A Multi-Sensor Fusion Method and System for Quantitative Early Warning and Online Monitoring of Corrosion Protection Coatings on Power Grid Steel Structures

Abstract

This invention relates to the field of steel structure anti-corrosion coating monitoring technology, and particularly to a multi-sensor fusion-based online monitoring method and system for quantitative early warning of anti-corrosion coatings on power grid steel structures. The method includes: deploying sensor components in the monitored area of ​​the power grid steel structure and collecting monitoring data, including coating electrochemical parameters, substrate corrosion parameters, environmental parameters, and electromagnetic field parameters; determining the coating degradation degree based on the coating electrochemical parameters and substrate corrosion parameters; determining an environmental corrosion correction coefficient based on the environmental parameters; determining an electromagnetic field influence coefficient based on the electromagnetic field parameters; and generating a coating health status assessment result based on the coating degradation degree, environmental corrosion correction coefficient, and electromagnetic field influence coefficient. The coating health status assessment result generated by this invention can reflect the degradation state of the anti-corrosion coating itself and clarify the degree of influence of the power grid electromagnetic field on the coating degradation process, thus providing information dimensions that better meet the needs of power grid steel structure anti-corrosion operation and maintenance.

Description

Technical Field

[0001] This invention relates to the technical field of monitoring anti-corrosion coatings on steel structures, and in particular to a multi-sensor fusion-based online monitoring method and system for quantitative early warning of anti-corrosion coatings on power grid steel structures. Background Technology

[0002] Anti-corrosion coatings are a core protective measure for outdoor steel structures such as power grid transmission towers and substation frames, isolating them from corrosive media and delaying substrate corrosion. Online monitoring of the health status of anti-corrosion coatings can effectively ensure the long-term safe and stable operation of power grid steel structures. Currently, existing methods for monitoring the health status of anti-corrosion coatings on steel structures mostly employ detection techniques such as electrochemical impedance spectroscopy.

[0003] However, steel structures such as power grid transmission towers and substation frames are subjected to alternating electromagnetic fields with superimposed 50Hz power frequency and higher harmonics such as the 3rd, 5th, and 7th orders for extended periods. This electromagnetic field directly affects the degradation process of anti-corrosion coatings. For example, alternating electromagnetic fields can induce repeated polarization relaxation effects in the polymers of the anti-corrosion coating, causing polymer chain segment breakage and reduced cross-linking degree, directly damaging the coating's density. This increases the penetration channels for corrosive media such as water, oxygen, and chloride ions, accelerating the coating's penetration and water absorption aging degradation. Macroscopically, this manifests as a decrease in coating resistance and an increase in coating capacitance, among other electrochemical characteristic parameters. Simultaneously, the alternating electromagnetic field of the power grid generates induced alternating currents at the interface between the steel structure substrate and the coating, intensifying the electrochemical reaction process at the interface, reducing charge transfer resistance, accelerating the peeling of the coating from the substrate, and promoting the anodic dissolution of the substrate metal, thus increasing the substrate corrosion rate.

[0004] Existing monitoring methods do not consider the impact of power frequency and harmonic electromagnetic field parameters unique to the power grid environment on the health status of coatings. They cannot quantify the degree of influence of electromagnetic fields on the deterioration process of anti-corrosion coatings, nor do they integrate multiple monitoring data for quantitative early warning. This results in a discrepancy between the coating health status assessment results and the actual deterioration status of the coating under actual power grid operating conditions. Summary of the Invention

[0005] This invention provides a multi-sensor fusion-based online monitoring method and system for quantitative early warning of anti-corrosion coatings on power grid steel structures, which can effectively solve the problems in the background art.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows: A multi-sensor fusion method for quantitative early warning online monitoring of anti-corrosion coatings on power grid steel structures includes: Sensing components are deployed in the area to be monitored on the steel structure of the power grid, and monitoring data is collected. The monitoring data includes coating electrochemical parameters, substrate corrosion parameters, environmental parameters, and electromagnetic field parameters. The degree of coating degradation is determined based on the coating electrochemical parameters and the substrate corrosion parameters. Based on the environmental parameters, determine the environmental corrosion correction coefficient; based on the electromagnetic field parameters, determine the electromagnetic field influence coefficient. Based on the degree of coating degradation, the environmental corrosion correction coefficient, and the electromagnetic field influence coefficient, a coating health status assessment result is generated.

[0007] Furthermore, the electrochemical parameters of the coating include at least one of coating resistance, coating capacitance, charge transfer resistance, and low-frequency phase angle; The substrate corrosion parameters include at least one of the metal substrate corrosion thinning amount and corrosion rate; The environmental parameters include relative humidity, temperature, salt spray deposition, and Cl. - At least one of the concentrations; The electromagnetic field parameters include at least one of electromagnetic field strength and frequency.

[0008] Furthermore, the sensing component includes at least an electrochemical impedance sensing unit, a resistive corrosion sensing unit, a temperature, humidity, and salt spray sensing unit, and an electromagnetic field sensing unit. All sensing units are centrally deployed at the same monitoring point, so that the acquisition areas of each sensing unit overlap spatially.

[0009] Further, based on the electrochemical parameters of the coating and the corrosion parameters of the substrate, the degree of coating degradation is determined, including: Obtain the initial baseline values ​​and real-time monitoring values ​​of the electrochemical parameters of the coating; Obtain the initial baseline values ​​and real-time monitoring values ​​of the substrate corrosion parameters; The coating degradation index is calculated based on the ratio between the initial baseline value and the real-time monitoring value, and is used to characterize the degree of coating degradation.

[0010] Further, based on the aforementioned environmental parameters, an environmental corrosion correction coefficient is determined, including: Obtain initial baseline values ​​and real-time monitoring values ​​for each environmental parameter; Based on the ratio of the real-time monitoring value of each environmental parameter to the initial baseline value, and combined with the preset environmental weighting coefficient, the environmental corrosion correction coefficient is calculated. When the environmental corrosion correction coefficient is greater than 1, it is determined that environmental factors accelerate coating deterioration; When the environmental corrosion correction coefficient is less than or equal to 1, it is determined that environmental factors have no significant accelerating effect on coating deterioration.

[0011] Further, based on the electromagnetic field parameters, the electromagnetic field influence coefficient is determined, including: Obtain measured electromagnetic field strength and safety electromagnetic field reference values; The electromagnetic field influence coefficient is obtained by calculating the ratio of the measured electromagnetic field strength to the safe electromagnetic field reference value. When the electromagnetic field influence coefficient is greater than 1, it is determined that the electromagnetic field accelerates the deterioration of the coating. When the electromagnetic field influence coefficient is less than or equal to 1, it is determined that the electromagnetic field has no significant effect on coating degradation.

[0012] Furthermore, the monitoring data also includes cathodic protection potential parameters; the method further includes: Based on the aforementioned cathodic protection potential parameters, determine the cathodic protection correction coefficient; The coating health status assessment results are corrected based on the cathodic protection correction factor.

[0013] Furthermore, the sensing component also includes an open-circuit potential sensing unit, which is electrically connected to the coating damage area or steel structure substrate through a conductive contact, and is used to collect cathodic protection potential parameters.

[0014] Further, determining the cathodic protection correction coefficient based on the cathodic protection potential parameters includes: When the self-corrosion potential is less than the first potential threshold, the cathodic protection correction coefficient is determined to be the first value; When the self-corrosion potential is greater than or equal to the first potential threshold and less than the second potential threshold, the cathodic protection correction coefficient is determined to be the second value. When the self-corrosion potential is greater than or equal to the second potential threshold, the cathodic protection correction coefficient is determined to be the third value; Wherein, the first value is less than the second value, and the second value is less than the third value.

[0015] Further, based on the coating degradation degree, the environmental corrosion correction coefficient, and the electromagnetic field influence coefficient, a coating health status assessment result is generated, including: A comprehensive evaluation index is calculated based on the degree of coating degradation, the environmental corrosion correction coefficient, and the electromagnetic field influence coefficient. The comprehensive evaluation index is compared with a preset early warning threshold; Based on the comparison results, a warning level is determined, which includes mild aging, moderate risk, and emergency warning.

[0016] Furthermore, the formula for calculating the coating degradation index is as follows: Wherein, DI represents the coating degradation index; Rc0 is the initial reference value of coating resistance, and Rc is the real-time value of coating resistance; Cc0 is the initial reference value of coating capacitance, and Cc is the real-time value of coating capacitance; Rct0 is the initial reference value of charge transfer resistance, and Rct is the real-time value of charge transfer resistance; ER0 is the initial reference value of corrosion thinning, and ER is the real-time value of corrosion thinning; α, β, γ, and δ represent the weighting coefficients corresponding to the coating resistance ratio, coating capacitance ratio, charge transfer resistance ratio, and corrosion thinning ratio, respectively.

[0017] Furthermore, the measured electromagnetic field strength uses the effective value of the measured multi-band synthesized electromagnetic field strength, calculated using the following formula: ; Where E is the measured electromagnetic field strength; E 50 E3 represents the effective value of the electromagnetic field intensity at a 50Hz power frequency, while E5 and E7 represent the effective values ​​of the electromagnetic field intensity of the 3rd, 5th, and 7th harmonics, respectively.

[0018] On the other hand, the present invention also provides a multi-sensor fusion-based online monitoring system for quantitative early warning of anti-corrosion coatings on power grid steel structures, comprising: A multi-sensor fusion component is deployed in the area to be monitored on the steel structure of the power grid to collect monitoring data including coating electrochemical parameters, substrate corrosion parameters, environmental parameters and electromagnetic field parameters; The monitoring terminal is connected to the multi-sensor fusion component via wired or wireless connection and is used to perform preprocessing operations on the collected monitoring data. A low-power wireless transmission module and a cloud-based health management platform are used to encrypt and upload pre-processed monitoring data to the cloud-based health management platform; the cloud-based health management platform is configured with: The coating degradation degree calculation module is used to determine the coating degradation degree based on the coating electrochemical parameters and the substrate corrosion parameters; The influence coefficient calculation module is used to determine the electromagnetic field influence coefficient based on the electromagnetic field parameters; and to determine the environmental corrosion correction coefficient based on the environmental parameters. The comprehensive evaluation module is used to calculate a comprehensive evaluation index based on the degree of coating degradation and the influence coefficient. The early warning decision module is used to compare the comprehensive evaluation index with the preset early warning threshold, determine the early warning level, and generate the coating health status evaluation result. The operation and maintenance management terminal is used to receive the coating health status assessment results, issue operation and maintenance instructions, and view monitoring data.

[0019] The technical solution of this invention achieves the following technical effects: By using the determination of the coating's own degradation characteristics as the main reference, while also taking into account the specific operating conditions of the power grid, the health status assessment of the coating is no longer divorced from the actual application environment of the power grid steel structure. This solves the limitations of existing anti-corrosion coating monitoring methods in power grid scenarios and enables targeted assessment of the health status of anti-corrosion coatings under power grid electromagnetic field conditions. Through the combination of the above steps, the generated coating health status assessment results can quantitatively reflect the degradation status of the anti-corrosion coating itself and clarify the degree of influence of power grid electromagnetic fields and environmental factors on the coating degradation process. Compared with existing monitoring methods that can only qualitatively determine coating degradation, the assessment results of this method include information dimensions that are more in line with the anti-corrosion operation and maintenance needs of power grid steel structures, enabling operation and maintenance personnel to understand the law of the effect of power grid operating conditions on coating degradation.

[0020] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

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

[0022] Figure 1 This is a flowchart illustrating the online monitoring method for quantitative early warning of anti-corrosion coatings on power grid steel structures based on multi-sensor fusion, as described in this invention. Figure 2 This is a structural diagram of the online monitoring system for quantitative early warning of anti-corrosion coatings on power grid steel structures based on multi-sensor fusion, as described in this invention. Detailed Implementation

[0023] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0024] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0025] like Figure 1 As shown, the present invention provides a multi-sensor fusion-based online monitoring method for quantitative early warning of anti-corrosion coatings on power grid steel structures, which specifically includes the following steps: Step S100: Deploy sensing components in the area to be monitored on the power grid steel structure and collect monitoring data, including coating electrochemical parameters, substrate corrosion parameters, environmental parameters and electromagnetic field parameters; Step S200: Determine the degree of coating degradation based on the coating electrochemical parameters and the substrate corrosion parameters; Step S300: Based on the environmental parameters, determine the environmental corrosion correction coefficient; based on the electromagnetic field parameters, determine the electromagnetic field influence coefficient. Step S400: Generate coating health status assessment results based on the coating degradation degree, the environmental corrosion correction coefficient, and the electromagnetic field influence coefficient.

[0026] In this embodiment, by incorporating the power grid frequency and harmonic electromagnetic field parameters into the monitoring data range, the degree of coating degradation is first determined based on the coating electrochemical and substrate corrosion parameters. Then, the electromagnetic field parameters are quantified into electromagnetic field influence coefficients, and the environmental parameters are quantified into environmental corrosion correction coefficients. Finally, the coating health status assessment results are generated by combining these parameters. Instead of simply superimposing various monitoring parameters, the influence of the electromagnetic field influence coefficient, environmental corrosion correction coefficient, and coating degradation degree is quantified and integrated. This system incorporates the influence of the power grid electromagnetic field and environmental parameters on coating degradation into the comprehensive assessment system of coating health status. This eliminates the assessment bias caused by ignoring the specific electromagnetic field conditions of the power grid from the assessment logic, enabling the assessment results to accurately reflect the true degradation state of the anti-corrosion coating under the actual operating conditions of the power grid. By primarily referencing the assessment of the coating's own degradation characteristics while also considering the specific operating conditions of the power grid, this method ensures that coating health status assessment is no longer divorced from the actual application environment of power grid steel structures. It overcomes the limitations of existing anti-corrosion coating monitoring methods in power grid scenarios, enabling targeted assessment of the health status of anti-corrosion coatings under power grid electromagnetic field conditions. Through the combination of these steps, the generated coating health status assessment results reflect the degradation state of the anti-corrosion coating itself and clarify the degree of influence of the power grid electromagnetic field on the coating degradation process. Compared to existing monitoring methods that can only determine the degree of coating degradation, this method's assessment results include information dimensions more closely aligned with the anti-corrosion operation and maintenance needs of power grid steel structures, allowing maintenance personnel to understand the influence of power grid operating conditions on coating degradation.

[0027] In a specific implementation, as an example of a 220kV transmission tower operating in a coastal C5-level corrosion environment, the steel structure base of the tower is made of Q345 steel and coated with a graphene-modified epoxy anti-corrosion coating. The monitoring area is selected in three high-risk corrosion zones: the middle section of the tower body, the end of the crossarm, and the root of the tower leg. These areas are prone to salt spray deposition, stress concentration, and significant changes in the electromagnetic field intensity of the power grid. The existing sensor deployment has problems such as the scattered arrangement of sensor units leading to spatial misalignment of the acquisition area, the installation methods of different sensor units not matching the structural characteristics of the monitored object, some installation operations damaging the original protective structure of the coating, and insufficient contact and adhesion between the sensor and the coating and substrate. This results in poor spatiotemporal matching of monitoring parameters, inability to directly acquire substrate corrosion parameters, and interference from spatial deviations in the acquisition of environmental and electromagnetic field parameters. This embodiment addresses the operating conditions and structural characteristics of high-risk corrosion zones in power grid steel structures. It designs a centralized, co-located deployment method for sensor units, matching the installation structure to the differences in the monitoring targets of each sensor unit. The specific implementation is as follows: Step S110: Mark a 5cm×5cm square centralized deployment area in each area to be monitored. The marking standard is that the coating surface of the deployment area is flat, undamaged, and free of stains, and is tightly bonded to the steel structure base without any hollow areas. After the marking is completed, degrease the coating surface of the deployment area with anhydrous ethanol, wipe it repeatedly twice until there is no floating dust or oil residue on the surface, and allow it to air dry naturally before proceeding with subsequent operations.

[0028] Step S120: The electrochemical impedance sensing unit adopts a three-electrode integrated structure. The working electrode material is the same as Q345 steel, and the sensitive surface area is 1 cm². 2 The measurement frequency range is 10 MHz to 10 kHz. The temperature, humidity, and salt spray sensing unit uses a surface-mount integrated structure, and the sensitive surface is treated with a polytetrafluoroethylene (PTFE) anti-salt spray hydrophobic coating to prevent salt spray deposition from covering the sensitive surface. The electromagnetic field sensing unit uses a miniature triaxial Hall structure with a measurement range of 0.01 mT to 50 mT and a frequency measurement range of 50 Hz to 1 MHz, suitable for the confined spaces of centralized deployment areas. The resistive corrosion sensing unit uses a metal thin-film structure made of the same material as Q345 steel, with a film thickness of 50 μm and a sensitive surface area of ​​0.8 cm². 2 The thickness direction of the sensitive surface is kept parallel to the interface of the coating substrate.

[0029] Step S130: At the geometric center of the calibrated centralized deployment area, a circular through-hole with a diameter of 3mm is opened using laser micro-cutting. The depth of the through-hole extends to the surface of the steel structure substrate. The laser power is controlled at 5W to avoid high-temperature burning of the substrate metal. The coating debris inside the through-hole is removed using a dust-free brush. The sensitive surface of the resistive corrosion sensing unit is tightly attached to the substrate surface. The sensor fixing end is welded to the substrate using spot welding. There are two welding points, which are symmetrically distributed. The welding current is controlled at 10A, and the welding time is 0.5s to prevent the sensor from being damaged by the high temperature of welding. After welding, the through-hole is filled in layers using graphene-modified epoxy repair adhesive of the same material as the coating of the area to be monitored. After filling, it is sanded with fine sandpaper until it is flush with the coating surface.

[0030] Step S140: The sensitive surfaces of the electrochemical impedance sensing unit, temperature and humidity salt spray sensing unit, and electromagnetic field sensing unit are brought into close contact with the coating surface of the centralized deployment area. The centers of the sensitive surfaces of the three sensing units coincide with the geometric center of the centralized deployment area, and the edge spacing between adjacent sensing units is no more than 1 cm. A two-component epoxy high-temperature resistant anti-corrosion adhesive is used for fixing. The adhesive is applied by dot coating with a thickness of 0.1-0.2 mm. The coating position is the edge area of ​​the non-sensitive surface of the sensor to avoid covering the sensitive surface with adhesive. The adhesive is cured at 25°C for 24 hours. After curing, the adhesion between the sensor and the coating surface is tested to ensure that the adhesion is not less than 5 MPa.

[0031] In step S150, each sensing unit is connected to the monitoring terminal via fluoroplastic sheathed shielded cables. The shielding layer of the shielded cable is grounded to suppress interference from the power grid's electromagnetic field on signal transmission. The connection between the cable and the sensor is double-sealed using 1mm thick heat shrink tubing. The shrinkage temperature of the heat shrink tubing is controlled at 120℃ to ensure that the sealing layer is gapless and wrinkle-free. All cables are laid along the surface of the steel structure of the tower and fixed with plastic cable ties at 50cm intervals to prevent damage to the connection points caused by the swaying of the cables due to sea wind.

[0032] Step S160: After completing the wiring, power on and debug each sensing unit, collect parameter signals under no-load conditions, and confirm that the signals are free of noise and drift and the values ​​are stable before completing the deployment of the sensing components. The monitoring terminal has a built-in high-precision real-time clock to provide a unified time reference for all sensing units. The acquisition trigger command is sent synchronously from the monitoring terminal to each sensing unit, with a command transmission delay of no more than 1ms, to ensure that the sampling start time of each sensing unit is synchronized. The electrochemical impedance sensing unit collects coating resistance, coating capacitance, charge transfer resistance, and low-frequency phase angle. The low-frequency phase angle is the phase angle of the electrochemical impedance spectrum of the anti-corrosion coating in its new state at the characteristic frequency of 10Hz, which is used to characterize the integrity of the coating substrate interface and the insulation performance of the coating medium. The resistive corrosion sensing unit collects the substrate corrosion thinning amount and corrosion rate. The temperature, humidity, and salt spray sensing unit collects the ambient relative humidity, temperature, salt spray deposition amount, and Cl. - The electromagnetic field sensing unit collects the electromagnetic field strength and frequency of the power grid's power frequency and harmonics. All collected parameters are accompanied by timestamps and corresponding monitoring point numbers to realize the spatiotemporal marking of the parameters.

[0033] In this embodiment, a fixed-size centralized deployment area is calibrated and pre-treated with degreasing to ensure complete spatial overlap of the acquisition areas of all sensing units. This eliminates parameter mismatch issues caused by spatial position deviations and ensures tight adhesion between the sensor sensitive surface and the coating surface. Each sensing unit is precisely matched to the power grid steel structure substrate material, the coastal high-salt-spray corrosion environment, and the power grid electromagnetic field conditions. Electrochemical impedance and resistive corrosion sensing units are made of the same material as the substrate, ensuring that the acquired parameters are synchronized with the characteristics of the actual coating substrate system, eliminating measurement deviations caused by material differences. The sensitive surfaces of the temperature, humidity, and salt spray sensing units are treated with anti-salt-spray hydrophobic treatment to prevent sensor failure in the coastal high-salt-spray environment. The electromagnetic field sensing unit adopts a miniature triaxial Hall structure, enabling installation in a small, centralized deployment area while simultaneously completing electromagnetic field measurements. The system achieves comprehensive intensity data acquisition, avoiding the omission of electromagnetic field parameters caused by single-axis acquisition. The resistive corrosion sensing unit utilizes a laser-embedded micro-cut through-hole method to minimize coating damage. Combined with repair adhesive of the same material as the original coating, it fully restores the coating's protective integrity, preventing the introduction of new corrosion risks during installation. The surface-adhesive sensing units feature overlapping sensitive surfaces, further enhancing spatial overlap of the acquisition area. The dot-coating adhesive application method prevents adhesive from covering the sensor's sensitive surface. Using the high-precision real-time clock of the monitoring terminal as a unified time reference, synchronous triggering commands ensure complete synchronization of sampling times for all sensing units. Combined with timestamps of parameters and monitoring point numbering, it achieves precise spatiotemporal matching of multiple monitoring parameters, eliminating subsequent data analysis errors caused by time deviations.

[0034] In a specific implementation, as one example, step S200 adopts the following implementation method: in-situ sub-point reference value calibration, real-time parameter validity verification, working condition adaptation weight allocation, and dimensionless multi-parameter ratio fusion calculation. The specific implementation process is as follows: Step S210: After the sensor components are deployed and powered on for testing, conduct in-situ calibration of the initial reference values ​​for the corresponding monitoring points. Calibration is performed during the daytime when there is no rain, the relative humidity is 40%–60%, and the ambient temperature is 20℃–25℃. During calibration, the test parameters for the electrochemical impedance spectroscopy unit are fixed as follows: excitation sinusoidal voltage amplitude 100mV, test frequency range 10mHz–10kHz, 50 frequency sampling points, integration time per frequency band 100ms, and the phase angle of the 10Hz characteristic frequency point is fixed as the low-frequency phase angle acquisition item to ensure the calibration data... The testing conditions were consistent with those for subsequent real-time monitoring data. Using the high-precision real-time clock of the monitoring terminal as a unified benchmark, the electrochemical impedance spectroscopy, resistive corrosion spectroscopy, and temperature, humidity, and salt spray spectroscopy units at the corresponding points were controlled to synchronously collect data. The sampling interval was set to 2 hours, with a continuous collection duration of 72 hours. 36 sets of raw data were acquired at each point. Outliers were removed from the collected raw data using the Grubbs criterion. After removing outliers with a significance level of 0.05, the arithmetic mean of the remaining valid data was taken as the initial benchmark value for that monitoring point. The specific definitions of each initial benchmark value are as follows: Initial reference value Rc0 for coating resistance: A reference for dimensionless ratio calculations, its physical meaning is the dielectric resistance of the anti-corrosion coating in its brand-new state, with dimensions in Ω·cm. 2 ; Initial reference value Cc0 for coating capacitance: A dimensionless reference for ratio calculation, physically representing the dielectric capacitance of the anti-corrosion coating in its brand-new state, with dimensions in F / cm. 2 ; Initial reference value for charge transfer resistance Rct0: A reference for dimensionless ratio calculations, physically representing the charge transfer resistance at the interface between the coating and the substrate in a brand-new state, with dimensions in Ω·cm. 2 ; Initial reference value ER0 for corrosion thinning: The reference value for the dimensionless ratio calculation. Its physical meaning is the minimum detectable corrosion thinning of the resistive corrosion sensing unit. The value is 10nm, and the dimension is nm. Environmental parameter baseline values: including temperature baseline value T0=25℃, relative humidity baseline value RH0=60%, salt spray deposition baseline value S0, Cl - The concentration baseline value is Cl0; where RH0, S0, and Cl0 are the arithmetic mean of environmental parameters collected synchronously at monitoring points for 72 consecutive hours within the calibration period, and S0 has the dimension of mg / m³. 2 •d, Cl0 has dimensions of mg / m 2•d serves as the reference standard for calculating the environmental corrosion correction factor.

[0035] Step S220: After completing the initial baseline calibration, the online monitoring phase begins, acquiring real-time monitoring values ​​at the corresponding monitoring points. The acquisition of real-time monitoring values ​​is perfectly matched to the synchronous triggering mechanism of step S100. The monitoring terminal synchronously sends acquisition commands to the electrochemical impedance spectroscopy (EIS) and resistive corrosion spectroscopy (RCS) units at the same monitoring point, ensuring complete synchronization of the acquisition timing of the two sets of parameters, and that the test parameters of the EIS unit are completely consistent with those in the initial calibration phase. The acquired real-time monitoring values ​​include the real-time coating resistance (Rc), coating capacitance (Cc), charge transfer resistance (Rct), corrosion thinning (ER), real-time ambient temperature (T), real-time relative humidity (RH), real-time salt spray deposition (S), and real-time Cl. - Concentration of Cl; The real-time value of corrosion thinning ER is the measured value of corrosion thinning of the steel structure substrate after temperature compensation. The specific temperature compensation correction formula is: ER = ER raw ×[1+α T [×(T-T0)], where ER raw The original acquired value of the resistive corrosion sensing unit, α T The temperature coefficient of resistance of Q345 steel is taken as 1.2 × 10⁻⁶. -5 / ℃, T is the ambient temperature collected in real time, and T0 is the reference temperature of 25℃ in the initial calibration stage. After correction, the interference of ambient temperature fluctuation on the metal thin film resistance measurement value is eliminated.

[0036] Step S230: Perform a validity check on the real-time monitoring values. The check rules are as follows: The first item is the verification of the validity of electrochemical parameters. Based on the change law of electrochemical parameters of graphene-modified epoxy coating from brand new to completely failed, two verification conditions are set: first, the phase angle of the real-time acquired electrochemical impedance spectrum at a frequency of 10 Hz is within the range of 5° to 85°; second, the real-time values ​​of Rc, Cc, and Rct are within the range of 0.01 times to 100 times the initial reference value of the corresponding point. If both conditions are met, the electrochemical parameters are judged to be valid; otherwise, they are judged as invalid data and will not be included in subsequent calculations. The second item is the validity verification of the substrate corrosion parameters. The real-time ER value after temperature compensation is compared with the converted value of the resistance change synchronously collected by the resistive corrosion sensing unit. If the relative deviation does not exceed 5%, the substrate corrosion parameters are deemed valid; otherwise, they are deemed invalid data and will not be included in subsequent calculations. The third item is the validity verification of environmental parameters, which sets two verification conditions: one is the real-time collection of temperature, relative humidity, salt spray deposition, and Cl. -The concentrations are all within the rated measurement range of the corresponding sensing unit; secondly, the relative deviation of each environmental parameter value collected synchronously for three consecutive times at the same location does not exceed 10%; if both conditions are met, the environmental parameter is deemed valid, otherwise it is deemed invalid data; for qualified environmental parameters, the sliding average of three consecutive collection values ​​is used to participate in the calculation of the environmental correction coefficient to avoid misjudgment caused by temporary environmental fluctuations due to a single extreme weather event.

[0037] Step S240: After verification, only data sets where both electrochemical parameters and substrate corrosion parameters are deemed valid during the same acquisition process are retained, and the coating degradation index calculation is then initiated. Preset weighting coefficients for the corresponding monitoring points are retrieved. These weighting coefficients are calibrated based on nearly 5 years of corrosion failure statistics for transmission towers in the same region, at the same voltage level, and with the same coating system. They are matched to the dominant corrosion factors at different points, and the sum of all weighting coefficients is always 1. Each weighting coefficient includes: α for the coating resistance ratio, representing the contribution of coating medium penetration degradation to the overall degradation level; β for the coating capacitance ratio, representing the contribution of coating water absorption aging degradation to the overall degradation level; γ for the charge transfer resistance ratio, representing the contribution of coating substrate interface peeling degradation to the overall degradation level; and δ for the corrosion thinning ratio, representing the contribution of steel structure substrate corrosion to the overall degradation level. Examples of weighting coefficient calibration values ​​for different monitoring points are as follows: Monitoring points at the end of the crossarm: α=0.35, β=0.25, γ=0.2, δ=0.2, suitable for working conditions where salt spray is easy to deposit and coating medium deterioration is the dominant factor in corrosion at this point; Monitoring points in the middle section of the tower: α=0.3, β=0.2, γ=0.25, δ=0.25, suitable for the working condition of balanced development of coating deterioration and substrate corrosion at this point; Monitoring points at the base of the tower legs: α=0.2, β=0.15, γ=0.25, δ=0.4, suitable for working conditions where water easily accumulates at this point and corrosion initiation at the base is the dominant corrosion factor.

[0038] Step S250: Based on the verified real-time monitoring values, the initial baseline values ​​of the corresponding points, and the preset weighting coefficients, calculate the dimensionless coating degradation index DI. The calculation formula is as follows: ; The calculated coating degradation index DI represents the current degree of degradation of the anti-corrosion coating at the monitoring point. The larger the DI value, the more severe the overall degradation of the coating. All ratio terms in the above formula are ratios of parameters with the same dimension, and are all dimensionless quantities. The weighting coefficients α, β, γ, and δ are all dimensionless constants, so the calculated DI is a dimensionless quantitative value. Since the coating resistance and charge transfer resistance decrease with coating degradation and interface peeling, the ratio of the initial reference value to the real-time value is used to characterize the degree of degradation. The coating capacitance and corrosion thinning increase with coating water absorption aging and substrate corrosion, so the ratio of the real-time value to the initial reference value is used to characterize the degree of degradation. The max(ER,ER0) method is used to ensure that when ER < ER0, the ratio is always 1, avoiding the logical contradiction of DI < 1, ensuring that DI = 1 corresponds to the anti-corrosion coating in a brand-new state, and that the DI value increases monotonically with the degree of degradation.

[0039] In this embodiment, the initial benchmark value calibration at the in-situ monitoring points eliminates the systematic deviation caused by the mismatch between the benchmark value and the actual coating state at the monitoring points. The benchmark value is fully compatible with the initial construction state and substrate characteristics of the coating at the corresponding points. Temperature compensation correction and dual-dimensional validity verification eliminate invalid data caused by strong electromagnetic interference from the power grid, ambient temperature fluctuations, and instantaneous environmental changes, avoiding misjudgments of the degree of degradation due to abnormal data participating in the calculation. The differentiated weight coefficient allocation for working condition adaptation matches the corrosion-dominant factors at different monitoring points of the tower, avoiding the dilution of the degradation characteristics of specific points by fixed weights, so that the calculated degradation index accurately reflects the actual degradation process of the corresponding points. The dimensionless degradation index calculation formula covers the entire chain of degradation process from coating medium water absorption and penetration, interface peeling, and substrate corrosion initiation, fully characterizing the actual degradation state of the anti-corrosion system.

[0040] In some embodiments of the present invention, the influence of electromagnetic field parameters is considered in the assessment of coating health status based on the quantitative correlation between the electromagnetic field of the power grid environment and the degradation process of the anti-corrosion coating. For example, the alternating electromagnetic field of the power grid frequency and harmonics destroys the dense polymer structure of the coating through polarization effect and accelerates the peeling of the coating interface and substrate corrosion through interface induced current. Moreover, the higher the electromagnetic field strength and the greater the proportion of harmonics, the more obvious the nonlinear accelerating effect on coating degradation. By synchronously collecting and quantifying the electromagnetic field parameters, the influence of power grid operating conditions on coating degradation can be corrected, and the assessment bias of existing methods can be eliminated. Therefore, step S300 adopts the implementation method of spatiotemporal synchronous acquisition, multi-band electromagnetic field parameter fusion, validity verification of measured values, calibration benchmark values ​​based on regulations and material properties, calculation of influence coefficients using the ratio method, and completion of degradation influence determination. The specific implementation process is as follows: Step S311: Using the high-precision real-time clock of the monitoring terminal as a unified time reference, control the electromagnetic field sensing unit to perform synchronous acquisition with the electrochemical impedance sensing unit and resistive corrosion sensing unit at the same location. The acquisition command is synchronously issued by the monitoring terminal, with a command transmission delay of no more than 1ms, ensuring that the electromagnetic field parameters completely correspond to the acquisition timestamps and monitoring point numbers of the coating electrochemical parameters and substrate corrosion parameters in step S200. The acquisition parameters of the electromagnetic field sensing unit are fixed as follows: frequency measurement range 50Hz~1MHz, covering the power grid frequency harmonic frequency band within 50Hz and 1MHz; magnetic field strength measurement range 0.01mT~50mT, completely consistent with the selection parameters of the sensing unit in step S100. During a single acquisition, the effective values ​​of the 50Hz power frequency electromagnetic field strength and the 3rd / 5th / 7th harmonic electromagnetic field strength are obtained respectively. The effective value E of the multi-band composite electromagnetic field strength is calculated by the root-sum-square method. The calculation formula is: ; Where E 50 The values ​​represent the effective values ​​of the power frequency electromagnetic field intensity. E3, E5, and E7 are the effective values ​​of the electromagnetic field intensity of the 3rd, 5th, and 7th harmonics, respectively. The effects of harmonic superposition are taken into account to reflect the electromagnetic field environment of the actual operation of the power grid.

[0041] Step S312: Pre-calibrate the safety electromagnetic field reference value E0. The calibration basis of the reference value is the electromagnetic aging resistance test data of the graphene modified epoxy anti-corrosion coating. The test environment is the maximum magnetic field strength under 1000h continuous electromagnetic field action without significant degradation of the dielectric properties of the coating. The calibration safety electromagnetic field reference value E0 = 0.1mT. After the reference value is calibrated, it is bound to the monitoring point number and stored, and remains unchanged throughout the entire monitoring cycle.

[0042] Step S313: After obtaining the effective value E of the measured synthetic electromagnetic field strength, first perform parameter validity verification. Two verification rules are set: the first is range verification, which determines that the measured E value is within the rated measurement range of 0.01mT~50mT of the electromagnetic field sensing unit; the second is stability verification, which determines that the relative deviation of the E value collected synchronously for three consecutive times at the same point does not exceed 10%. If both conditions are met, the measured E value is determined to be valid; otherwise, it is determined to be invalid data and will not participate in the subsequent influence coefficient calculation. Only the valid E value at the same time and location as the valid coating degradation parameter in step S200 is retained.

[0043] Step S314: After verification, calculate the electromagnetic field influence coefficient K. The calculation formula is: K=E / E0; E and E0 have the same dimensions in the formula, and the calculated K is a dimensionless constant. Based on the calculated electromagnetic field influence coefficient K, complete the judgment of the influence of the electromagnetic field on the coating degradation. The judgment rule is: when K>1, it is determined that the electromagnetic field accelerates the coating degradation; when K≤1, it is determined that the electromagnetic field has no significant effect on the coating degradation. Simultaneously, complete the degree of influence classification based on the K value. The classification rule is: when 1<K≤5, it is determined to be a slight acceleration; when K>5, it is determined to be a severe acceleration. The classification results are linked and stored with the coating degradation index of the corresponding monitoring point.

[0044] In this embodiment, the spatiotemporal acquisition design synchronized with the coating degradation parameters ensures that the electromagnetic field parameters are strictly matched with the coating degradation state at the corresponding time and location, and that the two have a direct correlation, thus solving the problem of inaccurate correlation analysis caused by the spatiotemporal misalignment of existing technical parameters. The calculation method of multi-band synthetic electromagnetic field intensity considers the superposition effect of power grid harmonics, closely matches the actual electromagnetic field environment of transmission towers, and avoids the problem of underestimating the degree of influence caused by using only power frequency values. The dual-dimensional validity verification eliminates abnormal data caused by instantaneous electromagnetic pulses. Based on the safety benchmark value calibrated by the coating material aging test, it has clear engineering test basis, and the calculated influence coefficient can directly guide on-site operation and maintenance, rather than being a theoretical value without basis.

[0045] Based on the aforementioned environmental parameters, the environmental corrosion correction coefficient for the corresponding monitoring point is calculated. The specific implementation process is as follows: Step S321: For the real-time monitoring values ​​of the synchronously collected environmental parameters, perform the same validity verification rules as in step S230, and retain only the moving average values ​​of valid environmental parameters that are in the same sequence and at the same location as the valid initial coating degradation index in S200.

[0046] Step S322: Retrieve the preset weighting coefficients of environmental parameters for the corresponding monitoring points. The weighting coefficients are calibrated based on the corrosion failure statistics of transmission towers in the same region, with the same voltage level and the same coating system over the past 5 years, matching the dominant environmental corrosion factors at different points. The sum of all weighting coefficients is always 1. Each weighting coefficient includes: the weighting coefficient ω corresponding to the temperature ratio item. T The weighting coefficient ω corresponding to the relative humidity ratio term RH The weighting coefficient ω corresponding to the salt spray deposition ratio term S Cl - The weighting coefficient ω corresponding to the concentration ratio term Cl Among them, the amount of salt spray deposition is related to Cl. -Although the two parameters, concentration and concentration, are somewhat correlated, they correspond to different stages and failure modes during coating degradation, thus avoiding double counting. Salt spray deposition characterizes the long-term cumulative effect of total salt content in the atmosphere, mainly corresponding to the overall water absorption and media penetration aging of the coating polymer system, and is the main environmental factor causing the overall performance degradation of the coating throughout its life cycle; Cl - Concentration characterizes the deposition level of reactive chloride ions in the atmosphere, mainly corresponding to anion adsorption and interfacial delamination at the coating-substrate interface, as well as the pitting corrosion initiation and propagation of the steel structure substrate. It is the core cause of localized coating damage and sudden corrosion of the substrate. The two parameters cover the two dimensions of overall coating aging and localized failure, respectively. Through differentiated weight allocation, it can adapt to the corrosion risk of different monitoring points. Specifically, the weight coefficient calibration values ​​for different monitoring points are as follows: Crossarm end monitoring point: ω T =0.1、ω RH =0.2、ω S =0.3、ω Cl =0.4, matching the working conditions at this location where salt spray is prone to deposition and chloride ion enrichment is the dominant environmental corrosion factor; Monitoring points in the middle section of the tower: ω T =0.15、ω RH =0.35、ω S =0.25、ω Cl =0.25, matching the working condition where temperature and humidity fluctuations at this location are the dominant environmental corrosion factors; Monitoring points at the base of the tower leg: ω T =0.1、ω RH =0.4、ω S =0.2、ω Cl =0.3, matching the working condition where high humidity and water accumulation at this location are the dominant environmental corrosion factors.

[0047] Step S323: Based on the verified moving average of environmental parameters, the initial baseline value of the corresponding point, and the preset environmental weight coefficient, calculate the dimensionless environmental corrosion correction coefficient. The calculation formula is as follows: Where F represents the environmental corrosion correction factor, T0 represents the initial baseline temperature; T represents the real-time sliding average temperature; RH0 represents the initial baseline relative humidity; RH represents the real-time sliding average relative humidity; S0 represents the initial baseline salt spray deposition; S represents the real-time sliding average salt spray deposition; Cl0 represents Cl - Initial concentration reference value; Cl represents Cl - Real-time moving average of concentration; In the formula for calculating the environmental corrosion correction coefficient, when the real-time value of the environmental parameter is lower than or equal to the initial reference value, the corresponding max function term is 0, and this term makes no additional contribution to the correction coefficient. The environmental corrosion correction coefficient F=1, indicating that the current environmental conditions have no additional corrosion acceleration effect compared to the calibrated reference conditions. When the real-time value of the environmental parameter is higher than the initial reference value, the corresponding term contributes a positive increment according to a preset weight. The larger the value of F, the more significant the accelerating effect of environmental factors on coating degradation. When the environmental corrosion correction coefficient F>1, it is determined that environmental factors accelerate coating degradation. When F=1, it is determined that the environmental conditions are consistent with the reference state and have no significant accelerating effect on coating degradation. Through this formula, the degree of corrosion acceleration when the environmental conditions deviate from the reference state can be accurately quantified.

[0048] In some embodiments of the present invention, step S400 adopts a method of coupled correction calculation of comprehensive evaluation index, calibration of graded early warning threshold for working condition adaptation, determination of deterioration cause tracing, matching of early warning level and output of evaluation results. The specific implementation process is as follows: Step S410: Retrieve valid basic data of the same time sequence from the corresponding monitoring point. The basic data includes the dimensionless coating degradation index DI obtained in step S200, the electromagnetic field influence coefficient K obtained in step S300, and the environmental corrosion correction coefficient F. All retrieved basic data are bound to the same collection timestamp and the unique number of the monitoring point. Only data groups in which DI, K, and F are all determined to be valid are retained and enter this calculation step.

[0049] Step S420: Based on the retrieved valid basic data, calculate the dimensionless comprehensive evaluation index DI'. The calculation formula is as follows: DI' = DI × F × K λ ; Wherein, λ is the electromagnetic field influence weighting coefficient, a dimensionless constant, calibrated based on the operating characteristics of the corresponding monitoring points. The calibration basis is the corrosion failure statistics of transmission towers in the same region, with the same voltage level and the same coating system over the past 5 years, matching the degree of influence of electromagnetic fields on coating deterioration at different points; the calibrated value of λ is different for different monitoring points. For example, λ=0.2 for the monitoring point at the end of the crossarm, λ=0.15 for the monitoring point in the middle section of the tower body, and λ=0.1 for the monitoring point at the root of the tower leg. This formula enables a multi-sensor deep fusion quantitative evaluation of coating degradation characteristics, environmental corrosion acceleration effects, and electromagnetic field acceleration effects; when K≤1, K λ ≈1, which has no significant corrective effect on the comprehensive evaluation index, and is completely consistent with the judgment rule in step S300 that when K≤1, the electromagnetic field has no significant effect on coating degradation; when K>1, the nonlinear accelerating effect of the electromagnetic field on coating degradation is reflected by power correction, which is in line with the law that the higher the electromagnetic field strength, the more significant the degradation acceleration effect under the actual working conditions of the power grid.

[0050] Step S430: Pre-calibrate the graded early warning thresholds that are compatible with the operating conditions of the monitoring points. The threshold calibration is based on the corrosion failure statistics of the same type of power grid steel structure in the same area and the coating life-cycle deterioration test data. The early warning thresholds are set as follows: DI'∈[1,1.5) corresponds to mild aging, DI'∈[1.5,2.5) corresponds to medium risk, and DI'≥2.5 corresponds to emergency warning. The thresholds are bound to the corresponding monitoring point numbers and stored. They can be calibrated according to the service life of the coating and changes in the regional corrosion environment throughout the entire monitoring cycle.

[0051] Step S440: Compare the calculated comprehensive evaluation index with the corresponding monitoring point's graded early warning threshold to determine the corresponding early warning level; simultaneously complete the source determination of deterioration causes, with the determination rules corresponding one-to-one with the basic data. The specific source determination of deterioration causes includes the following three determination rules. Single-factor-driven degradation determination: If DI≥1.2, F=1, K≤1, the degradation is determined to be caused by the coating's natural aging, without any additional accelerating effect from the environment or electromagnetic fields. If DI < 1.2, F > 1.2, and K ≤ 1, the degradation is determined to be caused by accelerated environmental corrosion. Further investigation can be conducted based on the weighted proportions of environmental parameters to trace the source back to Cl. - Concentration-driven, salt spray deposition-driven, or temperature and humidity fluctuation-driven; If DI < 1.2, F = 1, and K > 5, the degradation is determined to be caused by the electromagnetic field accelerating the degradation, without the additional effects of coating aging or environmental corrosion.

[0052] Two-factor synergistic degradation determination: If DI≥1.2, F>1, and K≤1, the degradation is determined to be caused by the synergistic effect of coating aging and environmental corrosion. When DI≥1.5 and 1<F≤1.2, the primary cause is the natural aging of the coating itself, and the secondary cause is a slight acceleration due to environmental factors. When 1.2≤DI<1.5 and F>1.2, the primary cause is accelerated environmental corrosion, and the secondary cause is the aging of the coating itself. If DI≥1.2, F=1, and K>1, the degradation is determined to be caused by the combined effect of coating aging and electromagnetic field acceleration. When DI≥1.5 and 1<K≤5, the primary cause is the natural aging of the coating, and the secondary cause is the slight acceleration of the electromagnetic field. When 1.2≤DI<1.5 and K>5, the primary cause is the severe acceleration of the electromagnetic field, and the secondary cause is the aging of the coating. If DI < 1.2, F > 1, and K > 1, the degradation is determined to be caused by the synergistic effect of environmental corrosion and electromagnetic field acceleration. When F > 1.2 and 1 < K ≤ 5, the primary cause is accelerated environmental corrosion, and the secondary cause is slight acceleration of the electromagnetic field. When 1 < F ≤ 1.2 and K > 5, the primary cause is severe acceleration of the electromagnetic field, and the secondary cause is accelerated environmental corrosion.

[0053] Three-factor synergistic degradation determination: If DI ≥ 1.2, F > 1, and K > 1, the degradation is determined to be caused by the combined effects of coating aging, accelerated environmental corrosion, and accelerated electromagnetic field action. Simultaneously, based on the deviations of DI, F, and K values, the primary and secondary causes are identified. When the deviation of DI is the highest (DI≥1.5, F≤1.5, K≤5), the main cause is the natural aging of the coating itself, and the secondary cause is the accelerated effect of environmental corrosion and electromagnetic field superposition. When the deviation of F is the highest (F>1.5, DI≤1.5, K≤5), the main cause is accelerated environmental corrosion, and the secondary cause is accelerated coating aging and electromagnetic field superposition. When the deviation of K is the highest (K>5, DI≤1.5, F≤1.5), the main cause is the severe acceleration of the electromagnetic field, and the secondary cause is the combined acceleration of coating aging and environmental corrosion.

[0054] Step S450: Generate coating health status assessment results. The assessment results include monitoring point number, collection timestamp, comprehensive assessment index value, corresponding warning level, deterioration cause determination result, and original parameter traceability information. The assessment results are stored in association with the historical monitoring data of the corresponding monitoring points and pushed synchronously to the operation and maintenance management terminal.

[0055] In this embodiment, a comprehensive evaluation index is calculated based on the power-law coupling correction of the coating degradation index and the electromagnetic field influence coefficient. This aligns with the nonlinear acceleration law of electromagnetic field on coating degradation under power grid operating conditions, solving the problem that the evaluation results caused by simple superposition in existing technologies do not match the actual health status of the coating. The operating condition-adapted graded early warning threshold matches the differences in corrosion-dominant factors and electromagnetic field environments at different monitoring points, avoiding the problems of delayed early warnings in high-risk areas and false early warnings in low-risk areas. The evaluation results are bound to timestamps, point numbers, and original parameters, providing complete traceability and meeting the requirements of full life-cycle management of power grid equipment.

[0056] As a preferred embodiment of the above, for the power grid steel structure equipped with a sacrificial anode cathodic protection system, a coupled correction of the comprehensive evaluation index using a cathodic protection correction coefficient is adopted. The specific implementation method is as follows: In this embodiment, the self-corrosion potential is denoted as OCP, with units of V; the cathodic protection correction coefficient is denoted as ε, a dimensionless constant; the first potential threshold is calibrated as -0.85V, and the second potential threshold is calibrated as -0.78V, determined based on the cathodic protection effectiveness criterion for the steel substrate; the first value is 0.8, the second value is 1.0, and the third value is 1.2, matching the superimposed influence law of cathodic protection effect and coating degradation; the comprehensive evaluation index DI' is calculated in step S420, and the warning level and degradation cause tracing results are determined in step S440. The specific implementation includes the following steps: Step T1: The open-circuit potential sensing unit uses a silver / silver chloride reference electrode. The sensitive end is electrically connected to the steel structure substrate of the iron tower through a conductive contact. The reference electrode is arranged close to the coating surface, forming a closed potential monitoring loop with the sacrificial anode and the steel structure substrate. The sensing unit is deployed together with the electrochemical impedance, electromagnetic field, and resistive corrosion sensing units at the same location, with an installation spacing of ≤5cm. Using the high-precision real-time clock of the monitoring terminal as a unified reference, the open-circuit potential sensing unit and the other sensing units receive synchronous acquisition commands. The command transmission delay does not exceed 1ms, ensuring that the cathodic protection potential parameters correspond completely with the acquisition timestamps and monitoring point numbers of the coating electrochemical, substrate corrosion, and electromagnetic field parameters. The acquired raw potential data is recorded as OCP. raw This serves as the basis for data on self-corrosion potential.

[0057] Step T2: Process the collected OCP raw Perform a two-level validity check. The first level is the range check, which determines OC (Out of Target) status. Praw Within the rated measurement range of the open-circuit potential sensing unit (-1.5V to +0.5V), data exceeding this range is considered invalid. The second stage is stability verification, which involves retrieving five consecutive synchronously acquired OCP data from the same location. raw Calculate their arithmetic mean to determine a single OCP. raw The relative deviation from the average value should not exceed 3%. If the deviation exceeds the limit, it is considered invalid data due to poor contact of the reference electrode. After both levels of verification are satisfied, the OCP will be... raw The effective self-corrosion potential (OCP) is determined. Potential data that fails the verification is discarded and will not be included in the subsequent correction coefficient calculation. Only the effective OCP values ​​that are in the same sequence and at the same location as the coating degradation and electromagnetic field parameters are retained.

[0058] Step T3: Based on the cathodic protection effectiveness criteria for steel substrates, and combined with the cathodic protection compatibility test data of Q345 steel in a coastal C5 salt spray environment, calibrate the cathodic protection potential judgment threshold, with the first potential threshold T... O1 =-0.85V, which is the critical potential for good cathodic protection of Q345 steel under this working condition; the second potential threshold T O2 =-0.78V, which is the critical potential for cathodic protection failure of Q345 steel under this working condition; the threshold is stored in conjunction with the monitoring point number, and can be finely adjusted by ±0.02V according to the changes in coastal salt spray concentration throughout the entire monitoring cycle to ensure compatibility with the on-site corrosion conditions.

[0059] Step T4: Compare the effective self-corrosion potential OCP with the calibrated potential threshold, and determine the corresponding cathodic protection correction coefficient ε according to the preset rules. The judgment and matching rules are: when OCP < T O1 When T is reached, the cathodic protection effect is determined to be good, and the first matching value ε = 0.8; when T O1 ≤OCP<TO2 When the cathodic protection effect is insufficient, the second value ε is matched to 1.0; when OCP ≥ T O2 When the cathodic protection fails, the third value ε=1.2 is matched; the correction coefficient ε is bound to the corresponding OCP value, monitoring point number, and collection timestamp to ensure spatiotemporal matching with the comprehensive evaluation index DI'.

[0060] Step T5: Retrieve the comprehensive evaluation index DI' that matches ε in time and space, and calculate the corrected comprehensive evaluation index DI''. The calculation formula is DI'' = DI' × ε, where DI' and ε are dimensionless numbers, and the calculated DI'' is also dimensionless. The formula logic matches the inhibition law of cathodic protection effect on coating degradation. When the cathodic protection effect is good, ε = 0.8, and a reduction correction is made to the comprehensive evaluation index to reflect the inhibition effect of cathodic protection on coating degradation and electromagnetic field acceleration. When the cathodic protection effect is insufficient, ε = 1.0, and no reduction correction is made. When the cathodic protection fails, ε = 1.2, and an amplification correction is made to characterize the superimposed promoting effect of cathodic protection failure on coating degradation and electromagnetic field acceleration.

[0061] Step T6: Re-compare the revised comprehensive evaluation index DI'' with the corresponding monitoring point's graded early warning threshold. Based on the comparison results, the early warning level is revised synchronously. The revision rule is: if DI'' crosses the threshold range, the early warning level is matched according to the new range; if DI'' does not cross the threshold range, the original early warning level is retained. At the same time, the source tracing results of deterioration causes are supplemented and revised based on the value of ε. The supplementary judgment rule is: when ε=1.2 and K>1, the cause judgment of cathodic protection failure and electromagnetic field acceleration synergistically promoting coating deterioration is added to the original source tracing results; when ε=1.2 and K≤1, the cause judgment of cathodic protection failure as the main promoting factor of coating deterioration is added to the original source tracing results; when ε=0.8 or ε=1.0, the original source tracing results are retained, and only the cathodic protection effect status is supplemented.

[0062] Step T7: Generate the coating health status assessment results after cathodic protection correction: Based on the corrected comprehensive assessment index DI'', warning level, and deterioration cause tracing results, generate complete corrected assessment results. The assessment results add the following to the original output items: effective self-corrosion potential OCP value, cathodic protection effect judgment result, cathodic protection correction coefficient ε value, and corrected comprehensive assessment index DI'' value. All new items are stored in association with the original potential data and previous calculation data, and the corrected assessment results are synchronously pushed to the operation and maintenance management terminal.

[0063] In this embodiment, the centralized deployment and synchronous acquisition design of the open-circuit potential sensing unit and other sensing units ensures strict spatiotemporal matching between cathodic protection potential parameters and coating degradation and electromagnetic field parameters. Two-level validity verification of the cathodic protection potential parameters quantitatively eliminates invalid data caused by over-range data from sensing units and poor contact with the reference electrode, preventing correction deviations caused by abnormal potential data participating in correction coefficient calculations. The cathodic protection potential threshold is calibrated based on the cathodic protection criteria for steel substrates combined with adaptability test data from coastal C5-level corrosion conditions, ensuring that the threshold determination results match the cathodic protection effect of the Q345 steel substrate of the iron tower. The values ​​of the cathodic protection correction coefficients correspond one-to-one with the cathodic protection effect, and the numerical design closely matches the inhibition / promotion law of the cathodic protection effect on coating degradation and electromagnetic field acceleration. The correction model adopts a direct coupling calculation method, with logic matching the field conditions. Synchronous correction of the comprehensive evaluation index, early warning level, and degradation cause tracing results achieves an upgrade from single-factor correction to multi-dimensional collaborative correction, avoiding the problem of early warning levels and cause determinations being out of sync with actual conditions due to only correcting the index.

[0064] Based on the same inventive concept as the multi-sensor fusion method for quantitative early warning online monitoring of anti-corrosion coatings on power grid steel structures described in the foregoing embodiments, this invention also provides a multi-sensor fusion system for quantitative early warning online monitoring of anti-corrosion coatings on power grid steel structures, such as... Figure 2 As shown, the system includes: The multi-sensor fusion component is deployed at fixed monitoring points within the designated area of ​​the power grid steel structure to be monitored. It is wired to the monitoring terminal via shielded cable for synchronous data acquisition. The multi-sensor fusion component integrates at least an electrochemical impedance sensing unit, a resistive corrosion sensing unit, a temperature, humidity, and salt spray sensing unit, and an electromagnetic field sensing unit. The acquisition area of ​​all sensing units completely covers the fixed monitoring points.

[0065] The monitoring terminal serves as the core of the system's edge processing, employing an ARM Cortex-M4 low-power core processor and a solar power module consisting of a 5W flexible solar panel and a 12000mAh lithium iron phosphate battery. It also features a built-in local data cache. The monitoring terminal is wired to the multi-sensor fusion component via a shielded cable and includes a built-in synchronization trigger module and a preprocessing module. The synchronization trigger module synchronously sends acquisition commands to all sensor units of the multi-sensor fusion component, with a command transmission delay of no more than 1ms, ensuring complete synchronization of the sampling start time of all sensor units. The preprocessing module performs median filtering for noise reduction, outlier removal, and multi-parameter spatiotemporal matching binding on the acquired monitoring data. The preprocessed data is stored in the local cache and simultaneously pushed to the low-power wireless transmission module.

[0066] The low-power wireless transmission module communicates with the monitoring terminal and supports NB-IoT, LoRa, and 4G wireless communication modes. It has a built-in AES encryption chip to encrypt the pre-processed monitoring data before uploading it to the cloud-based health management platform. The communication mode is adaptively adapted to the deployment scenario. The NB-IoT communication mode is used in the high-altitude power transmission tower scenario, while the LoRa local networking combined with 4G uplink communication mode is used in the substation architecture scenario, adapting to the communication needs of different power grid scenarios.

[0067] The cloud-based health management platform is the core of the system's processing layer. It connects with the low-power wireless transmission module via mobile internet to receive encrypted and uploaded monitoring data and then decrypt and store it. The platform is equipped with a data storage unit, a coating degradation degree calculation module, an electromagnetic field influence coefficient calculation module, a comprehensive evaluation module, and an early warning decision module. The system comprises several modules: a data storage unit for storing full monitoring data, initial baseline parameters of the coating in its new state, preset warning thresholds, historical assessment results, and model configuration parameters; a built-in coating degradation index calculation model with core operational logic fully matched to the coating degradation degree calculation module; a coating degradation degree calculation module for calculating a dimensionless coating degradation index based on decrypted coating electrochemical parameters and substrate corrosion parameters, combined with pre-stored initial baseline values, to determine the degree of coating degradation; an electromagnetic field influence coefficient calculation module for calculating a dimensionless electromagnetic field influence coefficient based on decrypted electromagnetic field parameters, combined with pre-stored safe electromagnetic field baseline values, to determine the degree of electromagnetic field influence on coating degradation; a comprehensive assessment module for calculating a dimensionless comprehensive assessment index based on the coating degradation index and electromagnetic field influence coefficient corresponding to the degree of coating degradation, through power-law coupling correction; and a warning decision module for comparing the calculated comprehensive assessment index with preset graded warning thresholds, matching and determining the corresponding warning level, simultaneously determining the source of degradation causes, and finally generating a complete coating health status assessment result. For scenarios with supporting cathodic protection systems, the platform adds a cathodic protection correction unit, which is used to determine the cathodic protection correction coefficient based on the collected cathodic protection potential parameters, correct the comprehensive evaluation index, and adjust the corresponding early warning threshold simultaneously.

[0068] The operation and maintenance management terminal is connected to the cloud-based health management platform via Ethernet / mobile internet communication. It includes three types of terminal devices: a PC-based monitoring platform, a mobile operation and maintenance APP, and an early warning information receiving terminal. The PC-based monitoring platform is used for centralized viewing of monitoring data across the entire site, historical data backtracking, model parameter configuration, and centralized issuance of operation and maintenance instructions. The mobile operation and maintenance APP is used for real-time data viewing, early warning information reception, and on-site handling reporting during on-site inspections. The early warning information receiving terminal is used for SMS push of graded early warning information. The operation and maintenance management terminal can fully receive the coating health status assessment results and graded early warning information pushed by the cloud platform, and can also issue operation and maintenance instructions such as parameter configuration and sampling strategy adjustment to the cloud platform and monitoring terminal.

[0069] The system described above in this invention can effectively realize a multi-sensor fusion-based online monitoring method for quantitative early warning of anti-corrosion coatings on power grid steel structures. The technical effects it can achieve are as described in the above embodiments, and will not be repeated here.

[0070] Although this application has been described in conjunction with specific features and embodiments, it is obvious that various modifications and combinations can be made thereto without departing from the spirit and scope of this application. Accordingly, this specification and accompanying drawings are merely exemplary illustrations of the application as defined herein, and are to be considered as covering any and all modifications, variations, combinations, or equivalents within the scope of this application. Clearly, those skilled in the art can make various alterations and modifications to this application without departing from its scope. Thus, if such modifications and modifications fall within the scope of this application and its equivalents, this application intends to include such modifications and modifications.

Claims

1. A multi-sensor fusion method for quantitative early warning online monitoring of anti-corrosion coatings on power grid steel structures, characterized in that, include: Sensing components are deployed in the monitoring area of ​​the power grid steel structure to collect monitoring data. The monitoring data includes coating electrochemical parameters, substrate corrosion parameters, environmental parameters, and electromagnetic field parameters. The coating electrochemical parameters include at least one of coating resistance, coating capacitance, charge transfer resistance, and low-frequency phase angle. The substrate corrosion parameters include at least one of metal substrate corrosion thinning and corrosion rate. The environmental parameters include relative humidity, temperature, salt spray deposition, and Cl-. - At least one of the concentrations; the electromagnetic field parameters include at least one of electromagnetic field strength and frequency; The degree of coating degradation is determined based on the coating electrochemical parameters and the substrate corrosion parameters. Based on the aforementioned environmental parameters, determine the environmental corrosion correction coefficient; Based on the electromagnetic field parameters, the electromagnetic field influence coefficient is determined, including: obtaining the measured electromagnetic field strength, wherein the measured electromagnetic field strength is the effective value of the measured multi-band synthesized electromagnetic field strength, and the calculation formula is: ； Where E is the measured electromagnetic field strength; E 50 E3, E5, and E7 are the effective values ​​of the electromagnetic field intensity at a 50Hz power frequency, and the effective values ​​of the electromagnetic field intensity of the 3rd, 5th, and 7th harmonics, respectively. The electromagnetic field influence coefficient K is calculated using the formula: K = E / E0; where E0 is the pre-calibrated safe electromagnetic field reference value. Based on the degree of coating degradation, the environmental corrosion correction coefficient, and the electromagnetic field influence coefficient, a coating health status assessment result is generated.

2. The online monitoring method for quantitative early warning of anti-corrosion coatings on power grid steel structures using multi-sensor fusion as described in claim 1, characterized in that, The sensing components include at least an electrochemical impedance sensing unit, a resistive corrosion sensing unit, a temperature and humidity salt spray sensing unit, and an electromagnetic field sensing unit. All sensing units are centrally deployed at the same monitoring point, so that the acquisition areas of each sensing unit overlap spatially.

3. The online monitoring method for quantitative early warning of anti-corrosion coatings on power grid steel structures using multi-sensor fusion as described in claim 2, characterized in that, Based on the electrochemical parameters of the coating and the corrosion parameters of the substrate, the degree of coating degradation is determined, including: Obtain the initial baseline values ​​and real-time monitoring values ​​of the electrochemical parameters of the coating; Obtain the initial baseline values ​​and real-time monitoring values ​​of the substrate corrosion parameters; The coating degradation index is calculated based on the ratio between the initial baseline value and the real-time monitoring value, and is used to characterize the degree of coating degradation.

4. The online monitoring method for quantitative early warning of anti-corrosion coatings on power grid steel structures using multi-sensor fusion as described in claim 3, characterized in that, Based on the aforementioned environmental parameters, the environmental corrosion correction factor is determined, including: Obtain initial baseline values ​​and real-time monitoring values ​​for each environmental parameter; Based on the ratio of the real-time monitoring value of each environmental parameter to the initial baseline value, and combined with the preset environmental weighting coefficient, the environmental corrosion correction coefficient is calculated. When the environmental corrosion correction coefficient is greater than 1, it is determined that environmental factors accelerate coating deterioration; When the environmental corrosion correction coefficient is less than or equal to 1, it is determined that environmental factors have no significant accelerating effect on coating deterioration.

5. The online monitoring method for quantitative early warning of anti-corrosion coatings on power grid steel structures using multi-sensor fusion as described in claim 4, characterized in that, Based on the electromagnetic field parameters, the electromagnetic field influence coefficient is determined, including: Obtain measured electromagnetic field strength and safety electromagnetic field reference values; The electromagnetic field influence coefficient is obtained by calculating the ratio of the measured electromagnetic field strength to the safe electromagnetic field reference value. When the electromagnetic field influence coefficient is greater than 1, it is determined that the electromagnetic field accelerates the deterioration of the coating. When the electromagnetic field influence coefficient is less than or equal to 1, it is determined that the electromagnetic field has no significant effect on coating degradation.

6. The online monitoring method for quantitative early warning of anti-corrosion coatings on power grid steel structures using multi-sensor fusion as described in claim 1, characterized in that, The monitoring data also includes cathodic protection potential parameters; the method further includes: Based on the aforementioned cathodic protection potential parameters, determine the cathodic protection correction coefficient; The coating health status assessment results are corrected based on the cathodic protection correction factor.

7. The online monitoring method for quantitative early warning of anti-corrosion coatings on power grid steel structures using multi-sensor fusion as described in claim 6, characterized in that, The sensing component also includes an open-circuit potential sensing unit, which is electrically connected to the coating damage area or steel structure substrate through a conductive contact, and is used to collect cathodic protection potential parameters.

8. The online monitoring method for quantitative early warning of anti-corrosion coatings on power grid steel structures using multi-sensor fusion as described in claim 7, characterized in that, The determination of the cathodic protection correction coefficient based on the cathodic protection potential parameters includes: When the self-corrosion potential is less than the first potential threshold, the cathodic protection correction coefficient is determined to be the first value; When the self-corrosion potential is greater than or equal to the first potential threshold and less than the second potential threshold, the cathodic protection correction coefficient is determined to be the second value. When the self-corrosion potential is greater than or equal to the second potential threshold, the cathodic protection correction coefficient is determined to be the third value; Wherein, the first value is less than the second value, and the second value is less than the third value.

9. The online monitoring method for quantitative early warning of anti-corrosion coatings on power grid steel structures using multi-sensor fusion as described in claim 5, characterized in that, Based on the coating degradation degree, the environmental corrosion correction coefficient, and the electromagnetic field influence coefficient, a coating health status assessment result is generated, including: A comprehensive evaluation index is calculated based on the degree of coating degradation, the environmental corrosion correction coefficient, and the electromagnetic field influence coefficient. The comprehensive evaluation index is compared with a preset early warning threshold; Based on the comparison results, a warning level is determined, which includes mild aging, moderate risk, and emergency warning.

10. The online monitoring method for quantitative early warning of anti-corrosion coatings on power grid steel structures using multi-sensor fusion according to claim 3, characterized in that, The formula for calculating the coating degradation index is as follows: ； Wherein, DI represents the coating degradation index; Rc0 is the initial reference value of coating resistance, and Rc is the real-time value of coating resistance; Cc0 is the initial reference value of coating capacitance, and Cc is the real-time value of coating capacitance; Rct0 is the initial reference value of charge transfer resistance, and Rct is the real-time value of charge transfer resistance; ER0 is the initial reference value of corrosion thinning, and ER is the real-time value of corrosion thinning; α, β, γ, and δ represent the weighting coefficients corresponding to the coating resistance ratio, coating capacitance ratio, charge transfer resistance ratio, and corrosion thinning ratio, respectively.

11. A multi-sensor fusion-based online monitoring system for quantitative early warning of anti-corrosion coatings on power grid steel structures, wherein the system is applied to the multi-sensor fusion-based online monitoring method for quantitative early warning of anti-corrosion coatings on power grid steel structures as described in claim 1, characterized in that... The system includes: A multi-sensor fusion component is deployed in the area to be monitored on the steel structure of the power grid to collect monitoring data including coating electrochemical parameters, substrate corrosion parameters, environmental parameters and electromagnetic field parameters; The monitoring terminal is connected to the multi-sensor fusion component via wired or wireless connection and is used to perform preprocessing operations on the collected monitoring data. A low-power wireless transmission module and a cloud-based health management platform are used to encrypt and upload pre-processed monitoring data to the cloud-based health management platform; the cloud-based health management platform is configured with: The coating degradation degree calculation module is used to determine the coating degradation degree based on the coating electrochemical parameters and the substrate corrosion parameters; The influence coefficient calculation module is used to determine the electromagnetic field influence coefficient based on the electromagnetic field parameters; and to determine the environmental corrosion correction coefficient based on the environmental parameters. The comprehensive evaluation module is used to calculate a comprehensive evaluation index based on the degree of coating degradation and the influence coefficient. The early warning decision module is used to compare the comprehensive evaluation index with the preset early warning threshold, determine the early warning level, and generate the coating health status evaluation result. The operation and maintenance management terminal is used to receive the coating health status assessment results, issue operation and maintenance instructions, and view monitoring data.

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