Metal force-bearing component environment adaptability quantitative evaluation method and device integrating apparent damage and mechanical damage characteristics

Abstract

The invention discloses a quantitative evaluation method and device for environmental adaptability of a metal force-bearing component integrating apparent damage and mechanical damage characteristics, and relates to the field of high environmental adaptability evaluation of products and structural life evaluation. The method comprises the following steps: firstly, acquiring historical data of apparent damage characteristics, historical data of mechanical property characteristics and historical data of environmental parameters of the metal bearing structure; then constructing an apparent damage-environmental stress dynamic model and a mechanical property-environmental stress dynamic model according to the obtained historical data; constructing a performance index model; and then evaluating the high environment adaptability of the metal bearing structure in different use environments according to the performance index model to obtain performance indexes at different time. According to the method, the environmental stress, the apparent damage and the mechanical property are comprehensively considered in the quantitative evaluation process of the environmental adaptation level of the product, and the accuracy and comprehensiveness of structural adaptation capability evaluation are improved.

Description

Technical Field

[0001] This application relates to the fields of product environmental adaptability assessment and structural life assessment, and in particular to a method and apparatus for quantitatively assessing the environmental adaptability of metal load-bearing components by comprehensively considering apparent damage and mechanical damage characteristics. Background Technology

[0002] With the development of technology and the continuous increase in industrial demand, equipment products face multiple environmental stress threats when serving in natural environments for extended periods, including temperature fluctuations, humidity erosion, and salt spray corrosion. These environmental factors cause the apparent damage (such as corrosion and cracks) and mechanical properties (such as strength and toughness) of equipment to exhibit complex dynamic degradation characteristics. Traditional equipment life assessment methods mainly rely on accelerated life testing and linear degradation models, which are difficult to fully reflect the complex conditions under actual use environments.

[0003] Existing corrosion failure prediction methods have several limitations, such as small sample sizes, insufficient consideration of the complexity of environmental factors, and significant deviations between predicted and actual lifespan results. Furthermore, existing mechanical performance evaluation methods typically do not consider the impact of environmental corrosion on material properties, or analyze only a single influencing factor, making it difficult to comprehensively reflect the interactions among various factors. These methods struggle to accurately predict the actual service life and performance changes of equipment in complex environments, impacting equipment design optimization and maintenance strategy development. Specifically, existing technologies suffer from the following drawbacks: 1) Traditional life assessment methods mainly rely on accelerated life testing and linear degradation models, which are difficult to fully reflect the complex conditions in actual use environments, resulting in a large deviation between the predicted results and the actual results.

[0004] 2) Existing corrosion failure prediction methods have problems such as small sample size and insufficient consideration of the complexity of environmental factors, making it difficult to accurately predict the actual service life of equipment in complex environments.

[0005] 3) Current mechanical property evaluation methods usually do not consider the impact of environmental corrosion on material properties, or only analyze a single influencing factor, making it difficult to fully reflect the interaction of various influencing factors.

[0006] 4) Existing technologies lack a quantitative assessment method for the environmental adaptability of equipment that can comprehensively consider environmental stress, apparent damage and mechanical properties, making it difficult to dynamically describe the adaptive change patterns of equipment in complex environments. Summary of the Invention

[0007] The purpose of this application is to provide a method and apparatus for quantitatively evaluating the environmental adaptability of metal load-bearing components by comprehensively considering both apparent damage and mechanical damage characteristics, so as to improve the accuracy and comprehensiveness of structural performance prediction.

[0008] To achieve the above objectives, this application provides the following solution.

[0009] Firstly, this application provides a method for quantitatively assessing the environmental adaptability of metal load-bearing components by comprehensively considering both apparent and mechanical damage characteristics, including: Historical data on apparent damage characteristics, mechanical performance characteristics, and environmental parameters of metal load-bearing structures were obtained. Based on historical data of apparent damage characteristics and historical data of environmental parameters, a dynamic model of apparent damage-environmental stress is constructed. Based on historical data of mechanical performance characteristics and historical data of environmental parameters, a dynamic model of mechanical performance-environmental stress is constructed. A performance index model is constructed based on the apparent damage-environmental stress dynamic model and the mechanical property-environmental stress dynamic model. The high environmental adaptability of the metal load-bearing structure under different usage environments is evaluated based on the performance index model, and performance indexes at different times are obtained.

[0010] Optionally, when the damage type of the metal load-bearing structure is corrosion damage, the apparent damage feature is the corrosion degree index; when the damage type of the metal load-bearing structure is crack damage, the apparent damage feature is the second moment and contrast of the crack edge; when the damage type of the metal load-bearing structure is coating peeling, the apparent damage feature is the coating failure rate. The mechanical property characteristics are: quasi-static tensile characteristics, impact toughness characteristics, or fatigue performance degradation characteristics; the quasi-static tensile characteristics are: extracted tensile strength, yield strength, or elastic modulus; the impact toughness characteristics are: energy absorbed per unit area; the fatigue performance degradation characteristics are: crack propagation rate.

[0011] Optionally, based on historical data of apparent damage characteristics and historical data of environmental parameters, a dynamic model of apparent damage-environmental stress is constructed, specifically including: Based on the fact that the development process of apparent damage includes a linear stage and an exponential acceleration stage, a piecewise nonlinear model is constructed. Based on historical data of apparent damage characteristics and historical data of environmental parameters, the parameters in the piecewise nonlinear model are solved to obtain the apparent damage-environmental stress dynamic model.

[0012] Optionally, the apparent damage-environmental stress dynamic model is: ; in, This represents the predicted value of the apparent damage characteristics at time t. The initial values ​​for the apparent damage characteristics. This represents the damage growth rate during the linear phase. This represents the critical time between the linear phase and the exponential acceleration phase. The rate of damage growth during the exponential acceleration phase. It is the Sigmoid transition function. For time integration variables, It is a nonlinear environmental stress coupling factor. = , for Humidity at that time for Salt spray concentration at that time for time , , These are the accelerating factors of humidity, salt spray concentration, and temperature on the apparent damage rate, respectively. This represents the interaction coefficient between humidity and salt spray. This represents the temperature-salt spray interaction coefficient.

[0013] Optionally, a dynamic model of mechanical properties and environmental stress is constructed based on historical data of mechanical performance characteristics and historical data of environmental parameters, specifically including: An environmental stress influence factor is introduced to construct a power-law Arrhenius model; Based on historical data of mechanical performance characteristics and historical data of environmental parameters, the parameters in the power-law-Arrhenius model are solved to obtain the dynamic model of mechanical performance-environmental stress.

[0014] Optionally, the mechanical property-environmental stress dynamic model is: ; in, This represents the predicted value of the mechanical performance characteristics at time t. These are the initial values ​​for the mechanical properties. and ' The parameter to be evaluated. For activation energy, The gas constant is , These are the accelerating factors of humidity and salt spray on the degradation of mechanical properties, respectively. The humidity at time t Let be the salt spray concentration at time t. Let be the temperature at time t.

[0015] Optionally, a performance index model is constructed based on the apparent damage-environmental stress dynamic model and the mechanical property-environmental stress dynamic model, specifically including: Based on the coupling mechanism of apparent damage and mechanical properties, a model for the influence of apparent damage on mechanical properties is determined. The influence model is as follows: ; in, For time The amount of change in mechanical properties caused by external damage over time. Predicted values ​​of apparent damage characteristics at time t. for humidity, for Salt spray concentration, for temperature, These are the static coupling coefficients. For dynamic coupling coefficients, , , ' These are the direct contribution coefficients of temperature, humidity, and salt spray concentration to the degradation of mechanical properties, respectively. Based on the aforementioned influence model, the mechanical performance-environmental stress dynamic model is modified using the following formula to obtain the modified mechanical performance-environmental stress dynamic model. ; in, The correction value representing the mechanical performance characteristics at time t. The predicted value representing the mechanical performance characteristics at time t; A performance index model is constructed based on the apparent damage-environmental stress dynamic model and the modified mechanical property-environmental stress dynamic model.

[0016] Optionally, the performance index model is: ; in, This represents the performance index of the metal load-bearing structure at time t. This is the correction value for the mechanical performance characteristics at time t. This represents the predicted value of the apparent damage characteristics at time t. This represents the critical mechanical property threshold at time t. The critical damage threshold at time t; , This is the initial critical mechanical property threshold. , , These are the influence coefficients of temperature, humidity, and salt spray concentration on the critical mechanical property threshold, respectively. For reference temperature, for humidity, for Salt spray concentration, for Temperature; , This is the initial critical damage threshold. , , These are the influence coefficients of temperature, humidity, and salt spray concentration on the critical damage threshold, respectively.

[0017] Based on the performance indicators at different times, the time when the performance indicators are less than the structural performance failure threshold is determined as the failure time; the remaining life of the metal load-bearing structure is obtained by subtracting the current time from the failure time.

[0018] Secondly, this application provides a device for quantitatively evaluating the environmental adaptability of metal load-bearing components based on the comprehensive characteristics of apparent damage and mechanical damage. The device is applied to the aforementioned method for quantitatively evaluating the environmental adaptability of metal load-bearing components based on the comprehensive characteristics of apparent damage and mechanical damage. The device includes: an apparent damage testing device, a mechanical performance testing device, an environmental testing device, and a host computer. The apparent damage testing device, the mechanical performance testing device, and the environmental testing device are used to acquire historical data on the apparent damage characteristics, mechanical performance characteristics, and environmental parameters of the metal load-bearing structure. The host computer is used to execute the above-mentioned quantitative evaluation method for the environmental adaptability of metal load-bearing components based on the comprehensive apparent damage and mechanical damage characteristics, to evaluate the high environmental adaptability of the metal load-bearing structure under different usage environments, and to obtain performance indicators at different times.

[0019] According to the specific embodiments provided in this application, this application has the following technical effects.

[0020] This application provides a method and apparatus for quantitatively assessing the environmental adaptability of metal load-bearing components by comprehensively considering apparent damage and mechanical damage characteristics. First, historical data on apparent damage characteristics, mechanical performance characteristics, and environmental parameters of the metal load-bearing structure are acquired. Then, based on the historical data on apparent damage characteristics and environmental parameters, a dynamic model of apparent damage-environmental stress is constructed. Next, based on the historical data on mechanical performance characteristics and environmental parameters, a dynamic model of mechanical performance-environmental stress is constructed. Based on the dynamic models of apparent damage-environmental stress and mechanical performance-environmental stress, a performance index model is constructed. Then, based on the performance index model, the time when the performance index is less than the structural performance failure threshold is determined as the failure time. The remaining life of the metal load-bearing structure is obtained by subtracting the current time from the failure time. This application comprehensively considers environmental stress, apparent damage, and mechanical performance in the performance prediction process, improving the accuracy and comprehensiveness of structural performance prediction. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a flowchart illustrating a method for quantitatively evaluating the environmental adaptability of metal load-bearing components by integrating apparent damage and mechanical damage characteristics, as provided in an embodiment of this application.

[0023] Figure 2 This is a schematic diagram of a device for quantitatively evaluating the environmental adaptability of a metal load-bearing component by comprehensively considering apparent damage and mechanical damage characteristics, provided as an embodiment of this application. Detailed Implementation

[0024] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0025] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0026] Based on the aforementioned background technology, there is an urgent need for an equipment life assessment method that can comprehensively consider environmental stress, apparent damage, and mechanical properties to improve the accuracy and comprehensiveness of equipment life prediction. This method should be able to dynamically describe the adaptive changes of equipment in complex environments, providing a scientific basis for equipment design, maintenance, and replacement, thereby extending equipment service life, reducing maintenance costs, and improving system reliability and safety.

[0027] In one exemplary embodiment, a method for quantitatively assessing the environmental adaptability of metal load-bearing components by comprehensively considering both apparent and mechanical damage characteristics is provided, such as... Figure 1 As shown, it includes the following steps 101-105.

[0028] Step 101: Obtain historical data on apparent damage characteristics, mechanical performance characteristics, and environmental parameters of the metal load-bearing structure.

[0029] Step 102: Based on historical data of apparent damage characteristics and historical data of environmental parameters, construct a dynamic model of apparent damage-environmental stress.

[0030] Step 103: Based on historical data of mechanical performance characteristics and historical data of environmental parameters, construct a dynamic model of mechanical performance-environmental stress.

[0031] Step 104: Construct a performance index model based on the apparent damage-environmental stress dynamic model and the mechanical property-environmental stress dynamic model.

[0032] Step 105: Obtain the performance indicators of the metal load-bearing structure under different usage environments and at different times based on the performance index model.

[0033] Implementing steps 101-105 above can improve the accuracy and comprehensiveness of the assessment of the structure's high environmental adaptability level.

[0034] In another exemplary embodiment, when the damage type of the metal load-bearing structure is corrosion damage, the above-mentioned apparent damage feature is the corrosion degree index; when the damage type of the metal load-bearing structure is crack damage, the above-mentioned apparent damage feature is the second moment and contrast of the crack edge; when the damage type of the metal load-bearing structure is coating peeling, the above-mentioned apparent damage feature is the coating failure rate.

[0035] Each apparent damage feature can be obtained using the following steps 201-202.

[0036] Step 201: Data acquisition and preprocessing. A multispectral imaging system is used in combination with polarized light and natural light illumination to achieve high-precision three-dimensional reconstruction of surface damage.

[0037] 1.1 Noise Suppression: Based on adaptive Gaussian filtering (window size 3×3, standard deviation σ=1.5), random noise is eliminated while preserving details of damaged edges.

[0038] 1.2 Contrast Enhancement: Adaptive Histogram Equalization Based on Limiting Contrast (CLAHE) algorithm (block size 64×64 pixels) is adopted to improve the damage characteristics of low contrast areas.

[0039] 1.3 Geometric correction: Image distortion is eliminated through perspective transformation to ensure spatial consistency of feature quantization results.

[0040] Step 202: Extract apparent damage features, determine the damage type, and quantify the damage based on the damage type; 2.1. For corrosion damage: (1) Based on the improved Canny algorithm (the dynamic threshold is determined by the Otsu method, low threshold = 0.4 × maximum gradient, high threshold = 0.8 × maximum gradient) to extract the corrosion contour, and combine it with morphological closing operation (circular structuring element, radius 5 pixels) to fill the holes; (2) Use a laser confocal 3D topology instrument (accuracy 0.1μm) to obtain the corrosion depth distribution and define the corrosion degree index (CDI): CDI=α0·Acorr+β0·Dcorr (1); Where Acorr is the corrosion area, Dcorr is the average depth, and α and β are weighting coefficients (calibrated through principal component analysis).

[0041] 2.2. For crack damage: (1) Identify the main direction of the crack by Radon transform and detect linear cracks by Hough transform (minimum length threshold = 50 pixels); (2) Calculate the second moment of the crack edge and the contrast based on the gray-level co-occurrence matrix (GLCM) to quantify the crack propagation trend. 2.3. For coating peeling: (1) Divide the peeling area in the HSV color space (H∈[0,50], S∈[0.3,1], V∈[0.5,1]) and combine the region growth algorithm to eliminate noise; (2) Calculate the proportion of peeling area and the coating failure rate.

[0042] In another exemplary embodiment, the above-mentioned mechanical property characteristics are: quasi-static tensile characteristics, impact toughness characteristics, or fatigue performance degradation characteristics; the quasi-static tensile characteristics are: extracted tensile strength, yield strength, or elastic modulus; the impact toughness characteristics are: energy absorbed per unit area; and the fatigue performance degradation characteristics are: crack propagation rate.

[0043] Each mechanical property characteristic can be obtained using the following steps 301-302.

[0044] Step 301, Quasi-static and Dynamic Mechanical Property Testing: (1) Quasi-static Tensile Test: According to ASTM E8 standard, stress-strain curves were obtained using a universal testing machine (loading rate 1 mm / min). Yield strength, tensile strength, and elastic modulus were extracted; (2) Impact Toughness Test: Based on ASTM E23 standard, Charpy V-notch specimens were used to calculate the energy absorbed per unit area: Where W is the impact energy and A is the cross-sectional area of ​​the notch.

[0045] Step 302: Perform fatigue performance degradation modeling, obtain fatigue life data using the step loading method, and describe the crack propagation rate using Pairs' law: (2); In the formula, This represents the stress intensity factor amplitude. and These are material constants (determined by fitting experimental data using the least squares method).

[0046] In another exemplary embodiment, step 102 described above can be replaced by steps 401-402.

[0047] Step 401: Based on the fact that the development process of apparent damage includes a linear stage and an exponential acceleration stage, a piecewise nonlinear model is constructed.

[0048] Step 402: Based on historical data of apparent damage characteristics and historical data of environmental parameters, solve for the parameters in the piecewise nonlinear model to obtain the apparent damage-environmental stress dynamic model.

[0049] In another exemplary embodiment, in step 401 above, based on the high correlation between damage development patterns and environmental stress, a piecewise nonlinear model is proposed by dividing the time domain and establishing a critical threshold dependent on environmental stress. Specifically: The model uses time-domain segmentation to divide the damage development process into a linear phase and an exponentially accelerating phase, with the critical time tc serving as the dividing point. 1) Linear stage ( ) based on We can obtain, (3); In the formula, This represents the predicted value of the apparent damage characteristics at time t. The initial values ​​for the apparent damage characteristics. The damage growth rate in the linear stage is the damage increment caused by a unit environmental stress. The damage rate is constant in this stage and is suitable for the initial stage when the environmental stress is low or the material has strong damage resistance. This stage is dominated by the accumulation of surface micro-defects, and the damage rate is constrained by the intrinsic resistance of the material. Exponential acceleration phase ( ) (4); In the formula: The function is the Sigmoid function, where λ controls the steepness of the transition. , , These are the accelerating factors of humidity, salt spray concentration, and temperature on the apparent damage rate, respectively. ζ and ξ For interaction coefficients, The interaction coefficient between humidity and salt spray characterizes the synergistic effect of humidity and salt spray. ， The interaction coefficient between temperature and salt spray represents the synergistic effect of temperature and salt spray.

[0050] This is a nonlinear environmental stress coupling factor; for humidity, for Salt spray concentration, for Temperature reflects the dynamic changes in environmental stress.

[0051] In another exemplary embodiment, the constructed apparent damage-environmental stress dynamic model is as follows: (5); in, This represents the predicted value of the apparent damage characteristics at time t. The initial values ​​for the apparent damage characteristics. This represents the damage growth rate during the linear phase. This represents the critical time between the linear phase and the exponential acceleration phase. The rate of damage growth during the exponential acceleration phase. It is the Sigmoid transition function. For time integration variables, It is a nonlinear environmental stress coupling factor. = , for Humidity at that time for Salt spray concentration at that time for time , , These are the accelerating factors of humidity, salt spray concentration, and temperature on the apparent damage rate, respectively. This represents the interaction coefficient between humidity and salt spray. This represents the temperature-salt spray interaction coefficient.

[0052] in, This reflects the material's ability to resist environmental erosion; critical time. t c The turning point from linear accumulation to accelerated failure in the marker damage mechanism is closely related to the material's microstructure. The Sigmoid transition function changes the two-stage transition process from "abrupt" to "gradual," conforming to the natural transition of the material from stable damage accumulation to accelerated failure under environmental stress; it introduces an integral form to dynamically accumulate environmental stress ( , , The real-time effect of damage rate can also be realized using discrete accumulation; , , It reflects the accelerating effect of humidity, salt spray concentration, and temperature on the exponential phase.

[0053] In another exemplary embodiment, step 103 described above can be replaced by steps 501-502.

[0054] Step 501: Introduce the environmental stress influence factor and construct the power-law Arrhenius model.

[0055] Step 502: Based on historical data of mechanical performance characteristics and historical data of environmental parameters, solve for the parameters in the power-law-Arrhenius model to obtain the dynamic model of mechanical performance-environmental stress.

[0056] In another exemplary embodiment, in step 501 above, the power-law Arrhenius model is extended to include the synergistic effect of humidity and salt spray, and an environmental stress influence factor is introduced to construct the power-law Arrhenius model.

[0057] In another exemplary embodiment, the constructed mechanical property-environmental stress dynamic model is as follows: (6); in, This represents the predicted value of the mechanical performance characteristics at time t. These are the initial values ​​for the mechanical properties. and ' The parameter to be evaluated. For activation energy, The gas constant is , These are the accelerating factors of humidity and salt spray on the degradation of mechanical properties, respectively. for humidity, for Salt spray concentration, for The temperature.

[0058] In another exemplary embodiment, step 104 described above can be replaced by steps 601-603.

[0059] Step 601: Based on the apparent damage-mechanical property coupling mechanism, determine the influence model of apparent damage on mechanical properties.

[0060] This application affects the model. Based on the existing static and dynamic coupling, a direct action term of environmental stress is introduced, specifically in the form of: (7); in, For time The amount of change in mechanical properties caused by apparent damage over time. Predicted values ​​of apparent damage characteristics at time t. for humidity, for Salt spray concentration, for temperature, These are the static coupling coefficients. For dynamic coupling coefficients, , , ' These are the direct contribution coefficients of temperature, humidity, and salt spray concentration to the degradation of mechanical properties, respectively. in, Characterizes the immediate weakening effect of unit damage area on mechanical properties (such as stress concentration caused by corrosion), unit MPa / mm. 2 ; Reflects the long-term impact of damage accumulation rate on performance degradation (such as crack propagation accelerating fatigue failure), unit MPa·day / mm²; , , 'This reflects the additional effects of environmental stress independent of damage (such as high-temperature-induced material softening), with units of MPa / ℃, MPa / %RH, and MPa / (g / m³), respectively. The damage rate.

[0061] Step 602: Based on the influence model, the mechanical performance-environmental stress dynamic model is modified using the following formula to obtain the modified mechanical performance-environmental stress dynamic model.

[0062] (8); in, The correction value representing the mechanical performance characteristics at time t. This represents the predicted value of the mechanical performance characteristics at time t.

[0063] Step 603: Construct a performance index model based on the apparent damage-environmental stress dynamic model and the modified mechanical property-environmental stress dynamic model.

[0064] In another exemplary embodiment, an environmentally adaptive growth model integration is implemented. Combining the above models, the performance index model is defined as follows: (9); in, This represents the performance index of the metal load-bearing structure at time t. This is the correction value for the mechanical performance characteristics at time t. This represents the predicted value of the apparent damage characteristics at time t. This represents the critical mechanical property threshold at time t. The critical apparent damage threshold at time t; , This is the initial critical mechanical property threshold. , , These are the influence coefficients of temperature, humidity, and salt spray concentration on the critical mechanical property threshold, respectively, obtained through accelerated aging test standards. For reference temperature (e.g., 25℃). for humidity, for Salt spray concentration, for The temperature.

[0065] , This is the initial critical apparent damage threshold. , , These are the influence coefficients of temperature, humidity, and salt spray concentration on the critical damage threshold, which were calibrated through accelerated aging tests. From the fracture toughness of the material And the critical stress intensity factor is determined, satisfying, (10); In the formula: This represents the maximum allowable stress of the material.

[0066] In another exemplary embodiment, step 105 is followed by steps 106 and 107.

[0067] Step 106: Based on the performance indicators at different times, determine the time when the performance indicators are less than the structural performance failure threshold, and use this time as the failure time; for example, when S(t) < 0.6, the product is determined to enter a high-risk state, and t at this time is the failure time.

[0068] Step 107: Subtract the current time from the failure time to obtain the remaining life of the metal load-bearing structure.

[0069] In another exemplary embodiment, in order to illustrate the implementation and effects of the above method embodiments, the following example is provided, specifically including steps 701-704.

[0070] Step 701: Obtain samples and collect sample data. Taking the flat plate specimen, tensile specimen and impact specimen of aluminum alloy 6061-T6 as the experimental objects, and taking the 30-day experiment in salt spray-humid heat coupling environment as an example, there are 5 parallel samples of each type. The corrosion area measurement test is a non-destructive test, so there are 5 samples in total. The other two types of tests are destructive tests, and the number of samples in each time period is 5, so there are 35 samples in each type. The specific experimental conditions are shown in Table 1.

[0071] Table 1 Experimental conditions

[0072] Step 702: Measured data of apparent damage and mechanical properties. The corrosion area, tensile strength and impact toughness were measured every 5 days. The values ​​are the average values ​​of 5 samples, as shown in Table 2.

[0073] Table 2 Measured data of apparent damage and mechanical properties

[0074] Step 703, apparent damage parameter calibration and error analysis: 1) Parameter calibration method Objective function: Minimize the root mean square error (RMSE).

[0075] RMSE= ; in, For time Model predictions of apparent damage characteristics at time. For time Measured values ​​of apparent damage characteristics at that time. The number of tests.

[0076] Optimization Algorithm: Bayesian Optimization (based on Gaussian process prior) The parameter boundaries are shown in Table 3.

[0077] Table 3 Parameter Range Calibration steps: 1) Data partitioning: The first 70% of the data (days 0-21) is used for calibration, and the last 30% (days 22-30) is used for validation; 2) 5-fold cross-validation: The 30-day experimental data is divided into 5 subsets (each 6 days is a fold), with 4 folds used as the training set and 1 fold as the validation set, and the average RMSE is calculated to verify the model stability, as shown in Table 4; 3) Rolling time window validation: The initial 7 days are used as the training window, which is gradually expanded to 21 days, and the data for the next 3 days is predicted to verify the generalization ability; 4) Bayesian optimization: The hyperparameter combination is selected to minimize the RMSE by iteratively updating the high-precision process model; 5) Convergence condition: The RMSE change is less than 0.1% after 10 consecutive iterations.

[0078] Table 4. RMSE of the three verification methods

[0079] Based on Bayesian optimization, 100 random initialization parameter calibration experiments were conducted, and the mean and standard deviation of each parameter were statistically analyzed (see Table 5). The results show that k1 = 0.052 ± 0.003, k2 = 0.180 ± 0.005, the critical time tc = 15 ± 0.5, and the parameter fluctuation range is less than 5%, verifying the stability of the calibration process. The calibration results are shown in Table 6.

[0080] Table 5. Stability analysis of apparent damage model parameter calibration Table 6 Calibration Results 2) Error sensitivity analysis The impact of measurement errors (corrosion area ±1.2%, intensity ±0.5%) on model calibration was quantified using Monte Carlo simulations (1000 random perturbations). The results showed that the fluctuation ranges of parameters k1 and k2 expanded to 0.050–0.054 and 0.178–0.182, respectively, with an RMSE increase of ≤0.1%, indicating that the model has strong anti-interference capabilities against experimental noise.

[0081] 3) Results and comparison of apparent damage experiments The measured apparent corrosion area and the model-predicted corrosion area are shown in Table 7, with a maximum error of <9%.

[0082] Table 7. Results of the apparent damage experiment

[0083] Step 704: Calibration and Error Analysis of Mechanical Property Degradation Parameters Model formula: ; Known parameters: Q = 5000 J / mol, R is the gas constant. =35℃ =80% =5g / m 3 .

[0084] Parameters to be calibrated: .

[0085] Calibration steps: 1) Substitute the experimental data into the model formula to establish the objective function (root mean square error, RMSE): RMSE= ; in, For time Model predictions of mechanical performance characteristics at that time For time The measured values ​​of the mechanical properties at that time, where N is the number of tests.

[0086] 2) Use a genetic algorithm for global optimization, with the parameter boundaries set as follows: , , , .

[0087] Calibration results: .

[0088] 3) Model Validation The model equations after substituting the calibration parameters are as follows: ; Calculation example (t=10 days), calculate the exponential term. 0.1415, calculate the environmental stress factor as 1 + 0.008 × 80 + 0.006 × 5 = 1.67, and substitute it into the model. The performance data for the remaining time points were calculated in the same manner. The measured values ​​of the tensile strength of the mechanical properties and the predicted values ​​of the model are shown in Table 8, with a maximum error of <2%.

[0089] Table 8 Errors between Measured and Predicted Mechanical Values

[0090] Beneficial effects This invention achieves high-precision three-dimensional reconstruction of surface damage by combining a multimodal image acquisition system with polarized light and natural light illumination technology. It overcomes the problems of low resolution and poor imaging quality of traditional planning vision systems, and improves the acquisition accuracy and reliability of surface damage features.

[0091] This invention proposes a complete method for automatic identification and quantification of apparent damage features, including the identification and quantification of various damage types such as corrosion damage, crack damage, and coating peeling. It breaks through the limitations of traditional methods that only target a single damage type and realizes comprehensive monitoring and evaluation of complex damage.

[0092] This invention establishes a dynamic model of apparent damage-environmental stress and a model of mechanical properties-environmental stress, which comprehensively consider the impact of multiple environmental stresses such as temperature fluctuations, humidity erosion, and salt spray corrosion on equipment, overcoming the simplistic treatment of traditional methods that only consider a single environmental factor.

[0093] This invention introduces a piecewise nonlinear model and a multi-dimensional coupling mechanism to describe the dynamic degradation law of apparent damage and mechanical properties under different environmental conditions, overcoming the shortcomings of traditional linear degradation models that cannot adapt to complex environmental changes.

[0094] This invention ensures the stability and generalization ability of the model through Bayesian optimization algorithms and multiple validation mechanisms (such as cross-validation and rolling time window validation), thereby improving the reliability and accuracy of the model in practical applications.

[0095] This invention can simultaneously predict multiple performance indicators such as corrosion area, strength, and toughness, realizing dynamic monitoring of the overall performance of equipment and providing a comprehensive and accurate scientific basis for equipment design optimization, maintenance strategy formulation, and life prediction.

[0096] Based on the same inventive concept, this application also provides a device for quantitatively evaluating the environmental adaptability of metal load-bearing components by comprehensively considering apparent damage and mechanical damage characteristics, used to implement the aforementioned method for quantitatively evaluating the environmental adaptability of metal load-bearing components by comprehensively considering apparent damage and mechanical damage characteristics. The solution provided by this device is similar to the solution described in the above method. Therefore, the specific limitations of one or more embodiments of the device for quantitatively evaluating the environmental adaptability of metal load-bearing components by comprehensively considering apparent damage and mechanical damage characteristics provided below can be found in the limitations of the method for quantitatively evaluating the environmental adaptability of metal load-bearing components by comprehensively considering apparent damage and mechanical damage characteristics described above, and will not be repeated here.

[0097] In one exemplary embodiment, such as Figure 2 As shown, a device for quantitatively evaluating the environmental adaptability of metal load-bearing components by comprehensively considering apparent damage and mechanical damage characteristics is provided, comprising: an apparent damage testing device, a mechanical performance testing device, an environmental testing device, and a host computer. The apparent damage testing device, the mechanical performance testing device, and the environmental testing device are used to acquire historical data on the apparent damage characteristics, mechanical performance characteristics, and environmental parameters of the metal load-bearing structure. The host computer is used to execute the quantitative evaluation method for the environmental adaptability of metal load-bearing components based on the comprehensive apparent damage and mechanical damage characteristics in the above embodiments, to provide a quantitative evaluation of the high environmental adaptability of the metal load-bearing structure under different usage environments, and to obtain performance indicators at different times.

[0098] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0099] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for quantitatively assessing the environmental adaptability of metal load-bearing components by comprehensively considering both apparent and mechanical damage characteristics, characterized in that, include: Historical data on apparent damage characteristics, mechanical performance characteristics, and environmental parameters of metal load-bearing structures were obtained. Based on historical data of apparent damage characteristics and historical data of environmental parameters, a dynamic model of apparent damage-environmental stress is constructed. Based on historical data of mechanical performance characteristics and historical data of environmental parameters, a dynamic model of mechanical performance-environmental stress is constructed. A performance index model is constructed based on the apparent damage-environmental stress dynamic model and the mechanical property-environmental stress dynamic model. The high environmental adaptability of the metal load-bearing structure under different usage environments is evaluated based on the performance index model, and performance indexes at different times are obtained.

2. The method for quantitatively evaluating the environmental adaptability of metal load-bearing components based on comprehensive apparent damage and mechanical damage characteristics according to claim 1, characterized in that, When the damage type of the metal load-bearing structure is corrosion damage, the apparent damage feature is the corrosion degree index; when the damage type of the metal load-bearing structure is crack damage, the apparent damage feature is the second moment and contrast of the crack edge; when the damage type of the metal load-bearing structure is coating peeling, the apparent damage feature is the coating failure rate. The mechanical property characteristics are: quasi-static tensile characteristics, impact toughness characteristics, or fatigue performance degradation characteristics; the quasi-static tensile characteristics are: extracted tensile strength, yield strength, or elastic modulus; the impact toughness characteristics are: energy absorbed per unit area; the fatigue performance degradation characteristics are: crack propagation rate.

3. The method for quantitatively evaluating the environmental adaptability of metal load-bearing components based on comprehensive apparent damage and mechanical damage characteristics according to claim 1, characterized in that, Based on historical data of apparent damage characteristics and environmental parameters, a dynamic model of apparent damage-environmental stress is constructed, which includes: Based on the fact that the development process of apparent damage includes a linear stage and an exponential acceleration stage, a piecewise nonlinear model is constructed. Based on historical data of apparent damage characteristics and historical data of environmental parameters, the parameters in the piecewise nonlinear model are solved to obtain the apparent damage-environmental stress dynamic model.

4. The method for quantitatively evaluating the environmental adaptability of metal load-bearing components based on comprehensive apparent damage and mechanical damage characteristics according to claim 3, characterized in that, The apparent damage-environmental stress dynamic model is as follows: ； in, This represents the predicted value of the apparent damage characteristics at time t. The initial values ​​for the apparent damage characteristics. This represents the damage growth rate during the linear phase. This represents the critical time between the linear phase and the exponential acceleration phase. The rate of damage growth during the exponential acceleration phase. It is the Sigmoid transition function. For time integration variables, It is a nonlinear environmental stress coupling factor. = , for Humidity at that time for Salt spray concentration at that time for The temperature at that time , , These are the accelerating factors of humidity, salt spray concentration, and temperature on the apparent damage rate, respectively. Indicates the interaction coefficient between humidity and salt spray. This represents the temperature-salt spray interaction coefficient.

5. The method for quantitatively evaluating the environmental adaptability of metal load-bearing components based on comprehensive apparent damage and mechanical damage characteristics according to claim 1, characterized in that, Based on historical data of mechanical performance characteristics and environmental parameters, a dynamic model of mechanical performance-environmental stress is constructed, which includes: An environmental stress influence factor is introduced to construct a power-law Arrhenius model; Based on historical data of mechanical performance characteristics and historical data of environmental parameters, the parameters in the power-law-Arrhenius model are solved to obtain the dynamic model of mechanical performance-environmental stress.

6. The method for quantitatively evaluating the environmental adaptability of metal load-bearing components based on comprehensive apparent damage and mechanical damage characteristics according to claim 5, characterized in that, The dynamic model of mechanical properties versus environmental stress is as follows: ； in, This represents the predicted value of the mechanical performance characteristics at time t. These are the initial values ​​for the mechanical properties. and ' The parameter to be evaluated. For activation energy, The gas constant is... , These are the accelerating factors of humidity and salt spray on the degradation of mechanical properties, respectively. for humidity, for Salt spray concentration, for The temperature.

7. The method for quantitatively evaluating the environmental adaptability of metal load-bearing components based on comprehensive apparent damage and mechanical damage characteristics according to claim 1, characterized in that, Based on the apparent damage-environmental stress dynamic model and the mechanical property-environmental stress dynamic model, a performance index model is constructed, which specifically includes: Based on the apparent damage-mechanical property coupling mechanism, a model for the influence of apparent damage on mechanical properties is determined. The influence model is as follows: ； in, For time The amount of change in mechanical properties caused by apparent damage over time. Predicted values ​​of apparent damage characteristics at time t. for humidity, for Salt spray concentration, for temperature, These are the static coupling coefficients. For dynamic coupling coefficients, , , ' These are the direct contribution coefficients of temperature, humidity, and salt spray concentration to the degradation of mechanical properties, respectively. Based on the aforementioned influence model, the mechanical performance-environmental stress dynamic model is modified using the following formula to obtain the modified mechanical performance-environmental stress dynamic model. ； in, The correction value representing the mechanical performance characteristics at time t. The predicted value representing the mechanical performance characteristics at time t; A performance index model is constructed based on the apparent damage-environmental stress dynamic model and the modified mechanical property-environmental stress dynamic model.

8. The method for quantitatively evaluating the environmental adaptability of metal load-bearing components based on comprehensive apparent damage and mechanical damage characteristics according to claim 7, characterized in that, The performance index model is as follows: ； in, This represents the performance index of the metal load-bearing structure at time t. This is the correction value for the mechanical performance characteristics at time t. This represents the predicted value of the apparent damage characteristics at time t. This represents the critical mechanical property threshold at time t. The critical damage threshold at time t; , This is the initial critical mechanical property threshold. , , These are the influence coefficients of temperature, humidity, and salt spray concentration on the critical mechanical property threshold, respectively. For reference temperature, for humidity, for Salt spray concentration, for Temperature; , This is the initial critical apparent damage threshold. , , These are the influence coefficients of temperature, humidity, and salt spray concentration on the critical apparent damage threshold, respectively.

9. The method for quantitatively evaluating the environmental adaptability of metal load-bearing components based on comprehensive apparent damage and mechanical damage characteristics according to claim 1, characterized in that, The high environmental adaptability of the metal load-bearing structure under different usage environments is evaluated based on the performance index model, and performance indices at different times are obtained. This process also includes: Based on the performance indicators at different times, the time when the performance indicators are less than the structural performance failure threshold is determined as the failure time. The remaining life of a metal load-bearing structure is obtained by subtracting the current time from the failure time.

10. A device for quantitatively evaluating the environmental adaptability of metal load-bearing components by comprehensively considering apparent damage and mechanical damage characteristics, characterized in that, include: Appearance damage testing device, mechanical performance testing device, environmental testing device, and host computer; The apparent damage testing device, the mechanical performance testing device, and the environmental testing device are used to acquire historical data on the apparent damage characteristics, mechanical performance characteristics, and environmental parameters of the metal load-bearing structure. The host computer is used to execute the method for quantitatively evaluating the environmental adaptability of metal load-bearing components based on the comprehensive apparent damage and mechanical damage characteristics as described in any one of claims 1-9, to evaluate the high environmental adaptability of the metal load-bearing structure under different usage environments, and to obtain performance indicators at different times.

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