Method and system for simulating corrosion fatigue performance of aluminum alloy material of high-speed rail vehicle body

Abstract

The invention discloses a high-speed rail vehicle body aluminum alloy material corrosion fatigue performance simulation method and system, and belongs to the technical field of material corrosion fatigue testing. The method comprises the following steps: acquiring multi-source data of a high-speed rail body aluminum alloy material on an actual service route; establishing a material corrosion conversion coefficient database; obtaining an equivalent mapping relation based on the service environment and the load input set; generating a laboratory equivalent accelerated environment spectrum; and executing the laboratory equivalent accelerated environment spectrum, obtaining material failure data, and if the comparison difference is not less than a preset threshold value, correcting the calculation parameters of the equivalent mapping relation and regenerating the spectrum system. Through synchronous acquisition and fusion analysis of the multi-source environmental data and the mechanical load and in combination with the corrosion conversion coefficient database construction and closed-loop verification optimization method, the problem of test result distortion caused by separation of a laboratory simulation environment and an actual service condition in the prior art is solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of material corrosion fatigue test, and in particular to a high-speed rail car body aluminum alloy material corrosion fatigue performance simulation method and system. BACKGROUND

[0002] With the rapid expansion of China's high-speed railway network, the operating environment of high-speed rail vehicles is becoming increasingly complex, and the aluminum alloy material of the car body is facing the severe challenge of corrosion and fatigue coupling during long-term service, and the degradation of material performance directly affects the safety and service life of train operation.

[0003] The existing corrosion fatigue test system usually realizes material durability evaluation through single environmental factor accelerated test or fixed load spectrum loading. This kind of system simply superimposes the data such as temperature and humidity, salt spray collected in the natural environment and the standard load spectrum, and performs constant environmental stress loading in the laboratory.

[0004] In the prior art, the laboratory accelerated test method generally has the problems of single environmental simulation and weak coupling of load and environment, and there is a significant difference between the laboratory accelerated conditions and the actual service environment, which leads to distortion of equivalence, and the life prediction based on the distorted experimental data has insufficient reliability, which further forces the engineering decision to adopt an overly conservative solution, causing resource waste. SUMMARY

[0005] The high-speed rail car body aluminum alloy material corrosion fatigue performance simulation method and system provided by the embodiments of the present application solve the problem of distorted test results caused by the serious disconnection between the laboratory simulation environment and the actual service conditions in the prior art, which further leads to inaccurate life prediction, conservative design and maintenance decision, and low resource utilization, and achieve the technical effect of constructing a high-fidelity equivalent accelerated environment spectrum driven by multi-source data, improving the authenticity of corrosion fatigue simulation and the engineering guidance value.

[0006] The high-speed rail car body aluminum alloy material corrosion fatigue performance simulation method provided by the embodiments of the present application comprises: acquiring multi-source data of a high-speed rail car body aluminum alloy material on an actual service route, and synchronously collecting a mechanical load spectrum of the car body to form a multi-source fused service environment and load input set;

[0007] Based on the load input set, a laboratory discrete environment node is constructed, and a material corrosion conversion coefficient database is established;

[0008] Based on the service environment and load input set, the material corrosion conversion coefficient database is called to obtain an equivalent mapping relationship between the actual service environment time and the laboratory preset strengthening environment time;

[0009] According to the equivalent mapping relationship, a laboratory equivalent accelerated environment spectrum containing environmental cycles and load cycles is generated;

[0010] Perform laboratory equivalent accelerated environment spectroscopy to obtain material failure data, and compare the data with the damage characteristics of actual service data;

[0011] If the comparison difference is not less than the preset threshold, the calculation parameters of the equivalent mapping relationship are corrected and the spectrum is regenerated until the difference converges.

[0012] Furthermore, the steps of acquiring multi-source data on the aluminum alloy material of the high-speed rail body along actual service routes, and simultaneously collecting the mechanical load spectrum of the body to form a multi-source fused service environment and load input set include:

[0013] The system automatically captures macro-meteorological data along the route released by meteorological monitoring stations through network interfaces and stores it serialized by timestamp.

[0014] Real-time stress change signals were collected using a Wheatstone bridge, and microenvironmental data were collected using temperature and humidity sensors and chloride ion deposition sensors.

[0015] The collected raw signals are preprocessed, and the preprocessed macro-meteorological data along the route are aligned with the micro-environment monitoring data on the time axis.

[0016] The environmental parameter sequence aligned with the time axis is merged with the stress time history data to construct a multidimensional structured dataset.

[0017] Furthermore, the steps for constructing discrete laboratory environment nodes include:

[0018] Traverse the service environment and load input set, statistically analyze the maximum, minimum and frequency distribution histograms of four dimensions: temperature, relative humidity, salt spray concentration and pH, and determine the effective simulation boundary of each environmental parameter;

[0019] Within the effective simulation boundary, the continuous environmental parameter space is discretized into a finite number of specific environmental state combination points;

[0020] For each specific combination of environmental conditions, a corresponding set of control instructions is generated, defining the constant temperature setpoint, constant relative humidity setpoint, concentration of corrosive medium solution, and spray flow rate parameters for that node.

[0021] Discretized environmental state combination points form a grid distribution in multidimensional space. The grid density is increased in areas where environmental parameters occur frequently and decreased in areas where they occur infrequently, thus constructing a laboratory environmental state matrix.

[0022] Further steps in establishing a database of material corrosion conversion coefficients include:

[0023] A standard reference environment is selected, and the corrosion conversion coefficient under the standard reference environment condition is defined as a value of one;

[0024] The corrosion current density of the material under steady state at each discrete environmental state combination point was measured sequentially.

[0025] Receive the transmitted current data and obtain the corrosion conversion coefficient corresponding to the environmental node;

[0026] Establish a one-to-one mapping key-value pair relationship between the coordinate parameters of all discrete environmental state combination points and their corresponding corrosion conversion coefficients, and store them in a relational database to form a digital corrosion conversion coefficient lookup table.

[0027] Furthermore, the steps to derive the equivalent mapping relationship between actual service environment time and laboratory preset enhanced environment time include:

[0028] Read the environmental parameter vector at each moment in the service environment and load input set, and obtain the instantaneous corrosion conversion coefficient at each moment;

[0029] The product of the instantaneous corrosion conversion coefficient over time during the entire service life is numerically integrated to obtain the total corrosion equivalent value accumulated by the material during the actual service life.

[0030] Set the parameter conditions of the laboratory preset enhancement environment, and retrieve the accelerated corrosion conversion coefficient corresponding to the enhancement environment from the database;

[0031] To obtain the theoretical experimental time required to achieve the same amount of corrosion damage under a laboratory-enhanced environment;

[0032] Based on the theoretical experimental duration and the actual service duration, a time acceleration factor is derived, and an equivalent mapping relationship is established between one hour of actual service and several minutes of laboratory-enhanced environment.

[0033] Furthermore, the steps for generating a laboratory equivalent accelerated environment spectrum that includes environmental cycling and load cycling include:

[0034] The collected mechanical load spectrum was processed by rainflow counting to extract stress cycle blocks with different amplitudes and average values, and then sorted and reorganized according to the degree of damage from large to small.

[0035] Based on the derived equivalent mapping relationship, a laboratory environment cycle is constructed to determine the duration, temperature change slope, and media injection timing of each stage.

[0036] The reconstructed stress cycle block is mapped to the laboratory environment cycle.

[0037] The output is a comprehensive control file containing a precise time triggering mechanism, a sequence of environmental control parameters, and a sequence of hydraulic servo loading instructions.

[0038] Furthermore, the steps for performing laboratory equivalent accelerated environment spectroscopy to obtain material failure data include:

[0039] The system sends temperature, humidity, and spray control commands to the integrated environmental test chamber via industrial fieldbus, and simultaneously sends mechanical waveform loading commands to the electro-hydraulic servo fatigue testing machine to drive the equipment operation.

[0040] The crack length change on the sample surface is measured in real time, and the crack length and corresponding cycle number are recorded at preset time intervals.

[0041] When the detected crack length reaches a set proportion of the sample width or the sample completely fractures, the automatic shutdown protection logic is triggered.

[0042] The load feedback signals, actual environmental parameter curves, and crack propagation data of the entire experimental process are packaged and stored, and the crack initiation lifetime, crack propagation rate, and total number of cycles at final fracture are extracted as a failure data set characterizing the material's resilience.

[0043] Furthermore, if the comparison difference is not less than a preset threshold, the steps of correcting the calculation parameters of the equivalent mapping relationship and regenerating the spectrum until the difference converges include:

[0044] Read the crack propagation rate curve obtained in the laboratory and the reference crack propagation rate curve measured in actual service or outdoor exposure tests, and obtain the relative error value of the two curves under the same stress intensity factor range.

[0045] If the absolute value of the relative error is not less than the preset threshold, it is determined to be a simulation distortion and the parameter correction algorithm is started.

[0046] The parameter correction algorithm adjusts the values ​​of high-weight environmental nodes in the material corrosion conversion coefficient database according to the positive or negative direction of the error.

[0047] The corrosion damage equivalent cumulative calculation is re-executed using the parameters adjusted by the parameter correction algorithm to generate a new laboratory equivalent accelerated environment spectrum until the relative error value is less than the set threshold. The parameters determined at this point are the final effective simulation parameters.

[0048] This application provides a system for simulating the corrosion fatigue performance of aluminum alloy materials for high-speed train car bodies, used to implement a method for simulating the corrosion fatigue performance of aluminum alloy materials for high-speed train car bodies, including:

[0049] Data acquisition module, database establishment module, mapping relationship acquisition module, environmental spectrum generation module, data comparison module, parameter correction module;

[0050] The data acquisition module is used to acquire multi-source data of the aluminum alloy material of the high-speed rail body on the actual service route, and simultaneously collect the mechanical load spectrum of the body to form a multi-source fusion service environment and load input set.

[0051] The database establishment module is used to construct laboratory discrete environment nodes based on the load input set and establish a material corrosion conversion coefficient database.

[0052] The mapping relationship acquisition module is used to call the material corrosion conversion coefficient database based on the service environment and load input set to obtain the equivalent mapping relationship between the actual service environment time and the laboratory preset strengthening environment time.

[0053] The environmental spectrum generation module is used to generate a laboratory equivalent acceleration environment spectrum that includes environmental cycles and load cycles based on the equivalent mapping relationship.

[0054] The data comparison module is used to perform laboratory equivalent accelerated environment spectroscopy, obtain material failure data, and compare the data with the damage characteristics of actual service data.

[0055] The parameter correction module is used to correct the calculation parameters of the equivalent mapping relationship and regenerate the spectrum if the comparison difference is not less than a preset threshold, until the difference converges.

[0056] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0057] By establishing a service environment and load input set that integrates multi-source data and constructing an equivalent mapping relationship based on a corrosion conversion coefficient database, the problem of low fidelity between laboratory accelerated test conditions and real service environments is effectively solved, significantly improving the realism and accuracy of experimental simulation.

[0058] Furthermore, by temporally coupling the laboratory-preset enhanced environment with the mechanical load spectrum to generate an equivalent accelerated environment spectrum, and by collecting material failure data in real time during execution and comparing it with actual service data for verification, the consistency between experimental data and actual service damage characteristics is ensured, thereby improving the confidence of life prediction and design optimization decisions based on experimental data.

[0059] Furthermore, by setting preset thresholds and using parameter correction algorithms for iterative optimization until the difference between experimental data and actual data converges, a complete closed-loop verification mechanism is formed, which avoids overly conservative design or frequent maintenance due to data distortion and improves resource utilization efficiency. Attached Figure Description

[0060] Figure 1A flowchart illustrating the method for simulating the corrosion fatigue performance of aluminum alloy materials for high-speed train bodies, as provided in this application embodiment;

[0061] Figure 2 A schematic diagram of the structure of the high-speed rail car body aluminum alloy material corrosion fatigue performance simulation system provided in the embodiments of this application. Detailed Implementation

[0062] This application provides a method and system for simulating the corrosion fatigue performance of aluminum alloy materials for high-speed rail vehicles. This solves the problem of distorted test results caused by a serious disconnect between the laboratory simulation environment and actual service conditions in the prior art. By constructing a service environment and load input set with multi-source data fusion, establishing a material corrosion conversion coefficient database, generating a laboratory equivalent accelerated environment spectrum, and performing closed-loop verification and optimization, this method achieves high-fidelity simulation of the corrosion fatigue behavior of aluminum alloy materials for high-speed rail vehicles, thereby improving the engineering guidance value and resource utilization efficiency of experimental data.

[0063] To better understand the above technical solutions, the following will provide a detailed explanation of the technical solutions in conjunction with the accompanying drawings and specific implementation methods.

[0064] like Figure 1 The diagram shows a flowchart of a method for simulating the corrosion fatigue performance of aluminum alloy materials for high-speed train bodies provided in this application. This method is applied to a system for simulating the corrosion fatigue performance of aluminum alloy materials for high-speed train bodies. The method includes the following steps: acquiring multi-source data of aluminum alloy materials for high-speed train bodies on actual service routes. The multi-source data includes macro-meteorological statistics and micro-environment dynamic monitoring data of key parts, and simultaneously collecting the mechanical load spectrum of key structures of the body to form a multi-source fusion service environment and load input set.

[0065] The main criteria for judging whether a vehicle body structure and its components are critical include:

[0066] Finite element stress analysis: The static and dynamic simulation of the whole vehicle structure is performed by computer-aided engineering software (such as ANSYS or Abaqus), the stress distribution cloud map is calculated, and the area with equivalent stress value exceeding 70% of the material yield strength is identified. These areas are considered as high stress areas, such as the connection between the car body chassis and the bogie, and the side wall welds.

[0067] Fatigue life assessment: Based on the international standard ISO12107, combined with the material SN curve and load spectrum, the fatigue life of the component is calculated. Components with fatigue life lower than the design life (usually thirty years) are identified as critical components, such as welded joints subjected to alternating loads.

[0068] Failure Mode and Effects Analysis (FMEA): In accordance with SAE J1739 standard, a systematic FMEA is conducted to assess the potential failure modes, failure causes and their impact on system safety for each component. Components with a severity score of more than eight (out of ten) are defined as critical components. For example, failure of a steering structure component may lead to derailment.

[0069] Based on the distribution range of environmental parameters in the load input set, a laboratory discrete environment node covering different temperatures, humidity and corrosive media concentrations is constructed. The corrosion rate ratio of the material at each discrete environment node relative to the standard reference environment is determined by basic corrosion experiments, and a material corrosion conversion coefficient database is established.

[0070] Based on the service environment and load input set, the material corrosion conversion coefficient database is called, and the equivalent mapping relationship between the actual service environment time and the laboratory preset strengthening environment time is obtained by using the principle of equivalent accumulation of corrosion damage.

[0071] Based on the equivalent mapping relationship, the temporal parameters of the laboratory's preset enhanced environment are coupled with the mechanical load spectrum in the time domain to generate the laboratory's equivalent accelerated environment spectrum, which includes environmental cycles and load cycles.

[0072] The controlled environment simulation and mechanical loading equipment perform a laboratory equivalent accelerated environment spectrum to obtain material failure data, and compare the damage characteristics of the data with those of actual service data.

[0073] If the comparison difference is not less than the preset threshold, the calculation parameters of the equivalent mapping relationship are corrected and the spectrum is regenerated until the difference converges.

[0074] If the difference between the comparison results is not less than the preset threshold, that is, if the difference between the comparison results is less than the preset threshold, it indicates that the consistency between the laboratory simulation results and the actual service data is within an acceptable range, and the simulation process is considered valid.

[0075] Furthermore, the steps of acquiring multi-source data on the aluminum alloy material of the high-speed rail body along actual service routes, and simultaneously collecting the mechanical load spectrum of the body to form a multi-source fused service environment and load input set include:

[0076] The system automatically captures macro-meteorological data along the route released by meteorological monitoring stations through network interfaces, including temperature, relative humidity, rainfall and sulfur dioxide concentration, and stores them serialized by timestamp.

[0077] Real-time stress change signals are collected by a Wheatstone bridge composed of resistance strain gauges arranged on the side walls, underframe and bogie areas of the high-speed train body. Microenvironmental data are collected by temperature and humidity sensors and chloride ion deposition sensors installed on the surface of the body. The sampling frequency is set to a high-frequency sampling mode that can capture transient impacts.

[0078] The collected raw signals are preprocessed, and high-frequency noise interference is removed by using a low-pass filter. Outliers are identified and removed by using the Grubbs criterion. The preprocessed macro-meteorological data and micro-environment monitoring data along the route are aligned on the time axis using a unified global positioning system time reference.

[0079] The environmental parameter sequence aligned with the time axis is merged with the stress time history data to construct a multidimensional structured dataset containing time, location, environmental factors, and mechanical response, which serves as the digital input base for subsequent simulations.

[0080] Furthermore, the steps for constructing discrete laboratory environment nodes covering different temperatures, humidity levels, and corrosive media concentrations include:

[0081] Traverse the service environment and load input set, statistically analyze the maximum, minimum and frequency distribution histograms of four dimensions: temperature, relative humidity, salt spray concentration and pH, and determine the effective simulation boundary of each environmental parameter;

[0082] Within the effective simulation boundary, the orthogonal experimental design method is used to discretize the continuous environmental parameter space into a finite number of specific environmental state combination points;

[0083] For each specific combination of environmental conditions, a corresponding set of control instructions is generated, defining the constant temperature setpoint, constant relative humidity setpoint, concentration of corrosive medium solution, and spray flow rate parameters for that node.

[0084] Discretized environmental state combination points form a grid distribution in multidimensional space. The grid density is increased in areas where environmental parameters occur frequently and decreased in areas where they occur infrequently, thus constructing a laboratory environmental state matrix that can comprehensively cover the actual operating conditions of high-speed rail and has a controllable computational load.

[0085] Furthermore, the steps for establishing a material corrosion conversion coefficient database include determining the ratio of the corrosion rate of the material at each discrete environmental node relative to the standard reference environment through basic corrosion experiments:

[0086] An air environment with a temperature of 25 degrees Celsius and a relative humidity of 50% under standard atmospheric pressure was selected as the standard reference environment, and the corrosion conversion coefficient under the standard reference environment was defined as a value of one.

[0087] Under the control of the electrochemical workstation, the aluminum alloy sample was subjected to potential scanning in the electrolytic cell that simulated each discrete combination of environmental conditions in the laboratory, and the corrosion current density of the material under steady state at each discrete combination of environmental conditions was measured.

[0088] Receive current data transmitted from the electrochemical workstation, divide the steady-state corrosion current density measured at each discrete environmental state combination point by the baseline corrosion current density measured under the standard reference environment, and use the quotient as the corrosion conversion coefficient corresponding to the corresponding environmental node.

[0089] Establish a one-to-one mapping key-value pair relationship between the coordinate parameters of all discrete environmental state combination points and their corresponding corrosion conversion coefficients, and store them in a relational database to form a digital corrosion conversion coefficient lookup table that supports fast querying and interpolation.

[0090] Furthermore, the steps for deriving the equivalent mapping relationship between actual service environment time and laboratory preset strengthening environment time using the principle of equivalent accumulation of corrosion damage include:

[0091] Read the environmental parameter vector at each moment in the service environment and load input set, and use this vector as an index to perform multidimensional linear interpolation in the material corrosion conversion coefficient database to obtain the instantaneous corrosion conversion coefficient at each moment.

[0092] The product of the instantaneous corrosion conversion coefficient over time during the entire service life is numerically integrated to obtain the total corrosion equivalent value accumulated by the material during the actual service life.

[0093] The formula for numerical integration is:

[0094] ;

[0095] In the formula, This is the total corrosion equivalent value, dimensionless, representing the relative cumulative corrosion damage. The time-dependent corrosion conversion coefficient is dimensionless and was obtained by querying a material corrosion conversion coefficient database and interpolating. For reference corrosion current density, measured in amperes per square meter, it was determined through electrochemical experiments under standard reference conditions. For time variables, in hours. The actual total service time, in hours, is obtained from the service environment and payload input.

[0096] In the formula, it is assumed that Its value remained constant at 1.2 throughout its service life. , , and thus for This is the total corrosion equivalent value.

[0097] Set the parameter conditions of the laboratory preset enhancement environment, and retrieve the accelerated corrosion conversion coefficient corresponding to the enhancement environment from the database;

[0098] By dividing the total corrosion equivalent value by the accelerated corrosion conversion coefficient, the theoretical experimental time required to achieve the same amount of corrosion damage under a laboratory-enhanced environment can be obtained.

[0099] Based on the theoretical experimental duration and the actual service duration, a time acceleration factor is derived. The ratio of the theoretical experimental duration to the actual service duration is the time acceleration factor. Based on this, an equivalent mapping relationship is established between one hour of actual service and several minutes of laboratory-enhanced environment.

[0100] Furthermore, the steps of temporally coupling the time-series parameters of the pre-set laboratory intensification environment with the mechanical load spectrum to generate the laboratory equivalent acceleration environment spectrum, which includes environmental cycles and load cycles, include:

[0101] The collected mechanical load spectrum was processed by rainflow counting to extract stress cycle blocks with different amplitudes and average values, and then sorted and reorganized according to the degree of damage from large to small.

[0102] Based on the obtained equivalent mapping relationship, a laboratory environment cycle consisting of a pre-corrosion stage, a corrosion fatigue coupling stage, and a drying stage was constructed, and the duration, temperature change slope, and media injection timing of each stage were determined.

[0103] The recombined stress cycle block is mapped to the corrosion fatigue coupling stage in the laboratory environment cycle to ensure that the loading action with high stress amplitude and the environmental state with high corrosion conversion coefficient are synchronously overlapped on the time axis.

[0104] The output includes a comprehensive control file containing a precise time triggering mechanism, a sequence of environmental control parameters, and a sequence of hydraulic servo loading instructions. This file defines the execution logic and termination conditions for each experimental step, forming a complete spectrum of laboratory equivalent accelerated environments.

[0105] Furthermore, the steps for obtaining material failure data by controlling the environment simulation and mechanical loading equipment to perform a laboratory equivalent accelerated environment spectrum include:

[0106] The system sends temperature, humidity, and spray control commands to the integrated environmental test chamber via industrial fieldbus, and simultaneously sends mechanical waveform loading commands to the electro-hydraulic servo fatigue testing machine, driving the equipment to operate according to the laboratory equivalent accelerated environment spectrum.

[0107] During equipment operation, the crack length change on the sample surface is measured in real time by a DC potential drop monitoring system or a compliance method crack monitoring device, and the crack length and corresponding cycle number are recorded at preset time intervals.

[0108] When the detected crack length reaches a set proportion of the sample width or the sample completely fractures, the automatic shutdown protection logic is triggered.

[0109] The data acquisition card packages and stores the load feedback signals, actual environmental parameter curves, and crack propagation data throughout the experiment, and extracts the crack initiation life, crack propagation rate, and total number of cycles at final fracture of the material as a failure data set characterizing the material's resilience.

[0110] Furthermore, if the comparison difference is not less than a preset threshold, the steps of correcting the calculation parameters of the equivalent mapping relationship and regenerating the spectrum until the difference converges include:

[0111] Read the crack propagation rate curve obtained in the laboratory and the reference crack propagation rate curve measured in actual service or outdoor exposure tests, and obtain the relative error value of the two curves under the same stress intensity factor range.

[0112] The relative error values ​​of the two curves under the same stress intensity factor range are obtained using the relative error value calculation formula:

[0113] ;

[0114] In the formula, The value is a relative error, expressed as a percentage, indicating the degree of deviation. The crack propagation rate is measured in the laboratory, in meters per cycle, and is obtained from a material failure dataset. The baseline crack propagation rate, measured in meters per cycle, is obtained from historical databases or standard data, based on actual service or outdoor exposure tests. The stress intensity factor range is expressed in megapascals square meters, and is used for calculation. The independent variable at time, through Calculation, where Geometric factor For stress range, The crack length is given.

[0115] In the formula, it is assumed that in hour;

[0116] , ;

[0117] but for .

[0118] If the absolute value of the relative error is not less than the preset threshold, it is determined to be a simulation distortion and the parameter correction algorithm is started.

[0119] The parameter correction algorithm adjusts the values ​​of high-weight environmental nodes in the material corrosion conversion coefficient database, or adjusts the time acceleration factor in the calculation of the equivalent mapping relationship, based on the positive or negative direction of the error.

[0120] Specifically, if the laboratory corrosion rate is low, the conversion coefficient of the high-humidity, high-salt nodes is increased by step size, and vice versa.

[0121] The corrosion damage equivalent cumulative calculation is re-executed using the parameters adjusted by the parameter correction algorithm to generate a new laboratory equivalent accelerated environment spectrum. The operator is then prompted to conduct the next round of verification experiments based on the new spectrum. This process is repeated until the relative error value is less than the set threshold. The parameters determined at this point are the final effective simulation parameters.

[0122] like Figure 2 The diagram shown is a structural schematic of the high-speed rail car body aluminum alloy material corrosion fatigue performance simulation system provided in this application embodiment. The high-speed rail car body aluminum alloy material corrosion fatigue performance simulation system provided in this application embodiment includes: a data acquisition module, a database establishment module, a mapping relationship acquisition module, an environmental spectrum generation module, a data comparison module, and a parameter correction module.

[0123] The data acquisition module is used to acquire multi-source data of the aluminum alloy material of the high-speed rail body on the actual service route, and simultaneously collect the mechanical load spectrum of the body to form a multi-source fusion service environment and load input set.

[0124] The database establishment module is used to construct laboratory discrete environment nodes based on the load input set and establish a material corrosion conversion coefficient database.

[0125] The mapping relationship acquisition module is used to call the material corrosion conversion coefficient database based on the service environment and load input set to obtain the equivalent mapping relationship between the actual service environment time and the laboratory preset strengthening environment time.

[0126] The environmental spectrum generation module is used to generate a laboratory equivalent acceleration environment spectrum that includes environmental cycles and load cycles based on the equivalent mapping relationship.

[0127] The data comparison module is used to perform laboratory equivalent accelerated environment spectroscopy, obtain material failure data, and compare the data with the damage characteristics of actual service data.

[0128] The parameter correction module is used to correct the calculation parameters of the equivalent mapping relationship and regenerate the spectrum if the comparison difference is not less than a preset threshold, until the difference converges.

[0129] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0130] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, in the form of a computer program product.

[0131] Those skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0132] In addition, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0133] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0134] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for simulating the corrosion fatigue performance of aluminum alloy materials for high-speed train car bodies, characterized in that, Includes the following steps: Acquire multi-source data on the aluminum alloy material of high-speed rail body on actual service routes, and simultaneously collect the mechanical load spectrum of the body to form a multi-source fusion service environment and load input set; Based on the load input set, a discrete laboratory environment node is constructed, and a database of material corrosion conversion coefficients is established. Based on the service environment and load input set, the material corrosion conversion coefficient database is called to obtain the equivalent mapping relationship between the actual service environment time and the laboratory preset strengthening environment time; Based on the equivalent mapping relationship, a laboratory equivalent acceleration environment spectrum containing environmental cycles and load cycles is generated; Perform laboratory equivalent accelerated environment spectroscopy to obtain material failure data, and compare the data with the damage characteristics of actual service data; If the comparison difference is not less than the preset threshold, the calculation parameters of the equivalent mapping relationship are corrected and the spectrum is regenerated until the difference converges.

2. The method for simulating the corrosion fatigue performance of aluminum alloy materials for high-speed train car bodies as described in claim 1, characterized in that, The steps for acquiring multi-source data on the aluminum alloy material of high-speed train bodies along actual service routes, and simultaneously collecting the mechanical load spectrum of the body to form a multi-source fused service environment and load input set include: The system automatically captures macro-meteorological data along the route released by meteorological monitoring stations through network interfaces and stores it serialized by timestamp. Real-time stress change signals were acquired using a Wheatstone bridge, and microenvironmental data were collected using temperature and humidity sensors and chloride ion deposition sensors. The collected raw signals are preprocessed, and the preprocessed macro-meteorological data along the route are aligned with the micro-environment monitoring data on the time axis. The environmental parameter sequence aligned with the time axis is merged with the stress time history data to construct a multidimensional structured dataset.

3. The method for simulating the corrosion fatigue performance of aluminum alloy materials for high-speed train car bodies as described in claim 1, characterized in that, The steps to construct a discrete laboratory environment node include: Traverse the service environment and load input set, statistically analyze the maximum, minimum and frequency distribution histograms of four dimensions: temperature, relative humidity, salt spray concentration and pH, and determine the effective simulation boundary of each environmental parameter; Within the effective simulation boundary, the continuous environmental parameter space is discretized into a finite number of specific environmental state combination points; For each specific combination of environmental conditions, a corresponding set of control instructions is generated, defining the constant temperature setpoint, constant relative humidity setpoint, concentration of corrosive medium solution, and spray flow rate parameters for that node. Discretized environmental state combination points form a grid distribution in multidimensional space. The grid density is increased in areas where environmental parameters occur frequently and decreased in areas where they occur infrequently, thus constructing a laboratory environmental state matrix.

4. The method for simulating the corrosion fatigue performance of aluminum alloy materials for high-speed train car bodies as described in claim 1, characterized in that, The steps to establish a database of material corrosion conversion coefficients include: A standard reference environment is selected, and the corrosion conversion coefficient under the standard reference environment condition is defined as a value of one; The corrosion current density of the material under steady state at each discrete environmental state combination point was measured sequentially. Receive the transmitted current data and obtain the corrosion conversion coefficient corresponding to the environmental node; Establish a one-to-one mapping key-value pair relationship between the coordinate parameters of all discrete environmental state combination points and their corresponding corrosion conversion coefficients, and store them in a relational database to form a digital corrosion conversion coefficient lookup table.

5. The method for simulating the corrosion fatigue performance of aluminum alloy materials for high-speed train car bodies as described in claim 1, characterized in that, The steps to derive the equivalent mapping relationship between actual service environment time and laboratory preset enhanced environment time include: Read the environmental parameter vector at each moment in the service environment and load input set, and obtain the instantaneous corrosion conversion coefficient at each moment; The product of the instantaneous corrosion conversion coefficient over time during the entire service life is numerically integrated to obtain the total corrosion equivalent value accumulated by the material during the actual service life. Set the parameter conditions of the laboratory preset enhancement environment, and retrieve the accelerated corrosion conversion coefficient corresponding to the enhancement environment from the database; To obtain the theoretical experimental time required to achieve the same amount of corrosion damage under a laboratory-enhanced environment; Based on the theoretical experimental duration and the actual service duration, a time acceleration factor is derived, and an equivalent mapping relationship is established between one hour of actual service and several minutes of laboratory-enhanced environment.

6. The method for simulating the corrosion fatigue performance of aluminum alloy materials for high-speed train car bodies as described in claim 1, characterized in that, The steps for generating a laboratory equivalent accelerated environment spectrum that includes environmental cycling and load cycling include: The collected mechanical load spectrum was processed by rainflow counting to extract stress cycle blocks with different amplitudes and average values, and then sorted and reorganized according to the degree of damage from large to small. Based on the derived equivalent mapping relationship, a laboratory environment cycle is constructed to determine the duration, temperature change slope, and media injection timing of each stage. The reconstructed stress cycle block is mapped to the laboratory environment cycle. The output is a comprehensive control file containing a precise time triggering mechanism, a sequence of environmental control parameters, and a sequence of hydraulic servo loading instructions.

7. The method for simulating the corrosion fatigue performance of aluminum alloy materials for high-speed train car bodies as described in claim 1, characterized in that, The steps for performing laboratory equivalent accelerated environment spectroscopy to obtain material failure data include: The system sends temperature, humidity, and spray control commands to the integrated environmental test chamber via industrial fieldbus, and simultaneously sends mechanical waveform loading commands to the electro-hydraulic servo fatigue testing machine to drive the equipment operation. The crack length change on the sample surface is measured in real time, and the crack length and corresponding cycle number are recorded at preset time intervals. When the detected crack length reaches a set proportion of the sample width or the sample completely fractures, the automatic shutdown protection logic is triggered. The load feedback signals, actual environmental parameter curves, and crack propagation data of the entire experimental process are packaged and stored, and the crack initiation lifetime, crack propagation rate, and total number of cycles at final fracture are extracted as a failure data set characterizing the material's resilience.

8. The method for simulating the corrosion fatigue performance of aluminum alloy materials for high-speed train car bodies as described in claim 1, characterized in that, If the comparison difference is not less than a preset threshold, the steps to correct the calculation parameters of the equivalent mapping relationship and regenerate the spectrum until the difference converges include: Read the crack propagation rate curve obtained in the laboratory and the reference crack propagation rate curve measured in actual service or outdoor exposure tests, and obtain the relative error value of the two curves under the same stress intensity factor range. If the absolute value of the relative error is not less than the preset threshold, it is determined to be a simulation distortion and the parameter correction algorithm is started. The parameter correction algorithm adjusts the values ​​of high-weight environmental nodes in the material corrosion conversion coefficient database according to the positive or negative direction of the error. The corrosion damage equivalent cumulative calculation is re-executed using the parameters adjusted by the parameter correction algorithm to generate a new laboratory equivalent accelerated environment spectrum until the relative error value is less than the set threshold. The parameters determined at this point are the final effective simulation parameters.

9. A system for simulating the corrosion fatigue performance of aluminum alloy materials for high-speed train car bodies, used to implement the method for simulating the corrosion fatigue performance of aluminum alloy materials for high-speed train car bodies as described in any one of claims 1-8, characterized in that, include: Data acquisition module, database establishment module, mapping relationship acquisition module, environmental spectrum generation module, data comparison module, parameter correction module; The data acquisition module is used to acquire multi-source data of the aluminum alloy material of the high-speed rail body on the actual service route, and simultaneously collect the mechanical load spectrum of the body to form a multi-source fusion service environment and load input set. The database establishment module is used to construct laboratory discrete environment nodes based on the load input set and establish a material corrosion conversion coefficient database. The mapping relationship acquisition module is used to call the material corrosion conversion coefficient database based on the service environment and load input set to obtain the equivalent mapping relationship between the actual service environment time and the laboratory preset strengthening environment time. The environmental spectrum generation module is used to generate a laboratory equivalent acceleration environment spectrum that includes environmental cycles and load cycles based on the equivalent mapping relationship. The data comparison module is used to perform laboratory equivalent accelerated environment spectroscopy, obtain material failure data, and compare the data with the damage characteristics of actual service data. The parameter correction module is used to correct the calculation parameters of the equivalent mapping relationship and regenerate the spectrum if the comparison difference is not less than a preset threshold, until the difference converges.

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