A cable internal corrosion risk warning method and system

Abstract

The present application relates to the technical field of bridge cable detection, and in particular to a method and system for early warning of internal corrosion risks of cables. The method comprises: obtaining a static parameter set of the cable, an external environmental parameter set, and an internal component state parameter set; constructing a steel wire micro-friction energy dissipation model based on the internal component state parameter set to determine the wear depth increment of the steel wire contact surface; constructing an environment-wear coupled corrosion model based on the external environmental parameter set and the wear depth increment of the steel wire contact surface to determine the corrosion development state information; determining and outputting a cable corrosion risk assessment report based on the corrosion development state information. The present application combines the interaction mechanism of mechanical wear and environmental corrosion to accurately predict the formation and evolution trend of corrosion hotspots of bridge cables, realize timely identification and early warning of high-risk locations of cable corrosion, timely check potential safety hazards inside the cable, and avoid local corrosion from expanding into structural damage.

Description

Technical Field

[0001] The present application relates to the technical field of bridge cable detection, and in particular to a cable internal corrosion risk early warning method and system. Background Art

[0002] With the rapid development of road traffic, cable-stayed bridges and suspension bridges with tensioned cables or chains as the main load-bearing structures have been widely used in modern bridge construction due to their advantages such as large span and clear force. As the main load-bearing component of the bridge, the corrosion state of the cable directly affects the safety of the bridge as its service time increases.

[0003] However, the existing internal corrosion detection process of bridge cables is still mainly based on regular manual inspection and assessment of cable components. The inspection efficiency is low and the personnel safety risk is high. It is difficult to detect potential corrosion damage inside the cable in a timely manner. In addition, the single-dimensional static inspection of the cable component itself is difficult to reflect the dynamic changes in the internal corrosion process of the cable component during operation. As a result, the assessment of the internal corrosion risk of the cable has a significant lag, making it difficult to timely detect potential safety hazards inside the cable. Summary of the Invention

[0004] The present application provides a cable internal corrosion risk early warning method and system to solve the above technical problems.

[0005] In a first aspect, the present application provides a cable internal corrosion risk early warning method, the method comprising:

[0006] Obtain the static parameter set, external environment parameter set and internal component status parameter set of the cable; construct a steel wire micro-friction energy dissipation model based on the internal component status parameter set to determine the wear depth increment of the steel wire contact surface; based on the external environment parameter set and the wear depth increment of the steel wire contact surface, construct an environment-wear coupled corrosion model to determine the corrosion development status information; based on the corrosion development status information, determine and output a cable corrosion risk assessment report.

[0007] Through this solution, a collaborative analysis of the cable's static parameter set, external environmental parameter set, and internal component status parameter set is performed. Combined with the interaction mechanism of mechanical wear and environmental corrosion, the formation and evolution trend of bridge cable corrosion hotspots can be accurately predicted. The corresponding cable corrosion risk assessment report can be provided to cable maintenance personnel, enabling timely identification and early warning of high-risk cable corrosion locations, timely investigation of potential safety hazards inside the cable, and prevention of local corrosion from expanding into structural damage, significantly improving the service life of the cable.

[0008] Optionally, the static parameter set of the cable includes the steel wire friction coefficient, the steel wire fatigue coefficient, the steel wire material hardness, the cable preload, the material baseline aging rate, the shell permeability coefficient, the steel wire protective layer thickness and the steel wire yield strength; the external environment parameter set includes the ambient temperature gradient distribution information, the ambient humidity distribution information and the air salt spray concentration; the internal component state parameter set includes the micro-slip information between steel wires, the dynamic load amplitude spectrum between steel wires, the alternating load action frequency and the alternating stress amplitude.

[0009] Through this solution, the static properties, environmental status and dynamic operation data of the cable are collected in multiple dimensions to build a full-factor data system for corrosion risk assessment, eliminate the data blind spots of traditional methods, establish a complete scientific data benchmark for subsequent environmental-wear coupling analysis, and improve the scientificity and comprehensiveness of the cable corrosion status assessment process.

[0010] Optionally, the method of constructing a steel wire micro-friction energy dissipation model based on the internal component state parameter set and determining the wear depth increment of the steel wire contact surface includes: determining the steel wire dynamic load amplitude corresponding to different time points at the current detection position within a preset unit detection time period based on the dynamic load amplitude spectrum between the steel wires; determining the steel wire contact surface pressure corresponding to different time points at the current detection position within the preset unit detection time period based on the alternating load action frequency and the steel wire dynamic load amplitude and the cable preload; determining the preset unit detection time period based on the micro-slip information between the steel wires. The micro-slip amount between the steel wires corresponding to different time points at the current detection position within the preset unit detection time period is determined; the number of load actions within the preset unit detection time period is determined according to the preset unit detection time period and the frequency of the alternating load action; the energy accumulation correction factor is determined according to the steel wire fatigue coefficient and the number of load actions; based on the energy accumulation correction factor, the contact surface pressure between the steel wires and the micro-slip amount between the steel wires, and according to the hardness of the steel wire material, the steel wire micro-friction energy dissipation model is constructed to determine the wear depth increment of the steel wire contact surface at the current detection position within the preset unit detection time period.

[0011] Through this scheme, the information reflecting the dynamic state of the cable is segmented and processed based on the detection position and the preset unit detection time period as the benchmark constraints. The dynamic load amplitude of the steel wire corresponding to different detection positions at different time points within the preset unit detection time period, the micro-slip amount between the steel wires and the number of load actions within the period are obtained. On this basis, the contact surface pressure and energy accumulation correction factors between the steel wires are quantitatively analyzed to obtain the correction factors. Then, a steel wire micro-friction energy dissipation model is constructed, which can reflect the micro-motion wear characteristics of the cable steel wire under the synergistic effect of friction and fatigue. The wear depth increment of the steel wire contact surface corresponding to different detection positions within the preset unit detection time period is obtained, so as to accurately and comprehensively reflect the wear condition of the cable under the influence of alternating loads.

[0012] Optionally, based on the energy accumulation correction factor, the contact surface pressure between the steel wires, and the fretting slip amount between the steel wires, and according to the hardness of the steel wire material, the steel wire fretting friction energy dissipation model is constructed, specifically the following formula:

[0013] ;

[0014] in, is the wear depth increment of the steel wire contact surface, is the energy accumulation correction factor, is the steel wire contact energy conversion coefficient, is the hardness of the steel wire material, The current detection position at the current time point The corresponding micro-slip between the steel wires is is the friction coefficient of the steel wire, is the steel wire fatigue coefficient, is the number of times the load acts, The current detection position at the current time point The contact surface pressure between the steel wires is as follows: The preset unit detection time period.

[0015] Through this scheme, mathematical analysis is used to describe the wear development of the steel wire under the synergistic effect of friction and fatigue based on the energy accumulation correction factor, the contact surface pressure between the steel wires, and the micro-slip between the steel wires, according to the hardness of the steel wire material. The wear depth increment of the steel wire contact surface is then quantified to accurately evaluate the wear rate of the steel wire at the current detection position under the influence of alternating loads, providing scientific data support for steel wire corrosion risk assessment.

[0016] Optionally, based on the frequency of the alternating load, according to the dynamic load amplitude of the steel wire and the cable preload, the contact surface pressure between the steel wires corresponding to different time points at the current detection position within the preset unit detection time period is determined, specifically by the following formula:

[0017] ;

[0018] in, The current detection position at the current time point The contact surface pressure between the steel wires is as follows: is the cable preload, The current time point The wire dynamic load amplitude under is the frequency of the alternating load action, The preset unit detection time period.

[0019] Through this solution, mathematical analysis is used to capture the periodic fluctuating pressure exerted by the alternating load on the steel wire based on the frequency of the alternating load, the amplitude of the dynamic load on the steel wire, and the cable preload. Combined with the cable preload exerted on the steel wire by the cable itself, the contact surface pressure between the steel wires is quantified, thereby improving the accuracy and scientific nature of the contact surface pressure between the steel wires, thereby making the incremental wear depth of the steel wire contact surface more accurate.

[0020] Optionally, based on the external environmental parameter set and according to the wear depth increment of the steel wire contact surface, an environment-wear coupling corrosion model is constructed to determine the corrosion development status information, including: determining the internal relative humidity and internal temperature of the cable according to the environmental temperature gradient distribution information and the environmental humidity distribution information; determining the internal salt spray deposition concentration of the cable according to the air salt spray concentration; based on the material baseline aging rate, the steel wire protective layer thickness, the alternating stress amplitude and the steel wire yield strength, according to the internal relative humidity, the internal temperature, the internal salt spray deposition concentration, the wear depth increment of the steel wire contact surface and the alternating load action frequency, performing an environment-wear coupling analysis on the cable corrosion development status, constructing the environment-wear coupling corrosion model, and determining the corrosion development rates corresponding to different detection positions; constructing the corrosion development status information according to the corrosion development rates corresponding to different detection positions.

[0021] Through this solution, an environment-wear coupling model is constructed to capture the synergistic effects of mechanical damage and chemical corrosion at the same time, significantly improving the corrosion rate prediction accuracy and avoiding the risk of underestimation of single-factor models. By combining the frequency and stress amplitude of alternating loads, the non-steady-state characteristics of corrosion development under actual working conditions are dynamically reflected, supporting adaptive analysis of sudden load changes. By quantitatively analyzing the corrosion development rates at different detection locations, accurate data support is provided for the positioning of high-corrosion risk areas.

[0022] Optionally, based on the material baseline aging rate, the steel wire protective layer thickness, the alternating stress amplitude and the steel wire yield strength, according to the internal relative humidity, the internal temperature, the internal salt fog deposition concentration, the steel wire contact surface wear depth increment and the alternating load action frequency, an environment-wear coupling analysis is performed on the cable corrosion development state, the environment-wear coupling corrosion model is constructed, and the corrosion development rate corresponding to different detection positions is determined, specifically according to the following formula:

[0023] ;

[0024] in, is the corrosion development rate, is the material baseline aging rate, is the shell permeability coefficient, is the internal salt spray deposition concentration, is the internal relative humidity, To preset humidity adjustment index, is the internal temperature, is the wear depth increment of the steel wire contact surface, is the thickness of the steel wire protective layer, is the preset dynamic load coupling factor, is the alternating stress amplitude, is the frequency of the alternating load action, is the preset load adjustment index, is the yield strength of the steel wire.

[0025] Through this scheme, mathematical analysis is used to describe the influence of environment, wear and dynamic stress on the corrosion rate of cables based on the material benchmark aging rate, steel wire protective layer thickness, alternating stress amplitude and steel wire yield strength, according to internal relative humidity, internal temperature, internal salt spray deposition concentration, steel wire contact surface wear depth increment and alternating load action frequency. Under the triple impact dimension, based on the material benchmark aging rate, the corrosion development rate is accurately quantified, thereby improving the accuracy and scientific nature of the corrosion development rate.

[0026] Optionally, the method of determining and outputting a cable corrosion risk assessment report based on the corrosion development status information includes: comparing the corrosion development rates corresponding to different detection positions with corresponding preset corrosion rate thresholds to determine comparison results; determining a safe position set, a subsequent key focus position set, and a high-risk position set based on the comparison results; highlighting and warning-marking the corresponding detection positions in the safe position set, the subsequent key focus position set, and the high-risk position set based on a three-dimensional color-differentiation labeling strategy to determine detection labeling warning information; and constructing and outputting the cable corrosion risk assessment report based on the detection labeling warning information.

[0027] This solution utilizes dynamic thresholds and multi-level classification to accurately distinguish risk areas at different development stages, avoiding the waste of subsequent maintenance resources or risk omissions caused by a "one-size-fits-all" assessment. A three-dimensional color-coded labeling strategy provides an intuitive view of corrosion risk, significantly reducing the complexity of manual analysis and improving the efficiency and scientific nature of subsequent maintenance planning.

[0028] Optionally, the method further includes: extracting a set of parameter change information corresponding to the corrosion development rate evaluation process of each high-risk location based on the set of high-risk locations; analyzing the set of parameter change information to determine the root cause of the corrosion risk corresponding to each high-risk location; based on a preset large language model, determining corresponding maintenance optimization suggestions according to the root cause of the corrosion risk, and adding the maintenance optimization suggestions to the cable corrosion risk assessment report.

[0029] Through this solution, the root causes of abnormal corrosion rates in high-risk locations are located, the root causes of corrosion risk are determined, and corresponding maintenance optimization suggestions are given for the root causes of corrosion risk based on the large language model. The maintenance optimization suggestions are added to the cable corrosion risk assessment report, providing maintenance personnel with targeted suggestions with reference significance and improving the efficiency and effectiveness of subsequent maintenance.

[0030] In a second aspect, the present application provides a cable internal corrosion risk early warning system, the system comprising:

[0031] A parameter collection module is used to obtain the static parameter set, external environment parameter set and internal component status parameter set of the cable; a wear analysis module is used to construct a steel wire micro-friction energy dissipation model based on the internal component status parameter set, and determine the wear depth increment of the steel wire contact surface; a coupling analysis module is used to construct an environment-wear coupling corrosion model based on the external environment parameter set and the wear depth increment of the steel wire contact surface, and determine the corrosion development status information; an output module is used to determine and output a cable corrosion risk assessment report based on the corrosion development status information.

[0032] Optionally, in the parameter collection module, the static parameter set of the cable includes the steel wire friction coefficient, the steel wire fatigue coefficient, the steel wire material hardness, the cable preload, the material baseline aging rate, the shell permeability coefficient, the steel wire protective layer thickness and the steel wire yield strength; the external environment parameter set includes the ambient temperature gradient distribution information, the ambient humidity distribution information and the air salt spray concentration; the internal component state parameter set includes the micro-slip information between steel wires, the dynamic load amplitude spectrum between steel wires, the alternating load action frequency and the alternating stress amplitude.

[0033] Optionally, the wear analysis module is specifically used to: determine the dynamic load amplitude of the steel wire corresponding to different time points at the current detection position within a preset unit detection time period based on the dynamic load amplitude spectrum between the steel wires; determine the contact surface pressure between the steel wires corresponding to different time points at the current detection position within the preset unit detection time period based on the alternating load action frequency, the dynamic load amplitude between the steel wires and the cable preload; determine the micro-slip amount between the steel wires corresponding to different time points at the current detection position within the preset unit detection time period based on the micro-slip information between the steel wires; determine the number of load actions within the preset unit detection time period based on the preset unit detection time period and the alternating load action frequency; determine the energy accumulation correction factor based on the steel wire fatigue coefficient and the number of load actions; construct the steel wire micro-friction energy dissipation model based on the energy accumulation correction factor, the contact surface pressure between the steel wires and the micro-slip amount between the steel wires and the hardness of the steel wire material to determine the wear depth increment of the steel wire contact surface at the current detection position within the preset unit detection time period.

[0034] Optionally, when the wear analysis module constructs the steel wire fretting friction energy dissipation model based on the energy accumulation correction factor, the contact surface pressure between the steel wires, and the fretting slip amount between the steel wires, according to the hardness of the steel wire material, the specific formula is as follows:

[0035] ;

[0036] in, is the wear depth increment of the steel wire contact surface, is the energy accumulation correction factor, is the steel wire contact energy conversion coefficient, is the hardness of the steel wire material, The current detection position at the current time point The corresponding micro-slip between the steel wires is is the friction coefficient of the steel wire, is the steel wire fatigue coefficient, is the number of times the load acts, The current detection position at the current time point The contact surface pressure between the steel wires is as follows: The preset unit detection time period.

[0037] Optionally, when the wear analysis module determines the contact surface pressure between the steel wires corresponding to different time points at the current detection position within the preset unit detection time period based on the alternating load action frequency, the dynamic load amplitude of the steel wire, and the cable preload, the specific formula is as follows:

[0038] ;

[0039] in, The current detection position at the current time point The contact surface pressure between the steel wires is as follows: is the cable preload, The current time point The wire dynamic load amplitude under is the frequency of the alternating load action, The preset unit detection time period.

[0040] Optionally, the coupling analysis module is specifically used to: determine the internal relative humidity and internal temperature of the cable according to the ambient temperature gradient distribution information and the ambient humidity distribution information; determine the internal salt spray deposition concentration of the cable according to the air salt spray concentration; based on the material baseline aging rate, the steel wire protective layer thickness, the alternating stress amplitude and the steel wire yield strength, perform an environment-wear coupling analysis on the cable corrosion development state according to the internal relative humidity, the internal temperature, the internal salt spray deposition concentration, the steel wire contact surface wear depth increment and the alternating load action frequency, construct the environment-wear coupling corrosion model, determine the corrosion development rate corresponding to different detection positions; construct the corrosion development state information according to the corrosion development rate corresponding to different detection positions.

[0041] Optionally, the coupling analysis module performs an environment-wear coupling analysis on the cable corrosion development state based on the material baseline aging rate, the steel wire protective layer thickness, the alternating stress amplitude, and the steel wire yield strength, according to the internal relative humidity, the internal temperature, the internal salt fog deposition concentration, the steel wire contact surface wear depth increment, and the alternating load action frequency, constructs the environment-wear coupling corrosion model, and determines the corrosion development rate corresponding to different detection positions. Specifically, the formula is as follows:

[0042] ;

[0043] in, is the corrosion development rate, is the material baseline aging rate, is the shell permeability coefficient, is the internal salt spray deposition concentration, is the internal relative humidity, To preset humidity adjustment index, is the internal temperature, is the wear depth increment of the steel wire contact surface, is the thickness of the steel wire protective layer, is the preset dynamic load coupling factor, is the alternating stress amplitude, is the frequency of the alternating load action, is the preset load adjustment index, is the yield strength of the steel wire.

[0044] Optionally, the output module is specifically used to: compare the corrosion development rates corresponding to different detection positions with the corresponding preset corrosion rate thresholds to determine the comparison results; determine the safe position set, the subsequent key focus position set and the high-risk position set according to the comparison results; highlight and warn the corresponding detection positions in the safe position set, the subsequent key focus position set and the high-risk position set according to the three-dimensional color differentiation labeling strategy to determine the detection labeling warning information; construct and output the cable corrosion risk assessment report based on the detection labeling warning information.

[0045] Optionally, the system also includes a root cause analysis module, which is specifically used to: extract a set of parameter change information corresponding to the corrosion development rate evaluation process of each high-risk location based on the set of high-risk locations; analyze the parameter change information set to determine the corrosion risk focus root cause corresponding to each high-risk location; based on a preset large language model, determine the corresponding maintenance optimization suggestions according to the corrosion risk focus root cause, and add the maintenance optimization suggestions to the cable corrosion risk assessment report. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0047] Figure 1 A schematic diagram of an application scenario provided in one embodiment of the present application;

[0048] Figure 2 A flowchart of a cable internal corrosion risk early warning method provided in one embodiment of the present application;

[0049] Figure 3 A schematic structural diagram of a cable internal corrosion risk warning system provided in one embodiment of the present application. DETAILED DESCRIPTION

[0050] To make the purpose, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0051] In this document, the term "and / or" simply describes a relationship between related objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A exists alone, A and B exist simultaneously, or B exists alone. Furthermore, the character " / " in this document, unless otherwise specified, generally indicates an "or" relationship between the related objects.

[0052] The embodiments of the present application are described in further detail below with reference to the accompanying drawings.

[0053] The existing internal corrosion detection process for bridge cables is still mainly based on regular manual inspection and assessment of cable components. This has low inspection efficiency and high personnel safety risks. It is difficult to detect potential corrosion damage inside the cable in a timely manner. In addition, the single-dimensional static inspection of the cable components themselves is difficult to reflect the dynamic changes in the internal corrosion process of the cable components during operation. As a result, the assessment of the internal corrosion risk of the cable has a significant lag, making it difficult to timely detect potential safety hazards inside the cable.

[0054] Based on this, the present application provides a cable internal corrosion risk warning method and system. This system collaboratively analyzes the cable static parameter set, external environmental parameter set, and internal component status parameter set, and combines the interaction mechanism between mechanical wear and environmental corrosion to accurately predict the formation and evolution trend of bridge cable corrosion hotspots. The corresponding cable corrosion risk assessment report is provided to cable maintenance personnel, enabling timely identification and early warning of high-risk cable corrosion locations, timely investigation of potential safety hazards inside the cable, and prevention of local corrosion from expanding into structural damage, significantly improving the service life of the cable.

[0055] Figure 1 This is a schematic diagram of an application scenario provided by this application. During corrosion risk testing of bridge cables, the method provided in this application can be applied to accurately predict the formation and evolution of corrosion hotspots in bridge cables, promptly identify potential safety hazards within the cables, and prevent localized corrosion from expanding into structural damage.

[0056] Specifically, the method of the present application is applied to any server, which communicates with the magnetic array sensor and the meteorological sensor. The server obtains the cable static parameter set provided by the cable designer, the internal component status parameter set provided by the magnetic array sensor, and the external environment parameter set provided by the meteorological sensor through the server, and performs a collaborative analysis of the cable static parameter set, the external environment parameter set, and the internal component status parameter set. Combined with the interaction mechanism of mechanical wear and environmental corrosion, the formation and evolution trend of bridge cable corrosion hotspots are accurately predicted, and the corresponding cable corrosion risk assessment report is provided to the cable maintenance personnel, so as to realize the timely identification and early warning of high-risk locations of cable corrosion, timely check the potential safety hazards inside the cable, avoid local corrosion from expanding into structural damage, and significantly improve the service life of the cable.

[0057] For specific implementation methods, please refer to the following embodiments.

[0058] Figure 2 This is a flow chart of a cable internal corrosion risk warning method provided by an embodiment of the present application. The method of this embodiment can be applied to the server in the above scenario. Figure 2 As shown, the method includes:

[0059] S201. Obtain a cable static parameter set, an external environment parameter set, and an internal component state parameter set.

[0060] The cable static parameter set may be a set of parameters used to characterize the inherent properties of the cable, such as the steel wire friction coefficient, the steel wire fatigue coefficient, etc., and may be provided by the cable designer.

[0061] The external environmental parameter set can be a set of parameters used to characterize the environmental state of the cable, such as ambient temperature, ambient humidity, air salt spray concentration (such as salt spray deposition in coastal areas), etc., which can be obtained through meteorological sensors carried by the cable-climbing robot.

[0062] The internal component state parameter set can be a parameter set used to characterize the internal operating dynamics of the cable, such as micro-slip information between wires, dynamic load amplitude spectrum between steel wires, etc. The internal component state parameter set can be obtained by a magnetic array sensor equipped on a cable-climbing robot.

[0063] Specifically, the essence of the internal corrosion risk of bridge cables is the coupling effect of steel wire micro-wear and external environmental corrosion factors. If we only rely on single-dimensional parameters (such as static parameters or environmental parameters), we cannot accurately assess the corrosion risk of the cable under dynamic operating conditions. By comprehensively obtaining the cable static parameter set (characterizing the material's wear and corrosion resistance), the external environmental parameter set (characterizing the intensity of the corrosion environment) and the internal component state parameter set (characterizing the dynamic wear state in actual operation), we can provide a complete data foundation for subsequent multi-dimensional coupling modeling.

[0064] S202. Construct a steel wire fretting friction energy dissipation model based on the internal component state parameter set, and determine the wear depth increment of the steel wire contact surface.

[0065] The steel wire fretting friction energy dissipation model can be a mathematical model for quantifying the relationship between energy loss and wear caused by fretting friction between steel wires.

[0066] The wear depth increment of the steel wire contact surface can be the change in the wear thickness of the steel wire surface caused by micro-friction per unit time.

[0067] Specifically, since bridge cables are the main load-bearing components of bridges and are dynamically affected by factors such as traffic volume and meteorological conditions, the load of bridge cables in the actual working process shows the characteristics of dynamic changes. The dynamic changes in load cause continuous micro-friction between the steel wires inside the cable (usually changes at the micron level). Long-term micro-friction will cause the protective layer (such as the galvanized layer) between the steel wires to be worn, exposing the fresh metal surface and accelerating the corrosion process. Through mathematical analysis, based on the internal component state parameter set that reflects the dynamic working state of the cable, a steel wire micro-friction energy dissipation model is established, and the wear depth increment of the steel wire contact surface is quantified, providing scientific data that can accurately reflect the dynamic wear state of the steel wire for the subsequent cable corrosion risk assessment process, so that the corrosion risk assessment process is highly consistent with the dynamic state of the cable.

[0068] S203. Based on the external environment parameter set and the wear depth increment of the steel wire contact surface, an environment-wear coupled corrosion model is constructed to determine the corrosion development state information.

[0069] The environment-wear coupled corrosion model can be a mathematical model that quantifies the synergistic corrosion effects of environmental corrosion factors and wear conditions on cables.

[0070] The corrosion development status information may be information characterizing the corrosion rate and risk level at different locations of the cable.

[0071] Specifically, cable corrosion is the result of the combined effects of fresh metal surfaces exposed by wear and environmental factors. If environmental corrosion or mechanical wear is analyzed separately, the coupling effect of the two will be ignored, resulting in inaccurate corrosion assessment results. For example, in the coastal high-salt fog environment, the destruction of the protective layer caused by wear will significantly accelerate electrochemical corrosion, leading to an increased risk of cable corrosion. Through mathematical analysis, combined with the external environmental parameter set and the incremental wear depth of the wire contact surface, an environmental-wear coupled corrosion model reflecting the synergistic corrosion effect of environment and wear is constructed to quantify the corrosion rates corresponding to different detection positions of the cable, integrate the corrosion development status information, and achieve a comprehensive assessment of the cable corrosion status.

[0072] S204. Determine and output a cable corrosion risk assessment report based on the corrosion development status information.

[0073] The cable corrosion risk assessment report can be a comprehensive report that includes elements such as corrosion risk level, high-risk location marking and maintenance recommendations.

[0074] Specifically, due to the very long travel of bridge cables (the main cable can reach several thousand meters), the cable corrosion risk shows significant spatial heterogeneity. It is necessary to locate and differentiate the high-risk corrosion areas in order to provide effective guidance data for subsequent maintenance work. According to the corrosion rate of different cable positions reflected in the corrosion development status information, the corrosion risk level of different cable positions is assessed. Through data visualization technology, the corrosion risk assessment results are integrated to construct a cable corrosion risk assessment report. The cable corrosion risk assessment report is provided to cable maintenance personnel to achieve early warning of high-risk corrosion areas of the cable.

[0075] Through this solution, a collaborative analysis of the cable's static parameter set, external environmental parameter set, and internal component status parameter set is performed. Combined with the interaction mechanism of mechanical wear and environmental corrosion, the formation and evolution trend of bridge cable corrosion hotspots can be accurately predicted. The corresponding cable corrosion risk assessment report can be provided to cable maintenance personnel, enabling timely identification and early warning of high-risk cable corrosion locations, timely investigation of potential safety hazards inside the cable, and prevention of local corrosion from expanding into structural damage, significantly improving the service life of the cable.

[0076] In some embodiments, the static parameter set of the cable includes the steel wire friction coefficient, the steel wire fatigue coefficient, the steel wire material hardness, the cable preload, the material baseline aging rate, the shell permeability coefficient, the steel wire protective layer thickness and the steel wire yield strength; the external environment parameter set includes the ambient temperature gradient distribution information, the ambient humidity distribution information and the air salt spray concentration; the internal component state parameter set includes the micro-slip information between the steel wires, the dynamic load amplitude spectrum between the steel wires, the alternating load action frequency and the alternating stress amplitude.

[0077] The wire friction coefficient can be a dimensionless parameter that characterizes the friction characteristics of the wire contact surface. The wire fatigue coefficient can be a quantitative parameter that characterizes the fatigue resistance of the wire material under alternating loads. The wire hardness can be a physical parameter that reflects the compressive resistance of the wire surface (such as the Rockwell hardness HRC value).

[0078] The cable preload can be the preload applied to the steel wires when they are bundled into cables during the cable manufacturing process.

[0079] The material baseline aging rate may be the natural corrosion rate of the cable material under a standard environment.

[0080] The shell permeability coefficient can be a parameter that characterizes the barrier ability of the cable outer surface protective layer (such as PE protective shell) to corrosive media (such as water, salt spray, etc.).

[0081] The steel wire protective layer thickness may be the initial thickness of the steel wire surface protective layer (e.g., galvanized layer) when the cable leaves the factory. The steel wire yield strength may be the critical stress value when the steel wire material undergoes plastic deformation.

[0082] Specifically, the static parameter set of the cable reflects the inherent properties and initial state of the material and is the benchmark for assessing corrosion risks. If the friction coefficient of the steel wire is ignored, the contribution of micro-friction energy loss to wear cannot be quantified; the lack of cable preload data will lead to deviations in the calculation of contact surface pressure; failure to consider the permeability coefficient of the protective layer will underestimate the penetration effect of the environmental corrosive medium; for example, under the same environmental conditions, high-yield strength steel wire has lower stress corrosion sensitivity, while low protective layer permeability coefficient can slow the salt spray erosion process; by integrating material properties (hardness, yield strength, friction coefficient, fatigue coefficient, baseline aging rate), protective performance (permeability coefficient, oxide layer thickness) and structural characteristics (preload), a complete static data benchmark is established for subsequent environmental-wear coupling analysis.

[0083] The ambient temperature gradient distribution information may be ambient temperature distribution information at different locations of the cable.

[0084] The environmental humidity distribution information may be spatial distribution data of relative humidity of air surrounding the cable.

[0085] The air salt spray concentration can be the content of salt particles in the unit volume of air around the cable.

[0086] Specifically, external environmental parameters are exogenous factors driving corrosion development. Temperature gradients affect the location of condensation within cables, and high humidity areas are prone to forming electrochemical corrosion microenvironments. Salt spray concentration directly determines the chloride ion penetration rate. For example, in bridge cables, salt spray concentration is typically higher on the windward side than on the leeward side, leading to non-uniform corrosion distribution. Using only single-point environmental data will fail to capture spatial heterogeneity. Multi-dimensional monitoring of temperature gradients, humidity distribution, and salt spray concentration can precisely locate corrosion hotspots under environmental influences.

[0087] The micro-slip information between steel wires can be the relative displacement amplitude of the contact surface of adjacent steel wires. When adjacent steel wires micro-slip, the magnetic field gradient field on the contact surface will show asymmetric distortion. The micro-slip information between steel wires can be obtained by comparing the difference in magnetic field intensity between adjacent sensor units in the magnetic array sensor, extracting the slip characteristic frequency, and then performing short-time Fourier transform on the magnetic field time domain signal.

[0088] The dynamic load amplitude spectrum between steel wires can be characteristic data reflecting the distribution of alternating load amplitude with frequency. The time-varying signal of the magnetic flux density of the cable steel wire during dynamic loading can be collected by a magnetic array sensor, combined with the stress time history quantified by the inverse magnetoelastic model, and the dynamic load amplitude spectrum between steel wires can be obtained by fast Fourier transform.

[0089] The frequency of the alternating load can be the main frequency component of the periodic external force borne by the cable. The significant periodic components can be extracted through the autocorrelation analysis of the dynamic stress time history to determine the frequency of the alternating load.

[0090] The alternating stress amplitude may be a cross-sectional stress fluctuation range of the cable under the influence of an alternating load. The alternating stress amplitude may be obtained by analyzing stress data collected by the magnetic array sensor using a rain flow counting algorithm.

[0091] Specifically, the internal component state parameters reveal the dynamic damage mechanism of the cable during operation; the micro-slip amount determines the wear depth increment; the dynamic load spectrum reflects the cumulative characteristics of fatigue damage; the alternating stress amplitude affects the tendency of stress corrosion cracking; for example, although high-frequency and low-amplitude alternating loads are not easy to cause instantaneous fracture, they will accelerate micro-motion wear; and low-frequency and high-amplitude loads are prone to cause macroscopic cracking of the protective layer; by real-time monitoring of these parameters, the corrosion prediction model can be dynamically corrected to avoid evaluation deviations caused by changes in working conditions.

[0092] Through this solution, the static properties, environmental status and dynamic operation data of the cable are collected in multiple dimensions to build a full-factor data system for corrosion risk assessment, eliminate the data blind spots of traditional methods, establish a complete scientific data benchmark for subsequent environmental-wear coupling analysis, and improve the scientificity and comprehensiveness of the cable corrosion status assessment process.

[0093] In some embodiments, based on the dynamic load amplitude spectrum between the steel wires, the dynamic load amplitude of the steel wire corresponding to different time points at the current detection position within a preset unit detection time period is determined; based on the alternating load action frequency, according to the steel wire dynamic load amplitude and the cable preload, the contact surface pressure between the steel wires corresponding to different time points at the current detection position within a preset unit detection time period is determined; based on the micro-slip information between the steel wires, the micro-slip amount between the steel wires corresponding to different time points at the current detection position within a preset unit detection time period is determined; based on the preset unit detection time period and the alternating load action frequency, the number of load actions within the preset unit detection time period is determined; based on the steel wire fatigue coefficient and the number of load actions, an energy accumulation correction factor is determined; based on the energy accumulation correction factor, the contact surface pressure between the steel wires and the micro-slip amount between the steel wires, according to the hardness of the steel wire material, a steel wire micro-friction energy dissipation model is constructed to determine the wear depth increment of the steel wire contact surface at the current detection position within the preset unit detection time period.

[0094] The preset unit detection time period may be a pre-set standard detection time window (eg, 10 minutes) for detecting a unit position of the cable, and is used to unify the data sampling durations of different detection positions.

[0095] Contact pressure between steel wires is the normal pressure on the contact surface of adjacent steel wires under the combined action of dynamic load and preload.

[0096] The energy accumulation correction factor reflects the amplification factor (dimensionless) of the effect of alternating load cycles on energy dissipation.

[0097] Specifically, due to the long cable travel, in order to ensure the detection efficiency and accuracy, under the constraint of a unified preset unit detection time period, according to the dynamic load amplitude spectrum between the steel wires, the micro-slip information between the steel wires and the frequency of the alternating load action, the dynamic load amplitude of the steel wires, the micro-slip amount between the steel wires and the number of load actions within the cycle corresponding to different time points in the detection time period at different positions of the cable are divided and extracted respectively; the spatiotemporal distribution of the dynamic load amplitude directly affects the cumulative effect of micro-wear of the steel wires, the micro-slip amount directly determines the cumulative rate of friction work, and the number of load actions reflects the cumulative effect of the alternating load; under the joint action of the dynamic load amplitude between the steel wires and the cable preload, the contact surface pressure between the steel wires will change, and the contact surface pressure between the steel wires directly determines the energy generated by the micro-friction between the steel wires. Mathematical analysis is used, combined with the time-varying superposition of preload and dynamic load, to quantify the contact surface pressure between the steel wires corresponding to different time points at the current detection position within a preset unit detection time period; at the same time, the alternating load has an amplifying effect on metal fatigue, and under the systematic action of fatigue and friction, the wear of the steel wire will be aggravated. Through mathematical analysis, the energy accumulation correction factor reflecting metal fatigue loading is quantified according to the steel wire fatigue coefficient and the number of load actions; and then according to the energy accumulation correction factor, the contact surface pressure between the steel wires, the micro-slip amount between the steel wires and the hardness of the steel wire material, the steel wire micro-friction energy dissipation model is used to realize the quantification of the wear depth increment of the steel wire contact surface corresponding to different detection positions within a preset unit detection time period, so as to accurately reflect the wear of the cable under the influence of alternating loads.

[0098] Through this scheme, the information reflecting the dynamic state of the cable is segmented and processed based on the detection position and the preset unit detection time period as the benchmark constraints. The dynamic load amplitude of the steel wire corresponding to different detection positions at different time points within the preset unit detection time period, the micro-slip amount between the steel wires and the number of load actions within the period are obtained. On this basis, the contact surface pressure and energy accumulation correction factors between the steel wires are quantitatively analyzed to obtain the correction factors. Then, a steel wire micro-friction energy dissipation model is constructed, which can reflect the micro-motion wear characteristics of the cable steel wire under the synergistic effect of friction and fatigue. The wear depth increment of the steel wire contact surface corresponding to different detection positions within the preset unit detection time period is obtained, so as to accurately and comprehensively reflect the wear condition of the cable under the influence of alternating loads.

[0099] In some embodiments, based on the energy accumulation correction factor, the contact surface pressure between the steel wires, and the micro-slip amount between the steel wires, a steel wire micro-friction energy dissipation model is constructed according to the hardness of the steel wire material, specifically the following formula (1):

[0100] (1)

[0101] in, is the wear depth increment of the wire contact surface, is the energy accumulation correction factor, is the steel wire contact energy conversion coefficient, is the hardness of the steel wire material, The current detection position at the current time point The corresponding micro-slip between the steel wires is is the friction coefficient of the steel wire, is the fatigue coefficient of the steel wire, is the number of load actions, The current detection position at the current time point The contact surface pressure between the lower steel wires, It is the preset unit detection time period.

[0102] The steel wire contact energy conversion coefficient can be the proportional coefficient of friction energy converted into material wear depth, which is determined by the material properties of the steel wire.

[0103] Specifically, in the case of fretting wear during the contact process of steel wires, the wear depth increment is directly related to energy dissipation. The slip between the steel wires and the contact surface pressure both contribute to energy dissipation. The wear volume is correlated with the contact pressure, slip and material hardness. Describe the work done by the wire under the influence of contact surface pressure and slip during the fretting friction process, and then use the integral term Characterizes the cumulative friction dissipation energy within a preset unit time period. The steel wire contact energy conversion coefficient directly determines the part of the dissipated friction energy that can be converted into wear depth. The larger the steel wire contact energy conversion coefficient, the larger the volume of the wear material. The hardness of the steel wire material is the ability to resist plastic deformation or wear. The hardness of the steel wire material plays a role in regulating the consumption rate in the denominator. The higher the hardness, the stronger the ability of the steel wire to resist wear. Reflects the influence of steel wire material properties on wear depth; since the steel wire micro-contact does not fully dissipate energy every time it slips, the efficiency of energy accumulation is affected by material fatigue. By introducing an energy accumulation correction factor, the fatigue characteristics of the steel wire under the influence of alternating loads are described, and the wear depth increment of the steel wire contact surface is quantified.

[0104] Through this scheme, mathematical analysis is used to describe the wear development of the steel wire under the synergistic effect of friction and fatigue based on the energy accumulation correction factor, the contact surface pressure between the steel wires, and the micro-slip between the steel wires, according to the hardness of the steel wire material. The wear depth increment of the steel wire contact surface is then quantified to accurately evaluate the wear rate of the steel wire at the current detection position under the influence of alternating loads, providing scientific data support for steel wire corrosion risk assessment.

[0105] In some embodiments, based on the frequency of the alternating load, the dynamic load amplitude of the steel wire and the cable preload, the contact surface pressure between the steel wires corresponding to different time points at the current detection position within a preset unit detection time period is determined, specifically, the following formula (2):

[0106] (2)

[0107] in, The current detection position at the current time point The contact surface pressure between the lower steel wires, is the cable preload, The current time point The dynamic load amplitude of the steel wire under is the frequency of alternating load action, It is the preset unit detection time period.

[0108] Specifically, since the alternating load has the characteristics of periodic fluctuation, through the formula (2) The periodic fluctuating pressure exerted by the alternating load on the steel wire is described, and then the contact surface pressure between the steel wires is quantified by combining the cable preload exerted by the cable itself on the steel wire.

[0109] Through this solution, mathematical analysis is used to capture the periodic fluctuating pressure exerted by the alternating load on the steel wire based on the frequency of the alternating load, the amplitude of the dynamic load on the steel wire, and the cable preload. Combined with the cable preload exerted on the steel wire by the cable itself, the contact surface pressure between the steel wires is quantified, thereby improving the accuracy and scientific nature of the contact surface pressure between the steel wires, thereby making the incremental wear depth of the steel wire contact surface more accurate.

[0110] In some embodiments, the internal relative humidity and internal temperature of the cable are determined based on the ambient temperature gradient distribution information and the ambient humidity distribution information; the internal salt spray deposition concentration of the cable is determined based on the air salt spray concentration; based on the material baseline aging rate, the thickness of the steel wire protective layer, the alternating stress amplitude and the steel wire yield strength, according to the internal relative humidity, internal temperature, internal salt spray deposition concentration, the wear depth increment of the steel wire contact surface and the alternating load action frequency, the cable corrosion development state is subjected to an environment-wear coupling analysis, an environment-wear coupling corrosion model is constructed, and the corrosion development rates corresponding to different detection positions are determined; according to the corrosion development rates corresponding to different detection positions, corrosion development status information is constructed.

[0111] The internal relative humidity may be a quantitative value used to reflect the relative humidity level inside the cable.

[0112] The internal temperature may be a quantitative value used to reflect the relative temperature inside the cable.

[0113] The internal salt spray deposition concentration can be a quantitative value used to reflect the salt concentration of the air inside the cable.

[0114] The corrosion development rate can be a quantitative value used to characterize the corrosion development speed of steel wire under the dual effects of environmental factors and wear.

[0115] Specifically, the corrosion condition of the steel wire in the cable will be affected by the temperature, humidity and salt spray concentration in the environment in which it is located. Specifically, the temperature increase usually accelerates the rate of chemical reactions, including oxidation reactions and corrosion reactions; humidity is one of the important factors affecting steel corrosion. In a high humidity environment, water easily forms an electrolyte solution, which promotes the electrochemical corrosion process; salt spray is a common corrosive medium, especially in coastal areas or areas where cross-sea bridges are located. The concentration of salt spray in the air is high, and salt ions (such as chloride ions) can significantly reduce the resistivity of water, thereby accelerating the occurrence of electrochemical corrosion reactions; through fluid simulation platforms such as FLUENT, based on the cable material properties and the shell material properties, the temperature conduction state and humidity diffusion inside the cable are simulated. The state and salt spray deposition state of the cable are simulated to establish the mapping relationship between the internal temperature, humidity and salt spray deposition concentration of the cable and the external environmental factors. On this basis, the internal temperature, internal relative humidity and internal salt spray deposition concentration are obtained respectively according to the ambient temperature gradient distribution information, ambient humidity distribution information and air salt spray concentration. On this basis, combined with the material properties and dynamic wear conditions of the cable, the environment-wear coupling analysis is carried out through mathematical analysis to construct the environment-wear coupling corrosion model. The corrosion development rate at different detection positions of the cable under the dual influence of environmental factors and dynamic wear is quantified, and the corrosion development state information is integrated to reflect the corrosion development state of the cable at different positions, so as to realize the quantitative prediction of the corrosion state of the cable.

[0116] Through this solution, an environment-wear coupling model is constructed to capture the synergistic effects of mechanical damage and chemical corrosion at the same time, significantly improving the corrosion rate prediction accuracy and avoiding the risk of underestimation of single-factor models. By combining the frequency and stress amplitude of alternating loads, the non-steady-state characteristics of corrosion development under actual working conditions are dynamically reflected, supporting adaptive analysis of sudden load changes. By quantitatively analyzing the corrosion development rates at different detection locations, accurate data support is provided for the positioning of high-corrosion risk areas.

[0117] In some embodiments, based on the material baseline aging rate, steel wire protective layer thickness, alternating stress amplitude and steel wire yield strength, according to the internal relative humidity, internal temperature, internal salt spray deposition concentration, steel wire contact surface wear depth increment and alternating load action frequency, an environment-wear coupling analysis is performed on the cable corrosion development state, an environment-wear coupling corrosion model is constructed, and the corrosion development rate is determined, specifically the following formula (3):

[0118] (3)

[0119] in, is the corrosion development rate, is the material baseline aging rate, is the shell permeability coefficient, is the internal salt spray deposition concentration, is the internal relative humidity, To preset humidity adjustment index, is the internal temperature, is the wear depth increment of the wire contact surface, is the thickness of the steel wire protective layer, is the preset dynamic load coupling factor, is the alternating stress amplitude, is the frequency of alternating load action, is the preset load adjustment index, is the yield strength of steel wire.

[0120] The preset humidity adjustment index may be a quantitative index for adjusting the nonlinear enhancement effect of humidity on the corrosion rate. The preset humidity adjustment index may be 1.5. When the humidity is greater than 75%, the corrosion rate increases exponentially.

[0121] The preset load adjustment index can be a quantitative index for adjusting the nonlinear effect of the load action frequency on the corrosion rate. The preset load adjustment index can be 0.3.

[0122] Specifically, through formula (3) Describe the influence of external environmental factors on the corrosion development rate through the molecular part It reflects the enhancement effect of internal salt mist deposition concentration and internal relative humidity on corrosion rate. The salt mist deposition concentration is linearly positively correlated with the corrosion rate, while the humidity is nonlinearly correlated with the corrosion rate (the corrosion rate will increase rapidly after the humidity reaches a certain threshold). Convert Celsius temperature to Kelvin temperature scale to reflect the regulation of temperature on ion migration rate, and introduce the overall influence of external environmental factors by the shell permeability coefficient condition; at the same time, Describes the effect of wear between steel wires on corrosion efficiency under dynamic load. The depth increment of steel wire due to wear determines the exposed area of ​​the inner metal of the steel wire. The larger the exposed area, the higher the corrosion rate. At the same time, the thicker the steel wire protective layer, the more difficult it is for the inner metal to be exposed due to wear. Therefore, Describe the relative increment of corrosion rate under wear, and use the logarithmic model to describe the nonlinear additive effect of wear state on corrosion rate; The effect of stress changes under alternating loads on the corrosion rate is described. The larger the stress amplitude and the higher the frequency of alternating loads, the greater the local strain energy of the cable and the higher the corrosion rate. The yield strength of the steel wire is introduced as a normalized benchmark for stress addition to control the numerical range. By combining the above three effects, the corrosion development rate is quantified based on the material benchmark aging rate.

[0123] Through this scheme, mathematical analysis is used to describe the influence of environment, wear and dynamic stress on the corrosion rate of cables based on the material benchmark aging rate, steel wire protective layer thickness, alternating stress amplitude and steel wire yield strength, according to internal relative humidity, internal temperature, internal salt spray deposition concentration, steel wire contact surface wear depth increment and alternating load action frequency. Under the triple impact dimension, based on the material benchmark aging rate, the corrosion development rate is accurately quantified, thereby improving the accuracy and scientific nature of the corrosion development rate.

[0124] In some embodiments, the corrosion development rates corresponding to different detection positions are compared with the corresponding preset corrosion rate thresholds to determine the comparison results; based on the comparison results, the safe position set, the subsequent key focus position set and the high-risk position set are determined respectively; based on the three-dimensional color differentiation labeling strategy, the corresponding detection positions in the safe position set, the subsequent key focus position set and the high-risk position set are highlighted and labeled as warnings to determine the detection labeling warning information; based on the detection labeling warning information, a cable corrosion risk assessment report is constructed and output.

[0125] The three-dimensional color differentiation labeling strategy can be a method of visually labeling locations of different risk levels in the cable model based on red, yellow, and green colors.

[0126] The safe position set may be a set of detection positions where the corrosion rate is within a safe range, and the safety range may be evaluated based on a standard of being 80% lower than a corresponding threshold.

[0127] The subsequent key focus location set may be a set of detection locations with a high corrosion rate that require special attention during subsequent detection and maintenance. The assessment of a high corrosion rate may be based on a corresponding threshold of 80%-95%.

[0128] The high-risk location set may be a detection location set where the corrosion development rate is too high, corresponding to a cable section requiring urgent maintenance. The assessment of the excessively high corrosion development rate may be based on a standard of exceeding a corresponding threshold of 95%.

[0129] The detection and marking warning information can be obtained by marking the corresponding risks at different positions of the cable and obtaining marked information.

[0130] Specifically, the stress states and environments of different sections of the cable are different. If a unified threshold is used for assessment, it will lead to missed detections in high-risk areas or false alarms in low-risk areas. By presetting dynamic thresholds that match the location characteristics, the accuracy of risk assessment can be improved. In the process of safety level classification, if only "safe" and "high risk" are divided, it cannot reflect the intermediate state of corrosion development (such as a temporary rate increase but not reaching the critical value). Adding a "subsequent key attention" level can guide maintenance personnel to implement hierarchical management and optimize the allocation of subsequent maintenance resources. Through a three-dimensional color-differentiation labeling strategy, the risk distribution of different cable locations can be intuitively clarified, thereby improving the readability of the cable corrosion risk assessment report.

[0131] This solution utilizes dynamic thresholds and multi-level classification to accurately distinguish risk areas at different development stages, avoiding the waste of subsequent maintenance resources or risk omissions caused by a "one-size-fits-all" assessment. A three-dimensional color-coded labeling strategy provides an intuitive view of corrosion risk, significantly reducing the complexity of manual analysis and improving the efficiency and scientific nature of subsequent maintenance planning.

[0132] In some embodiments, based on a set of high-risk locations, a parameter change information set is extracted during the evaluation process of the corrosion development rate corresponding to each high-risk location; the parameter change information set is analyzed to determine the root cause of the corrosion risk corresponding to each high-risk location; based on a preset large language model, the corresponding maintenance optimization suggestions are determined according to the root cause of the corrosion risk, and the maintenance optimization suggestions are added to the cable corrosion risk assessment report.

[0133] The parameter change information set may be a set of parameters that dynamically change during the corrosion assessment process at a high-risk location.

[0134] The root cause of corrosion risk may be the dominant factor type that leads to accelerated corrosion in specific high-risk locations, such as "salt spray penetration dominant type" and "moisture-heat coupling dominant type".

[0135] The preset large language model may be a large language reasoning model used to provide corresponding maintenance recommendations based on the corrosion risk and focusing on the root cause. The preset large language model may be an existing large language model, such as ChatGPT.

[0136] Maintenance optimization recommendations can be maintenance recommendations that focus on the root causes of corrosion risks.

[0137] Specifically, the accelerated corrosion at the same high-risk location may be driven by different factors (such as salt spray erosion and mechanical fatigue) or a combination of factors. If only the risk level is output without identifying the dominant root cause, the maintenance measures will not match the actual problem (for example, incorrectly implementing stress relief in the salt spray-dominated area), reducing the effectiveness of maintenance. By extracting the parameters that have a significant impact on the corrosion rate from the parameter change information set, the corresponding influencing factors are used as the root cause of the corrosion risk, and corresponding maintenance optimization suggestions are given through the preset large language model. The natural language generation technology based on the large language model can dynamically associate parameter change patterns with industry knowledge bases (such as ASTM maintenance standards and historical case libraries), and output personalized and explainable maintenance suggestions to adapt to diverse root cause combination scenarios, provide maintenance personnel with targeted suggestions with reference significance, and improve the efficiency and effectiveness of subsequent maintenance.

[0138] Through this solution, the root causes of abnormal corrosion rates in high-risk locations are located, the root causes of corrosion risk are determined, and corresponding maintenance optimization suggestions are given for the root causes of corrosion risk based on the large language model. The maintenance optimization suggestions are added to the cable corrosion risk assessment report, providing maintenance personnel with targeted suggestions with reference significance and improving the efficiency and effectiveness of subsequent maintenance.

[0139] Figure 3 This is a structural diagram of a cable internal corrosion risk warning system provided by an embodiment of the present application, such as Figure 3 As shown, a cable internal corrosion risk early warning system 300 of this embodiment includes: a parameter collection module 301 , a wear analysis module 302 , a coupling analysis module 303 and an output module 304 .

[0140] The parameter collection module 301 is used to obtain the static parameter set, external environment parameter set and internal component status parameter set of the cable; the wear analysis module 302 is used to construct a steel wire micro-friction energy dissipation model based on the internal component status parameter set, and determine the wear depth increment of the steel wire contact surface; the coupling analysis module 303 is used to construct an environment-wear coupling corrosion model based on the external environment parameter set and the wear depth increment of the steel wire contact surface, and determine the corrosion development status information; the output module 304 is used to determine and output a cable corrosion risk assessment report based on the corrosion development status information.

[0141] Optionally, in the parameter collection module 301, the static parameter set of the cable includes the steel wire friction coefficient, the steel wire fatigue coefficient, the steel wire material hardness, the cable preload, the material baseline aging rate, the shell permeability coefficient, the steel wire protective layer thickness and the steel wire yield strength; the external environment parameter set includes the ambient temperature gradient distribution information, the ambient humidity distribution information and the air salt spray concentration; the internal component state parameter set includes the micro-slip information between steel wires, the dynamic load amplitude spectrum between steel wires, the alternating load action frequency and the alternating stress amplitude.

[0142] Optionally, the wear analysis module 302 is specifically used to: determine the dynamic load amplitude of the steel wire corresponding to different time points at the current detection position within a preset unit detection time period based on the dynamic load amplitude spectrum between the steel wires; determine the contact surface pressure between the steel wires corresponding to different time points at the current detection position within the preset unit detection time period based on the alternating load action frequency, the dynamic load amplitude between the steel wires and the cable preload; determine the micro-slip amount between the steel wires corresponding to different time points at the current detection position within the preset unit detection time period based on the micro-slip information between the steel wires; determine the number of load actions within the preset unit detection time period based on the preset unit detection time period and the alternating load action frequency; determine an energy accumulation correction factor based on the steel wire fatigue coefficient and the number of load actions; construct the steel wire micro-friction energy dissipation model based on the energy accumulation correction factor, the contact surface pressure between the steel wires and the micro-slip amount between the steel wires, and according to the hardness of the steel wire material, to determine the wear depth increment of the steel wire contact surface at the current detection position within the preset unit detection time period.

[0143] Optionally, when the wear analysis module 302 constructs the steel wire fretting friction energy dissipation model based on the energy accumulation correction factor, the contact surface pressure between the steel wires, and the fretting slip amount between the steel wires, according to the hardness of the steel wire material, the specific formula is as follows:

[0144] ;

[0145] in, is the wear depth increment of the steel wire contact surface, is the energy accumulation correction factor, is the steel wire contact energy conversion coefficient, is the hardness of the steel wire material, The current detection position at the current time point The corresponding micro-slip between the steel wires is is the friction coefficient of the steel wire, is the steel wire fatigue coefficient, is the number of times the load acts, The current detection position at the current time point The contact surface pressure between the steel wires is as follows: The preset unit detection time period.

[0146] Optionally, when the wear analysis module 302 determines the contact surface pressure between the steel wires corresponding to different time points at the current detection position within the preset unit detection time period based on the alternating load action frequency, the dynamic load amplitude of the steel wire, and the cable preload, the specific formula is as follows:

[0147] ;

[0148] in, The current detection position at the current time point The contact surface pressure between the steel wires is as follows: is the cable preload, The current time point The wire dynamic load amplitude under is the frequency of the alternating load action, The preset unit detection time period.

[0149] Optionally, the coupling analysis module 303 is specifically used to: determine the internal relative humidity and internal temperature of the cable according to the ambient temperature gradient distribution information and the ambient humidity distribution information; determine the internal salt spray deposition concentration of the cable according to the air salt spray concentration; based on the material baseline aging rate, the steel wire protective layer thickness, the alternating stress amplitude and the steel wire yield strength, according to the internal relative humidity, the internal temperature, the internal salt spray deposition concentration, the steel wire contact surface wear depth increment and the alternating load action frequency, perform an environment-wear coupling analysis on the cable corrosion development state, construct the environment-wear coupling corrosion model, determine the corrosion development rate corresponding to different detection positions; construct the corrosion development state information according to the corrosion development rate corresponding to different detection positions.

[0150] Optionally, the coupling analysis module 303 performs an environment-wear coupling analysis on the cable corrosion development state based on the material baseline aging rate, the steel wire protective layer thickness, the alternating stress amplitude, and the steel wire yield strength, according to the internal relative humidity, internal temperature, internal salt fog deposition concentration, the steel wire contact surface wear depth increment, and the alternating load action frequency, constructs the environment-wear coupling corrosion model, and determines the corrosion development rate, specifically using the following formula:

[0151] ;

[0152] in, is the corrosion development rate, is the material baseline aging rate, is the shell permeability coefficient, is the internal salt spray deposition concentration, is the internal relative humidity, To preset humidity adjustment index, is the internal temperature, is the wear depth increment of the steel wire contact surface, is the thickness of the steel wire protective layer, is the preset dynamic load coupling factor, is the alternating stress amplitude, is the frequency of the alternating load action, is the preset load adjustment index, is the yield strength of the steel wire.

[0153] Optionally, the output module 304 is specifically used to: compare the corrosion development rates corresponding to different detection positions with the corresponding preset corrosion rate thresholds to determine the comparison results; determine the safe position set, the subsequent key focus position set and the high-risk position set according to the comparison results; highlight and warn the corresponding detection positions in the safe position set, the subsequent key focus position set and the high-risk position set according to the three-dimensional color differentiation labeling strategy to determine the detection labeling warning information; construct and output the cable corrosion risk assessment report based on the detection labeling warning information.

[0154] Optionally, the system also includes a root cause analysis module 305, which is specifically used to: extract a parameter change information set corresponding to the corrosion development rate evaluation process of each high-risk location based on the high-risk location set; analyze the parameter change information set to determine the corrosion risk focus root cause corresponding to each high-risk location; based on a preset large language model, determine the corresponding maintenance optimization suggestion according to the corrosion risk focus root cause, and add the maintenance optimization suggestion to the cable corrosion risk assessment report.

[0155] The system of this embodiment can be used to execute the method of any of the above embodiments. Its implementation principles and technical effects are similar and will not be described in detail here.

Claims

1. A cable internal corrosion risk early warning method, characterized in that: include: Obtaining cable static parameter set, external environment parameter set and internal component state parameter set; According to the internal component state parameter set, a steel wire fretting friction energy dissipation model is constructed to determine the wear depth increment of the steel wire contact surface; Based on the external environment parameter set and the wear depth increment of the steel wire contact surface, an environment-wear coupled corrosion model is constructed to determine the corrosion development state information; Determine and output a cable corrosion risk assessment report based on the corrosion development status information; The static parameter set of the cable includes steel wire friction coefficient, steel wire fatigue coefficient, steel wire material hardness, cable preload, material reference aging rate, shell permeability coefficient, steel wire protective layer thickness and steel wire yield strength; The external environment parameter set includes ambient temperature gradient distribution information, ambient humidity distribution information and air salt spray concentration; The internal component state parameter set includes the micro-slip information between the steel wires, the dynamic load amplitude spectrum between the steel wires, the alternating load action frequency and the alternating stress amplitude; The method of constructing a steel wire fretting friction energy dissipation model based on the internal component state parameter set and determining the wear depth increment of the steel wire contact surface includes: Determining the dynamic load amplitudes of the steel wires corresponding to different time points at the current detection position within a preset unit detection time period according to the dynamic load amplitude spectrum between the steel wires; Based on the frequency of the alternating load, according to the dynamic load amplitude of the steel wire and the cable preload, determining the contact surface pressure between the steel wires corresponding to different time points at the current detection position within the preset unit detection time period; Determine, based on the inter-wire micro-slip information, the inter-wire micro-slip amounts corresponding to different time points at the current detection position within the preset unit detection time period; Determining the number of load actions within the preset unit detection time period according to the preset unit detection time period and the alternating load action frequency; determining an energy accumulation correction factor according to the steel wire fatigue coefficient and the number of load actions; Based on the energy accumulation correction factor, the contact surface pressure between the steel wires, and the fretting slip amount between the steel wires, and according to the hardness of the steel wire material, a steel wire fretting friction energy dissipation model is constructed to determine the wear depth increment of the steel wire contact surface at the current detection position within the preset unit detection time period; The steel wire fretting friction energy dissipation model is constructed based on the energy accumulation correction factor, the contact surface pressure between the steel wires, and the fretting slip amount between the steel wires, according to the hardness of the steel wire material. Specifically, it is the following formula: ； in, is the wear depth increment of the steel wire contact surface, is the energy accumulation correction factor, is the steel wire contact energy conversion coefficient, is the hardness of the steel wire material, The current detection position at the current time point The corresponding micro-slip between the steel wires is is the friction coefficient of the steel wire, is the steel wire fatigue coefficient, is the number of times the load acts, The current detection position at the current time point The contact surface pressure between the steel wires is as follows: The preset unit detection time period.

2. The method according to claim 1, characterized in that Based on the frequency of the alternating load, according to the dynamic load amplitude of the steel wire and the cable preload, the contact surface pressure between the steel wires corresponding to different time points at the current detection position within the preset unit detection time period is determined, specifically by the following formula: ； in, The current detection position at the current time point The contact surface pressure between the steel wires is as follows: is the cable preload, The current time point The wire dynamic load amplitude under is the frequency of the alternating load action, The preset unit detection time period.

3. The method according to claim 2, characterized in that The method of constructing an environment-wear coupled corrosion model based on the external environment parameter set and the wear depth increment of the steel wire contact surface to determine the corrosion development state information includes: determining the internal relative humidity and internal temperature of the cable according to the ambient temperature gradient distribution information and the ambient humidity distribution information; Determining the internal salt mist deposition concentration of the cable according to the air salt mist concentration; Based on the material baseline aging rate, the thickness of the steel wire protective layer, the alternating stress amplitude, and the steel wire yield strength, and according to the internal relative humidity, the internal temperature, the internal salt fog deposition concentration, the wear depth increment of the steel wire contact surface, and the alternating load action frequency, an environment-wear coupling analysis is performed on the cable corrosion development state, the environment-wear coupling corrosion model is constructed, and the corrosion development rates corresponding to different detection positions are determined; The corrosion development status information is constructed according to the corrosion development rates corresponding to different detection positions.

4. The method according to claim 3, characterized in that Based on the material benchmark aging rate, the steel wire protective layer thickness, the alternating stress amplitude, and the steel wire yield strength, and according to the internal relative humidity, the internal temperature, the internal salt fog deposition concentration, the steel wire contact surface wear depth increment, and the alternating load action frequency, an environment-wear coupling analysis is performed on the cable corrosion development state, and the environment-wear coupling corrosion model is constructed to determine the corrosion development rate corresponding to different detection positions. Specifically, the following formula is used: ； in, is the corrosion development rate, is the material baseline aging rate, is the shell permeability coefficient, is the internal salt spray deposition concentration, is the internal relative humidity, To preset humidity adjustment index, is the internal temperature, is the wear depth increment of the steel wire contact surface, is the thickness of the steel wire protective layer, is the preset dynamic load coupling factor, is the alternating stress amplitude, is the frequency of the alternating load action, is the preset load adjustment index, is the yield strength of the steel wire.

5. The method according to claim 4, characterized in that Determining and outputting a cable corrosion risk assessment report based on the corrosion development status information includes: Comparing the corrosion development rates corresponding to different detection positions with corresponding preset corrosion rate thresholds to determine comparison results; According to the comparison results, a safe location set, a subsequent key focus location set, and a high-risk location set are determined respectively; According to the three-dimensional color differentiation labeling strategy, the corresponding detection locations in the safe location set, the subsequent key focus location set, and the high-risk location set are highlighted and labeled as warnings to determine the detection labeling warning information; Based on the detection and marking warning information, the cable corrosion risk assessment report is constructed and output.

6. The method according to claim 5, characterized in that The method further comprises: Extracting, based on the set of high-risk locations, a parameter change information set corresponding to the corrosion development rate evaluation process at each high-risk location; Analyze the parameter change information set to determine the corrosion risk focus root cause corresponding to each high-risk location; Based on the preset large language model, the corresponding maintenance optimization suggestions are determined according to the corrosion risk focus on the root cause, and the maintenance optimization suggestions are added to the cable corrosion risk assessment report.

7. A cable internal corrosion risk warning system, applied to a cable internal corrosion risk warning method according to claims 1-6, characterized in that: include: Parameter collection module, used to obtain cable static parameter set, external environment parameter set and internal component state parameter set; a wear analysis module for constructing a steel wire fretting friction energy dissipation model based on the internal component state parameter set and determining the wear depth increment of the steel wire contact surface; A coupling analysis module is used to construct an environment-wear coupling corrosion model based on the external environment parameter set and the wear depth increment of the steel wire contact surface to determine the corrosion development status information; An output module, configured to determine and output a cable corrosion risk assessment report based on the corrosion development status information; In the parameter collection module, the cable static parameter set includes steel wire friction coefficient, steel wire fatigue coefficient, steel wire material hardness, cable preload, material reference aging rate, shell permeability coefficient, steel wire protective layer thickness and steel wire yield strength; The external environment parameter set includes ambient temperature gradient distribution information, ambient humidity distribution information and air salt spray concentration; The internal component state parameter set includes the micro-slip information between the steel wires, the dynamic load amplitude spectrum between the steel wires, the alternating load action frequency and the alternating stress amplitude; The wear analysis module is specifically used to: Determining the dynamic load amplitudes of the steel wires corresponding to different time points at the current detection position within a preset unit detection time period according to the dynamic load amplitude spectrum between the steel wires; Based on the frequency of the alternating load, according to the dynamic load amplitude of the steel wire and the cable preload, determining the contact surface pressure between the steel wires corresponding to different time points at the current detection position within the preset unit detection time period; Determine, based on the inter-wire micro-slip information, the inter-wire micro-slip amounts corresponding to different time points at the current detection position within the preset unit detection time period; Determining the number of load actions within the preset unit detection time period according to the preset unit detection time period and the alternating load action frequency; determining an energy accumulation correction factor according to the steel wire fatigue coefficient and the number of load actions; Based on the energy accumulation correction factor, the contact surface pressure between the steel wires, and the fretting slip amount between the steel wires, and according to the hardness of the steel wire material, a steel wire fretting friction energy dissipation model is constructed to determine the wear depth increment of the steel wire contact surface at the current detection position within the preset unit detection time period; The wear analysis module constructs the steel wire fretting friction energy dissipation model based on the energy accumulation correction factor, the contact surface pressure between the steel wires, and the fretting slip amount between the steel wires according to the hardness of the steel wire material. Specifically, the model is as follows: ； in, is the wear depth increment of the steel wire contact surface, is the energy accumulation correction factor, is the steel wire contact energy conversion coefficient, is the hardness of the steel wire material, The current detection position at the current time point The corresponding micro-slip between the steel wires is is the friction coefficient of the steel wire, is the steel wire fatigue coefficient, is the number of times the load acts, The current detection position at the current time point The contact surface pressure between the steel wires is as follows: The preset unit detection time period.

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