Suspension bridge main cable dehumidification system and method based on distributed humidity monitoring

Abstract

The invention discloses a suspension bridge main cable dehumidification system and dehumidification method based on distributed humidity monitoring, and belongs to the field of suspension bridge main cable humidity monitoring and dehumidification. The suspension bridge main cable dehumidification system comprises a three-dimensional humidity monitoring network, an optical fiber demodulator, an intelligent control module and a distributed dehumidification module which are implanted or embedded into a suspension bridge main cable; the three-dimensional humidity monitoring network is electrically connected with the optical fiber demodulator through an outgoing line, the optical fiber demodulator is electrically connected with the input end of the intelligent control module, and the output end of the intelligent control module is connected with the distributed dehumidification module. By the adoption of the suspension bridge main cable dehumidification system and method based on distributed humidity monitoring, the problems that the internal humidity gradient of a large-section main cable is large, single-point monitoring is inaccurate, dehumidification control is extensive and the like are solved, visual early warning and linkage precise protection of the internal corrosion environment of the main cable can be achieved, and the durability and safety of the suspension bridge main cable are remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of humidity monitoring and dehumidification technology for suspension bridge main cables, and particularly to a dehumidification system and method for suspension bridge main cables based on distributed humidity monitoring. Background Technology

[0002] As the core load-bearing component of a suspension bridge, the main cable's structural integrity and durability directly determine the overall safety performance, service life, and operational reliability of the bridge, making it a key component ensuring long-term stable operation. The main cable is typically made of tens of thousands of high-strength galvanized steel wires twisted together. The corrosion rate of these high-strength steel wires is significantly positively correlated with the relative humidity of the environment—increased humidity accelerates the loss of the galvanized layer on the wire surface and the electrochemical corrosion reaction of the base steel, leading to a decline in the mechanical properties of the main cable. In severe cases, this can cause structural safety hazards and even threaten the operational safety of the bridge.

[0003] To slow down the corrosion process of the steel wires inside the main cable and extend its service life, the engineering field generally adopts the main cable dehumidification system as the core protection method. Its core principle is to continuously introduce dry air into the main cable to reduce the relative humidity of the internal environment and create a low-humidity environment that is not conducive to the corrosion of steel wires, thereby achieving the goal of corrosion protection.

[0004] However, existing main cable dehumidification systems and supporting monitoring technologies still have the following key technical deficiencies in practical engineering applications, making it difficult to meet the actual needs of high-precision protection for the main cables of long-span suspension bridges: 1. Inefficient monitoring methods and incomplete data: Current mainstream dehumidification systems largely rely on single-point electronic humidity sensors deployed near the air inlet and outlet cable clamps to collect data. However, for long-span suspension bridges, the diameter of the main cable cross-section often exceeds 1 meter. Due to the structural characteristics of the main cable, external environmental infiltration, and differences in airflow distribution, the internal humidity distribution exhibits a significant three-dimensional gradient characteristic, resulting in extremely poor humidity field uniformity. Single-point monitoring can only obtain humidity data at local points, failing to comprehensively and accurately capture the overall humidity distribution pattern within the main cable, and even more so, failing to reflect humidity differences in different radial layers and axial regions. This leads to serious deviations in the assessment of the actual corrosion environment inside the main cable.

[0005] 2. Lack of precision and coordination in dehumidification control: Due to the limited scope of monitoring data, existing dehumidification systems lack targeted control strategies, often employing a "coarse-grained overall dehumidification" mode—regardless of the humidity levels in different areas within the main cable, all dehumidification operations are performed using uniform airflow parameters (air volume, duration). This mode leads to insufficient dehumidification in high-humidity areas, failing to effectively inhibit corrosion; on the other hand, it causes excessive dehumidification in low-humidity areas, resulting in significant energy waste.

[0006] 3. Corrosion status is difficult to predict and maintenance lacks a basis: The main cable is a closed composite structure, with the internal steel wires wrapped inside the protective layer and twisting structure, making its corrosion status impossible to directly observe or assess. Current technology can only indirectly infer corrosion risk through single-point humidity data. It cannot establish a quantitative correlation between humidity distribution and steel wire corrosion rate, nor can it predict corrosion development trends based on monitoring data. This results in bridge maintenance work often being in a "post-maintenance" state, lacking a scientific and effective basis for preventive maintenance, and failing to avoid structural safety risks caused by main cable corrosion from the source. Summary of the Invention

[0007] The purpose of this invention is to provide a dehumidification system and method for the main cable of a suspension bridge based on distributed humidity monitoring, thereby solving the aforementioned technical problems.

[0008] To achieve the above objectives, the present invention provides a dehumidification system for the main cable of a suspension bridge based on distributed humidity monitoring, including a three-dimensional humidity monitoring network, an optical fiber demodulator, an intelligent control module, and a distributed dehumidification module embedded or embedded inside the main cable of the suspension bridge. The three-dimensional humidity monitoring network includes multiple grating humidity sensing optical fibers arranged axially along the entire length inside the main cable of the suspension bridge. The multiple grating humidity sensing optical fibers are arranged in a multi-layer ring array along the transverse cross section of the main cable of the suspension bridge, and multiple humidity-sensitive grating measuring points are uniformly engraved on the grating humidity sensing optical fibers. The three-dimensional humidity monitoring network is electrically connected to the fiber optic demodulator via lead-out lines. The fiber optic demodulator is electrically connected to the input end of the intelligent control module, and the output end of the intelligent control module is connected to the distributed dehumidification module.

[0009] Preferably, the distributed dehumidification module includes a dehumidifier unit and multiple cable clamp pairs axially spaced on the main cable of the suspension bridge. Each cable clamp pair includes an air inlet cable clamp and an air outlet cable clamp. The air inlet cable clamp is connected to the air outlet of the dehumidifier unit via an air inlet pipe, forming an air blowing dehumidification passage for the dehumidifier unit, the air inlet cable clamp, the main cable of the suspension bridge, and the air outlet cable clamp. An electric regulating valve is installed on the air intake clamp, and both the electric regulating valve and the dehumidifier unit are connected to the intelligent control module.

[0010] Preferably, the spatial resolution of the fiber optic demodulator is greater than 0.5m, and the humidity measurement accuracy is not less than ±2%RH.

[0011] A dehumidification method for a suspension bridge main cable dehumidification system based on distributed humidity monitoring includes the following steps: S1. Deployment of a three-dimensional humidity monitoring network: During the process of bundling multiple steel wires into the main cable of a suspension bridge, multiple grating humidity sensing optical fibers are embedded in multiple steel wires in a multi-layer ring array; or multiple grating humidity sensing optical fibers are embedded in the gaps between the steel wires of the main cable of the suspension bridge in a multi-layer ring array; or multiple grating humidity sensing optical fibers are encapsulated with fiber composite materials to make a composite sensing unit with the same size as the steel wires of the main cable of the suspension bridge, which is used to replace several steel wires in the main cable; and the fiber optic demodulator is connected by lead-out lines. S2. System initialization and startup: The fiber demodulator emits a laser into the grating humidity sensing fiber and receives the reflected signal from the humidity-sensitive grating measurement point. The fiber demodulator determines the measurement point position based on the optical time-domain reflection principle and calculates the humidity value by monitoring the drift of the Bragg wavelength of the reflected signal. It generates a three-dimensional humidity distribution map inside the main cable of the suspension bridge and transmits the humidity distribution map and positioning data to the intelligent control module. S3. The intelligent control module calls the built-in humidity gradient analysis algorithm to perform full-domain analysis on the received three-dimensional humidity distribution data, calculate the humidity gradient change inside the main cable, identify high humidity areas, humidity anomaly points and their corresponding spatial coordinates, and at the same time determine the air intake cable clamp control zone to which the high humidity area belongs. S4. The intelligent control module generates targeted dehumidification commands based on the humidity value, range, and distribution characteristics of the high-humidity area. The dehumidification commands include the opening parameters of the electric regulating valve of the corresponding zone air intake clamp, the working status parameters of the dehumidifier unit, and the air supply duration threshold. The module drives the dehumidifier unit to start or adjust the output power through control signals, and independently regulates the electric regulating valve of the target zone air intake clamp to deliver dry air to the high-humidity area in a directional manner, thereby achieving zoned dehumidification. S5. During the dehumidification process, the three-dimensional humidity monitoring network continuously collects humidity data inside the main cable of the suspension bridge. The fiber optic demodulator updates the three-dimensional humidity distribution map in real time and feeds it back to the intelligent control module. The intelligent control module dynamically tracks the humidity change trend in high-humidity areas. When the humidity value of the target high-humidity area drops below the preset safety threshold, the intelligent control module issues a feedback command to adjust the opening of the corresponding electric regulating valve and the power of the dehumidifier unit to restore it to normal operation. If the humidity does not meet the standard, the air supply parameters are continuously optimized to form a closed-loop dehumidification control to ensure that the entire main cable area maintains a low-humidity safe environment.

[0012] Therefore, the beneficial effects of the suspension bridge main cable dehumidification system and dehumidification method based on distributed humidity monitoring adopted in this invention are as follows: 1. Comprehensive and accurate monitoring, solving the problem of humidity gradient measurement: With the help of distributed grating array sensing technology, through the deployment of sensing optical fibers along the entire axial length and radial multiple points of the main cable, real-time humidity data of the entire area and cross section inside the main cable can be densely collected, accurately capturing the humidity gradient changes inside the large cross section of the main cable, completely solving the problem that traditional single-point monitoring cannot fully reflect the true humidity status of the main cable, and realizing the visualization of humidity distribution. 2. Precise and efficient dehumidification, with coordinated response and energy saving: A humidity distribution-driven coordinated dehumidification mechanism is constructed. The intelligent control module accurately identifies high-humidity areas based on real-time humidity maps and adjusts the airflow and duration of the corresponding zone air intake clamps accordingly, achieving "on-demand dehumidification." This avoids the problems of insufficient or excessive dehumidification caused by traditional extensive dehumidification methods and significantly reduces energy consumption. 3. Enhance structural safety and durability: By accurately monitoring and controlling the humidity environment inside the main cable, the corrosion reaction of high-strength steel wire caused by high humidity environment is suppressed from the source, the mechanical properties of the main cable are slowed down, the service life of the main cable is effectively extended, and the overall safety and stability level and long-term durability of the suspension bridge are improved. 4. Supports intelligent early warning and provides scientific basis for maintenance: The system can accumulate historical data on the humidity distribution of the main cable over a long period of time. Combined with the correlation between steel wire corrosion and humidity, it can analyze the internal corrosion development trend of the main cable, realize early prediction and early warning of corrosion risks, provide quantitative data support for the formulation of bridge preventive maintenance, and promote the transformation of maintenance mode from "post-maintenance" to "pre-prevention".

[0013] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0014] Figure 1 This is a schematic diagram of the dehumidification system for the main cable of a suspension bridge based on distributed humidity monitoring, as described in this invention. Figure 2 This is a layout diagram of the three-dimensional humidity monitoring network of the suspension bridge main cable dehumidification system based on distributed humidity monitoring as described in this invention; wherein, (a) is a radial layout diagram; and (b) is an axial layout diagram. Figure 3 This is a schematic diagram of the partitioning described in the embodiment.

[0015] Figure Labels 1. Grating humidity sensing fiber; 11. Humidity-sensitive grating measuring point; 2. Main cable of suspension bridge; 21. Steel wire. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely illustrative of the embodiments of the present invention and are not intended to limit the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of this application. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout.

[0017] It should be noted that the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion, such as a process, method, system, product, or server that includes a series of steps or units, not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such process, method, product, or device.

[0018] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0019] like Figure 1 and Figure 2 As shown, the dehumidification system for the main cable 2 of the suspension bridge based on distributed humidity monitoring includes a three-dimensional humidity monitoring network, a fiber optic demodulator, an intelligent control module, and a distributed dehumidification module embedded or inlaid inside the main cable 2 of the suspension bridge. The three-dimensional humidity monitoring network includes multiple grating humidity sensing fibers 1 arranged axially along the entire length inside the main cable 2 of the suspension bridge. The multiple grating humidity sensing fibers 1 are arranged in a multi-layer ring array along the transverse cross section of the main cable 2 of the suspension bridge. Multiple humidity-sensitive grating measuring points 11 are uniformly engraved on the grating humidity sensing fibers 1. The three-dimensional humidity monitoring network is electrically connected to the fiber optic demodulator via lead-out lines. The fiber optic demodulator is electrically connected to the input end of the intelligent control module. The output end of the intelligent control module is connected to the distributed dehumidification module.

[0020] The distributed dehumidification module includes a dehumidifier unit and multiple cable clamp pairs axially spaced on the main cable 2 of the suspension bridge. Each cable clamp pair includes an air inlet cable clamp and an air outlet cable clamp. The air inlet cable clamp is connected to the air outlet of the dehumidifier unit via an air inlet pipe, forming an air blowing dehumidification passage for the dehumidifier unit, the air inlet cable clamp, the main cable 2 of the suspension bridge, and the air outlet cable clamp. An electric regulating valve is installed on the air inlet cable clamp, and both the electric regulating valve and the dehumidifier unit are connected to the intelligent control module.

[0021] The fiber optic demodulator has a spatial resolution greater than 0.5m and a humidity measurement accuracy of no less than ±2%RH.

[0022] The dehumidification method for the main cable 2 dehumidification system of a suspension bridge based on distributed humidity monitoring includes the following steps: S1. Deployment of a three-dimensional humidity monitoring network: During the process of bundling multiple steel wires 21 into the main cable 2 of the suspension bridge, multiple grating humidity sensing optical fibers 1 are embedded in the multiple steel wires 21 in a multi-layer ring array; or multiple grating humidity sensing optical fibers 1 are embedded in the gaps between the steel wires 21 of the main cable 2 of the suspension bridge in a multi-layer ring array; or multiple grating humidity sensing optical fibers 1 are encapsulated with fiber composite materials to make a composite sensing unit with the same size as the steel wires 21 of the main cable 2 of the suspension bridge, to replace several steel wires in the main cable; and the fiber optic demodulator is connected by lead-out lines. S2. The system is initialized and started. The fiber demodulator emits a laser to the grating humidity sensing fiber 1 and receives the reflected signal from the humidity-sensitive grating measuring point 11. The fiber demodulator determines the measuring point position according to the optical time domain reflection principle and calculates the humidity value by monitoring the drift of the Bragg wavelength of the reflected signal. It generates a three-dimensional humidity distribution map inside the main cable 2 of the suspension bridge and transmits the humidity distribution map and positioning data to the intelligent control module. S3. The intelligent control module calls the built-in humidity gradient analysis algorithm to perform full-domain analysis on the received three-dimensional humidity distribution data, calculate the humidity gradient change inside the main cable, identify high humidity areas, humidity anomaly points and their corresponding spatial coordinates, and at the same time determine the air intake cable clamp control zone to which the high humidity area belongs. S4. The intelligent control module generates targeted dehumidification commands based on the humidity value, range, and distribution characteristics of the high-humidity area. The dehumidification commands include the opening parameters of the electric regulating valve of the corresponding zone air intake clamp, the working status parameters of the dehumidifier unit, and the air supply duration threshold. The module drives the dehumidifier unit to start or adjust the output power through control signals, and independently regulates the electric regulating valve of the target zone air intake clamp to deliver dry air to the high-humidity area in a directional manner, thereby achieving zoned dehumidification. S5. During the dehumidification process, the three-dimensional humidity monitoring network continuously collects humidity data inside the main cable 2 of the suspension bridge. The fiber optic demodulator updates the three-dimensional humidity distribution map in real time and feeds it back to the intelligent control module. The intelligent control module dynamically tracks the humidity change trend in the high humidity area. When the humidity value of the target high humidity area drops below the preset safety threshold, the intelligent control module issues a feedback command to adjust the opening of the corresponding electric regulating valve and the power of the dehumidifier unit to restore the normal operating state. If the humidity does not meet the standard, the air supply parameters are continuously optimized to form a closed-loop dehumidification control to ensure that the entire main cable area maintains a low humidity safety environment.

[0023] Step S2 specifically includes the following steps: S21. After system initialization, the fiber optic demodulator emits broadband laser light into the grating humidity sensing fiber embedded inside the main cable of the suspension bridge and receives the reflected light. S22. Based on reflected light, the fiber optic demodulator determines the measurement point location according to the principle of optical time-domain reflection (the demodulator measures the time difference between the emitted light and the reflected light of each specific wavelength (corresponding to a grating measurement point)). Because light travels one round trip within the optical fiber, the distance... Equal to the speed of light in an optical fiber ( (Multiplied by half the time difference): ; in, ; In the formula, , and These represent axial coordinates, radial coordinates, and circumferential coordinates, respectively. This indicates the initial length of the grating humidity sensing fiber optic cable axially deployed. Indicates the first The preset radius of each radial annular layer; Indicates the first in the same ring layer The preset circumferential angle of the grating humidity sensing fiber; Indicates the fiber optic length between the measuring point and the fiber optic demodulator (unit: meter, m). The speed of light in a vacuum is approximately meters per second (m / s); This represents the time delay between the emitted laser pulse and the received reflected pulse from a specific humidity-sensitive grating measuring point (unit: seconds, s). This represents the effective refractive index of the grating humidity sensing fiber. This value is determined by the material and structure of the fiber and is a known parameter. Simultaneously, the humidity value is calculated by monitoring the drift of the Bragg wavelength of the reflected signal. ; in, ; In the formula, This indicates the current relative humidity value at the measuring point. This indicates the reference humidity value, which is the ambient humidity at the time of calibration. This indicates the current Bragg wavelength (unit: nanometers, nm) of the reflected light from a certain measurement point, as measured in real time by the fiber optic demodulator. The humidity sensitivity coefficient (unit: nm / %RH) represents the change in Bragg wavelength for every 1% change in relative humidity (RH). This coefficient is obtained through laboratory calibration and is a known constant or a variable with a known relationship for a specific fiber Bragg grating coating material and process. This represents the initial Bragg wavelength (unit: nanometers, nm) obtained by calibration at the same humidity-sensitive grating measurement point under a reference humidity environment. This represents the amount of Bragg wavelength shift (unit: nanometers, nm), and ; This indicates the change in relative humidity (unit: %RH). S23. Perform step S2 above on all humidity-sensitive grating measurement points inside the main cable of the suspension bridge in the fiber optic demodulator, and then convert the three-dimensional spatial coordinates of each measurement point. and its corresponding real-time humidity value By associating and combining data, and using spatial interpolation algorithms, a visualized three-dimensional humidity distribution map of the main cable of a suspension bridge is generated in the software.

[0024] Preferably, step S3 specifically includes the following steps: S31. Multi-dimensional feature extraction: Extract structured data from the three-dimensional humidity distribution map to obtain the real-time three-dimensional humidity distribution matrix. ; At the same time, the following features were extracted from the historical database: Spatial gradient features Calculate the humidity gradient amplitude at each measuring point in three-dimensional space: ; In the formula, Indicates the measuring point Humidity gradient magnitude in three-dimensional space; Indicates the measuring point The spatial neighborhood; Distance weights; Indicates the measuring point spatial neighborhood The index of a certain measurement point within; and These represent the current measuring points. Corresponding real-time humidity value and spatial neighborhood Internal test points The corresponding real-time humidity value; Time-of-change characteristics : Calculate the humidity at each measuring point within a certain time window Internal trends: ; In the formula, Indicates the measuring point At any moment The characteristics of humidity change rate over time; and Representing the measuring points respectively At the present moment and time The corresponding real-time humidity value; Statistical anomalies Based on long-term historical humidity data of the measuring point or the area, calculate the degree of deviation of the current humidity value from its historical distribution. ; In the formula, Indicates the measuring point At any moment The statistical anomalies in humidity; Indicates the measuring point The mean of the corresponding long-term historical humidity data; Indicates the measuring point The standard deviation of the corresponding long-term historical humidity data; absolute humidity value The current real-time humidity value at the measuring point is used as the absolute humidity value. ; S32. Establish a dynamic risk scoring function (The higher the score, the greater the urgency and priority of dehumidification intervention at that point.) Used for comprehensive evaluation of measuring points. Risk of abnormal humidity: ; In the formula, The function representing the effect of absolute humidity can be a piecewise function, for example: when Below the long-term safety threshold The impact is minimal at times; when Between Corrosion Critical Threshold It increases linearly between [a certain point]; beyond [a certain point]... The subsequent exponential growth was intended to emphasize the severity of the high humidity. This represents the spatial gradient influence function. A larger humidity gradient indicates that moisture may be accumulating locally or that there are infiltration pathways, meaning there may be a risk even if the absolute humidity is not high. This function assigns a higher risk weight to areas with high gradients. This represents the effect of the rate of change over time, for areas where humidity is rising rapidly. >0) is given a positive weight, and the area that is drying ( <0) Apply negative weighting or reduce the weight; This represents the statistical anomaly impact function. For areas where humidity values ​​significantly deviate from the historical normal range, even if they do not exceed the absolute threshold, they are considered to be in an abnormal state. Each represents the dynamic weight coefficient of each feature, and ; S33. Setting dynamic risk scoring thresholds , , , , and All represent weighting coefficients; and Representing time respectively Normalized mean and standard deviation of humidity at all measuring points on the main cable of the suspension bridge; Indicates the seasonal correction factor; Indicates the historical humidity deviation coefficient; This indicates the percentage of measurement points with localized high humidity. S34, All The measurement points are marked as risk points, and the DBSCAN algorithm based on spatial distance is used to aggregate all risk points into one or more continuous three-dimensional spatial risk regions. S35. Calculate the average risk score of the three-dimensional spatial risk area. And based on the average risk score They are divided into different levels, and a dehumidification intensity strategy is generated based on the level. At the same time, the geometric center coordinates of each three-dimensional spatial risk area are calculated, and combined with the pre-established cable clip partition-three-dimensional spatial mapping table, the control range of the intake cable clip corresponding to the area is determined. S35. Output a list of three-dimensional spatial risk areas to obtain the target high humidity area. Each area includes its spatial boundary, risk level, core humidity characteristics, dehumidification intensity strategy, and a list of intake clip IDs responsible for regulation.

[0025] Preferably, in step S5, if the humidity in the target high-humidity area does not drop to the safe threshold within the expected time... At this point, the system will initiate an adaptive air supply parameter optimization algorithm based on the PID control concept; The specific steps are as follows: First, set the optimization target as humidity deviation. ,and , This indicates real-time humidity monitoring. This indicates the safety threshold; the evaluation metric is set as the dehumidification response rate. ,and Set air supply parameters: opening degree of electric regulating valve Dehumidifier unit power and air supply duration ; Then, an incremental PID control algorithm is used to adjust the air supply parameters: ; In the formula, Indicates the valve opening adjustment amount; Indicates the proportionality coefficient; Indicates the integral coefficient; Represents the differential coefficient; If the humidity still does not meet the standard, the system will activate the multi-parameter collaborative optimization module and adjust according to the following rules: like If the humidity decreases slowly, then increase the humidity level. and and increase ,extend Until the standard is met; This indicates the minimum allowable dehumidification response rate; like Then increase and reduce Until the standard is met; This indicates the maximum allowable rate of change in humidity deviation; like Then, the historical data learning module is activated, calling the optimal parameter combination under the same operating conditions; at the same time, a fuzzy control strategy is adopted to adjust... , , The weights; Indicates the initial time; The system records the initial humidity distribution for each adjustment. Air supply parameter combination Final humidity response and response time Establish an experience database so that when the same humidity distribution pattern reappears, the historical optimal parameters can be directly called.

[0026] Preferably, step S5 is followed by step S6, which involves summarizing historical humidity distribution data and generating the corrosion trend of the main cable of the suspension bridge based on the historical humidity distribution data.

[0027] Preferably, in step S6, the system summarizes historical three-dimensional humidity distribution data monitored over a long period of time and combines it with a steel wire corrosion kinetic model to quantitatively assess and predict the corrosion development in different areas inside the main cable of the suspension bridge. The specific generation method is as follows: S61. Data Preparation and Feature Extraction: Extract the following data series from the historical database: Humidity time series. measuring points In time relative humidity values ​​and temperature time series Time tags: And spatial coordinates: ; S62. Establish a humidity-dependent corrosion rate model: ; In the formula, Indicates the measuring point In time The corrosion rate; This represents the corrosion rate constant; Indicates real-time relative humidity; Indicates the corrosion threshold humidity; Indicates the humidity impact index; Represents the temperature effect function, and , Indicates activation energy. Represents the gas constant. Indicates reference temperature; S63. Calculate the cumulative corrosion depth based on a humidity-dependent corrosion rate model: ; In the formula, Indicates the measuring point From the initial time up to the current time The cumulative corrosion depth; Indicates the monitoring time interval; This indicates the total number of times the monitoring data was sampled; Indicates the measuring point At any moment The instantaneous corrosion rate; Indicates the measuring point In the Second sampling time The corrosion rate; S64, Based on historical cumulative corrosion depth sequence A time series forecasting model is used to predict corrosion trends over a future period. The prediction formula is expressed as follows: ; In the formula, Indicates the future Predicted corrosion depth after time; and All represent linear trend coefficients; and They represent the first Seasonal cycle item The amplitude and period; and the trend decomposition model expression is as follows: ; In the formula, Indicates the long-term trend; Indicates a seasonal periodic term; Indicates random noise; S65. Risk Level Classification: Safety: ; Warning: ; High risk: ; S66, outputs corrosion depth distribution map, trend prediction curve and risk level classification, and predicts corrosion depth exceeding [a certain value] in the future. The system will automatically issue a warning at that time.

[0028] Example like Figure 3 As shown, taking a long-span suspension bridge as an example, six optical fiber gratings for humidity sensing (one in the center and five around the perimeter) are installed inside the main cable of the suspension bridge, with one humidity-sensitive grating measuring point set every meter along the axial direction. The demodulator adopts a quasi-distributed demodulation method with a spatial resolution of 1 meter. The dehumidification module has 20 pairs of air inlet / outlet clamps.

[0029] After the system was operational, on a certain day, the intelligent control module detected that the humidity in a certain section of the main cable of the suspension bridge (covered by three adjacent cable clamps) remained above 50%, while the humidity in other areas was below 35%. The intelligent control module then instructed to increase the airflow to the three air intake cable clamps leading to that section. After 48 hours, the humidity in that section dropped below 40%, and the system automatically restored the airflow to normal levels. This process effectively avoided the potential risk of corrosion in that localized area and saved approximately 15% more energy than continuous high-speed dehumidification, fully demonstrating the effectiveness and economy of the synchronized and precise dehumidification mechanism of this invention.

[0030] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A dehumidification system for the main cable of a suspension bridge based on distributed humidity monitoring, characterized in that: It includes a three-dimensional humidity monitoring network, an optical fiber demodulator, an intelligent control module, and a distributed dehumidification module implanted or embedded inside the main cable of the suspension bridge. The three-dimensional humidity monitoring network includes multiple grating humidity sensing optical fibers arranged axially along the entire length inside the main cable of the suspension bridge. The multiple grating humidity sensing optical fibers are arranged in a multi-layer ring array along the transverse cross section of the main cable of the suspension bridge, and multiple humidity-sensitive grating measuring points are uniformly engraved on the grating humidity sensing optical fibers. The three-dimensional humidity monitoring network is electrically connected to the fiber optic demodulator via lead-out lines. The fiber optic demodulator is electrically connected to the input end of the intelligent control module, and the output end of the intelligent control module is connected to the distributed dehumidification module.

2. The suspension bridge main cable dehumidification system based on distributed humidity monitoring according to claim 1, characterized in that: The distributed dehumidification module includes a dehumidification unit and multiple cable clamp pairs axially spaced on the main cable of the suspension bridge. Each cable clamp pair includes an air inlet cable clamp and an air outlet cable clamp. The air inlet cable clamp is connected to the air outlet of the dehumidification unit via an air inlet pipe, forming an air blowing dehumidification path for the dehumidification unit, the air inlet cable clamp, the main cable of the suspension bridge, and the air outlet cable clamp. An electric regulating valve is installed on the air intake clamp, and both the electric regulating valve and the dehumidifier unit are connected to the intelligent control module.

3. The suspension bridge main cable dehumidification system based on distributed humidity monitoring according to claim 2, characterized in that: The fiber optic demodulator has a spatial resolution greater than 0.5m and a humidity measurement accuracy of no less than ±2%RH.

4. The dehumidification method for a suspension bridge main cable dehumidification system based on distributed humidity monitoring as described in claim 2 or 3, characterized in that: Includes the following steps: S1. Deployment of a three-dimensional humidity monitoring network: During the process of bundling multiple steel wires into the main cable of a suspension bridge, multiple grating humidity sensing optical fibers are embedded in multiple steel wires in a multi-layer ring array; or multiple grating humidity sensing optical fibers are embedded in the gaps between the steel wires of the main cable of the suspension bridge in a multi-layer ring array; or multiple grating humidity sensing optical fibers are encapsulated with fiber composite materials to make a composite sensing unit with the same size as the steel wires of the main cable of the suspension bridge, which is used to replace several steel wires in the main cable; and the fiber optic demodulator is connected by lead-out lines. S2. System initialization and startup: The fiber demodulator emits a laser into the grating humidity sensing fiber and receives the reflected signal from the humidity-sensitive grating measurement point. The fiber demodulator determines the measurement point position based on the optical time-domain reflection principle and calculates the humidity value by monitoring the drift of the Bragg wavelength of the reflected signal. It generates a three-dimensional humidity distribution map inside the main cable of the suspension bridge and transmits the humidity distribution map and positioning data to the intelligent control module. S3. The intelligent control module calls the built-in humidity gradient analysis algorithm to perform full-domain analysis on the received three-dimensional humidity distribution data, calculate the humidity gradient change inside the main cable, identify high humidity areas, humidity anomaly points and their corresponding spatial coordinates, and at the same time determine the air intake cable clamp control zone to which the high humidity area belongs. S4. The intelligent control module generates targeted dehumidification commands based on the humidity value, range, and distribution characteristics of the high-humidity area. The dehumidification commands include the opening parameters of the electric regulating valve of the corresponding zone air intake clamp, the working status parameters of the dehumidifier unit, and the air supply duration threshold. The module drives the dehumidifier unit to start or adjust the output power through control signals, and independently regulates the electric regulating valve of the target zone air intake clamp to deliver dry air to the high-humidity area in a directional manner, thereby achieving zoned dehumidification. S5. During the dehumidification process, the three-dimensional humidity monitoring network continuously collects humidity data inside the main cable of the suspension bridge. The fiber optic demodulator updates the three-dimensional humidity distribution map in real time and feeds it back to the intelligent control module. The intelligent control module dynamically tracks the humidity change trend in high-humidity areas. When the humidity value of the target high-humidity area drops below the preset safety threshold, the intelligent control module issues a feedback command to adjust the opening of the corresponding electric regulating valve and the power of the dehumidifier unit to restore it to normal operation. If the humidity does not meet the standard, the air supply parameters are continuously optimized to form a closed-loop dehumidification control to ensure that the entire main cable area maintains a low-humidity safe environment.

5. The dehumidification method for a suspension bridge main cable dehumidification system based on distributed humidity monitoring according to claim 4, characterized in that: Step S2 specifically includes the following steps: S21. After system initialization, the fiber optic demodulator emits broadband laser light into the grating humidity sensing fiber embedded inside the main cable of the suspension bridge and receives the reflected light. S22. Based on reflected light, the fiber optic demodulator determines the measurement point location according to the principle of optical time-domain reflection: ； in, ； In the formula, , and These represent axial coordinates, radial coordinates, and circumferential coordinates, respectively. This indicates the initial length of the grating humidity sensing fiber optic cable axially laid out. Indicates the first The preset radius of each radial annular layer; Indicates the first in the same ring layer The preset circumferential angle of the grating humidity sensing fiber; This indicates the length of the optical fiber between the measuring point and the optical fiber demodulator. This represents the speed of light in a vacuum. This represents the time delay between emitting a laser pulse and receiving a reflected pulse from a specific humidity-sensitive grating measurement point; Indicates the effective refractive index of the grating humidity sensing fiber; Simultaneously, the humidity value is calculated by monitoring the drift of the Bragg wavelength of the reflected signal. ； in, ； In the formula, This indicates the current relative humidity value at the measuring point. Indicates a reference humidity value; This indicates the current Bragg wavelength of the reflected light from a certain measuring point, as measured in real time by the fiber optic demodulator. The humidity sensitivity coefficient represents the humidity sensitivity coefficient of the humidity-sensitive grating. This represents the initial Bragg wavelength obtained by calibration at the same humidity-sensitive grating measurement point under a reference humidity environment. This represents the amount of wavelength shift in the Bragg wavelength, and ; This indicates the amount of change in relative humidity; S23. Perform step S2 above on all humidity-sensitive grating measurement points inside the main cable of the suspension bridge in the fiber optic demodulator, and then convert the three-dimensional spatial coordinates of each measurement point. and its corresponding real-time humidity value By associating and combining data, and using spatial interpolation algorithms, a visualized three-dimensional humidity distribution map of the main cable of a suspension bridge is generated in the software.

6. The dehumidification method for a suspension bridge main cable dehumidification system based on distributed humidity monitoring according to claim 5, characterized in that: Step S3 specifically includes the following steps: S31. Multi-dimensional feature extraction: Extract structured data from the three-dimensional humidity distribution map to obtain the real-time three-dimensional humidity distribution matrix. ; At the same time, the following features were extracted from the historical database: Spatial gradient features Calculate the humidity gradient amplitude at each measuring point in three-dimensional space: ； In the formula, Indicates the measuring point Humidity gradient magnitude in three-dimensional space; Indicates the measuring point Spatial neighborhood; Distance weights; Indicates the measuring point spatial neighborhood The index of a certain measurement point within; and These represent the current measuring points. Corresponding real-time humidity value and spatial neighborhood Internal test points The corresponding real-time humidity value; Time-of-change characteristics : Calculate the humidity at each measuring point within a certain time window Internal trends: ； In the formula, Indicates the measuring point At any moment The characteristics of humidity change rate over time; and Representing the measuring points At the present moment and time The corresponding real-time humidity value; Statistical anomalies Based on long-term historical humidity data of the measuring point or the area, calculate the degree of deviation of the current humidity value from its historical distribution. ； In the formula, Indicates the measuring point At any moment The statistical anomalies in humidity; Indicates the measuring point The mean of the corresponding long-term historical humidity data; Indicates the measuring point The standard deviation of the corresponding long-term historical humidity data; absolute humidity value The current real-time humidity value at the measuring point is used as the absolute humidity value. ; S32. Establish a dynamic risk scoring function Used for comprehensive evaluation of measuring points Risk of abnormal humidity: ； In the formula, This represents the function representing the effect of absolute humidity. Represents the spatial gradient influence function; The function representing the effect of the rate of change over time; This represents a function representing the impact of statistical anomalies. Each represents the dynamic weight coefficient of each feature, and ; S33. Setting dynamic risk scoring thresholds , , , , and All represent weighting coefficients; and Representing time respectively Normalized mean and standard deviation of humidity at all measuring points on the main cable of the suspension bridge; Indicates the seasonal correction factor; Indicates the historical humidity deviation coefficient; This indicates the percentage of measurement points with localized high humidity. S34, All The measurement points are marked as risk points, and the DBSCAN algorithm based on spatial distance is used to aggregate all risk points into one or more continuous three-dimensional spatial risk regions. S35. Calculate the average risk score of the three-dimensional spatial risk area. And based on the average risk score They are divided into different levels, and a dehumidification intensity strategy is generated based on the level. At the same time, the geometric center coordinates of each three-dimensional spatial risk area are calculated, and combined with the pre-established cable clip partition-three-dimensional spatial mapping table, the control range of the intake cable clip corresponding to the area is determined. S35. Output a list of three-dimensional spatial risk areas to obtain the target high humidity area. Each area includes its spatial boundary, risk level, core humidity characteristics, dehumidification intensity strategy, and a list of intake clip IDs responsible for regulation.

7. The dehumidification method for a suspension bridge main cable dehumidification system based on distributed humidity monitoring according to claim 6, characterized in that: In step S5, if the humidity in the target high-humidity area fails to drop to the safe threshold within the expected time... At this point, the system will initiate an adaptive air supply parameter optimization algorithm based on the PID control concept; The specific steps are as follows: First, set the optimization target as humidity deviation. ,and , This indicates real-time humidity monitoring. Indicates the safety threshold; The evaluation metric is set as dehumidification response rate. ,and ; Set air supply parameters: Electric regulating valve opening Dehumidifier unit power and air supply duration ; Then, an incremental PID control algorithm is used to adjust the air supply parameters: ； In the formula, Indicates the valve opening adjustment amount; Indicates the proportionality coefficient; Indicates the integral coefficient; Represents the differential coefficient; If the humidity still does not meet the standard, the system will activate the multi-parameter collaborative optimization module and adjust according to the following rules: like If the humidity decreases slowly, then increase the humidity level. and and increase ,extend Until the standard is met; This indicates the minimum allowable dehumidification response rate; like Then increase and reduce Until the standard is met; This indicates the maximum allowable rate of change in humidity deviation; like Then, the historical data learning module is activated, calling the optimal parameter combination under the same operating conditions; at the same time, a fuzzy control strategy is adopted to adjust... , , The weights; Indicates the initial time; The system records the initial humidity distribution for each adjustment. Air supply parameter combination Final humidity response and response time Establish an experience database so that when the same humidity distribution pattern reappears, the historical optimal parameters can be directly called.

8. The dehumidification method for a suspension bridge main cable dehumidification system based on distributed humidity monitoring according to claim 7, characterized in that: Step S5 is followed by step S6, which involves summarizing historical humidity distribution data and generating the corrosion trend of the main cable of the suspension bridge based on the historical humidity distribution data.

9. The dehumidification method for a suspension bridge main cable dehumidification system based on distributed humidity monitoring according to claim 8, characterized in that: In step S6, the system summarizes historical three-dimensional humidity distribution data from long-term monitoring and combines it with a steel wire corrosion kinetic model to quantitatively assess and predict the corrosion development in different areas inside the main cable of the suspension bridge. The specific generation method is as follows: S61. Data Preparation and Feature Extraction: Extract the following data series from the historical database: Humidity time series. measuring points In time relative humidity values ​​and temperature time series Time tags: And spatial coordinates: ; S62. Establish a humidity-dependent corrosion rate model: ； In the formula, Indicates the measuring point In time The corrosion rate; This represents the corrosion rate constant; Indicates real-time relative humidity; Indicates the corrosion threshold humidity; Indicates the humidity impact index; Represents the temperature effect function, and , Indicates activation energy. Represents the gas constant. Indicates reference temperature; S63. Calculate the cumulative corrosion depth based on a humidity-dependent corrosion rate model: ； In the formula, Indicates the measuring point From the initial time up to the current time The cumulative corrosion depth; Indicates the monitoring time interval; This indicates the total number of times the monitoring data was sampled; Indicates the measuring point At any moment The instantaneous corrosion rate; Indicates the measuring point In the Second sampling time The corrosion rate; S64, Based on historical cumulative corrosion depth sequence A time series forecasting model is used to predict corrosion trends over a future period. The prediction formula is expressed as follows: ； In the formula, Indicates the future Predicted corrosion depth after time; and All represent linear trend coefficients; and They represent the first Seasonal cycle item The amplitude and period; and the trend decomposition model expression is as follows: ； In the formula, Indicates the long-term trend; Indicates a seasonal periodic term; Indicates random noise; S65. Risk Level Classification: Safety: ; Warning: ; High risk: ; S66, outputs corrosion depth distribution map, trend prediction curve and risk level classification, and predicts corrosion depth exceeding [a certain value] in the future. The system will automatically issue a warning at that time.

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