigue life analysis model is established based on the initial fatigue damage values ​​of the structural points of the string structure and environmental impact factors, and the predicted fatigue life values ​​of the string structure are generated. The specific methods for generating dynamic stress at structural points of the string structure include: Through the formula: Dynamic stress at structural points of the generated string structure ; In the formula, E represents the Young's modulus of the string structure material, d represents the characteristic thickness of the string structure material, and n is a constant term. This represents the curvature of the i-th mode of the string structure at position x. This represents the generalized coordinates of the i-th mode of the string structure at evaluation time t; where the generalized coordinates refer to the dimensionless parameters characterizing the temporal evolution of the mode amplitude, used to dynamically quantify the contribution ratio of the i-th mode in the vibration response. The specific methods for generating the environmental impact factors include: Based on the ambient temperature, generate temperature influence factors; Based on environmental corrosivity parameters, generate corrosion influencing factors; An environmental impact analysis model is established based on temperature and corrosion factors to generate environmental impact factors. The specific expression of the environmental impact analysis model is as follows: In the expression, This represents environmental impact factors. This represents the temperature influence factor. This indicates the corrosiveness factor; The specific methods for generating the temperature influence factor include: Through the formula: Generation temperature influence factor ; In the formula, Q represents the activation energy of the string structure material, and R represents the ideal gas constant. The value indicated is the reference temperature, while T represents the current ambient temperature. The specific methods for generating the corrosive influencing factors include: Through the formula: Corrosion-influencing factors ; In the formula, This represents the corrosion impact factor caused by the corrosive environment P at assessment time t. This represents a function of the short-term corrosion time constant. This represents a function of the long-term corrosion time constant. This represents the cumulative exposure time of the string structure. A is the short-term amplitude coefficient, and B is the long-term amplitude coefficient. The amplitude coefficient refers to the maximum damage ratio that the corrosion effect can achieve.

2. The method for predicting the multimodal fatigue life of string vibration according to claim 1, characterized in that, The method for generating the equivalent zero average stress amplitude specifically includes: Through the formula: Generating equivalent zero mean stress amplitude ; In the formula, This represents the stress amplitude. This represents the average stress. This represents the ultimate tensile strength of a string structure material at room temperature.

3. The method for predicting the multimodal fatigue life of string vibration according to claim 1, characterized in that, The specific methods for generating the initial fatigue damage values ​​of the structural points of the string structure include: Through the formula: Initial fatigue damage values ​​of structural points in the generated string structure ; In the formula, This represents the equivalent zero mean stress amplitude. The number of stress cycles that occur. This indicates the equivalent zero mean stress amplitude. The number of cycles required for material failure, k represents the time period. The total number of different equivalent zero mean stress amplitudes identified within the range, where j is the index of the different equivalent zero mean stress amplitudes; among them, in the equivalent zero mean stress amplitude The number of cycles required to cause material failure It is obtained based on the material reference SN curve of the string structure.

4. The method for predicting the multimodal fatigue life of string vibration according to claim 1, characterized in that, The specific methods for generating the fatigue life prediction value of the string structure include: Based on the initial fatigue damage values ​​of the structural points of the string structure and the environmental impact factors, a comprehensive fatigue damage value is generated; A fatigue life analysis model is established based on the comprehensive fatigue damage value to generate the predicted fatigue life value of the string structure.

5. The method for predicting the multimodal fatigue life of string vibration according to claim 4, characterized in that, The specific methods for generating the comprehensive fatigue damage value include: Through the formula: Generate comprehensive fatigue damage value ; In the formula, This represents the initial fatigue damage value at a structural point in the string structure. This represents environmental impact factors; The specific expression of the fatigue life analysis model is as follows: In the expression, This represents the predicted fatigue life value for a string structure. This represents the critical damage value for fatigue failure of the string structure. This indicates a time period Comprehensive fatigue damage value within, This represents the cumulative total fatigue damage value over time. This represents the increment of the overall fatigue damage value. This represents the increment of the overall fatigue damage value at the current moment. The length of the time window, This represents the current rate of damage accumulation in the string structure.

6. A multimodal fatigue life prediction system for string vibration, characterized in that, This system is used to execute the string vibration multimodal fatigue life prediction method according to any one of claims 1-5, specifically including: The data acquisition unit is used to acquire characteristic data of the string structure, curvature during multimodal vibration, and environmental data of the environment in which the string structure is located. Among them, the characteristic data includes the Young's modulus and characteristic thickness of the string structure material; the curvature during multimodal vibration refers to the curvature change relative to the static shape of the string structure when it is not vibrating. The dynamic stress analysis unit is used to generate dynamic stress at structural points of the string structure based on the characteristic data of the string structure and the curvature during multimodal vibration. The stress cycle analysis unit is used to process the dynamic stress of the structural points of the string structure using the rainflow counting method, and to analyze the complete stress cycle, which includes stress amplitude and average stress. The equivalent zero mean stress amplitude generation unit is used to generate the equivalent zero mean stress amplitude based on the stress amplitude and the mean stress. The preliminary fatigue damage analysis unit is used to generate the initial fatigue damage values ​​of the structural points of the string structure based on the material reference SN curve of the string structure and the equivalent zero mean stress amplitude. The environmental impact analysis unit is used to establish an environmental impact analysis model and generate environmental impact factors based on the environmental parameters of the environment in which the string structure is located. Among them, the environmental data includes environmental temperature and environmental corrosivity parameters; environmental corrosion intensity refers to environmental parameters that can cause corrosion to the string structure. The fatigue life prediction unit is used to establish a fatigue life analysis model based on the initial fatigue damage values ​​of the structural points of the string structure and environmental impact factors, and to generate the fatigue life prediction value of the string structure.

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