A material corrosion service performance evaluation method based on digital twin

Abstract

The present invention provides a digital twin-based material corrosion service performance evaluation method, belonging to the technical field of material performance testing. The method comprises: S101, establishing a corrosion data perception and sensing system; S102, constructing a corrosion information database; S103, using the corrosion information database, cleaning and processing the online and offline material corrosion data into corrosion characteristics required for modeling, namely, reprocessing data; S104, using the online environmental data and reprocessing data of multiple materials as inputs to an intelligent digital corrosion mechanism model. The model incorporates the corrosion evolution laws of the materials to establish a highly generalizable, mesoscopic to macroscopic, cross-scale intelligent digital corrosion mechanism model. This model provides lifespan predictions for the corrosion performance of in-service materials, thereby realizing a digital twin of the material corrosion service performance. The present invention can further improve the speed of material corrosion performance evaluation while ensuring equivalent acceleration.

Description

Technical Field

[0001] The present invention relates to the technical field of material performance testing, and in particular to a material corrosion service performance evaluation method based on digital twins. Background Art

[0002] Material corrosion prevention and repair have always played a significant role in the national economy, and evaluating material corrosion performance has always been a laborious and time-consuming task. Because materials exhibit different corrosion phenomena and mechanisms under different service environments, this poses a significant challenge to evaluating material corrosion performance. Currently, most evaluation methods analyze and evaluate based on monitoring data, lacking a method that truly combines monitoring data with real-time correction and evolutionary reasoning of material corrosion mechanism models. Summary of the Invention

[0003] The embodiment of the present invention provides a material corrosion service performance evaluation method based on digital twins, which can further improve the corrosion performance evaluation speed of materials while ensuring equivalent acceleration. The method includes:

[0004] S101, establish a corrosion data perception sensing system;

[0005] S102, constructing a corrosion information database, designing an accelerated environmental spectrum based on the corrosion life of the material, conducting an accelerated environmental spectrum experiment in a corrosion acceleration test chamber, verifying the equivalence of the accelerated environmental spectrum in terms of corrosion mechanism and corrosion results, and acquiring online environmental data, online material corrosion data, and offline material corrosion data from offline testing through an established corrosion data sensing system, and storing the data in the corrosion information database; wherein the accelerated environmental spectrum includes: an original environmental spectrum and an equivalent accelerated environmental spectrum;

[0006] S103, cleaning and processing the online and offline corrosion data of the material into the corrosion characteristics required for modeling through the corrosion information database, i.e., reprocessing the data;

[0007] S104 uses the online environmental data and reprocessing data of multiple materials as the input of the corrosion intelligent digital mechanism model. The corrosion evolution law of the material is combined in the model to establish a cross-scale corrosion intelligent digital mechanism model from mesoscopic to macroscopic with strong generalization ability, provide life prediction for the corrosion performance of service materials, and realize the digital twin of material corrosion service performance.

[0008] Furthermore, the establishment of the corrosion data sensing system includes:

[0009] On the basis of the existing corrosion acceleration test chamber, environmental monitoring collection and control sensors, material online corrosion data acquisition sensors and material offline corrosion data receivers for offline testing are added; wherein, the environmental monitoring control sensors modify the environmental parameters of the corrosion acceleration test chamber after receiving the modification instructions for the environmental parameters from the corrosion intelligent digital mechanism model; wherein, when the corrosion intelligent digital mechanism model recognizes that the original environmental spectrum can be equivalently accelerated again, it sends an instruction to modify the environmental parameters to the environmental monitoring control sensors, and after receiving the environmental parameter modification instructions, the control sensors modify the environmental parameters of the corrosion acceleration test chamber in real time.

[0010] Furthermore, the corrosion data perception sensing system established in S101 is used to adjust the acceleration conditions of the corrosion acceleration test chamber, and the accelerated online environmental data and processing data are obtained through S102 and S103 respectively, that is, the equivalent acceleration environment spectrum is obtained using the digital twin method.

[0011] Furthermore, the online environmental data and reprocessing data of multiple materials are used as inputs to the corrosion intelligent digital mechanism model. The corrosion evolution law of the materials is combined in the model to establish a cross-scale corrosion intelligent digital mechanism model with strong generalization ability from mesoscopic to macroscopic. This provides life prediction for the corrosion performance of in-service materials and realizes the digital twin of material corrosion service performance, including:

[0012] The online environmental data and reprocessing data are used as inputs to the corrosion intelligent digital mechanism model. The corrosion evolution law of the material is combined in the model to establish a corrosion intelligent digital mechanism model for a single material.

[0013] By using multiple materials and repeatedly establishing the intelligent digital mechanism model of corrosion of a single material, we can obtain a cross-scale intelligent digital mechanism model of corrosion from mesoscopic to macroscopic with strong generalization ability, provide life prediction for the corrosion performance of service materials, and realize the digital twin of material corrosion service performance.

[0014] Furthermore, after using online environmental data and reprocessing data of multiple materials as inputs to the corrosion intelligent digital mechanism model, incorporating the corrosion evolution laws of the materials into the model, establishing a cross-scale corrosion intelligent digital mechanism model with strong generalization capability from mesoscopic to macroscopic, providing life prediction for the corrosion performance of in-service materials, and realizing the digital twin of the material corrosion service performance, the method further includes:

[0015] Build a digital twin support and display platform for material service performance.

[0016] Furthermore, the material service performance digital twin support and display platform is used to view the operation status of the corrosion acceleration test chamber, the storage status of the corrosion information database, the actual experimental conditions of the material and the real-time evolution of the corrosion intelligent digital mechanism model.

[0017] Furthermore, the material service performance digital twin support and display platform supports the function of integrated redevelopment and the incorporation of digital twins of various service performances.

[0018] The beneficial effects brought about by the technical solution provided by the embodiment of the present invention include at least:

[0019] 1) Using digital twins to achieve equivalent acceleration (including corrosion mechanisms and corrosion results) can significantly reduce the time and cost of material corrosion service performance evaluation;

[0020] 2) Considering the impact of the corrosion environment on the microscopic corrosion process of the material, online and offline corrosion data are combined with online environmental data, and the online and offline corrosion data are analyzed and processed to generate reprocessed data for the corrosion digital intelligent mechanism model to call. In the process of digital simulation, modeling and display are carried out from the mesoscopic to the macroscopic scale, which can realize the twinning of the entire corrosion evolution process from the mesoscopic to the macroscopic scale, and can visualize the entire corrosion process in real time;

[0021] 3) The corrosion acceleration test chamber and the corrosion intelligent digital mechanism model are mapped to each other, and the automatic iteration of the digital twin method can identify the range of equivalent acceleration according to the mechanism model, issue environmental parameter change instructions for the corrosion acceleration test chamber, and monitor feedback data through environmental monitoring sensors;

[0022] 4) It can realize an intelligent dynamic environmental spectrum, further improving the corrosion performance evaluation speed of materials while ensuring equivalent acceleration;

[0023] 5) The digital intelligent corrosion mechanism model trained using big data can achieve reasonable prediction of the corrosion service performance of materials in unknown environments, that is, predict the future. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0025] Figure 1 A schematic flow chart of a material corrosion service performance evaluation method based on digital twins provided in an embodiment of the present invention;

[0026] FIG2( a ) is a schematic diagram of three-dimensional XCT test results of an aluminum alloy sample provided by an embodiment of the present invention;

[0027] FIG2( b ) is a schematic diagram of a three-dimensional reconstruction of the microstructure of an aluminum alloy sample provided by an embodiment of the present invention;

[0028] Figure 3 A schematic diagram of the original environmental spectrum of corrosion service performance of aluminum alloy in a certain place provided by an embodiment of the present invention;

[0029] Figure 4 Schematic diagram of an example of a digital twin display platform for material service performance provided by an embodiment of the present invention;

[0030] Figure 5 A schematic diagram of a secondary current level set model provided by an embodiment of the present invention;

[0031] Figure 6 A schematic diagram of a real-time simulation corrosion expansion path provided by an embodiment of the present invention;

[0032] Figure 7 A schematic diagram of the acceleration environment spectrum after equivalent acceleration provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0033] To make the objectives, technical solutions and advantages of the present invention more clear, the embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.

[0034] like Figure 1 As shown, an embodiment of the present invention provides a material corrosion service performance evaluation method based on digital twins, including:

[0035] S101, establishing a corrosion data sensing system; specifically, the following steps may be included:

[0036] Based on the existing corrosion acceleration test chamber, environmental monitoring collection and control sensors are added, including temperature, humidity, light, SO2 and salt spray. When the corrosion intelligent digital mechanism model recognizes that the original environmental spectrum can be equivalently accelerated, it sends an instruction to the environmental monitoring control sensor to modify the environmental parameters. After receiving the instruction to modify the environmental parameters, the control sensor modifies the environmental parameters of the corrosion acceleration test chamber in real time.

[0037] Add online material corrosion data acquisition sensors to obtain online material corrosion data, including industrial cameras, ultrasonic thickness probes, ultrasonic guided wave probes, resistance probes, ACM galvanic sensors, optical fiber sensors, etc.

[0038] Since it is necessary to analyze the microscopic corrosion mechanism of the material, it is also necessary to add offline corrosion data receivers for offline testing of materials, including microscopes, spectrometers, 3D profilometers, XCT (X-ray computed tomography), etc., to obtain offline corrosion data of materials;

[0039] The multi-source heterogeneous data such as pictures, matrix arrays, text and videos obtained through the above means need to be input into the material corrosion information database for call by the digital twin platform.

[0040] It should be noted that in practical applications, the type of sensor used is determined by the actual situation.

[0041] S102, constructing a corrosion information database, designing accelerated environmental spectra (including original environmental spectra and equivalent accelerated environmental spectra) based on the corrosion life of the material, conducting accelerated environmental spectrum experiments in a corrosion acceleration test chamber, verifying the equivalence of the accelerated environmental spectra in terms of corrosion mechanism and corrosion results, and acquiring online environmental data, online material corrosion data, and offline material corrosion data from offline testing through an established corrosion data perception sensing system and storing them in the corrosion information database;

[0042] In this embodiment, the corrosion acceleration test chamber records online environmental data and material online corrosion data in real time during operation. After the offline material test is completed, the offline material corrosion data is input as raw data through the offline corrosion data receiver and stored in the corrosion information database.

[0043] S103, cleaning and processing the online and offline corrosion data of the material into the corrosion characteristics required for modeling through the corrosion information database, i.e., reprocessing the data;

[0044] In this embodiment, the corrosion information database constructed is used to classify, clean, process and store multi-source heterogeneous online and offline corrosion data. Specifically:

[0045] The online and offline corrosion data are combined as raw data. The corrosion information database analyzes and processes the online and offline corrosion data to generate the initial and boundary conditions required for the corrosion intelligent digital mechanism model in S104, including: material surface morphology, thickness loss, corrosion products and corrosion extension path information, and stores this information as reprocessed data of the raw data in the corrosion information database to provide the required parameters for the corrosion intelligent digital mechanism model.

[0046] S104, establishing a corrosion intelligent digital mechanism model: using online environmental data and reprocessing data of multiple materials as input to the corrosion intelligent digital mechanism model, incorporating the corrosion evolution laws of the materials into the model, establishing a cross-scale corrosion intelligent digital mechanism model with strong generalization capability from mesoscopic to macroscopic, providing life prediction for the corrosion performance of in-service materials, and realizing a digital twin of the corrosion service performance of materials; specifically, the following steps may be included:

[0047] A1: Use online environmental data and reprocessing data as inputs to the corrosion intelligent digital mechanism model. Integrate the corrosion evolution law of the material into the model to establish a corrosion intelligent digital mechanism model for a single material.

[0048] In this embodiment, online environmental data and reprocessing data (for example, information such as material surface morphology, thickness loss, corrosion products and corrosion extension path) are used as inputs of the corrosion intelligent digital mechanism model. The corrosion evolution law of the material is combined in the model to establish a mesoscopic to macroscopic cross-scale single material corrosion intelligent digital mechanism model, such as the secondary current level set model, the phase field corrosion model, the cellular automaton and the tertiary current finite element model.

[0049] In this embodiment, the intelligent digital mechanism model of corrosion can realize the switching coupling of corrosion models for different corrosion conditions of materials. Combined with algorithms such as machine learning, through the continuous input of a large amount of test data (including online environmental data and reprocessing data), the correction parameters (compensation parameters or equations of physical equation parameters in the digital mechanism model, such as correction of corrosion extension rate parameters of different grains in the material and compensation equation of second-phase corrosion activation factor, etc.) are continuously iteratively corrected and fitted. Ultimately, the real-time service performance of the material under the service environment can be predicted and evaluated, realizing the digital twin of the material's corrosion service performance.

[0050] In this embodiment, the training process of the intelligent digital corrosion mechanism model of a single material includes:

[0051] 1) Design an accelerated environmental spectrum based on the experimental atmospheric exposure data (or existing material corrosion data) and environmental data of Site A; that is, design the original environmental spectrum based on the corrosion life of the material;

[0052] 2) Conduct accelerated environmental spectrum experiments in a corrosion acceleration test chamber to verify the equivalence of the accelerated environmental spectrum in terms of corrosion mechanism and corrosion results;

[0053] 3) Based on the original environmental spectrum in 1), the corrosion data sensing system is used to adjust the acceleration conditions of the corrosion acceleration test chamber, such as temperature, humidity, light and salt spray, to further deteriorate the test chamber conditions, thereby increasing the acceleration rate of material corrosion. Through S102 monitoring of the material's online corrosion data and recording of the material's offline corrosion data, combined with S103 analysis and processing of these two types of corrosion data, the equivalence of the material corrosion mechanism in 1) is ensured. At this time, the digital twin method is used to quickly obtain a more efficient and comprehensive equivalent accelerated environmental spectrum. This saves a lot of time and labor costs for the subsequent service performance evaluation of the material at Site A;

[0054] 4) In actual application, if this material is in service at location A, the remaining life of the material can be predicted based on the corrosion intelligent digital mechanism model generated by the previous method S104 through periodic statistics of actual environmental parameters, thereby determining the inspection and maintenance time.

[0055] 5) Based on the equivalent accelerated environmental spectrum in 3), the actual environmental parameter range that can be equivalently applied is broadened to provide life prediction for the corrosion performance of service materials in more areas.

[0056] In this embodiment, the equivalent accelerated environment spectrum method is used to predict the corrosion service performance of actual metal structural materials.

[0057] A2, using multiple materials, repeatedly establishes the operation of the intelligent digital mechanism model of corrosion of a single material, and obtains a cross-scale intelligent digital mechanism model of corrosion from mesoscopic to macroscopic with strong generalization ability, provides life prediction for the corrosion performance of service materials, and realizes the digital twin of the material corrosion service performance.

[0058] In this embodiment, the influence of the corrosion environment on the microscopic corrosion process of the material is taken into consideration, and the online and offline corrosion data are combined with the online environmental data. The online and offline corrosion data are analyzed and processed to generate reprocessing data for the corrosion digital intelligent mechanism model to call. In the process of digital simulation, the modeling and display are carried out from the mesoscopic to the macroscopic scale, and the twinning of the entire corrosion evolution process from the mesoscopic to the macroscopic scale can be realized. This embodiment focuses on the corrosion mechanism inside the material, rather than just a single corrosion parameter, such as corrosion rate, corrosion thinning amount, etc., so the digital twin of the corrosion mechanism model at the mesoscopic scale can be realized.

[0059] In this embodiment, the digital twin method is used to achieve equivalent acceleration, which can significantly shorten the evaluation time, manpower and material resources for the corrosion service performance of materials.

[0060] In this embodiment, after using online environmental data and reprocessing data of multiple materials as inputs to the intelligent digital corrosion mechanism model, incorporating the corrosion evolution laws of the materials into the model, and establishing a cross-scale intelligent digital corrosion mechanism model with strong generalization capability from mesoscopic to macroscopic, providing life prediction for the corrosion performance of in-service materials and realizing the digital twin of the material corrosion service performance, the method further includes:

[0061] A digital twin support and display platform for material service performance has been established. This platform enables real-time shared access across multiple platforms, including web, tablet, and mobile devices, and incorporates a three-tiered management system consisting of managers, researchers, and visitors. The platform allows users to view the operational status of the corrosion acceleration test chamber, the storage status of the corrosion information database, actual material testing results, and the real-time evolution of the intelligent digital corrosion mechanism model. The platform also supports integrated redevelopment and the incorporation of digital twins for various service performance indicators, such as corrosion fatigue and creep.

[0062] The digital twin-based material corrosion service performance evaluation method described in the embodiment of the present invention establishes a corrosion data perception sensing system, a corrosion information database, a corrosion intelligent digital mechanism model and a material service performance digital twin support and display platform to jointly form a digital twin for material corrosion service performance evaluation, which can effectively respond to changes in the material service environment and corrosion performance.

[0063] In this example, an environmental profile was designed based on the actual material corrosion lifespan and tested in an accelerated test chamber to verify the equivalence of the accelerated environmental profile in terms of corrosion mechanism and corrosion results. Machine learning and other algorithms were then used to autonomously learn and modify compensation parameters in the intelligent digital corrosion mechanism model. Ultimately, the digital twin was able to independently control the environmental profile to achieve an equivalent acceleration of the material corrosion lifespan. Simultaneously, the intelligent digital corrosion mechanism model was trained using a large amount of material corrosion and environmental data, ultimately enabling reasonable predictions of the corrosion performance of materials in unknown environments.

[0064] The material corrosion service performance evaluation method based on digital twins described in the embodiment of the present invention can at least have the following beneficial effects:

[0065] 1) Using digital twins to achieve equivalent acceleration (including corrosion mechanisms and corrosion results) can significantly reduce the time and cost of material corrosion service performance evaluation;

[0066] 2) Considering the impact of the corrosion environment on the microscopic corrosion process of the material, online and offline corrosion data are combined with online environmental data, and the online and offline corrosion data are analyzed and processed to generate reprocessed data for the corrosion digital intelligent mechanism model to call. In the process of digital simulation, modeling and display are carried out from the mesoscopic to the macroscopic scale, which can realize the twinning of the entire corrosion evolution process from the mesoscopic to the macroscopic scale, and can visualize the entire corrosion process in real time;

[0067] 3) The corrosion acceleration test chamber and the corrosion intelligent digital mechanism model are mapped to each other, and the automatic iteration of the digital twin method can identify the range of equivalent acceleration according to the mechanism model, issue environmental parameter change instructions for the corrosion acceleration test chamber, and monitor feedback data through environmental monitoring sensors;

[0068] 4) It can realize an intelligent dynamic environmental spectrum, further improving the corrosion performance evaluation speed of materials while ensuring equivalent acceleration;

[0069] 5) The digital intelligent corrosion mechanism model trained using big data can achieve reasonable prediction of the corrosion service performance of materials in unknown environments, that is, predict the future.

[0070] To better understand the material corrosion service performance evaluation method based on digital twins provided in an embodiment of the present invention, the processing of multiple parallel aluminum alloy specimens is used as an example to illustrate the method. The method can mainly include the following steps:

[0071] Step 1: Process multiple aluminum alloy parallel specimens for XCT (as shown in Figure 2(a)) and EBSD (electron backscatter diffraction) characterization. The aluminum alloy microstructure is analyzed and three-dimensionally reconstructed, as shown in Figure 2(b). This provides a source of material intrinsic parameters for the intelligent digital corrosion mechanism model, such as the structure and size of the second phase, grain size, and Euler angle distribution.

[0072] Step 2: Process multiple parallel aluminum alloy specimens and place them in the corrosion acceleration test chamber simultaneously. Different parallel aluminum alloy specimens are equipped with functions that provide different parameters, such as ultrasonic thickness measurement, industrial camera, offline XRD (X-ray diffraction), offline 3D profilometer, etc.

[0073] Step 3: Based on the original environmental spectrum of a place, such as Figure 3 As shown, the environmental parameters of the corrosion acceleration test chamber are set. One cycle of the environmental spectrum represents the corrosion result of outdoor aluminum alloy in one year of service. The online environmental data and the online corrosion data of the material captured by the sensor are written into the corrosion information database in real time.

[0074] Step 4: Take out parallel aluminum alloy samples for offline testing at regular intervals, such as 7 days, 14 days, 21 days, 28 days, etc. Use microscopes, spectrometers, 3D profilometers, XCT and other means to characterize the material service conditions at different time periods. Write the data into the corrosion information database as the material offline corrosion data, and display it in combination with the material service performance digital twin support display platform, such as Figure 4 At this point, the online and offline corrosion data of the material are combined as raw data, and then cleaned and processed into the corrosion characteristics required for modeling, that is, reprocessed data, to provide the required parameters for the corrosion intelligent digital mechanism model;

[0075] Step 5: Combine the reprocessing data obtained from the cleaning process in the database, such as pit size, three-dimensional morphological distribution, corrosion product information, corrosion current density online change trend, etc., to establish a Figure 5 The secondary current level set model can simulate the corrosion path process of corrosion pits and intergranular corrosion in real time, such as Figure 6 As shown in the figure, combined with continuous database acquisition, the obtained data continuously modifies the intelligent digital corrosion mechanism model, including the corrosion growth rate compensation equations for different grains, until a perfect match is achieved. At this point, a complete intelligent digital corrosion mechanism model for this environmental spectrum has been obtained.

[0076] Step 6: Use the corrosion data intelligent perception system to perceive and process the corrosion information of physical specimens, and combine it with the corrosion intelligent digital mechanism model to further improve the acceleration ratio of the corrosion acceleration experiment, such as Figure 7 As shown in the figure, at this time, the cycle period for obtaining the equivalent accelerated environmental spectrum is reduced from 14 days to 9 days, while ensuring the equivalence of the material corrosion mechanism. Using this digital twin method, a more efficient and comprehensive equivalent accelerated environmental spectrum can be quickly obtained.

[0077] Step 7: Repeat steps 1-5 using multiple materials and multiple environment spectra. When the repetition reaches dozens of times or more, a digital twin entity with very strong generalization capabilities will be obtained.

[0078] Step 8: The digital twin is then assigned to an unknown environment and material system. It will provide a comprehensive lifespan trend. As environmental parameter monitoring inputs are fed into the digital twin, it can display the material's current corrosion mechanism and remaining lifespan in real time, enabling a reasonable prediction of the maintenance time. By re-inputting maintenance results, the digital twin can proactively learn and provide even more accurate predictions.

[0079] 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 in the scope of protection of the present invention.

Claims

1. A material corrosion service performance evaluation method based on digital twins, characterized in that: include: S101, establish a corrosion data perception sensing system; S102, constructing a corrosion information database, designing an accelerated environmental spectrum based on the corrosion life of the material, conducting an accelerated environmental spectrum experiment in a corrosion acceleration test chamber, verifying the equivalence of the accelerated environmental spectrum in terms of corrosion mechanism and corrosion results, and acquiring online environmental data, online material corrosion data, and offline material corrosion data from offline testing through an established corrosion data sensing system, and storing the data in the corrosion information database; wherein the accelerated environmental spectrum includes: an original environmental spectrum and an equivalent accelerated environmental spectrum; S103, cleaning and processing the online and offline corrosion data of the material into the corrosion characteristics required for modeling through the corrosion information database, i.e., reprocessing the data; S104 uses online environmental data and reprocessing data of multiple materials as input to the intelligent digital corrosion mechanism model. The model incorporates the corrosion evolution laws of the materials to establish a cross-scale intelligent digital corrosion mechanism model with strong generalization capabilities, from mesoscopic to macroscopic. This model provides life prediction for the corrosion performance of in-service materials and realizes the digital twin of the material corrosion service performance. Wherein, the establishment of the corrosion data perception sensing system includes: On the basis of the existing corrosion acceleration test chamber, environmental monitoring collection and control sensors, material online corrosion data acquisition sensors and material offline corrosion data receivers for offline testing are added; wherein, the environmental monitoring control sensors modify the environmental parameters of the corrosion acceleration test chamber after receiving the modification instructions for the environmental parameters from the corrosion intelligent digital mechanism model; wherein, when the corrosion intelligent digital mechanism model recognizes that the original environmental spectrum can be equivalently accelerated again, it sends an instruction to modify the environmental parameters to the environmental monitoring control sensors, and after receiving the environmental parameter modification instructions, the control sensors modify the environmental parameters of the corrosion acceleration test chamber in real time.

2. The material corrosion service performance evaluation method based on digital twin according to claim 1 is characterized in that: The corrosion data perception sensing system established by S101 is used to adjust the acceleration conditions of the corrosion acceleration test chamber, and the accelerated online environmental data and processing data are obtained through S102 and S103 respectively, that is, the equivalent acceleration environment spectrum is obtained using the digital twin method.

3. The material corrosion service performance evaluation method based on digital twin according to claim 1 is characterized in that: The online environmental data and reprocessing data of multiple materials are used as inputs to the intelligent digital corrosion mechanism model. The corrosion evolution laws of the materials are combined in the model to establish a cross-scale intelligent digital corrosion mechanism model with strong generalization ability from mesoscopic to macroscopic. This model provides life prediction for the corrosion performance of in-service materials and realizes the digital twin of material corrosion service performance, including: The online environmental data and reprocessing data are used as inputs to the corrosion intelligent digital mechanism model. The corrosion evolution law of the material is combined in the model to establish a corrosion intelligent digital mechanism model for a single material. By using multiple materials and repeatedly establishing the intelligent digital mechanism model of corrosion of a single material, we can obtain a cross-scale intelligent digital mechanism model of corrosion from mesoscopic to macroscopic with strong generalization ability, provide life prediction for the corrosion performance of service materials, and realize the digital twin of material corrosion service performance.

4. The material corrosion service performance evaluation method based on digital twin according to claim 1 is characterized in that: After using online environmental data and reprocessing data of multiple materials as inputs to the corrosion intelligent digital mechanism model, incorporating the corrosion evolution laws of the materials into the model, and establishing a cross-scale corrosion intelligent digital mechanism model with strong generalization capability from mesoscopic to macroscopic, providing life prediction for the corrosion performance of in-service materials and realizing the digital twin of the material corrosion service performance, the method further includes: Build a digital twin support and display platform for material service performance.

5. The material corrosion service performance evaluation method based on digital twin according to claim 4 is characterized in that: The material service performance digital twin support and display platform is used to view the operation status of the corrosion acceleration test chamber, the storage status of the corrosion information database, the actual experimental conditions of the material and the real-time evolution of the corrosion intelligent digital mechanism model.

6. The material corrosion service performance evaluation method based on digital twin according to claim 4 is characterized in that: The material service performance digital twin support and display platform supports the function of integrated redevelopment and the incorporation of digital twins of various service performances.

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