A method and system for dynamic monitoring and adaptive pressure regulation of salt spray corrosion of an adsorption disc of a wall-climbing robot for offshore wind power

Abstract

This invention discloses a method and system for dynamic monitoring and adaptive pressure regulation of salt spray corrosion on the adsorption plate of an offshore wind turbine wall-climbing robot. The method includes the following steps: system initialization, performing sensor self-calibration and configuring operating parameters; collecting data on vacuum level, salt spray concentration, and contact status, processing the data, and transmitting it to a central processing unit; evaluating the degree of sealing performance degradation using a corrosion-vacuum correlation model, and predicting the remaining lifespan of the adsorption plate using a lifespan prediction algorithm; when the adsorption force is below a safety threshold, initiating adaptive pressure regulation control to dynamically adjust the vacuum pump power; and generating a maintenance decision report based on the monitoring results. This invention, by adding a multi-source sensor array to the adsorption system and combining the multi-source sensor array with the corrosion-vacuum correlation model, achieves dynamic monitoring and lifespan prediction of the adsorption plate corrosion state, as well as adaptive adjustment of the remaining lifespan of the adsorption plate and the vacuum level, thereby improving the operational safety and maintenance efficiency of the offshore wind turbine wall-climbing robot.

Description

Technical Field

[0001] This invention relates to the field of offshore wind power operation and maintenance technology, specifically to a method and system for dynamic monitoring and adaptive voltage regulation of salt spray corrosion on the adsorption plate of an offshore wind turbine wall-climbing robot. Background Technology

[0002] Offshore wind turbine towers are exposed to high salt spray corrosion environments for extended periods. The adsorption plates of wall-climbing robots, as critical components ensuring safe operation, experience gradual deterioration in their sealing performance due to salt spray corrosion. This leads to decreased vacuum levels and weakened adsorption force, potentially causing equipment falls in severe cases. Currently, maintenance of the adsorption plates relies primarily on periodic replacement, lacking a real-time monitoring and early warning mechanism for corrosion status. Traditional methods cannot detect the actual degree of corrosion on the adsorption plates, potentially resulting in premature replacement leading to resource waste or delayed replacement causing safety hazards. Furthermore, fixed-power vacuum pump control strategies struggle to adapt to changes in sealing performance caused by corrosion, failing to achieve dynamic compensation of adsorption force. Therefore, an intelligent control method is urgently needed that can monitor the corrosion status of the adsorption plates in real time, predict remaining lifespan, and adaptively adjust adsorption force. Summary of the Invention

[0003] The purpose of this invention is to provide a method and system for dynamic monitoring and adaptive pressure regulation of salt spray corrosion of the adsorption plate of an offshore wind turbine wall-climbing robot. This method enables dynamic monitoring and life prediction of salt spray corrosion of the robot's adsorption plate. By designing an adaptive pressure regulation control strategy, the vacuum pump power is dynamically adjusted according to the changes in sealing performance caused by corrosion, thereby ensuring stable adsorption force.

[0004] To achieve the above objectives, the present invention is specifically implemented through the following technical solutions: On one hand, this invention provides a method for dynamic monitoring and adaptive pressure regulation of salt spray corrosion on the adsorption plate of an offshore wind turbine wall-climbing robot, comprising the following steps: S1: System initialization, performing sensor self-test calibration and configuring operating parameters; S2: Collects data on vacuum level, salt spray concentration, and contact status, processes the data, and transmits it to the central processing unit; S3: The degree of sealing performance degradation is evaluated by the corrosion-vacuum degree correlation model, and the remaining life of the adsorption plate is predicted by the life prediction algorithm; S4: When the adsorption force is lower than the safety threshold, the adaptive voltage regulation control is activated to dynamically adjust the vacuum pump power. S5: Generate maintenance decision reports based on monitoring results and trigger maintenance actions through a tiered early warning mechanism; S6: Stores and manages all monitoring data, and regularly optimizes model parameters and control algorithms.

[0005] Furthermore, in step S3, in the corrosion-vacuum degree correlation model module: The model structure includes a corrosion accumulation term over time and an environmental factor correction term. The model parameters are periodically optimized using an adaptive algorithm. The model includes the cumulative effect of salt spray deposition, material corrosion characteristics, and environmental temperature and humidity factors to account for factors affecting sealing performance degradation.

[0006] Furthermore, the specific algorithm and formula of the corrosion-vacuum degree correlation model are as follows: ; in, express t The difference between the actual vacuum level and the initial vacuum level of the adsorption disk at any given time; This indicates the design vacuum level when the adsorption disk is not corroded; t This indicates the total operating time of the adsorption disk in a salt spray environment; This indicates the real-time salt spray concentration after environmental compensation; k This represents the combined rate coefficient that integrates mechanisms such as electrochemical corrosion and crevice corrosion. m This represents the nonlinear effect of salt spray concentration on corrosion. p An index representing the time-acceleration index of corrosion degradation; This indicates the inherent corrosion resistance coefficient of the adsorption disk sealing material; T This indicates the ambient temperature detected by the sensor; H This indicates the relative humidity of the environment monitored by the sensor; ,in This is the output value of the salt spray sensor after internal environmental compensation.

[0007] Furthermore, in step S3, the lifetime prediction algorithm adopts an improved degradation modeling method, which integrates the current corrosion state, historical degradation patterns and environmental load characteristics, and dynamically updates the prediction results through a sliding time window mechanism.

[0008] Furthermore, the lifetime prediction algorithm specifically establishes the following degradation model: ; in, This refers to the vacuum decay rate; The corrosion sensitivity coefficient of the material; This represents the current salt spray concentration; and Indicates the proportionality coefficient; The current vacuum level; The remaining service life is from the current moment t When the vacuum level drops to the failure threshold Time required: ; in, , , These are the average values ​​of salt spray concentration, temperature, and humidity, respectively. This is the preset failure threshold.

[0009] Further, in step S4, the adaptive voltage regulation control includes: The adjustment amount is calculated based on the vacuum deviation, and the control parameters are optimized using a proportional-integral-derivative (PID) algorithm. By monitoring the trend of adsorption force changes in real time, the power output of the vacuum pump is adjusted to maintain the designed adsorption force.

[0010] Furthermore, the adaptive voltage regulation algorithm outputs a vacuum pump power adjustment, calculated using the following formula: ; in, Indicates the amount of power adjustment; For vacuum degree deviation, This represents the rate of change of vacuum degree deviation. , , The parameters are for PID control, based on the real-time estimated sealing efficiency of the adsorption plate. Dynamic adjustment, the calculation formula is as follows: ; in, This is the initial value of the vacuum level; ; ; ; in, , , These are the baseline control parameters.

[0011] On the other hand, the present invention also provides a system applicable to the dynamic monitoring and adaptive pressure regulation method for salt spray corrosion of the adsorption disk of the offshore wind turbine wall-climbing robot described in any of the above claims, comprising: The multi-source sensor monitoring module is used to collect real-time data on vacuum pressure distribution, salt spray concentration, and contact status of the adsorption plate through a distributed vacuum sensor array, an environmentally adaptable salt spray concentration sensor, and a contact status detection module. The corrosion-vacuum degree correlation model module is used to dynamically update model parameters based on the multivariate correlation model of salt spray concentration, exposure time and vacuum degree decay to characterize the degradation law of sealing performance. The remaining life prediction algorithm module is used to integrate real-time monitoring data, historical performance data and environmental load characteristics, and uses a sliding time window mechanism to predict the remaining life of the adsorption disk. The adaptive pressure control module is used to trigger the vacuum pump power control strategy based on the vacuum deviation, and dynamically optimizes the control parameters through intelligent adjustment algorithm to maintain the designed adsorption force. The intelligent maintenance decision support module generates a comprehensive report that includes corrosion status assessment and maintenance recommendations, and provides a basis for maintenance decisions through data visualization technology.

[0012] Furthermore, in the multi-source sensor monitoring module: The vacuum sensor uses corrosion-resistant pressure sensing elements, which are arranged in a grid pattern to cover the key sealing area of ​​the adsorption plate. The salt spray concentration sensor is equipped with an automatic environmental parameter compensation mechanism to eliminate the influence of temperature and humidity on detection accuracy. The contact state detection module, based on array-type pressure sensing technology, senses the contact pressure distribution characteristics between the adsorption plate and the tower surface in real time.

[0013] Furthermore, in the adaptive voltage regulation control module: The intelligent adjustment algorithm calculates the adjustment amount based on the vacuum deviation and its change characteristics, and precisely controls the start-up, shutdown and speed of the vacuum pump through the power drive unit; the system continuously monitors the pressure regulation effect and dynamically optimizes the control parameters to adapt to the performance degradation trend of the adsorption plate.

[0014] The technical solution of this invention is to add a multi-source sensor array to the adsorption system, establish a correlation model between salt spray corrosion and vacuum degree decay, and combine the multi-source sensor array with the corrosion-vacuum degree correlation model to realize dynamic monitoring and life prediction of the corrosion state of the adsorption plate, as well as prediction of the remaining life of the adsorption plate and adaptive adjustment of the vacuum degree, thereby improving the operational safety and maintenance efficiency of the offshore wind power climbing robot.

[0015] It has the following advanced technological effects: 1) Real-time monitoring and early warning: Dynamic monitoring of the corrosion status of the adsorption plate is achieved through multi-source sensors to promptly detect performance degradation trends; 2) Accurate lifespan prediction: Combining historical data and real-time monitoring, the remaining lifespan of the adsorption plate is predicted to avoid premature or delayed replacement; 3) Adaptive adsorption force control: The vacuum pump power is dynamically adjusted according to changes in sealing performance caused by corrosion to maintain stable adsorption force; 4) Intelligent operation and maintenance support: Scientific decision-making basis is provided through data visualization and remote monitoring to reduce operation and maintenance costs and safety risks. A remaining lifespan prediction algorithm based on a sliding time window is proposed to improve prediction accuracy and real-time performance; An adaptive pressure regulation control strategy is designed to dynamically adjust the vacuum pump power according to changes in sealing performance caused by corrosion to ensure stable adsorption force. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating the steps of the dynamic monitoring and adaptive voltage regulation method of the present invention; Figure 2 This is a flowchart illustrating an embodiment of the present invention; Figure 3 This is a schematic diagram of the overall structure of the present invention. Detailed Implementation

[0017] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments.

[0018] On the one hand, such as Figure 1 and Figure 2 As shown, this invention provides a method for dynamic monitoring and adaptive pressure regulation of salt spray corrosion on the adsorption plate of an offshore wind turbine wall-climbing robot, comprising the following steps: S1: System initialization, performing sensor self-test calibration and configuring operating parameters.

[0019] Specifically, after the wall-climbing robot system is started, it first executes a sensor system self-test and calibration procedure to verify the working status of each monitoring module. It then configures system operating parameters, including key parameters such as vacuum safety threshold, salt spray concentration warning level, and adsorption force compensation trigger conditions. Finally, it loads the material characteristic data and initial performance benchmarks of the adsorption disk to establish a complete equipment status profile.

[0020] S2: Collects data on vacuum level, salt spray concentration, and contact status, processes the data, and transmits it to the central processing unit.

[0021] Specifically, during the robot's inspection operation, a multi-source data acquisition system is simultaneously activated. A vacuum sensor array continuously monitors the vacuum pressure distribution in different areas of the adsorption plate, and the acquired data undergoes filtering and noise reduction processing. A salt spray concentration sensor detects the concentration of corrosive media in the environment in real time and performs environmental parameter compensation. A contact state detection module fully records the contact characteristics between the adsorption plate and the working surface. All monitoring data is transmitted to the central processing unit via a dedicated communication network.

[0022] S3: The degree of sealing performance degradation is assessed by using a corrosion-vacuum degree correlation model, and the remaining life of the adsorption plate is predicted by a life prediction algorithm.

[0023] Specifically, in this embodiment, based on real-time multi-source monitoring data, a corrosion-vacuum degree correlation model comprehensively analyzes the current sealing performance status of the adsorption disk. The system employs a dynamic evaluation algorithm, combining historical performance data and real-time monitoring results to accurately calculate the degree of performance degradation of the adsorption disk. The remaining life prediction module, based on the established degradation model, integrates the current corrosion state, historical degradation patterns, and environmental load characteristics, dynamically updates the prediction results through a sliding time window mechanism, periodically updates the remaining life prediction of the adsorption disk, and provides reliability assessment results.

[0024] S4: When the adsorption force is lower than the safety threshold, the adaptive pressure regulation control is activated to dynamically adjust the vacuum pump power.

[0025] Specifically, in this embodiment, when the system determines that the adsorption force is below the safe operating threshold, it automatically initiates the vacuum adjustment program. The intelligent control system calculates the vacuum pump adjustment parameters in real time based on vacuum monitoring data using advanced control algorithms. It preferably employs a proportional-integral-derivative (PID) algorithm to optimize the control parameters, precisely controlling the vacuum pump's operating state through the power drive unit and adjusting the vacuum pump's power output to maintain the designed adsorption force. During the adjustment process, the system continuously monitors the trend of adsorption force changes and dynamically optimizes the control parameters to ensure stable operation of the adsorption system.

[0026] S5: Generates maintenance decision reports based on monitoring results and triggers maintenance actions through a tiered early warning mechanism.

[0027] Specifically, in this embodiment, the system establishes a tiered early warning mechanism based on corrosion status assessment and lifespan prediction results. When performance abnormalities are detected or maintenance thresholds are reached, early warning information is automatically generated and detailed maintenance suggestions are provided. The health status of the adsorption plate, performance degradation trends, and maintenance decision-making basis are clearly displayed through a human-machine interface, supporting on-site maintenance personnel to quickly formulate maintenance plans.

[0028] S6: Stores and manages all monitoring data, and regularly optimizes model parameters and control algorithms.

[0029] Specifically, in this embodiment, the system establishes a complete data management system to store all monitoring data, control records, and maintenance decision information. The corrosion prediction model and control algorithm parameters are periodically optimized based on new data, and the system's operational effectiveness is verified through a performance evaluation module, continuously improving monitoring accuracy and control performance.

[0030] In some specific embodiments, in the corrosion-vacuum degree correlation model module of step S3: the model structure includes a corrosion accumulation term and an environmental factor correction term in the time dimension, and the model parameters are periodically optimized through an adaptive algorithm; the model includes the salt spray deposition accumulation effect, material corrosion characteristics and environmental temperature and humidity influence factors to realize the factors of sealing performance degradation.

[0031] Specifically, in this embodiment, the specific algorithm and formula for the corrosion-vacuum degree correlation model in step S3 are as follows: ; in, express t The difference between the actual vacuum level and the initial vacuum level of the adsorption disk at any given time, in kPa. This indicates the design vacuum level (kPa) when the adsorption disk is not corroded. t This indicates the total operating time of the adsorption disk in a salt spray environment, expressed in hours. Real-time salt spray concentration after environmental compensation / mg / m³ 3 ; k This represents the combined rate coefficient that integrates mechanisms such as electrochemical corrosion and crevice corrosion. m This represents the nonlinear effect of salt spray concentration on corrosion. p An index representing the time-acceleration index of corrosion degradation; This indicates the inherent corrosion resistance coefficient of the adsorption disk sealing material; T Indicates the ambient temperature detected by the sensor in °C; H This indicates the ambient relative humidity (RH) monitored by the sensor. as well as, ,in This is the output value of the salt spray sensor after internal environmental compensation.

[0032] The corrosion-vacuum degree correlation model in this invention includes a corrosion accumulation term in the time dimension and an environmental factor correction term. The model parameters are periodically optimized through an adaptive algorithm. Taking into full account the working environment of the offshore wind power climbing robot, the cumulative effect of salt spray deposition, material corrosion characteristics and environmental temperature and humidity influencing factors are integrated into the model to realize the analysis of sealing performance degradation factors and timely detect performance degradation trends.

[0033] In an even preferred embodiment, in step S3, the lifetime prediction algorithm employs an improved degradation modeling method, which integrates the current corrosion state, historical degradation patterns, and environmental load characteristics, and dynamically updates the prediction results through a sliding time window mechanism.

[0034] Specifically, in this embodiment, the lifetime prediction algorithm is based on the influence of multiple factors such as salt spray concentration, temperature, and humidity on vacuum degree decay, and establishes the following degradation model: ; in, Vacuum decay rate / kPa / s; The corrosion sensitivity coefficient of the material; Salt spray concentration / mg / m 3 ; , Indicates the proportionality coefficient; Current vacuum level in kPa; The remaining service life is from the current moment t When the vacuum level drops to the failure threshold Time required: ; in, , , These are the average values ​​of salt spray concentration, temperature, and humidity, respectively. This is the preset failure threshold.

[0035] The lifespan prediction algorithm in this invention combines historical data with real-time monitoring, enabling dynamic monitoring of salt spray corrosion on the adsorption plate of the wall-climbing robot and accurate prediction of the remaining lifespan of the adsorption plate, avoiding premature or late replacement and providing a basis for adaptive adjustment.

[0036] In some embodiments, in step S4, the adaptive pressure regulation control includes: calculating the adjustment amount based on the vacuum deviation, optimizing the control parameters using a proportional-integral-derivative (PID) algorithm; and adjusting the power output of the vacuum pump to maintain the designed adsorption force by monitoring the adsorption force change trend in real time.

[0037] Specifically in this embodiment, the adaptive voltage regulation algorithm output is the vacuum pump power adjustment amount, calculated using the following formula: ; in, Indicates the power adjustment amount in W; Vacuum deviation / kPa Vacuum degree deviation change rate / kPa / s; , , The parameters are for PID control, based on the real-time estimated sealing efficiency of the adsorption plate. Dynamic adjustment, the calculation formula is as follows: ; in, The initial vacuum level is expressed in kPa. ; ; ; in, , , These are the baseline control parameters.

[0038] By analyzing multi-dimensional data, the vacuum pump power is dynamically adjusted based on the changes in sealing performance caused by corrosion, thereby maintaining stable adsorption force.

[0039] On the other hand, the present invention also provides a system for dynamic monitoring and adaptive voltage regulation of salt spray corrosion of the adsorption disk of an offshore wind power climbing robot, applicable to any of the above embodiments, such as... Figure 3 As shown, the system includes: The multi-source sensor monitoring module is used to collect real-time data on vacuum pressure distribution, salt spray concentration, and contact status of the adsorption plate through a distributed vacuum sensor array, an environmentally adaptable salt spray concentration sensor, and a contact status detection module. The corrosion-vacuum degree correlation model module is used to dynamically update model parameters based on the multivariate correlation model of salt spray concentration, exposure time and vacuum degree decay to characterize the degradation law of sealing performance. The remaining life prediction algorithm module is used to integrate real-time monitoring data, historical performance data and environmental load characteristics, and uses a sliding time window mechanism to predict the remaining life of the adsorption disk. The adaptive pressure control module is used to trigger the vacuum pump power control strategy based on the vacuum deviation, and dynamically optimizes the control parameters through intelligent adjustment algorithm to maintain the designed adsorption force. The intelligent maintenance decision support module generates a comprehensive report that includes corrosion status assessment and maintenance recommendations, and provides a basis for maintenance decisions through data visualization technology.

[0040] In some embodiments, in the multi-source sensor monitoring module: The vacuum sensor uses corrosion-resistant pressure sensing elements, which are arranged in a grid pattern to cover the key sealing area of ​​the adsorption plate. The salt spray concentration sensor is equipped with an automatic environmental parameter compensation mechanism to eliminate the influence of temperature and humidity on detection accuracy. The contact state detection module, based on array-type pressure sensing technology, senses the contact pressure distribution characteristics between the adsorption plate and the tower surface in real time.

[0041] The function of the multi-source sensor monitoring module is to configure a distributed vacuum sensor array, an environmentally adaptable salt spray concentration sensor, and a contact state detection module in the wall-climbing robot's adsorption system.

[0042] Specifically, the vacuum sensor employs corrosion-resistant pressure sensing elements, arranged in a grid pattern to cover the critical sealing area of ​​the adsorption disk, monitoring the vacuum pressure distribution at each location in real time. The salt spray concentration sensor is equipped with an automatic environmental parameter compensation mechanism to accurately detect the salt spray corrosion intensity in the working area. The contact area detection module, based on array-type pressure sensing technology, senses the contact state and pressure distribution characteristics between the adsorption disk and the tower surface in real time. All sensors utilize an anti-interference data transmission protocol to ensure the integrity and real-time nature of the monitoring data.

[0043] The corrosion-vacuum correlation model comprehensively considers the cumulative effect of salt spray deposition, the influence of environmental temperature and humidity, and the corrosion characteristics of materials, and dynamically updates model parameters through an adaptive algorithm. The model structure includes a corrosion accumulation term over time and an environmental factor correction term, accurately characterizing the degradation pattern of the adsorption disk's sealing performance. The system periodically optimizes and corrects the model parameters based on the latest monitoring data to ensure prediction accuracy.

[0044] The remaining life prediction algorithm module, based on real-time monitoring of vacuum level changes and historical salt spray exposure data, uses an improved degradation modeling method to predict the remaining lifespan of the adsorption disk. The algorithm integrates current corrosion status assessment results, historical performance degradation patterns, and environmental load characteristics to establish a lifespan prediction model that considers the influence of multiple factors. The prediction process employs a sliding time window mechanism to dynamically update the prediction results and promptly triggers early warning signals when abnormal degradation trends are detected.

[0045] In one specific embodiment, in the adaptive voltage regulation control module: The intelligent adjustment algorithm calculates the adjustment amount based on the vacuum deviation and its change characteristics, and precisely controls the start-up, shutdown and speed of the vacuum pump through the power drive unit; the system continuously monitors the pressure regulation effect and dynamically optimizes the control parameters to adapt to the performance degradation trend of the adsorption plate.

[0046] The adaptive pressure regulation control module automatically activates the vacuum compensation mechanism when the monitoring system detects a decrease in adsorption force exceeding a preset safety threshold. The control system employs an intelligent adjustment algorithm to calculate the adjustment amount in real time based on the vacuum deviation and its changing characteristics, adjusting the vacuum pump's operating state through a precise power control strategy. The system is equipped with operational status monitoring functions to evaluate the pressure regulation effect in real time and dynamically optimize control parameters, ensuring that the adsorption force remains within the design requirements range.

[0047] Furthermore, the intelligent maintenance decision support module automatically generates comprehensive reports based on multi-source monitoring data and intelligent analysis results, including corrosion status assessment, performance degradation analysis, and maintenance recommendations. It clearly displays the corrosion distribution of key components of the adsorption plate through data visualization technology and provides scientific maintenance decision recommendations based on lifespan prediction results. The system supports remote data access and status monitoring, providing comprehensive information support for operation and maintenance management.

[0048] A wall-climbing robot at an offshore wind farm is used as a specific embodiment of the adsorption plate salt spray corrosion dynamic monitoring and adaptive pressure regulation method and system of this invention: 1) Install a gridded vacuum sensor on the surface of the adsorption plate, and simultaneously deploy a salt spray concentration sensor and a contact status detection module; 2) The salt spray accumulation effect is analyzed using a corrosion-vacuum degree correlation model, and the remaining lifespan of the adsorption disk is predicted using a lifespan prediction algorithm; 3) When the vacuum level is detected to drop to 80% of the safety threshold, the adaptive voltage regulation module is activated, adjusting the vacuum pump power to 120% output; 4) The system generates a maintenance report and recommends replacing the suction plate before the remaining lifespan expires to avoid the risk of the equipment falling.

[0049] The specific embodiments described in this invention are merely illustrative of the invention and are not intended to limit it. Those skilled in the art can make modifications to these embodiments without contributing any inventive step after reading this specification, but such modifications are protected by patent law as long as they fall within the scope of the claims of this invention.

Claims

1. A method for dynamic monitoring and adaptive voltage regulation of salt spray corrosion on the adsorption plate of an offshore wind turbine wall-climbing robot, characterized in that, Includes the following steps: S1: System initialization, performing sensor self-test calibration and configuring operating parameters; S2: Collects data on vacuum level, salt spray concentration, and contact status, processes the data, and transmits it to the central processing unit; S3: The degree of sealing performance degradation is evaluated by the corrosion-vacuum degree correlation model, and the remaining life of the adsorption plate is predicted by the life prediction algorithm; S4: When the adsorption force is lower than the safety threshold, the adaptive voltage regulation control is activated to dynamically adjust the vacuum pump power. S5: Generate maintenance decision reports based on monitoring results and trigger maintenance actions through a tiered early warning mechanism; S6: Stores and manages all monitoring data, and regularly optimizes model parameters and control algorithms.

2. The method for dynamic monitoring and adaptive voltage regulation of salt spray corrosion of the adsorption disk of the offshore wind turbine wall-climbing robot according to claim 1, characterized in that, In step S3, the corrosion-vacuum degree correlation model module includes a corrosion accumulation term and an environmental factor correction term in the time dimension. The model parameters are periodically optimized through an adaptive algorithm. The model includes the salt spray deposition accumulation effect, material corrosion characteristics, and environmental temperature and humidity influencing factors to realize the factors of sealing performance degradation.

3. The method for dynamic monitoring and adaptive voltage regulation of salt spray corrosion of the adsorption disk of the offshore wind turbine wall-climbing robot according to claim 1, characterized in that, The specific algorithm and formula for the corrosion-vacuum degree correlation model are as follows: ； in, express t The difference between the actual vacuum level and the initial vacuum level of the adsorption disk at any given time; This indicates the design vacuum level when the adsorption disk is not corroded; t This indicates the total operating time of the adsorption disk in a salt spray environment; This indicates the real-time salt spray concentration after environmental compensation; k This represents the combined rate coefficient that integrates mechanisms such as electrochemical corrosion and crevice corrosion. m This represents the nonlinear effect index of salt spray concentration on corrosion. p An index representing the time-acceleration index of corrosion degradation; This indicates the inherent corrosion resistance coefficient of the adsorption disk sealing material; T This indicates the ambient temperature detected by the sensor; H This indicates the relative humidity of the environment monitored by the sensor; ,in This is the output value of the salt spray sensor after internal environmental compensation.

4. The method for dynamic monitoring and adaptive voltage regulation of salt spray corrosion of the adsorption plate of the offshore wind turbine wall-climbing robot according to claim 1, characterized in that, In step S3, the lifetime prediction algorithm adopts an improved degradation modeling method, which integrates the current corrosion state, historical degradation patterns and environmental load characteristics, and dynamically updates the prediction results through a sliding time window mechanism.

5. The method for dynamic monitoring and adaptive pressure regulation of salt spray corrosion of the adsorption disk of the offshore wind turbine wall-climbing robot according to claim 1, characterized in that, Specifically, the lifetime prediction algorithm establishes the following degradation model: ； in, This refers to the vacuum decay rate; The corrosion sensitivity coefficient of the material; Real-time salt spray concentration; , Indicates the proportionality coefficient; The current vacuum level; The remaining service life is from the current moment t When the vacuum level drops to the failure threshold Time required: ； in, , , These are the average values ​​of salt spray concentration, temperature, and humidity, respectively. This is the preset failure threshold.

6. The method for dynamic monitoring and adaptive voltage regulation of salt spray corrosion of the adsorption disk of the offshore wind power climbing robot according to claim 1, characterized in that, In step S4, the adaptive voltage regulation control includes: The adjustment amount is calculated based on the vacuum deviation, and the control parameters are optimized using a proportional-integral-derivative (PID) algorithm. By monitoring the trend of adsorption force changes in real time, the power output of the vacuum pump is adjusted to maintain the designed adsorption force.

7. The method for dynamic monitoring and adaptive voltage regulation of salt spray corrosion of the adsorption disk of the offshore wind turbine wall-climbing robot according to claim 1, characterized in that, The adaptive voltage regulation algorithm outputs a vacuum pump power adjustment, calculated using the following formula: ； in, Indicates the amount of power adjustment; For vacuum degree deviation, This represents the rate of change of vacuum degree deviation. , , The parameters are for PID control, based on the real-time estimated sealing efficiency of the adsorption plate. The adjustment is dynamic, and the calculation formula is as follows: ； in, This is the initial value of the vacuum level; ； ； ； in, , , These are the baseline control parameters.

8. A system applicable to the dynamic monitoring and adaptive pressure regulation method for salt spray corrosion of the adsorption disk of a marine electric wall-climbing robot according to any one of claims 1-7, characterized in that, include: The multi-source sensor monitoring module is used to collect real-time data on vacuum pressure distribution, salt spray concentration, and contact status of the adsorption plate through a distributed vacuum sensor array, an environmentally adaptable salt spray concentration sensor, and a contact status detection module. The corrosion-vacuum degree correlation model module is used to dynamically update model parameters based on the multivariate correlation model of salt spray concentration, exposure time and vacuum degree decay to characterize the degradation law of sealing performance. The remaining life prediction algorithm module is used to integrate real-time monitoring data, historical performance data and environmental load characteristics, and uses a sliding time window mechanism to predict the remaining life of the adsorption disk. The adaptive pressure control module is used to trigger the vacuum pump power control strategy based on the vacuum deviation, and dynamically optimizes the control parameters through intelligent adjustment algorithm to maintain the designed adsorption force. The intelligent maintenance decision support module generates a comprehensive report that includes corrosion status assessment and maintenance recommendations, and provides a basis for maintenance decisions through data visualization technology.

9. The offshore wind power wall-climbing robot adsorption plate salt spray corrosion dynamic monitoring and adaptive voltage regulation system according to claim 8, characterized in that, In the multi-source sensor monitoring module: The vacuum sensor uses corrosion-resistant pressure sensing elements, which are arranged in a grid pattern to cover the key sealing area of ​​the adsorption plate. The salt spray concentration sensor is equipped with an automatic environmental parameter compensation mechanism to eliminate the influence of temperature and humidity on detection accuracy. The contact state detection module, based on array-type pressure sensing technology, senses the contact pressure distribution characteristics between the adsorption plate and the tower surface in real time.

10. The offshore wind power climbing robot adsorption plate salt spray corrosion dynamic monitoring and adaptive voltage regulation system according to claim 8, characterized in that, In the adaptive voltage regulation control module: The intelligent adjustment algorithm calculates the adjustment amount based on the vacuum deviation and its change characteristics, and precisely controls the start-up, shutdown and speed of the vacuum pump through the power drive unit; the system continuously monitors the pressure regulation effect and dynamically optimizes the control parameters to adapt to the performance degradation trend of the adsorption plate.

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