A wing structure corrosion monitoring and prevention method fusing multi-level defect information

Abstract

The application provides a wing structure corrosion monitoring and prevention method fusing multi-level defect information, and the steps are: 1, establishing a coating protection stage life model; 2, establishing a corrosion growth stage life model; 3, establishing a crack propagation stage life model; 4, corrosion detection and maintenance planning based on multi-level defect information. The application has the advantages that: for the wing easy-to-corrode structure with multi-level defect states in complex natural environment, the key environmental factors affecting the structure corrosion fatigue process are quantitatively analyzed, the accuracy of corrosion prediction is improved; the coupling damage comprehensive evolution mode of different level defects is identified, the multi-level and multi-stage corrosion process model based on the fault delay propagation mechanism is established, and the accuracy of corrosion evaluation is improved; the integrated prevention and control design and optimization scheme fusing corrosion online monitoring and preventive protection is innovatively proposed, the wing structure performance decline and safety failure risk caused by corrosion fatigue are reduced, and the utilization rate of protection resources is improved.

Description

Technical Field

[0001] This invention provides a method for monitoring and controlling corrosion of wing structures by integrating multi-level defect information, specifically an optimization method for wing structure inspection and protection based on a multi-stage damage process model of corrosion fatigue. Targeting easily corroded wing structures with multi-level defect states under complex natural environments, this invention quantitatively analyzes key environmental factors affecting the structural corrosion fatigue process, identifies the coupled damage evolution patterns of different levels of defects, establishes a multi-level, multi-stage corrosion process model based on the fault delay propagation mechanism, and innovatively proposes an integrated control design and optimization scheme that combines online corrosion monitoring and preventative protection, reducing the performance degradation and safety risks of wing structures caused by corrosion fatigue. This invention overcomes the problems of low defect information utilization and insufficient integration of monitoring, protection, and control in existing technologies, and is applicable to the field of corrosion monitoring and protection control of typical aircraft wing structures such as carrier-based aircraft in natural environments. Background Technology

[0002] In recent years, the demand for marine resource development has expanded significantly. However, the service environment of ocean-going equipment is complex and variable, with long-term exposure to harsh conditions characterized by high temperature, high humidity, high salt spray, high winds and sandstorms, and strong ultraviolet radiation. Affected by dynamic environmental factors such as alternating wet and dry conditions and temperature variations, corrosion problems are becoming increasingly severe. In particular, the low corrosion resistance of carrier-based aircraft and other equipment is incompatible with the high corrosive conditions of the ocean environment, significantly exacerbating the coupled effects of corrosion and fatigue, severely restricting the improvement of equipment readiness and combat capabilities. Simultaneously, the aviation industry suffers from severe corrosion and loss, urgently requiring effective solutions to the high losses caused by corrosion.

[0003] Due to the influence of complex environmental factors, corrosion fatigue prevention and control in ocean-going equipment is more difficult than conventional fatigue prevention and control. To meet the development requirements of high reliability, long service life, and precision for ocean-going equipment, it is necessary to develop intelligent protection schemes that integrate multi-level defect information, employ online corrosion monitoring methods, analyze the real-time health status of equipment, and guide corrosion protection measures. On the other hand, it is also necessary to establish damage evolution prediction models for ocean-going equipment in complex corrosive media to improve the reliability and operational readiness of wing structures in complex corrosive environments. Furthermore, traditional theories typically define the system failure process simply as two stages: a normal stage and a failure delay stage. However, in actual engineering problems, the corrosion stage of a system exhibits multi-stage characteristics. Therefore, it is necessary to mine multi-level defect information to comprehensively describe the corrosion fatigue process and accurately implement corrosion prevention and control measures.

[0004] To ensure the reliability of wing structures and the economic efficiency of corrosion prevention and control planning in complex natural environments, this invention proposes a wing structure corrosion monitoring and control method that integrates multi-level defect information. Targeting wing structures affected by typical environmental factors such as temperature, humidity, and chloride ions, it utilizes and improves a multi-stage failure delay model, adopts an optimal detection corrosion monitoring method, and plans an integrated prevention and control optimization scheme for online monitoring and preventive protection of wing structure corrosion, thereby reducing the risk of performance degradation and safety failures caused by corrosion fatigue. Summary of the Invention

[0005] The purpose of this invention is to reduce the risk of structural performance degradation and safety failures in carrier-based aircraft caused by corrosion fatigue, and to overcome the problems of insufficient utilization of defect information and low integration of monitoring, prevention and control in existing corrosion prevention and control methods. This invention proposes a corrosion monitoring and control method for wing structures that integrates multi-level defect information. Targeting easily corroded wing structures with multi-level defect states in complex natural environments, this invention quantitatively analyzes key environmental factors of corrosion, identifies the coupled damage evolution mode of defects at each level, establishes a multi-level, multi-stage corrosion process model, and formulates an integrated prevention and control design and optimization scheme that integrates online corrosion monitoring and preventive protection. This ensures the combat readiness of carrier-based aircraft and the economy of corrosion prevention and control planning in complex natural environments.

[0006] To achieve the above objectives, the applicable equipment conditions for this invention are as follows: Condition 1: The corrosion fatigue damage process model conforms to multi-stage characteristics. Considering the structural damage tolerance design characteristics under the influence of corrosion fatigue in the open ocean environment, the corrosion fatigue of the wing structure exhibits multi-stage characteristics. Initially, the equipment operates under normal conditions, potential defects appear under the action of internal and external forces, and eventually develop into crack failure after a period of time. Specifically, under the combined influence of the corrosive environment and alternating loads, the corrosion fatigue process of the wing structure can be divided into: a) Coating protection stage: Organic coatings can isolate structural corrosion, but they will degrade over time in extreme ocean environments until they fail; b) Corrosion growth stage: After the coating fails, initial corrosion points or pits form on the surface of the wing structure. Corrosion fatigue damage gradually accumulates inside, and the corrosion points expand. c) Crack propagation stage: The pit gradually increases in size, and when the stress intensity reaches the threshold, the crack begins to initiate; d) Equipment failure stage: Due to the corrosive environment, the cracks gradually extend to the critical length, after which the cracks expand rapidly, causing the wing structure to break rapidly, resulting in structural failure and equipment failure.

[0007] Therefore, as Figure 2 The wing structure shown exhibits a finite number of corrosion fatigue states. , of which (a) This indicates the normal operating state, i.e., the coating protection stage; (b) This indicates a minor defect state, i.e., the corrosion growth stage; (c) This indicates a severe defect state, i.e., the crack propagation stage; and (d) This indicates the failure stage, where the crack has expanded to a critical size.

[0008] Condition 2 states that in the corrosion life model, the various stages of corrosion are independent and follow a certain random distribution process. This model combines the influence of complex environments and the characteristics of corrosion fatigue to quantify corrosion life. for: (1) In the formula: and These represent the lifespan of the coating protection stage, the corrosion growth stage, and the crack propagation stage, respectively.

[0009] Based on the conditions and ideas of the above-mentioned application objects, this invention provides a method for monitoring and controlling corrosion of wing structures by integrating multi-level defect information. This method is implemented through the following four steps: Step 1: Establish a lifetime model for the coating protection stage state This is the coating protection stage. During the coating's durability, the corrosion process completely ceases. However, with continued exposure to the complex open ocean environment, the wing structure coating gradually degrades until it ages and fails. Numerous literature reviews and experimental results indicate that the coating lifetime for wing structure corrosion follows a log-normal distribution, i.e. ,exist At any given time, its parameters can be estimated through corrosion and operational data analysis. The probability density of coating failure due to corrosion on the wing structure is: (2) In the formula: Indicates the cumulative operating time of the wing structure; Indicates the wing structure in Corrosion failure probability density at any given time; and These are the logarithmic coating lifetimes. The mean and standard deviation.

[0010] Furthermore, the wing structure lifetime distribution function during the coating protection stage can be obtained as follows: (3) In the formula: The cumulative distribution function represents the standard normal distribution.

[0011] Step 2: Establish a lifetime model for the corrosion growth stage state This is the corrosion growth stage, which occurs after coating failure, where the wing structure, lacking coating protection, is subjected to corrosion by complex environmental factors. This stage primarily involves the electrochemical corrosion process of the structural substrate and the formation and growth of pits, influenced by the operating environment, substrate characteristics, and processing techniques. Furthermore, research generally suggests that once the protective layer on the structural surface fails, the nucleation process of the pits ceases. In addition, the size of these pits is typically on the micrometer scale, similar to inclusions in the material; therefore, nucleation degradation is ignored in the actual modeling of this stage, focusing instead on the pitting growth of the wing structure.

[0012] Considering the influence of various environmental factors on the corrosion process, based on a generalized stochastic process model incorporating environmental parameter terms under the influence of typical environmental factors such as temperature, humidity, and chloride ions, the corrosion life of the wing structure during the corrosion propagation stage is considered to follow a degradation model based on the comprehensive environmental influence of the Wiener process, namely: (4) In the formula: This indicates the corrosion depth of the wing structure, representing the degree of corrosion accumulation. The item representing the corrosion effect caused by environmental factors; Refers to a set of environmental parameters, including key ocean environmental factors such as temperature, humidity, chloride ion concentration, and sulfur dioxide. Represents the rate parameter. Indicates the diffusion coefficient; This represents standard Brownian motion.

[0013] Based on engineering experience and historical data, a critical corrosion threshold is further introduced. The lifetime probability density function for the corrosion growth stage of the wing structure can be derived as follows: (5) Furthermore, the lifetime distribution function of the corrosion growth stage of the wing structure can be derived as follows: (6) In the formula: This represents the characteristic equations of the effects of various environmental factors, which describe the impact of various environments on atmospheric corrosion.

[0014] Taking further consideration of the complex marine atmospheric environment at coastal airports or on ships, the main focus is on temperature ( ),humidity( ) and chloride ions ( ) as a corrosion effect term The study focuses on environmental factors. Based on widely adopted environmental effect models, the influence functions of the three types of environmental factors can be expressed as: (7) (8) (9) In the formula: These represent empirical coefficients in various environmental effect models.

[0015] Furthermore, the corrosion effect term in equation (4) can be expressed in the following specific form: (10) In the formula: This represents an empirical coefficient estimated using environmental data; This represents a correction term resulting from the coupling effects of environmental factors such as temperature, humidity, and chloride ions.

[0016] Step 3: Establish a life model for the crack propagation stage state During the crack propagation stage, as the stress intensity on the pits formed during the corrosion growth stage gradually increases, cracks begin to form and propagate on the surface of the wing structural material, thus entering the crack propagation stage. Cracks only form in the pits when the stress factor intensity reaches a certain threshold level. Research shows that the stress-strain behavior of crack propagation conforms to the standard Paris model, meaning the surface crack propagation rate can be expressed as a relationship between it and the stress intensity factor range: (11) In the formula: Indicates the length of the surface crack; Indicates the number of cycles in which the crack propagates; It is the increase in crack length in each cycle; This indicates the load frequency, primarily considering the cyclic loads on the wing structure; and These represent the surface crack propagation coefficient and propagation exponent, respectively, which are related to material properties and can be obtained through linear regression. This indicates the range of surface crack stress intensity factors, i.e. Based on relevant research, it can be obtained that... The empirical formula is: (12) In the formula: Indicates the thickness of the wing structural plates; This indicates the stress amplitude.

[0017] Further description of wing structural corrosion failure as surface cracks from initial size Extended to critical failure crack size Fatigue cycle count during the crack propagation stage and the life stage for: (13) In the formula: Indicates the crack geometry correction factor; Material-related indices representing crack propagation rate; This indicates the impact of the initial stage of crack propagation on fatigue life. This indicates the effect of crack size on fatigue life as the crack propagates to the failure stage; In addition, the surface crack propagation coefficient It has uncertainty and can be considered to follow a log-normal distribution, that is... ,in The logarithmic mean and logarithmic standard deviation of the texture spread coefficient are derived from experimental data on the surface materials of the wing structure. Because Uncertainty It also follows a log-normal distribution, that is Therefore, the number of fatigue cycles required for the crack to extend to the critical length. The probability density function is: (14) In the formula: , ; Further set the time for each fatigue cycle as The lifespan of the wing structure during the crack propagation stage is... for: (15) Therefore, the lifespan of the wing structure during the crack propagation stage also follows a log-normal distribution, i.e. Its probability density function can be expressed as: (16) In the formula: The logarithmic mean and logarithmic standard deviation represent the crack propagation stage lifetime. , ; Furthermore, the life distribution function of the crack propagation stage of the wing structure can be derived as follows: (17) In the formula, The cumulative distribution function representing the standard normal distribution is, i.e. .

[0018] state This is the failure stage, where surface cracks gradually propagate to the critical failure crack size. The resulting wing structure failure state is when the wing structure is damaged and ceases normal operation. The critical failure crack size is related to the material properties and is a hyperparameter.

[0019] Step 4: Corrosion Detection and Maintenance Planning Based on Multi-Level Defect Information Regular inspections are an effective way to reveal the health status of engineering systems, enabling timely maintenance activities to avoid safety risks and economic losses caused by sudden failures. For wing structures, the primary consideration is based on inspection intervals. Regular major inspections are conducted, ignoring defects detected during inspections; that is, the system status can be determined through inspection regardless of whether it is in a state of minor or serious defect. For example... Figure 2 As shown, the present invention provides a corrosion detection and maintenance strategy that considers multi-level defect information.

[0020] First, based on the multi-stage corrosion degradation characteristics, the wing structure failure process is divided into three independent stages: normal, initial defect, and severe defect, with the corresponding random duration of each stage being... and Corresponding to the probability density distribution function and cumulative distribution function These stages correspond to the models in steps 1-3, respectively. Furthermore, the times at which the system is detected in a mild and severe state during the detection process are respectively... and .

[0021] Secondly, maintenance personnel need to perform maintenance and updates on the wing structure based on the system's status. Regarding the cost per maintenance operation, if the inspection reveals a minor defect, it is easy to repair and restore the system to a new state; however, if the system is in a severely defective state, it requires more time and relatively higher costs. Therefore, the average maintenance and update cost for minor defects is... Below the average cost of critical defects In terms of maintenance categories, in order to reduce the risk of corrosion failure of the wing structure, maintenance personnel need to carry out two types of maintenance planning: (a) fault repair, which is the maintenance work carried out in a timely manner after the wing structure is passively stopped due to a fault during operation; and (b) preventive protection, which is the protective work carried out by actively stopping the aircraft after defects are detected in the wing structure during inspection.

[0022] Finally, a cost rate model was established based on the renewal payoff theory, and the expected maintenance cost rate was minimized by determining the optimal inspection interval. The wing structure corrosion repair and renewal payoff model mainly consists of two parts: (1) the expected total cost within the renewal cycle. (2) Expected length of the update cycle .

[0023] (18) in, This indicates the total expected cost during the fault maintenance update cycle. ; This indicates the total expected cost during the update cycle of preventative protection. ; Indicates the expected length of the update cycle for fault maintenance; This indicates the expected length of the update cycle for preventative protective measures.

[0024] Corresponding and Based on the timing of the fault occurrence, it can be categorized into fault repair. and preventive protection Two scenarios, assuming the probability of each scenario is denoted by . The following section calculates the maintenance costs and event duration for these two scenarios respectively.

[0025] Scenario 1: Fault Repair If the wing structure is at a certain detection point If a malfunction occurs, immediate post-mortem maintenance is required. Because inspection can perfectly identify defect conditions, fault repair requires that the normal and initial defect phases be addressed within the inspection interval. Internal termination. Therefore, the probability of fault repair. for: (19) Furthermore, the wing structure in The probability density distribution function for corrosion failure at any given time is: (20) Correspondingly, the expected total cost during the fault maintenance update cycle. for: (twenty one) The expected length of the fault maintenance update cycle is: (twenty two) Scenario 2: Preventive Protection If the wing structure is at the detection point If a minor defect is identified, preventative protection updates are required immediately. The probability of preventative protection occurring in this situation is... as follows: (twenty three) If the wing structure is in a state of serious defect at the inspection point In this situation, the probability of preventative protection occurring is... for: (twenty four) Correspondingly, the expected total cost during the update cycle of preventative protection for: (25) The expected length of the update cycle for preventative protective equipment is: (26) After determining the corrosion detection and maintenance strategy for the wing structure and establishing a cost rate model, optimization algorithms can be used to solve for the optimal amount that minimizes maintenance costs and select the optimal detection interval.

[0026] Through the above steps, this invention establishes a method for monitoring and controlling corrosion of wing structures that integrates multi-level defect information, achieving full-stage, multi-level corrosion damage evolution estimation that integrates coating degradation, diverse corrosion environments, and crack propagation. By combining key environmental factors, it solves the problem of how to scientifically and efficiently plan corrosion monitoring and protection control of wing structures under complex natural environments.

[0027] The advantages and beneficial effects of this invention are as follows: 1. This invention develops a corrosion stochastic model that integrates multiple environmental factors, capturing the long-term impact of various complex environments on the corrosion process of wing structures, and improving the accuracy of wing structure corrosion assessment. 2. This invention establishes a multi-level, multi-stage corrosion process model based on the fault delay propagation mechanism. Considering the physicochemical properties of the wing structure corrosion process, it comprehensively describes the coupled damage evolution mode of different levels of defects in the coating protection stage, corrosion growth stage, and crack propagation stage, thereby improving the accuracy of wing structure corrosion prediction. 3. This invention introduces an integrated prevention and control design and optimization scheme that combines online corrosion monitoring and preventive protection. Based on condition monitoring to reveal the defect status, it enables dynamic adjustment of the planning scheme according to the severity of the defects, thereby reducing downtime and economic losses and improving the utilization rate of maintenance resources. 4. The method described in this invention is scientific, and its application is closely related to actual shipborne equipment, making it valuable for widespread application. Attached Figure Description

[0028] Figure 1 This is a flowchart of the method described in this invention.

[0029] Figure 2 This refers to the multi-stage corrosion fatigue degradation process described in this invention.

[0030] Figure 3 This invention relates to a corrosion detection and maintenance strategy based on multi-level defect information. Detailed Implementation

[0031] The invention will be further illustrated below with examples.

[0032] The wing spars in the wing structure are typical structures prone to corrosion. Based on data from a certain type of carrier-based aircraft's Corrosion Prevention and Control Program (CPCP) regarding corrosion areas, corrosion depths at various detection points, equipment failure times, and coating failure times of various similar wing spars, the specific implementation method is as follows: Step 1: Establish a lifetime model for the coating protection stage; The wing sparsity coating lifetime data in Table 1 were extracted using CPCP. Analysis and fitting verified that the coating lifetime for wing structural corrosion follows a log-normal distribution. Further processing of the data from Table 1 using formula (2) yielded a total of... Using data points, we fitted lifetime model parameters to the coating degradation data: (27) (28) Finally, the mean and standard deviation estimates of the log-normal distribution that the coating lifetime for wing structural corrosion follows are obtained as follows:

[0033] Table 1. Lifespan of the wing spars of a certain type of carrier-based aircraft (days)

[0034] Step 2: Establish a lifetime model for the corrosion growth stage; Based on experience in wing structure maintenance, a critical corrosion threshold was set. The value is 2mm. Based on various detection time points in CPCP. wing structure corrosion depth and the corresponding temperature ( ), relative humidity ( ) and chloride ion concentration ( Based on the data, the parameters of the corrosion growth stage lifetime model are estimated using the maximum likelihood estimation method according to the following maximum likelihood function.

[0035] First, determine the maximum likelihood estimate for the deterministic part: (29) (30) (31) The estimated value of the non-random component is then calculated as follows: (32) Next, determine the maximum likelihood estimate of the random component: (33) In the formula: This represents the residual corrosion depth of the wing structure.

[0036] Finally, the model parameters are estimated using the maximum likelihood method, resulting in: Furthermore, by substituting the parameters into formulas (5), (6), and (10), the probability density function and cumulative distribution function of the lifespan during the corrosion growth stage of the wing structure can be calculated.

[0037] Step 3: Establish a lifetime model for the crack propagation stage; According to the stress analysis, the wing structure is subjected to cyclic loads during operation. The main load-bearing structure is the LY12CZ aluminum alloy spars, as shown in Table 2. The stress amplitude of this structure is as follows: and frequency Cyclic load, plate thickness The thickness is 4mm. The relevant aluminum alloy material properties include: surface crack propagation index. The critical failure crack size is 3. The thickness is 6mm. The time for each fatigue cycle is assumed to be... .

[0038] Furthermore, based on the corrosion fatigue damage detection results of the wing spars of naval aircraft related to naval aviation engineering, the surface crack propagation coefficient... Following a log-normal distribution, the mean and standard deviation were obtained by fitting relevant research parameters. Furthermore, by substituting its distribution and the data in Table 2 into formulas (12), (16), and (17), the probability density function and cumulative distribution function of the life of the wing structure during the crack propagation stage can be calculated.

[0039] Step 4: Corrosion detection and maintenance planning based on multi-level defect information; Based on actual maintenance data and relevant research, the relevant cost parameters for maintenance activities are shown in Table 2.

[0040] Table 2 Maintenance Cost Parameters

[0041] Based on the data in Table 2, the phased life models from steps one, two, and three are substituted into the corrosion detection and maintenance planning model based on multi-level defect information. Using the GA toolbox in MATLAB, the optimal detection interval and the lowest maintenance cost rate can be obtained. .

[0042] The proposed strategy is further compared with two traditional strategies, namely (a) a corrosion monitoring and protection control method for carrier-based aircraft based on single-stage corrosion degradation. To mitigate interference factors, it adopts the corrosion life model of formula (4), still considering three maintenance types; and (b) a single corrective maintenance strategy, i.e., maintenance is only performed during the severe defect and failure stages. The comparison results show that the proposed maintenance strategy is cost-effective, reducing costs by 10.1% and 12.4% respectively compared with the single-stage model and the corrective maintenance strategy. This solves the problem of how to scientifically plan the protection and control of easily corroded structures of airfoils in complex natural environments, achieving the expected goal.

[0043] In summary, this invention provides a corrosion monitoring and control method that integrates multi-level defect information for wing structures affected by corrosion fatigue under complex natural environments. By quantitatively analyzing key environmental factors affecting the corrosion fatigue process of structures, it identifies coupled damage evolution modes of multi-level defects such as coating degradation, multi-environment corrosion, and crack propagation failure, establishes a multi-level, multi-stage corrosion process model, and plans an integrated prevention and control optimization scheme that integrates online corrosion monitoring and preventive protection.

Claims

1. A method for monitoring and controlling corrosion of airfoil structures by integrating multi-level defect information, characterized in that, Includes the following steps: Step 1: Establish a lifetime model for the coating protection stage state This is the coating protection stage; during the coating's durability period, the corrosion process completely stops, and the coating lifetime for wing structure corrosion follows a log-normal distribution, i.e. ,exist The timing is estimated through corrosion and operational data analysis. Step 2: Establish a lifetime model for the corrosion growth stage state The corrosion growth stage occurs after coating failure, when the wing structure, lacking coating protection, is subjected to corrosion by complex environmental factors. Considering the influence of various environmental factors on the corrosion process, and based on a generalized stochastic process model incorporating environmental parameters such as temperature, humidity, and chloride ions, the corrosion life of the wing structure during the corrosion propagation stage is considered to follow a degradation model based on the Wiener process and the comprehensive environmental impact, i.e.: (4) In the formula: This indicates the corrosion depth of the wing structure, representing the degree of corrosion accumulation. The item representing the corrosion effect caused by environmental factors; Refers to a set of environmental parameters, including key ocean environmental factors such as temperature, humidity, chloride ion concentration, and sulfur dioxide. Represents the rate parameter. Indicates the diffusion coefficient; Represents standard Brownian motion; Step 3: Establish a life model for the crack propagation stage state During the crack propagation stage, as the stress intensity on the pits formed during the corrosion growth stage gradually increases, cracks begin to form and propagate on the surface of the wing structural material, entering the crack propagation stage. Cracks will only form in the pits when the stress factor intensity reaches a certain threshold level. The surface crack propagation rate is expressed as follows: (11) In the formula: Indicates the length of the surface crack; Indicates the number of cycles in which the crack propagates; It is the increase in crack length in each cycle; This indicates the load frequency, taking into account the cyclic loads on the wing structure; and These represent the surface crack propagation coefficient and propagation exponent, respectively, which are related to material properties and are obtained through linear regression. This indicates the range of surface crack stress intensity factors, i.e. ; Step 4: Corrosion Detection and Maintenance Planning Based on Multi-Level Defect Information First, based on the multi-stage corrosion degradation characteristics, the wing structure failure process is divided into three independent stages: normal, initial defect, and severe defect, with the corresponding random duration of each stage being... and Corresponding to the probability density distribution function and cumulative distribution function This indicates that the time during the detection process when the system was detected to be in a minor or severe state was respectively... and ; Secondly, maintenance personnel need to perform maintenance and updates on the wing structure based on the system status. Regarding the cost per maintenance session, if the inspection shows the system is in a minor defect state, it is easy to repair and restore it to a new state; if the system is in a serious defect state, it requires more time and relatively higher costs. Therefore, the average maintenance and update cost for minor defects is... Below the average cost of critical defects ; In terms of maintenance categories, in order to reduce the risk of corrosion failure of the wing structure, maintenance personnel need to carry out two types of maintenance planning: fault repair, which is the maintenance work carried out in a timely manner after the wing structure is passively stopped due to a fault during operation; and preventive protection, which is the protective work carried out by actively stopping the aircraft after defects are detected in the wing structure during inspection. Finally, a cost rate model is established based on the update payoff theory, and the expected maintenance cost rate is minimized by determining the optimal detection interval.

2. The method for monitoring and controlling corrosion of wing structures by integrating multi-level defect information according to claim 1, characterized in that: In step 1, the probability density of coating failure due to corrosion of the wing structure is: (2) In the formula: Indicates the cumulative operating time of the wing structure; Indicates the wing structure in Corrosion failure probability density at any given time; and These are the logarithmic coating lifetimes. The mean and standard deviation.

3. The method for monitoring and controlling corrosion of wing structures by integrating multi-level defect information according to claim 2, characterized in that: The wing structure lifetime distribution function during the coating protection stage is: (3) In the formula: The cumulative distribution function represents the standard normal distribution.

4. The method for monitoring and controlling corrosion of wing structures by integrating multi-level defect information according to claim 1, characterized in that: In step 2, a critical corrosion threshold is introduced. The lifetime probability density function for the corrosion growth stage of the wing structure is: (5) Furthermore, the lifetime distribution function of the corrosion growth stage of the wing structure is derived as follows: (6) In the formula: This represents the characteristic equation of environmental factor effects, which describes the impact of various environments on atmospheric corrosion.

5. The method for monitoring and controlling corrosion of wing structures by integrating multi-level defect information according to claim 4, characterized in that: Temperature ,humidity and chloride ions As a corrosion effect term Environmental factors, the influence functions of the three types of environmental factors are expressed as follows: (7) (8) (9) In the formula: These represent empirical coefficients in various environmental effect models.

6. A method for monitoring and controlling corrosion of wing structures by integrating multi-level defect information as described in claim 1 or 5, characterized in that: The corrosion effect term in equation (4) can be expressed in the following form: (10) In the formula: This represents an empirical coefficient estimated using environmental data; This represents a correction term resulting from the environmental coupling effect of temperature, humidity, and chloride ions.

7. The method for monitoring and controlling corrosion of wing structures by integrating multi-level defect information according to claim 1, characterized in that: In step 3, we obtain The empirical formula is: (12) In the formula: Indicates the thickness of the wing structural plates; This indicates the stress amplitude.

8. The method for monitoring and controlling corrosion of wing structures by integrating multi-level defect information according to claim 7, characterized in that: The corrosion failure of the wing structure is caused by surface cracks from the initial size. Extended to critical failure crack size Fatigue cycle count during the crack propagation stage and the life stage for: (13) In the formula: Indicates the crack geometry correction factor; Material-related indices representing crack propagation rate; This indicates the impact of the initial stage of crack propagation on fatigue life. This indicates the effect of crack size on fatigue life as the crack propagates to the failure stage; In addition, the surface crack propagation coefficient It has uncertainty and is assumed to follow a log-normal distribution, i.e. ,in, The logarithmic mean and logarithmic standard deviation of the crack propagation coefficient are used to characterize the average level and uncertainty dispersion of the crack propagation performance of the material, and are derived from experimental data of the wing structure surface material; due to Uncertainty It also follows a log-normal distribution, that is ,in The logarithmic mean and logarithmic standard deviation represent the number of fatigue cycles; therefore, the number of fatigue cycles required for the crack to propagate to the critical length. The probability density function is FF1A (14) In the formula: , ; Further set the time for each fatigue cycle as The lifespan of the wing structure during the crack propagation stage is... for: (15)。 9. The method for monitoring and controlling corrosion of wing structures by integrating multi-level defect information according to claim 8, characterized in that: The lifespan of the crack propagation stage in the wing structure also follows a log-normal distribution, i.e. The probability density function is expressed as: (16) In the formula: The logarithmic mean and logarithmic standard deviation represent the crack propagation stage lifetime. , ; Furthermore, the life distribution function of the crack propagation stage in the wing structure is derived as follows: (17) In the formula, The cumulative distribution function representing the standard normal distribution is, i.e. .

10. The method for monitoring and controlling corrosion of wing structures by integrating multi-level defect information according to claim 1, characterized in that: In step 4, the compensation model for wing structure corrosion repair and replacement consists of two parts. Components: (1) Total expected cost during the update cycle (2) Expected length of the update cycle ; (18) in, This indicates the total expected cost during the fault maintenance update cycle. ; This indicates the total expected cost during the update cycle of preventative protection. ; Indicates the expected length of the update cycle for fault maintenance; This indicates the expected length of the update cycle for preventative protective measures.

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